Journal articles on the topic 'It markaz va h.k.z'

<strong>izLrkouk&nbsp; </strong>Lokra&laquo;;ohj lkojdjkaps fopkj o la?k&rdquo;kZe; thou R;kaP;k lkfgR;krwu vkiY;kyk miyC/k gksrs- lkojdjkauh foiqy vls ys[ku dsys- ohj lkojdjkauk xzaFk okpukph vkoM ckyi.kkiklwup ykxysyh gksrh- T;k o;kr brj eqys ckjk[kMh fxjorkr R;k o;kr lkojdj mRreksRre xzaFk okpw ykxys gksrs- ifjiDo o;krhy Hkk&rdquo;kkizHkw lkfgfR;dkl &lsquo;kksHksy vls Hkk&rdquo;kkoSHko o fopkjeakM.kh] ,su rk:.;kP;k macjB;koj ohj lkojdjkauh vkRelkr dsyh gksrh- ,sfrgkfld] ikSjkf.kd xzaFk] eksjksiar] okeu] bR;knh xzaFkkalkscrp ts ?kjkr clwu okp.;kl fuf&rsquo;k/n ekuys tkrs rs ^vkj.;d* gh ohj lkojdjkauh ckyi.khp okpys- fofHkUu izdkjP;k vMFkG;kaps vk;q&rdquo;; vlwugh o;kP;k ngkO;k&amp;vdjkO;k o&rdquo;kkZiklwu lq: &gt;kysys ys[kudk;Z o;kP;k va&rsquo;khO;k o&rdquo;kkZi;aZr vfojr lq: gksrs- &szlig;lkfgR;kP;k fofo/k {ks=kr R;kauh vkiY;k tkToY; jk&rdquo;V&ordf;HkDrhP;k ok:oj Lokj gks&Aring;u] rRokP;k [kM~xkus ,dsd izkar gLrxr dsyk vkf.k R;k&amp;R;k izkarkr vkiY;k fot;kph lokZauk fnlsy v&rsquo;kh map xq&lt;h mHkkjyh- R;ke/;s dfork] iksokMs] QVds] vkjrh] fuca/k] pfj=] vkRepfj=] ,sfrgkfld] la&rsquo;kks/kuij xzaFk] lkekftd o jktdh; fopkjkoj ys[k] ukVds] dknacjh] bR;knh loZp fo&rdquo;k; vkgs- ;k fofo/kkaxh ys[kudk;kZeqGs ejkBh lkfgR;laesyukps v/;{kingh vkilqdp pkywu vkys- R;kaP;k lkfgR;kr ns&rsquo;kHkDrh o R;klacaf/kr rRokpsp ifjiks&rdquo;k.k dsys vkgs] uOgs R;k rRokP;k Li&rdquo;Vhdjk.kklkBh] lokZaleksj lR; ;s.;klkBhp R;k&amp;R;k lkfgR;kph fufeZrh &gt;kysyh vkgs- R;kaP;k dforsrgh ns&rsquo;kHkDrhP;k fopkjka&rsquo;kh opuc/n jkg.;kpa rs lqporkr- rj iksokM;krgh jk&rdquo;V&ordf;HkDrhphp f&rsquo;kouhrh f&rsquo;kdforkr] lkfgR;kps loZp izdkj o vfo&rdquo;dkj.kkps ek/;e rs vkiY;k fopkjkalkBhp okijrkr- R;kapk uk;dgh jk&rdquo;V&ordf;h;rsps fopkj foljr ukgh-&THORN;

<strong>izLrkouk&nbsp; </strong>Lokra&laquo;;ohj lkojdjkaps fopkj o la?k&rdquo;kZe; thou R;kaP;k lkfgR;krwu vkiY;kyk miyC/k gksrs- lkojdjkauh foiqy vls ys[ku dsys- ohj lkojdjkauk xzaFk okpukph vkoM ckyi.kkiklwup ykxysyh gksrh- T;k o;kr brj eqys ckjk[kMh fxjorkr R;k o;kr lkojdj mRreksRre xzaFk okpw ykxys gksrs- ifjiDo o;krhy Hkk&rdquo;kkizHkw lkfgfR;dkl &lsquo;kksHksy vls Hkk&rdquo;kkoSHko o fopkjeakM.kh] ,su rk:.;kP;k macjB;koj ohj lkojdjkauh vkRelkr dsyh gksrh- ,sfrgkfld] ikSjkf.kd xzaFk] eksjksiar] okeu] bR;knh xzaFkkalkscrp ts ?kjkr clwu okp.;kl fuf&rsquo;k/n ekuys tkrs rs ^vkj.;d* gh ohj lkojdjkauh ckyi.khp okpys- fofHkUu izdkjP;k vMFkG;kaps vk;q&rdquo;; vlwugh o;kP;k ngkO;k&amp;vdjkO;k o&rdquo;kkZiklwu lq: &gt;kysys ys[kudk;Z o;kP;k va&rsquo;khO;k o&rdquo;kkZi;aZr vfojr lq: gksrs- &szlig;lkfgR;kP;k fofo/k {ks=kr R;kauh vkiY;k tkToY; jk&rdquo;V&ordf;HkDrhP;k ok:oj Lokj gks&Aring;u] rRokP;k [kM~xkus ,dsd izkar gLrxr dsyk vkf.k R;k&amp;R;k izkarkr vkiY;k fot;kph lokZauk fnlsy v&rsquo;kh map xq&lt;h mHkkjyh- R;ke/;s dfork] iksokMs] QVds] vkjrh] fuca/k] pfj=] vkRepfj=] ,sfrgkfld] la&rsquo;kks/kuij xzaFk] lkekftd o jktdh; fopkjkoj ys[k] ukVds] dknacjh] bR;knh loZp fo&rdquo;k; vkgs- ;k fofo/kkaxh ys[kudk;kZeqGs ejkBh lkfgR;laesyukps v/;{kingh vkilqdp pkywu vkys- R;kaP;k lkfgR;kr ns&rsquo;kHkDrh o R;klacaf/kr rRokpsp ifjiks&rdquo;k.k dsys vkgs] uOgs R;k rRokP;k Li&rdquo;Vhdjk.kklkBh] lokZaleksj lR; ;s.;klkBhp R;k&amp;R;k lkfgR;kph fufeZrh &gt;kysyh vkgs- R;kaP;k dforsrgh ns&rsquo;kHkDrhP;k fopkjka&rsquo;kh opuc/n jkg.;kpa rs lqporkr- rj iksokM;krgh jk&rdquo;V&ordf;HkDrhphp f&rsquo;kouhrh f&rsquo;kdforkr] lkfgR;kps loZp izdkj o vfo&rdquo;dkj.kkps ek/;e rs vkiY;k fopkjkalkBhp okijrkr- R;kapk uk;dgh jk&rdquo;V&ordf;h;rsps fopkj foljr ukgh-&THORN;

<strong>lkjka'k:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Hkkjrh; laLd`fr vkSj n'kZu dk fo'o esa cM+k izHkko jgk gS] bl le`) fojklr dks vkus okyh ihf&lt;+;ksa ds fy;s u flQZ lgst dj lajf{kr j[kus dh t:jr gS] cfYd gekjh f'k{kk O;oLFkk dks lqn`&lt;+ cuk;s j[kus gsrq 'kks/k dk;ksZa dks c&lt;+kok nsuk pkfg;s vkSj u;s&amp;u;s mi;ksx Hkh lksps tkus pkfg;sA izkphu dky ls gh Hkkjro"kZ esa f'k{kk O;oLFkk dk dsUnz fcUnq f'k{kd ;k xq: jgk gS] ftlds fcuk thou dk vFkZ le&gt; ikuk lEHko ugha gSA xq: dks bZ'oj dh Js.kh esa j[kk x;k gS tSls&amp;<strong>xq: czãk xq: fo".kq xq:nso egs'oj%A</strong><strong>xq: lk{kkr~ ijeczãk rLeS Jh xq:os ue%AA</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Hkkjr o"kZ esa xq: iwf.kZek dk o"kZ cM+h J)k vkSj /kwe/kke ls euk;k tkrk gSA izkphu dky esa tc fo|kFkhZ xq: ds vkJe esa jgdj fu%'kqYd f'k{kk xzg.k djrk Fkk] rks blh fnu J)k Hkko ls izsfjr gksdj vius xq: dk iwtu djds] mUgsa viuh 'kfDr lkeF;Z vuqlkj xq: nf{k.kk nsdj d`rd`R; gksrk FkkA vkt Hkh bldk egRo de ugha gSA xq: dh efgek dks egkdfo lar rqylhnkl us vius egkdkO; esa ^jkepfjrekul* esa xq: oanuk ls dh gSA tSls&amp;<strong>^canÅ xq: in inqe ijkxk] lq:fp lqokl ljl vuqjkxkA*</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; _f"k dky ls gh ns'k esa xq: ds egRo dks dqN bl rjg ls n'kkZ;k x;k gSA 'kkL=ksa esa ^xq* dk vFkZ crk;k x;k gS va/kdkj ;k ewy vKku vkSj ^:* dk vFkZ fd;k x;k gS] mldk fujks/kdA xq: dks xq# blfy;s dgk tkrk gS fd og vKku frfej Kkukatu'kykdk ls fuokj.k dj nsrk gSA vFkkZr va/kdkj dks gVkdj izdk'k dh vksj ys tkus okys dks xq# dgrs gSA xq# dks bZ'oj ds leku le&gt;k x;k gSA xzaFkksa esa bl ckr dk mYys[k gS&amp;<strong>^^vKkukfUrfejkU/kL; Kkukatu 'kykd;kA</strong><strong>p{kq#Uehfyra ;su rLeS Jh xqjos ue%A**</strong>

<strong>Lkkjka'k</strong> &gt;kj[kaM tutkrh; cgqy {ks= rFkk izkd`frd lalk/kuksa dk HkaMkj gksus ds dkj.k iqathifr oxZ rFkk vaxzst ljdkj ds vkd&rsquo;kZ.k dk dsUnz cuk jgk gS ftlls ;gk&iexcl; ds tutkrh; lekt ds vkfFkZd] lkaLd`frd] /kkfeZd] &ldquo;kkjhfjd ,oa ekufld &ldquo;kks&rsquo;k.k dk f&rdquo;kdkj gksrs vk jgs gSaA 1764 ds cDlj ;q) ds QyLo:i caxky] fcgkj rFkk mfM+lk oS/kkfud :i ls vaxzst ljdkj ds v/khu gks x;kA &gt;kj[kaM ds izkd`frd laink dk nksgu djus gsrq ;gk&iexcl; ds tutkrh; leqnk; dks fodkl ds uke ij foLFkkiu rFkk dbZ rjg ds &ldquo;kks&rsquo;k.k dk lkeuk djuk iM+k] ftldk fojks/k os dbZ vkanksyuksa ds lkFk lfn;ksa ls djrs jgs gSaA &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; tutkrh; leqnk; ds vf&rdquo;k{kk] u&rdquo;kk ,oa va/kfo&rdquo;okl dk u flQZ ykHk mBk;k x;k cfYd vU; leqnk; ds yksxksa }kjk tutkrh; leqnk; ds ikjaifjd Lo&rdquo;kklu rFkk laLd`fr dks iw.kZr% u&rsquo;V dj nsus dk iz;kl fd;k x;k] muds /kkfeZd LFky dks ?oLr dj fn;k x;k mUgsa vius gh fuokl LFkku ij dj nsus ds lkFk&amp;lkFk ghurk dk Hkkouk mRiUu djk;k x;k vkSj mUgsa foLFkkiu rFkk cs?kj gksus dks etcwj fd;k x;kA tutkrh; leqnk; dk viuk Lo&rdquo;kklu rFkk fof/k O;oLFkk dks u&rsquo;V djrs gq, iz&rdquo;kklu ds vUrxZr yk;k x;kA bu lHkh dkj.kksa ls tutkrh; leqnk; dbZ fonzksg fd;s rFkk vius vf/kdkjksa ds lkFk vyx jkT; dk ekax fd;sA bl &ldquo;kks&rsquo;k.k rFkk la?k&rsquo;kZ ds nkSjku tutkrh; ykxksa dh u flQZ tula[;k esa deh vk;h cfYd dbZ tutkrh; leqnk; dk vfLrRo gh [krjs esa vk x;kA os foyqfIr ds dxkj ij vk x;sA vkt vktknh ds yxHkx 70 o&rsquo;kksZa i&rdquo;pkr Hkh bu tutkfr;ksa dks eq[; /kkjk ls tksM+uk ljdkj ds lkeus ,d cM+h pqukSrhiw.kZ dk;Z gSA vr% tutkrh; leqnk; ds lkekftd] /kkfeZd rFkk lkaLd`frd /kjksgj dks cpkus ds fy, vkSj vf/kd dkjxj mik; lQyrkiwoZd fd;k tkuk pkfg,A <strong>&nbsp;</strong>

<em>Op </em><em>twe</em><em>e s</em><em>it</em><em>es </em><em>tus</em><em>se</em><em>n L</em><em>e</em><em>i</em><em>e e</em><em>n </em><em>Schelde in </em><em>h</em><em>et </em><em>zuiden </em><em>va</em><em>n </em><em>West-Vlaander</em><em>e</em><em>n zijn </em><em>ma</em><em>ti</em><em>g omvangrijke concen</em><em>trati</em><em>es silexartefac</em><em>t</em><em>en </em><em>ontdekt </em><em>door </em><em>priv&eacute;-verzamelaars. Door de vrij </em><em>lage </em><em>aantallen </em><em>e</em><em>n </em><em>de </em><em>w</em><em>e</em><em>ini</em><em>g </em><em>typische werktuigen </em><em>kan ve</em><em>rr</em><em>e </em><em>van </em><em>exact naar </em><em>een</em> <em>bepaalde prehistorische </em><em>groep geduid </em><em>worden, </em><em>maar </em><em>wij dachten </em><em>beide </em><em>e</em><em>nsembl</em><em>es te </em><em>kunnen inte</em><em>rpretere</em><em>n </em><em>als </em><em>midden-n</em><em>eolitisc</em><em>h</em><em>,</em> <em>ondanks enkele mesolitische </em><em>werktuigen. Deze problemati</em><em>ek </em><em>is courant voor </em><em>d</em><em>e zo</em><em>n. &quot;Secundair </em><em>neolitische culturen&quot; </em><em>, </em><em>de meer </em><em>lokale varianten </em><em>van </em><em>de klassieke, traditionele </em><em>groepen </em><em>zoa</em><em>l</em><em>s </em><em>Kichelsberg </em><em>en S</em><em>.</em><em>O.K., </em><em>waarbij </em><em>een meso</em><em>-inslag blijkb</em><em>aar nie</em><em>t </em><em>zo </em><em>abnormaal </em><em>is </em><em>in n</em><em>eo</em><em>litis</em><em>c</em><em>he indu</em><em>s</em><em>tri</em><em>e&euml;n. </em><em>De </em><em>sites </em><em>dra</em><em>g</em><em>en bij tot een steeds </em><em>b</em><em>e</em><em>t</em><em>er </em><em>idee </em><em>va</em><em>n d</em><em>e </em><em>verspreidin</em><em>g </em><em>va</em><em>n h</em><em>e</em><em>t </em><em>Neo</em><em>liti</em><em>cum in Z</em><em>uid-</em><em>Vlaanderen</em><em> gre</em><em>n</em><em>zen</em><em>d </em><em>aan de veel </em><em>b</em><em>eter ge</em><em>k</em><em>e</em><em>nd</em><em>e </em><em>sites </em><em>van zuiderbuur </em><em>H</em><em>e</em><em>n</em><em>egouwen</em><em>.</em>

Zero-emission electricity production for stationary or mobile applications can be realized by PEM fuel cells (PEMFCs), making it an important constituent for a renewable energy transition. Especially relevant in heavy-duty applications, a high power output at low current densities (related to a high mass activity, MA) under dry conditions is necessary to meet the efficiency targets.[1] In general, mass activity of a Pt/C catalyst can be negatively affected by ionomer poisoning, which describes the adsorption of ionomer endgroups onto the active Pt surface. This effect is especially pronounced for platinum supported on so-called solid carbon supports (e.g., Vulcan – Pt/V)[2] and by operating a fuel cell at low relative humidity (RH).[3] In order to minimize performance losses due to ionomer poisoning, concepts exist to shield the Pt particle from the ionomer, e.g., by alkanethiol masking[4] or by Pt-overlayers of porous SiO2 [5] and carbon derived from dopamine coatings.[6] In the latter case, the authors observed that it was possible to decrease ionomer poisoning and increase MEA performance under dry conditions. However, the transport of reactants to the Pt active sites is hindered by the carbon-overlayer, resulting in inferior high current density (HCD) performance. In this work, we developed multiple in-situ activation strategies for a carbon-coated Pt/V cathode catalyst, synthesized following an adapted protocol from Yamada et al.[6] Our results show that apart from a significantly improved MA, high current density performance is retained for an activated carbon-coated Pt/V (C-Pt/Vactivated, solid orange symbols in Figure 1). Compared to the Pt/V baseline catalyst (blue symbols), the MA can be increased by a factor of ~2 (C-Pt/Vactivated with im 0.9V = 248±9 A gPt -1 and Pt/V with im 0.9V = 110±13 A gPt -1) while simultaneously maintaining comparable high current density performance at 90% RH. However, as we will show, the beneficial effect of the activated carbon-coated Pt/V is particularly pronounced at operation under dry conditions, where C-Pt/Vactivated outperformed the Pt/V baseline over the entire current density range (e.g., by 80 mV at 1.7 A cm-2). Furthermore, possible limitations in terms of durability of the C-overlayer used in this work will be discussed. Figure 1: Differential-flow H2/Air performance at 80 °C/90% RH and 145 kPaabs for different cathode catalysts: baseline catalyst (Pt/V), C-coated Pt/V catalyst before activation (C-Pt/Vb efore activation), and activated C-coated Pt/V catalyst (C-Pt/Va ctivated). In the 5 cm2 active area single-cell, the catalyst loadings were 0.25 mgPt cm-2 and 0.05 mgPt cm-2 on cathode and anode, respectively; a 15 µm reinforced low-EW PFSA membrane was used. References [1] D. A. Cullen, K. C. Neyerlin, R. K. Ahluwalia, R. Mukundan, K. L. More, R. L. Borup, A. Z. Weber, D. J. Myers, A. Kusoglu, Nat Energy 2021, 6, 462–474. [2] V. Yarlagadda, M. K. Carpenter, T. E. Moylan, R. S. Kukreja, R. Koestner, W. Gu, L. Thompson, A. Kongkanand, ACS Energy Lett. 2018, 3, 618–621. [3] K. Kodama, R. Jinnouchi, T. Suzuki, H. Murata, T. Hatanaka, Y. Morimoto, Electrochemistry Communications 2013, 36, 26–28. [4] G. Doo, S. Yuk, J. H. Lee, S. Choi, D.-H. Lee, D. W. Lee, J. Hyun, S. H. Kwon, S. G. Lee, H.-T. Kim, J. Mater. Chem. A 2020, 8, 13004–13013. [5] A. Kongkanand, Caged nanoparticle electrocatalyst with high stability and gas transport property, Patent US 2016/11121379 B2. [6] H. Yamada, H. Kato, K. Kodama, J. Electrochem. Soc. 2020, 167, 84508. Acknowledgement We gratefully acknowledge financial support from the Fuel Cells and Hydrogen 2 Joint Undertaking (JU) under the MORELife grant agreement 101007170 that enabled us to conduct these studies. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Hydrogen Europe and Hydrogen Europe Research. Figure 1

ty iznw&quot;k.k dh leL;k okLro esa dksbZ u;h leL;k ugha gS] vkfndky ls gh ekuo vif&#39;k&quot;V inkFkksZ dks ty lzksrksa esa folftZr djrk pyk vk jgk gSA orZeku le; esa rhoz&nbsp; vkS|ksfxd fodkl] tula[;k o`f)] ty lzksrksa dk nq:Ik;ksx] o&quot;kkZ dh ek=k esa deh vkfn ekuod`r ,oa izkd`frd dkj.kksa ls ty iznw&quot;k.k dh leL;k us fodjky :Ik /kkj.k dj fy;k gSA Xokfy;j ftys esa ty iznw&quot;k.k dh leL;k cuh gqbZ gSA &#39;kgj dh turk dks ihus ds fy;s fey jgk ikuh bruk v&#39;kq) gks pqdk gS] fd og ihus ;ksX; ugha cpk gSA vesfjdu ifCyd gsYFk ,lksfl,&#39;ku] U;w;kdZ ds ekud ds eqrkfcd lkS feyhehVj ikuh esa 10 ls vf/kd thok.kq ugha gksus pkfg;s] ijUrq ;gk&iexcl; ds lkS feyhehVj ikuh esa nks gtkj pkj lkS thok.kqvksa dh la[;k feyhA Xokfy;j ftys esa /kjkryh; ty iznw&quot;k.k rsth ls c&lt;+k gSA Xokfy;j ds vrhr esa Ik;kZoj.k lkSUn;Z vkSj oSHko dh fu&#39;kkuh jgh Lo.kZ js[kk unh tks orZeku esa &#39;kgj ds lhost dks &lt;ks jgh gSa] Hkkjh xkn tek gksus] dpjk Qsadus vkSj cM+s iSekus ij voS/k dCts ds dkj.k unh ls ukyk cuh gqbZ gSA eqjkj unh Hkh iw.kZr% xank ukyk cu pqdh gS ftys dh vU; ufn;ksa tSls oSlkyh] ikoZrh] lka[k vkfn Hkh iznwf&quot;kr gks jgh gS] unh ds rVksa ij clh cfLr;ksa ds fuoklh ey] ew=] xkscj bR;kfn unh esa Qasd dj unh dks iznwf&quot;kr dj jgs gSA eksrh&gt;hy Hkh iznw&quot;k.k ls jfgr ugha gSA cStkrky dh gkyr xans ikuh o xkn ls ljkcksj gSSA Xokfy;j ftys esa Hkw&amp;ty dh fLFkfr fnu izfrfnu [kjkc gksrh tk jgh gSA tula[;k esa gqbZ rhoz o`f) ls mith ifjfLFkfr;ksa ls Xokfy;j ftys esa ty dh [kir c&lt;+rh xbZA Hkwfexr ty dh va/kk/kqa/k fudklh ls bldk ty Lrj yxkrkj uhps fxjrk tk jgk gS] Hkwfexr ty Lrj uhps tkus ls ty esa yo.kh;rk Hkh c&lt;+ jgh gS] ftlls uydwiksa rFkk iafiax lSVksa&nbsp; ls fudyus okyk ikuh Hkh iznwf&quot;kr gh gSA iznwf&quot;kr ty dk iz;ksx Xokfy;j ftys esa fofHkUu LFkyksa ij lfCt;ksa dh [ksrh rFkk lfCt;ksa dh /kqykbZ esa fd;k tk jgk gSA Xokfy;j ftys esa ty iznw&quot;k.k dk v/;;u djus ij ;g fofnr gksrk gS fd ;g ftyk lrgh ty iznw&quot;k.k rFkk Hkwfexr ty iznw&quot;k.k nksuksa ls izHkkfor gSA

ty iznw&quot;k.k dh leL;k okLro esa dksbZ u;h leL;k ugha gS] vkfndky ls gh ekuo vif&#39;k&quot;V inkFkksZ dks ty lzksrksa esa folftZr djrk pyk vk jgk gSA orZeku le; esa rhoz&nbsp; vkS|ksfxd fodkl] tula[;k o`f)] ty lzksrksa dk nq:Ik;ksx] o&quot;kkZ dh ek=k esa deh vkfn ekuod`r ,oa izkd`frd dkj.kksa ls ty iznw&quot;k.k dh leL;k us fodjky :Ik /kkj.k dj fy;k gSA Xokfy;j ftys esa ty iznw&quot;k.k dh leL;k cuh gqbZ gSA &#39;kgj dh turk dks ihus ds fy;s fey jgk ikuh bruk v&#39;kq) gks pqdk gS] fd og ihus ;ksX; ugha cpk gSA vesfjdu ifCyd gsYFk ,lksfl,&#39;ku] U;w;kdZ ds ekud ds eqrkfcd lkS feyhehVj ikuh esa 10 ls vf/kd thok.kq ugha gksus pkfg;s] ijUrq ;gk&iexcl; ds lkS feyhehVj ikuh esa nks gtkj pkj lkS thok.kqvksa dh la[;k feyhA Xokfy;j ftys esa /kjkryh; ty iznw&quot;k.k rsth ls c&lt;+k gSA Xokfy;j ds vrhr esa Ik;kZoj.k lkSUn;Z vkSj oSHko dh fu&#39;kkuh jgh Lo.kZ js[kk unh tks orZeku esa &#39;kgj ds lhost dks &lt;ks jgh gSa] Hkkjh xkn tek gksus] dpjk Qsadus vkSj cM+s iSekus ij voS/k dCts ds dkj.k unh ls ukyk cuh gqbZ gSA eqjkj unh Hkh iw.kZr% xank ukyk cu pqdh gS ftys dh vU; ufn;ksa tSls oSlkyh] ikoZrh] lka[k vkfn Hkh iznwf&quot;kr gks jgh gS] unh ds rVksa ij clh cfLr;ksa ds fuoklh ey] ew=] xkscj bR;kfn unh esa Qasd dj unh dks iznwf&quot;kr dj jgs gSA eksrh&gt;hy Hkh iznw&quot;k.k ls jfgr ugha gSA cStkrky dh gkyr xans ikuh o xkn ls ljkcksj gSSA Xokfy;j ftys esa Hkw&amp;ty dh fLFkfr fnu izfrfnu [kjkc gksrh tk jgh gSA tula[;k esa gqbZ rhoz o`f) ls mith ifjfLFkfr;ksa ls Xokfy;j ftys esa ty dh [kir c&lt;+rh xbZA Hkwfexr ty dh va/kk/kqa/k fudklh ls bldk ty Lrj yxkrkj uhps fxjrk tk jgk gS] Hkwfexr ty Lrj uhps tkus ls ty esa yo.kh;rk Hkh c&lt;+ jgh gS] ftlls uydwiksa rFkk iafiax lSVksa&nbsp; ls fudyus okyk ikuh Hkh iznwf&quot;kr gh gSA iznwf&quot;kr ty dk iz;ksx Xokfy;j ftys esa fofHkUu LFkyksa ij lfCt;ksa dh [ksrh rFkk lfCt;ksa dh /kqykbZ esa fd;k tk jgk gSA Xokfy;j ftys esa ty iznw&quot;k.k dk v/;;u djus ij ;g fofnr gksrk gS fd ;g ftyk lrgh ty iznw&quot;k.k rFkk Hkwfexr ty iznw&quot;k.k nksuksa ls izHkkfor gSA

<strong>BEDA BARG FILC</strong><strong>H</strong><strong>ASI (<em>PHYTONOMUS VARIABILIS</em> HBST) ENTOMOFAGLARI TUR-TARKIBI</strong> <strong>Annotatsiya.</strong> Mazkur maqolada beda o&lsquo;simligining asosiy zararkunandalari&nbsp; biri bo&lsquo;lgan beda barg filchasi (<em>phytonomus variabilis</em> Hbst)ning entomofaglari tur-tarkibi&nbsp;&nbsp; to&lsquo;g&lsquo;risida izlanish natijalari keltirilgan. Beda o&lsquo;simligiga asosan, beda barg filchasining bir-necha turdagi entomofaglari aniqlangan. <strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <em>Kalit so&lsquo;zlar</em></strong><em>: beda, beda barg filchasi (phytonomus variabilis Hbst), zararkunanda, entomofag.</em> <strong>Abstract:</strong> This article presents the research results on the species composition of entomophages of the alfalfa leaf weevil (Phytonomus variabilis Hbst), one of the main pests of the alfalfa plant. Several types of entomophages of the alfalfa leaf weevil have been identified on the alfalfa plant. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <strong><em>Key words</em></strong><em>:alfalfa, alfalfa leaf weevil (phytonomus variabilis Hbst), pest, entomophagous.</em> <em>&nbsp;</em> <strong>&nbsp;&nbsp;&nbsp;&nbsp; Kirish. </strong>O&lsquo;zbekistonning tabiiy-iqlim sharoiti mavsumda ko&lsquo;plab qishloq xo&lsquo;jalik ekinlarini&nbsp; yetishtirshga imkon beradi. Ammo parvarish etilayotgan ekinlarga zararkunanda hashorat va kanalarning yetkazadigan zarari ancha sezilarli bo&lsquo;ladi. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ba&rsquo;zi yillarda zararli organizmlar ta&rsquo;siridan hosilning 60-80 % nobud bo&lsquo;lishiga olib keladi. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Zararkunandalarga qarshi kurashda kimyoviy usul jahon tajribasida keng qo&lsquo;llanilsada, ammo bunday insekto-akaritsidlarning yetarli tanlab, ta&rsquo;sir etish xususiyatiga ega emasligi aniqlandi, ya&rsquo;ni pestitsidlar birinchi navbatda zararkunandalar ommaviy rivojlanishining oldini oladigan tabiiy kushandalari hisoblangan entomofag-hasharotlar, hashoratxo&lsquo;r qushlar va boshqalarni qirib yo&lsquo;qotadi. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bundan tashqari, ko&lsquo;pchilik zararkunandalar pestitsidlarga barqarorlik hosil qilganligi tufayli agrobiotsenozlar fitosanitariya holati va qishloq xo&lsquo;jalik ekinlarini yetishtirish iqtisodiyotiga ham salbiy ta&rsquo;sir ko&lsquo;rsatadi. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1960 yillarda 200 dan oshiq bo&lsquo;g&lsquo;imoyoqlilar pestitsidlarga nisbatan chidamli bo&lsquo;lib qolgan bo&lsquo;lsalar 80-yillari ularning soni 500 dan oshib ketgan (Zaxarenko, 2001). &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bularning hammasi o&lsquo;simliklarni himoya qilish mutaxassislarida biologik himoyaga nisbatan keskin qiziqish uyg&lsquo;otib, bunda aniqlanuvchi omillar tariqasida qishloq xo&lsquo;jalik ekinlari zararkunandalari miqdorini chegaralaydigan yirtqichlar, parazit yoki kasallik qo&lsquo;zg&lsquo;atuvchilarni alohida qayd qilish o&lsquo;rinlidir. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Respublikamizda biologik himoya usuli ishlab chiqish va uni amaliyotga keng joriy qilish sohasida ma&rsquo;lum yutuqlarga erishildi. Biolaboratoriya va biofabrikalar soni ham keskin o&lsquo;sdi. Adabiyotlarda bulardan tashqari fitonomus entomofaglarining 21 dan ortiq turi keltirilgan. Bizning kuzatishlarimiz mobaynida shulardan xonqizi va oltinko&lsquo;z kabi yirtqichlarning miqdori va ahamiyati yuqoriligi aniqlandi. &nbsp; <strong>1-rasm. Fitonomus entomafagi-xon qizi qo&lsquo;ng&lsquo;izi imagosi</strong> <strong>&nbsp;</strong> Fitonomus entomofaglari, ularni miqdorini saklab qolish va faolligini oshirish to&lsquo;g&lsquo;risida adabiyotlarda tavsiyalar bir kancha olimlar tomonidan berilgan. Bizning kuzatishlarimizda ham dala atrofida begona, nektarga boy o&lsquo;simliklar ko&lsquo;p bo&lsquo;lganda eptomofaglarning xususan batiplektesning miqdori ko&lsquo;pligi kuzatildi. Shuning uchun birinchidan kimyoviy moddalarni qo&lsquo;llamaslik va nektarga boy begona o&lsquo;tlarni kechroq gerbitsidlar qo&lsquo;llamay, o&lsquo;roq bilan o&lsquo;rib va so&lsquo;ligancha dalada qoldirib (bunday qilinganda uchadigan entomofaglar daladan olib ketilishdan qutulishga ulguradi),keyin olib ketilsa maqsadga muvofiq bo&lsquo;ladi. Entomofaglar miqdorini saqlab qolish uchun bedapoyalar atrofidagi begona o&lsquo;tlarni aprelni o&lsquo;rtasida o&lsquo;rib olish va maydalab ko&lsquo;k yemga o&lsquo;radigan o&lsquo;ruvchi agregatlar oldiga o&lsquo;simlikni silkitib entomofaglarni saqlab qolish uchun moslamalar qo&lsquo;yilishi tavsiya etilgan. &nbsp; &nbsp; <strong>Xulosa. </strong>Fitonomus zararkunandalariga qarshi ko&lsquo;proq agrotexnik va biologik qarshi kurash usullaridan foydalanish maqsadga mofiq bo&lsquo;ladi. Fitonomusga qarshi kurash samaradorligini oshirish va uning zararini tez fursatda cheklash uchun beda agrotsenozida kuz, qish va bahor oylarida mazkur hasharot miqdorini, uni taqib etuvchi foydali hasharot va kasallik ko&lsquo;zgatuvchi patogen jonzotlarni hisobga olib, shu asosda zarur kurash tadbirlari va vositalarini qo&lsquo;llashni rejlashtirish lozim.

<strong>Anotatsiya:</strong> Ushbu maqolada O&#39;zbek tili leksikasi tasnifi,leksika turlari,haqida ma&lsquo;lumotlar berilgan. O&lsquo;zbеk tili lеksikasi tasnifi turlari. Leksemani turlicha tasniflash mumkin. Quyida uning ayrimlarini ko&lsquo;rib o&lsquo;tamiz. Leksemalar o&lsquo;zlashgan-o&lsquo;zlashmaganligiga ko&lsquo;ra ikkiga bo&lsquo;linadi: a) o&lsquo;z qatlam; b) o&lsquo;zlashma qatlam. O&lsquo;zbеk tilidagi turkiy so&lsquo;zlar o&lsquo;z qatlam dеyiladi: mеn, sеn, biz, o&lsquo;qi, oq, kеt, bir, bеsh. O&lsquo;z qatlamga oid leksemalarning muhim bеlgilari quyidagilar: 1) bu qatlamga oid leksemalarning o&lsquo;zagi asosan, bir-ikki bo&lsquo;g&lsquo;inli bo&lsquo;ladi: ol, bеr, qol, ota, uka, qo&lsquo;y, echki kabi; 2) bir bo&lsquo;g&lsquo;inli so&lsquo;z ko&lsquo;proq [unli+undosh], [undosh+unli+undosh] shakliga ega: ol, kun, kul, bo&lsquo;l, qil; 3) ikki bo&lsquo;g&lsquo;inli so&lsquo;z ko&lsquo;proq ochiq bo&lsquo;g&lsquo;indan tuziladi: ikki, olma, ola; 4) leksema [r], [l], [v], [h] tovushi bilan boshlanmaydi; 5) leksema oxiri [e], [u], [o] unlisi bilan tugamaydi (undov, taqlid so&lsquo;z, dе fе&rsquo;li bundan mustasno); 6) leksema tarkibida sirg&lsquo;aluvchi [j], bo&lsquo;g&lsquo;iz [h] tovushi uchramaydi (undov va taqlid bundan mustasno); 7) leksemada ikki unli yonma-yon kеlmaydi: saodat, baayni, mutolaa, maorif kabi; 8) sof o&lsquo;zbеkcha qo&lsquo;shimcha undosh bilan boshlanadi: -chi, -li, -lik, -la kabi. Ayrimi unli bilan ham boshlanadi: -im, -ib kabi. Bunda tovush orttirilishi mavjud; 9) [f], [d] kabi yumshoq va lab-tish [v] undoshi sof o&lsquo;zbеkcha leksemaga xos emas: daftar, dard, dil, dunyo, falak, vagon kabi; 10) o&lsquo;zak holidagi fе&rsquo;l, son, taqlid leksema faqat o&lsquo;z qatlamga mansub; 11) o&lsquo;z qatlamga mansub leksema o&lsquo;zagi alohida talaffuz qilinganda, tovush o&lsquo;zgarishi yuz bеrmaydi. O&lsquo;zak holida tovush o&lsquo;zgarishiga uchragan leksema o&lsquo;zlashma qatlamga mansub: go&lsquo;sht, dard, hukm, daftar, kitob kabi; 12) boshqa tildan o&lsquo;zlashgan leksema asosida shu tilda yasalgan so&lsquo;z ham o&lsquo;z qatlamga mansub bo&lsquo;ladi: kitobxona, nonchi, ma&rsquo;rifatli, komputеrchi kabi, 13) o&lsquo;z qatlam leksemasi tutuq bеlgisi bilan yozilmaydi.Qarindosh bo&lsquo;lmagan tildan kirib kеlgan leksema o&lsquo;zlashma, olinma yoki o&lsquo;zlashma qatlam dеyiladi: kitob, daftar, non, ma&rsquo;rifat, tеlеfon, komputеr.O&lsquo;zbеk tilidagi o&lsquo;zlashma leksemaning asosiy qismini fors-tojik, arab tilidan o&lsquo;zlashgan ham ruscha, xalqaro leksema tashkil qiladi.O&lsquo;zbеk tilidagi fors-tojikcha leksemani fonеtik ko&lsquo;rinishiga ko&lsquo;ra o&lsquo;zbеkcha leksemadan farqlash qiyin. Lеkin ayrim muhim bеlgisi mavjud: 1) sirg&lsquo;aluvchi dj tovushi fors-tojikcha leksemada uchraydi: mujda, gijda, mujgon kabi; 2) leksema oxirida undosh qator kеladi: taxt, baxt, dard, go&lsquo;sht, farzand, daraxt kabi; 3) o unlisi cho&lsquo;zib aytiladi: non, darmon, bahor kabi. Lеkin buning barchasi ham asosiy bеlgi bo&lsquo;lolmaydi. O&lsquo;zbеk tilida arabcha o&lsquo;zlashmalar ham talay. Ularning muhim bеlgisi: 1) tutuq bеlgili so&lsquo;z arab tiliga mansub (ruscha, xalqaro leksemalar mustasno); 2) ko&lsquo;plik qo&lsquo;shimchasi leksema oldida bo&lsquo;ladi: xulq-axloq, shе&rsquo;r-ash&rsquo;or, xabar-axbor kabi. 3) -ot, -at, illo, -ullo, -iy, -viy unsuri bilan tugagan leksemalar, asosan, arab tiliga xos: axborot, hayvonot, nabotot, shaxsiyat, tabiat, Abdullo, adabiyot, oilaviy, ilmiy kabi; 4) arabcha leksema tarkibida g, dj, ch, p, ng tovushlari uchramaydi; 5) leksema boshida -ik, -iq, -ak, -mu, -ma unsuri bo&lsquo;ladi: ikrom, iqror, akram, muallim, maktab, mahorat kabi. Leksemalarning qo&lsquo;llanishiga ko&lsquo;ra tasnifi. Leksema qo&lsquo;llanish miqdoriga ko&lsquo;ra farqlanadi. Ko&lsquo;pgina leksemalar chеklanmagan, ba&rsquo;zisi kam qo&lsquo;llanishga ega. Shu jihatdan leksemalar ikki turga bo&lsquo;linadi: a) qo&lsquo;llanishi chеgaralanmagan leksema; b) qo&lsquo;llanishi chеgaralangan leksema. Qo&lsquo;llanilishi chеgaralanmagan leksemalar. O&lsquo;zbеk tili lug&lsquo;at tarkibining asosini ana shu qatlam tashkil etadi. Qo&lsquo;llanilishi chеgaralanmagan leksemalarni shu tilda so&lsquo;zlashuvchi kishi, qanday shеvaga, qaysi hududga, qaysi kasb yoki sohaga mansub bo&lsquo;lishidan qat&rsquo;i nazar, chеklanmagan darajada ishlatadi. Qo&lsquo;llanilishi chеgaralanmagan leksemalar barcha turkumda mavjud: Fе&rsquo;l: ishlamoq, kеlmoq, olmoq, ko&lsquo;rsatmoq, buyurmoq, saylamoq. Ot: ota, ona, non, suv, stol, eshik, tog&lsquo;, yer, shamol, radio. Sifat: shirin, achchiq, qizil, ko&lsquo;k, katta-kichik, xunuk, go&lsquo;zal. Son: bir, o&lsquo;n, yuz, ming. Ravish: hamisha, ba&rsquo;zan, ataylab, hozir, ilgari.Olmosh: kim, nima, qanday, nima qilib, qancha, shu, biz, hamma. Undov va modal: xo&lsquo;p, mayli, rahmat. Ko&lsquo;makchi: uchun, bilan, singari: Bog&lsquo;lovchi: ham, va, bilan, ammo. Yuklama: faqat, xuddi, hatto. Qo&lsquo;llanilishi chеgaralanmagan leksemalarning aksariyati umumturkiy va o&lsquo;zbеkcha. Ammo, shu bilan birga, ular orasida o&lsquo;zlashmasi ham ko&lsquo;p. Masalan: Tojikcha: go&lsquo;sht, non, dard, bobo, dugona, do&lsquo;st.Arabcha: avlod, bilan, inson, sinf, millat, himoya:Qo&lsquo;llanishi chеgaralangan leksemalar ikki guruhga bo&lsquo;linadi: a) qo&lsquo;llanish davri chеgaralangan leksemalar; b) qo&lsquo;llanish doirasi chеgaralangan leksemalar Xuloasa qilib aytganda ,qo&lsquo;llanish davri chеgaralangan leksemalar. Davr taraqqiyoti, ijtimoiy hayotdagi o&lsquo;zgarish tilning lеksikasida ancha sеzilarli. Bunda to&lsquo;rt holat kuzatiladi. Birinchidan, ayrim leksemalar eskirib, istе&rsquo;moldan chiqib kеtsa, ikkinchidan,allaqachon istе&rsquo;moldan chiqib kеtgan leksemalar qayta &ldquo;jonlanadi&rdquo;, uchinchidan, yangi-yangi leksemalar paydo bo&lsquo;ladi, to&lsquo;rtinchidan,nofaol so&lsquo;z faollashadi, istе&rsquo;mol doirasi kеngayadi, ma&rsquo;nosida o&lsquo;zgarish yuz bеradi. Hozirgi adabiy tildagi eskirgan leksemalar eski leksemalar,yangi leksemalarning jami yangi leksemalar, na eskirgan, na yangilik bo&lsquo;yog&lsquo;iga ega bo&lsquo;lgan so&lsquo;z zamonaviy leksemalar dеb yuritiladi. Dеmak, o&lsquo;zbеk tili lеksikasini tarixiylik nuqtayi nazaridan uchta asosiy qatlamga bo&lsquo;lib o&lsquo;rganish mumkin: 1) zamonaviy lеksika; 2) eskirgan lеksika; 3) yangi lеksika.Zamonaviy leksemalar. Hozirgi o&lsquo;zbеk adabiy tili lеksikasining asosini zamonaviy lеksika tashkil etadi. Bu lеksika umumistе&rsquo;mol leksemalar, qo&lsquo;llanilishi chеgaralanmagan leksemalar, faol leksemalar kabi atamalar bilan ham yuritiladi. Eskirgan leksemalar. Eski qatlamga oid leksemalar o&lsquo;ziga xos xususiyatiga ko&lsquo;ra ikkiga bo&lsquo;linadi: 1) tarixiy leksemalar; 2) arxaik leksemalar.

Particle suspension reactors for solar water splitting are capable of generating hydrogen at a cost that is competitive with hydrogen produced from steam methane reforming.1-3 Our team has validated a reactor design that resembles Nature’s Z-scheme where two stacked and connected photocatalyst particle suspension reactor beds together drive overall solar water splitting.3 Electron (and proton) management between the beds occurs by transport of a redox shuttle through a nanoporous separator. Efficient designs require that the redox shuttle is selectively oxidized and reduced at the particles that drive H2 evolution and O2 evolution, respectively. By device physics numerical simulations we showed that even for highly efficient reactor designs (10% STH efficiency) redox shuttle transport between the beds can be sustained with only passive diffusion.3 In my presentation I will report on our team’s recent progress on this design. Using finite-element numerical analyses we modelled and simulated the transient mass transport processes, light absorption, electrochemical kinetics, gas crossover, and thermal transport in the proposed reactor. Experimentally, we synthesized, characterized, and evaluated the photo(electro)chemical performance of the most promising photocatalyst nanocrystallites (BiVO4, WO3, and Rh-doped SrTiO3) as mesoporous thin films and as particles in model reactors, and in the presence of several different redox shuttles and at various pH values. For H2-evolving Rh-doped SrTiO3, we demonstrated that in the presence of Fe(II) the limiting rate of Fe(III) reduction decreases and the rate of H2 evolution increases; however, these desired processes occurred along with undesired Fe(III) reduction and undesired H2 oxidation. Introduction of Ru cocatalysts enhanced performance by increasing the rate of H2 evolution and to a lesser extent undesired Fe(III) reduction. For O2-evolving WO3, we showed that O2 does not interfere with collection of electrons and that selectivity toward Fe(III) reduction is possible at moderate concentrations of Fe(III). Overall, results from several studies using a series of redox shuttles and photocatalyst particles will be presented. Collectively, our efforts represent strides toward achieving a high-level of techno-economic viability in solar water splitting reactors. Acknowledgments: This work was supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Fuel Cell Technologies Incubator Program under Award No. DE-EE0006963 and Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231. References: D. James, G. N. Baum, J. Perez and K. N. Baum, Technoeconomic Analysis of Photoelectrochemical (PEC) Hydrogen Production, Directed Technologies Inc., (US DOE Contract no. GS-10F-009J), Arlington, VA, 2009. A. Pinaud, J. D. Benck, L. C. Seitz, A. J. Forman, Z. Chen, T. G. Deutsch, B. D. James, K. N. Baum, G. N. Baum, S. Ardo, H. Wang, E. Miller, and T. F. Jaramillo, Energy &amp; Environmental Science, 2013, 6, 1983–2002. Bala Chandran, S. Breen, Y. Shao, S. Ardo, and A. Z. Weber, Energy &amp; Environmental Science, 2017, Accepted Manuscript, DOI: 10.1039/C7EE01360D.

The ongoing pandemic of COVID-19 has forced us to consider using available drugs in the shortfall of vaccines and established treatment. Cotrimoxazole is one of the oldest drugs presently used in the prevention and treatment of opportunistic infections in the human immune deficiency virus (HIV) etc. It is a combination of two drugs Trimethoprim and Sulfamethoxazole. This cost-effective old drug is well tolerated among the population with the concomitant use of folic acid; moreover, it also looks after the secondary infections. To conclude, Cotrimoxazole can be used as critically ill COVID-19 patients.&#x0D; &#x0D; References &#x0D; &#x0D; Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive care Med. 2020;46(5): 846–48. https://doi.org/10.1007/s00134-020-05991-x&#x0D; Rozin A, Schapira D, Braun-Moscovici Y, Nahir AM. Cotrimoxazole treatment for rheumatoid arthritis. Semin Arthritis Rheum. 2001;31(2):133-41.&#x0D; Bourke CD, Gough EK, Pimundu G, Shonhai A, Berejena C, Terry L, et al. Cotrimoxazole reduces systemic inflammation in HIV infection by altering the gut microbiome and immune activation. Sci Transl Med. 2019;11(486): eaav0537. https://doi.org/10.1126/scitranslmed. aav0537&#x0D; Liu B, Li M, Zhou Z, Guan X, Xiang Y. Can we use interleukin-6 (IL-6) blockade for coronavirus disease 2019 (COVID-19)-induced cytokine release syndrome (CRS)? J Autoimmun. 2020; 111:102452. https://doi.org/10.1016/j.jaut.2020.102452&#x0D; Vickers IE, Smikle MF. The immunomodulatory effect of antibiotics on the secretion of tumour necrosis factor alpha by peripheral blood mononuclear cells in response to Stenotrophomonas maltophilia stimulation. West Indian Med J. 2006;55(3):138-41. https://doi.org/10.1590/s0043-31442006000300002&#x0D; Onyebuagu PC, Kiridi K, Pughikumo DT. Effects of septrin administration on blood cells parameters in humans. Int. J. Basic Appl. Innov. Res, 2014;3(1): 14 -8. https://www.ajol.info/index.php/ijbair/article/view/104688&#x0D; Ho JMW, Juurlink DN. Considerations when prescribing trimethoprim– sulfamethoxazole. CMAJ. 2011; 183(16):1851-8. https://doi.org/10.1503/cmaj.111152&#x0D; Mahan CS, Walusimbi M, Johnson DF, Lancioni C, Charlebois E, Baseke J, et al. Tuberculosis treatment in HIV infected Ugandans with CD4 counts .350 cells/mm3 reduces immune activation with no effect on HIV load or CD4 count. PLoS one.2010;5(2): e9138. https://doi.org/10.1371/journal.pone.0009138&#x0D; Varney VA, Smith B, Quirke G, Parnell H, Ratnatheepan S, Bansal AS, et al. P49 the effects of oral cotrimoxazole upon neutrophil and monocyte activation in patients with pulmonary fibrosis and healthy controls; does this relate to its action in idiopathic pulmonary fibrosis. Thorax. 2017;72: A109. http://dx.doi.org/10.1136/thoraxjnl-2017-210983.191&#x0D;

<em>Ushbu maqolada</em><em> </em><em>M</em><em>а</em><em>ml</em><em>а</em><em>k</em><em>а</em><em>timizd</em><em>а</em><em> </em><em>а</em><em>m</em><em>а</em><em>lg</em><em>а</em><em> </em><em>о</em><em>shiril</em><em>а</em><em>yotg</em><em>а</em><em>n tub iqtis</em><em>о</em><em>diy isl</em><em>о</em><em>h</em><em>о</em><em>tl</em><em>а</em><em>rd</em><em>а</em><em> f</em><em>ао</em><em>l t</em><em>а</em><em>dbirk</em><em>о</em><em>rlikni riv</em><em>о</em><em>jl</em><em>а</em><em>ntirishg</em><em>а</em><em> </em><em>а</em><em>l</em><em>о</em><em>hid</em><em>а</em><em> e&rsquo;</em><em>tib</em><em>о</em><em>r q</em><em>а</em><em>r</em><em>а</em><em>tilm</em><em>о</em><em>qd</em><em>а</em><em>. R</em><em>е</em><em>spublik</em><em>а</em><em>mizd</em><em>а</em><em> eksp</em><em>о</em><em>rtni h</em><em>а</em><em>r t</em><em>о</em><em>m</em><em>о</em><em>nl</em><em>а</em><em>m</em><em>а</em><em> qo&lsquo;ll</em><em>а</em><em>b-quvv</em><em>а</em><em>tl</em><em>а</em><em>sh</em><em> </em><em>v</em><em>а</em><em> r</em><em>а</em><em>g&lsquo;b</em><em>а</em><em>tl</em><em>а</em><em>ntirish,</em><em> </em><em>uning h</em><em>а</em><em>jmi b</em><em>а</em><em>rq</em><em>а</em><em>r</em><em>о</em><em>r o&lsquo;sishini t</em><em>а</em><em>&rsquo;</em><em>minl</em><em>а</em><em>sh v</em><em>а</em><em> t</em><em>а</em><em>rkibini</em><em> </em><em>t</em><em>а</em><em>k</em><em>о</em><em>mill</em><em>а</em><em>shtirish, m</em><em>а</em><em>ml</em><em>а</em><em>k</em><em>а</em><em>timizning eksp</em><em>о</em><em>rt s</em><em>а</em><em>l</em><em>о</em><em>hiyatini </em><em>о</em><em>shirishd</em><em>а</em><em> </em><em>х</em><em>ususiy t</em><em>а</em><em>dbirk</em><em>о</em><em>rlikning r</em><em>о</em><em>lini h</em><em>а</em><em>r t</em><em>о</em><em>m</em><em>о</em><em>nl</em><em>а</em><em>m</em><em>а</em><em> </em><em>о</em><em>shirish, eksp</em><em>о</em><em>rtchi k</em><em>о</em><em>r</em><em>хо</em><em>n</em><em>а</em><em>l</em><em>а</em><em>rni</em><em> m</em><em>о</em><em>liyaviy qo&lsquo;ll</em><em>а</em><em>b-quvv</em><em>а</em><em>tl</em><em>а</em><em>shni</em><em> </em><em>yan</em><em>а</em><em>d</em><em>а</em><em> kuch</em><em>а</em><em>ytirish,</em><em> </em><em>milliy m</em><em>а</em><em>hsul</em><em>о</em><em>tl</em><em>а</em><em>rning</em><em> </em><em>t</em><em>а</em><em>shqi b</em><em>о</em><em>z</em><em>о</em><em>rl</em><em>а</em><em>rd</em><em>а</em><em>gi</em><em> r</em><em>а</em><em>q</em><em>о</em><em>b</em><em>а</em><em>tb</em><em>а</em><em>rd</em><em>о</em><em>shligini must</em><em>а</em><em>hk</em><em>а</em><em>ml</em><em>а</em><em>sh v</em><em>а</em><em> v</em><em>а</em><em>lyut</em><em>а</em><em> tushuml</em><em>а</em><em>rini ko&lsquo;p</em><em>а</em><em>ytirish h</em><em>о</em><em>zirgi kund</em><em>а</em><em> </em><em>m</em><em>а</em><em>ml</em><em>а</em><em>k</em><em>а</em><em>timizd</em><em>а</em><em> h</em><em>а</em><em>l qilinishi l</em><em>о</em><em>zim bo&lsquo;lg</em><em>а</em><em>n d</em><em>о</em><em>lz</em><em>а</em><em>rb</em><em> </em><em>m</em><em>а</em><em>s</em><em>а</em><em>l</em><em>а</em><em>l</em><em>а</em><em>rd</em><em>а</em><em>n</em><em> </em><em>s</em><em>а</em><em>n</em><em>а</em><em>l</em><em>а</em><em>di. Bund</em><em>а</em><em> birinchi</em><em> </em><em>n</em><em>а</em><em>vb</em><em>а</em><em>td</em><em>а</em><em>,&nbsp; t</em><em>а</em><em>dbirk</em><em>о</em><em>rlik sub</em><em>&rsquo;</em><em>е</em><em>ktl</em><em>а</em><em>rining t</em><em>а</em><em>shqi iqtis</em><em>о</em><em>diy f</em><em>ао</em><em>liyatini m</em><em>о</em><em>liyal</em><em>а</em><em>shtirish tizimini t</em><em>а</em><em>k</em><em>о</em><em>mill</em><em>а</em><em>shtirish,</em><em> </em><em>а</em><em>yniqs</em><em>а</em><em> tij</em><em>о</em><em>r</em><em>а</em><em>t b</em><em>а</em><em>nkl</em><em>а</em><em>rining</em><em> </em><em>bu j</em><em>а</em><em>r</em><em>а</em><em>yond</em><em>а</em><em>gi ishtir</em><em>о</em><em>ki v</em><em>а</em><em> f</em><em>ао</em><em>lligini riv</em><em>о</em><em>jl</em><em>а</em><em>n</em><em>tirish to&lsquo;g&lsquo;risida fikir va mulohazalar keltirilgan.</em>

<strong>ABSTRACT</strong> <strong>Background:</strong> This study attempted to review the medical records of all patients with spinal bone metastases presented to Alexandria Clinical Oncology and Nuclear Medicine Department (ACOD), Alexandria Main University Hospital during the period from January 2003 to December 2012. <strong>Patients and Methods:</strong> A total of 350 patients were included in this study. Medical records were retrospectively reviewed and data were collected as regard demographic data, medical history, Clinical data, Investigations and diagnostic work up, treatment modalities and treatment outcomes. <strong>Results:</strong> we observed that the origin of the tumor in the majority of cases was breast cancer (31.1%), followed by prostate cancer 17.7% then multiple myeloma 17.1%.The female patients presented with the highest percentage 60.9%.performance status according Eastern Cooperative Oncology Group ( ECOG) score was 0-2 in 58% of patients. The majority of patients were complaining of pain (98.6%). A considerable percentage of cases presented with symptoms of spinal cord compression (30%). Improvement regarding pain after treatment with radiotherapy was reported in (42.6%) of patients. Motor function improvement was (89.7%) at 8 weeks for patients presented with paresis and treated early. Type of primary tumor was the most significant prognostic factor (HR=6.873 and 4.431, P &lt;0.001). <strong>Conclusions:</strong> Breast cancer, prostate cancer and multiple myeloma constituted the most common primaries that develop spinal metastases. A higher incidence of spinal metastases in women compared with men. The predominant symptom in patients with spinal metastases was pain. Patients who developed spinal metastases were at risk of spinal cord compression. The goals of treatment were to relieve pain and prevent complications. External beam radiotherapy has been the mainstay for palliating pain resulting from spinal metastases. Early initiation of radiotherapy promote better functional outcome. Type of primary tumor was identified as the most powerful prognostic factor for patients with spinal metastases. <strong>Key Words:</strong> Spinal metastases, clinical oncology, breast cancer, prostate cancer and multiple&nbsp;myeloma. <strong>REFERENCES</strong> &nbsp; Helweg-Larsen S, Sorensen PS. Symptoms and signs in metastatic spinal cord compression: a study of progression from first symptom until diagnosis in 153 patients. Eur J Cancer 1994; 30A: 396-8. Ortiz Gomez JA. The incidence of vertebral body metastases. Int Orthop 1995; 19: 309-11. Nayyar T. Spinal metastates. In: Thamburaj VA (ed). Textbook of contemporary neurosurgery. Vol. 1 &amp; 2. New Delhi, India: Jaypee Brothers, Medical Publishers Pvt. Limited; 2012. 1471-83. Van der Sande JJ, Boogerd W, Kroger R, Kapelle AC. Recurrent spinal epidural metastases: a pro-spective study with a complete follow up. J Neurol Neurosurg Psychiatry 1999; 66: 623-7. Sagban WJ, Ridha SMS, Hasan ZN. Comparison between metastatic spinal tumor of unknown primary tumor with a known primary. World J Neurosci 2015;6(01):18. Camins MB, Jenkins AL, Singhal A, Perrin RG. Tumors of the vertebral axis: benign, primary malignant, and metastatic tumors. In: Winn RH, Youmans JR (eds). Youmans neurological surgery. 5^th ed. Philadelphia: W.B. Saunders Company; 2004. 4835-68. Bach F, Larsen BH, Rohde K, B&oslash;rgesen SE, Gjerris F, B&oslash;ge-Rasmussen T, et al. Metastatic spinal cord compression. Occurrence, symptoms, clinical presentations and prognosis in 398 patients with spinal cord compression. Acta Neurochir (Wien) 1990; 107: 37-43. Jacobs WB, Perrin RG. Evaluation and treatment of spinal metastases: an overview. Neurosurg Focus 2001; 11: e10. Ruckdeschel JC. Early detection and treatment of spinal cord compression. Oncology (Williston Park) 2005; 19: 81-6. Costelloe CM, Rohren EM, Madewell JE, Hamaoka T, Theriault RL, Yu TK, et al. Imaging bone metastases in breast cancer: techniques and recommendations for diagnosis. Lancet Oncol 2009; 10: 606-14. B&uuml;nger C, Laursen M, Hansen E. A new algorithm for the surgical treatment of spinal metastases. Spine 1999; 24: 101-5. Tokuhashi Y, Matsuzaki H, Oda H, Oshima M, Ryu J. A revised scoring system for preoperative evaluation of metastatic spine tumor prognosis. Spine 2005; 30: 2186-91. Cole JS, Patchell RA. Metastatic epidural spinal cord compression. Lancet Neurol 2008; 7: 459-66. Chow E, Harris K, Fan G, Tsao M, Sze WM. Palliative radiotherapy trials for bone metastases: a systematic review. J Clin Oncol 2007; 25: 1423-36. Landreneau FE, Landreneau RJ, Keenan RJ, Ferson PF. Diagnosis and management of spinal metastases frombreast cancer. J Neurooncol 1995; 23: 121-34. Costa L, Major PP. Effect of bisphosphonates on pain and quality of life in patients with bone metastases. Nat Clin Pract Oncol 2009; 6: 163-74. Jansson K, Bauer H. Survival complication and outcome in 282 patients operate neurological deficit due to thoracic or lumbar spinal metastases. Eur Spine J 2006; 15: 196-202. Zaikova O, Foss&aring; SD, Bruland &Oslash;S, Giercksky KE, Sandstad B, Skjeldal S. Radiotherapy or surgery for spine metastases? A population-based study of 903 patients in the south-eastern region of Norway.&nbsp;Acta Orthopaedica 2011; 82: 365-71. Gasbarrini A, Li H, Cappuccio M, Mirabile L, Paderni S, Terzi S, et al. Efficacy evaluation of a new treatment algorithm for spinal metastases. Spine (Phila Pa 1976) 2010; 35: 1466-70. Harel R, Angelov L.&nbsp;Spine metastases: current treatments and future directions.&nbsp;Eur J Cancer 2010; 46: 2696-707. Rades D, Fehlauer F, Schulte R, Veninga T, Stalpers LJ, Basic H, et al. Prognostic factors for local control and survival after radiotherapy of metastatic spinal cord compression. J Clin Oncol 2006; 24: 3388-93. Porika Raju and Estari Mamidala (2015). Anti-diabetic activity of compound isolated from Physalis angulata fruit extracts in alloxan induced diabetic rats. The Ame J Sci &amp; Med Res, 2015,1(1); Pages 1 -6. doi:10.17812/ajsmr2015.11.1. &nbsp; Papastefanou S, Alpantaki K, Akra G, Katonis P. Predictive value ofop Tokuhashi and Tomita scores in patients with metastatic spine disease. Acta Orthop Traumatol Turc 2012; 46: 50-6. Botterell EH, Fitzgerald GN. Spinal cord compression produced by extradural malignant tumors. Can Med Assoc J 1959; 80: 791-6. Georgy&nbsp;BA. Metastatic spinal lesions: state-of-the-art treatment options and future trends.&nbsp;AJNR Am J Neuroradiol&nbsp;2008; 29: 1605-11. Yang Z, Yang Y, Zhang Y, Zhang Z, Chen Y, Shen Y, et al. Minimal access versus open spinal surgery in treating painful spine metastasis: A systematic review. World J Surg Oncol 2015; 13: 68. Paholpak P, Sirichativapee W, Wisanuyotin T, Kosuwon W, Jeeravipoolvarn P. Prevalence of Known and Unknown Primary Tumor Sites In Spinal Metastasis Patients. Open Orthop J 2012; 6: 440-4. Hartsell WF, Scott CB, Bruner DW, Scarantino CW, Ivker RA, Roach M 3rd, et al. Randomized trial of short- versus long-course radiotherapy for palliation of painful bone metastases. J Natl Cancer Inst 2005; 97: 798-804. Zaikova O, Foss&aring; SD, Kongsgaard U, Kval&oslash;y S, Giercksky KE, Skjeldal S. Pain after palliative radiotherapy for spine metastases. Clin Oncol 2010; 22: 828-36. Kataoka M, Kunisada T, Tanaka M, Takeda K, Itani S, Sugimoto Y, et al. Statistical analysis of prognostic factors for survival in patients with spinal metastasis. Acta Med Okayama 2012; 66: 213-9

e4139111This article features schools and school districts with successful induction programs, all easily replicable. Increasingly, research confirms that teacher and teaching quality are the most powerful predictors of student success. In short, principals ensure higher student achievement by assuring better teaching. To do this, effective administrators have a new teacher induction program available for all newly hired teachers, which then seamlessly becomes part of the lifelong, sustained professional development program for the district or school. What keeps a good teacher are structured, sustained, intensive professional development programs that allow new teachers to observe others, to be observed by others, and to be part of networks or study groups where all teachers share together, grow together, and learn to respect each other’s work.ResumoEste artigo apresenta escolas e distritos escolares com programas bem sucedidos de indução, todos facilmente replicáveis. Cada vez mais, a pesquisa confirma que o professor e a qualidade do ensino são os mais poderosos preditores do sucesso do aluno. Em suma, os diretores garantem maior desempenho dos alunos, garantindo melhor ensino. Para fazer isso, os administradores eficazes têm um novo programa de indução de professores disponível para todos os professores recém-contratados, que então se torna parte do programa de desenvolvimento profissional sustentado ao longo da vida para o distrito ou escola. O que mantém um bom professor são programas estruturados, constantes e intensivos de desenvolvimento profissional que permitem que os novos professores observem outros, sejam observados por outros e façam parte de redes ou grupos de estudo onde todos os professores compartilham juntos, crescem juntos e aprendem a respeitar o trabalho um do outro.Tradução do original WONG, Harry K. “Induction Programs That Keep New Teachers Teaching and Improving”. NASSP Bulletin – Vol. 88 No 638 March 2004. © Harry K. Wong Publications, Inc. por Adriana Teixeira Reis.Palavras-chave: Programas de indução, Professor iniciante, Desenvolvimento profissional docente.Keywords: Induction programs, Beginner teacher, Teacher professional development.ReferencesALLINGTON, R. (2003). The six ts of effective elementary literacy instruction. Retrieved from www.readingrockets.org / article.php?ID=413.BREAUX, A., &amp; WONG, H. (2003). New teacher induction: How to train, support, and retain new teachers. Mountain View, CA: Harry K. Wong Publications.BRITTON, E., PAINE, L., PIMM, D., &amp; RAIZEN, S. (Eds.). (2003). Comprehensive teacher induction: Systems for early career learning. State: Kluwer Academic Publishers and WestEd.CROSS, C. T., &amp; RIGDEN, D. W. (2002, April). Improving teacher quality [Electronic version]. American School Board Journal, 189(4), 24–27.DARLING-HAMMOND, L., &amp; SYKES, G. (2003). Wanted: A national teacher sup- ply policy for education: The right way to meet the “highly qualified teacher” challenge. Education Policy Analysis Archives, 11(33). Retrieved from http: // epaa.asu.edu / epaa / v11n33 /DARLING-HAMMOND, L., &amp; YOUNGS, P. (2002). Defining “highly qualified teachers”: What does scientifically-based research actually tell us? Educational Researcher, 31(9), 13–25.DEPAUL, A. (2000). Survival guide for new teachers: How new teachers can work effec- tively with veteran teachers, parents, principals, and teacher educators. Jessup, MD: U.S. Department of Education, Office of Educational Research and Improvement.DRUMMOND, S. (2002, April 18). What will it take to hold onto the next gen- eration of teachers? Harvard Graduate School of Education News. Retrieved from www.gse.harvard.edu / news / features / ngt04182002.htmlELMORE, R. (2002, January/ February). The limits of “change.” Harvard Education Letter. Retrieved from www.edletter.org / past / issues / 2002-jf / limitsofchange.shtmlFEIMAN-NEMSER, S. (1996). Teacher mentoring: A critical review. Washington, DC: ERIC Clearinghouse on Teaching and Teacher Education. (ERIC Document Reproduction Service No. ED397060)FULLAN, M. (2001). The new meaning of educational change (3rd ed.). New York: Teachers College Press.FULLAN, M. (2003). Change forces with a vengeance. London: Routledge Falmer.GARET, M., Porter, A., DESMOINE, L., BIRMAn, B., &amp; KWANG, S. K. (2001). What makes professional development effective? American Educational Research Journal, 38(4), 915–946.GREENWALD, R., HEDGES, L., &amp; LAINE, R. (1996). The effect of school resources on student achievement. Review of Educational Research, 66(3), 361–396.HANUSHEK, E. A., KAIN, J. F., &amp; RIVKIN, S. G. (2001). Why public schools lose teachers (NBER Working Paper No. 8599). Cambridge, MA: National Bureau of Economic Research.HARE, D., &amp; HEAP, J. (2001). Effective teacher recruitment and retention strategies in the Midwest. Naperville, IL: North Central Regional Laboratory. Re- trieved June 26, 2002, from www.ncrel.org / policy/ pubs / html / strategy/ index.htmlHASSEL, E. (1999). Professional development: Learning from the best. Naperville, IL: North Central Regional Educational Laboratory.HIEBERT, H., GALLIMORE, R., &amp; STIGLER, J. (2002). A knowledge base for the teaching profession: What would it look like and how can we get one? Educational Researcher, 31(5), 3–15.JOHNSON, S., &amp; BIRKELAND, S. (2003). Pursuing a sense of success: New teach- ers explain their career decisions. American Educational Research Journal, 40(3), 581–617.JOHNSON, S. M., &amp; KARDOS, S. M. (2002). Keeping new teachers in mind. Educational Leadership, 59(6), 13–16.KARDOS, S. (2003, April). Integrated professional culture: Exploring new teachers’ experiences in 4 states. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL.LEHMAN, P. (2003, November 26). Ten steps to school reform at bargain prices. Education Week, 23(13), 36, 28.LIU, E. (2003, April). New teachers’ experiences of hiring: Preliminary findings from a 4-state study. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL.MARTIN, S. (2003, March). From the ground up: Building your own university. Paper presented at the annual meeting of the Association of Supervision and Curriculum Development, San Francisco, CA.NORTH CAROLINA TEACHING FELLOWS COMMISSION. (1995). Keeping talented teach- ers. Raleigh, NC: Public School Forum of North Carolina.PALOMBO, M. (2003). A network that puts the net to work. Journal of Staff Development, 24(1), 24–28.ROTHMAN, R. (2002 / 2003). Transforming high schools into small learning communities. Challenge Journal, 6(2), 1–8.SANDERS, W. (1996). Cumulative and residual effects of teachers on future student academic achievement. Knoxville, TN: University of Tennessee Value-Added Research &amp; Assessment Center.SAPHIER, J., FREEDMAN, S., &amp; ASCHHEIM, B. (2001). Beyond mentoring: How to nurture, support, and retain new teachers. Newton, MA: Teachers21.SCHLAGER, M., FUSCO, J., KOCH, M., CRAWFORD, V., &amp; PHILLIPS, M. (2003, July). Designing equity and diversity into online strategies to support new teachers. Paper presented at the National Educational Computing Conference (NECC), Seattle, WA.SERPELL, Z., &amp; BOZEMAN, L. (1999). Beginning teacher induction: A report of beginning teacher effectiveness and retention. Washington, DC: National Partnership for Excellence and Accountability in Teaching.WONG, H. (2001, August 8). Mentoring can’t do it all. Education Week, 20(43), pp. 46, 50.WONG, H. (2002a). Induction: The best form of professional development. Educational Leadership, 59(6), 52–55.WONG, H. (2002b). Play for keeps. Principal Leadership, 3(1), 55–58.WONG, H. (2003a). Collaborating with colleagues to improve student learn- ing. ENC Focus, 11(6), 9.WONG, H. (2003b, October). Induction: How to train, support, and retain new teachers. Paper presented at the conference of the National Staff Development Council.WONG, H. (2003c). Induction programs that keep working. In M. Scherer (Ed.), Keeping good teachers ( pp. 42–49). Alexandria, VA: Association of Supervision and Curriculum Development.WONG, H., &amp; ASQUITH, C. (2002). Supporting new teachers. American School Board Journal, 189(12), p. 22.YOUNGS, P. (2003). State and district policies related to mentoring and new teacher induction in Connecticut. New York: National Commission on Teaching and America’s Future.

<strong>ABSTRACT</strong> The current scenarios among academicians are that they are in the rat race to either publish their work in high indexed journals or perish. This is paving the way for mushrooming up ghostwriters in the academic sector. Ghostwriting is a process of receiving help from a professional writer to create scholarly content on behalf of the author who gets official end credit. There are numerous unethical forms of academic deceitfulness to start with; it can be from the fabrication of the data to multiple submissions at various journals with minor changes, plagiarism and finally ghostwriting which is a non- traditional unethical sort of problem. These ghostwriters can work on various capacities as individual freelancers or consultants; they might also be attached to major publishing houses and are hired by individuals or firms to write the manuscripts for well-known journals citing it for established authors. This is a modern kind of plagiarism and has a lot of adverse effects, thus resulting in unethical practices followed in the academic sector. In this present article, the author tries to discuss the concept of ghostwriting, motivation for writing, types and possible strategies are been suggested to overcome it. &nbsp; <strong>REFERENCE</strong> Scott-Lichter D. Reston, Va. (2009). Editorial Policy Committee, Council of Science Editors. CSE&#39;s White Paper on Promoting Integrity in Scientific Journal Publications, 2009 Update. Available from URL: http://www.councilscienceeditors .org/ files /public /entire_whitepaper.pdf . Lines, L. (2016). Ghostwriters guaranteeing grades? The quality of online ghostwriting services available to tertiary students in Australia. Teaching in Higher Education, 21(8), 889&ndash;914. doi:10.1080/13562517.2016.1198759 Jacobs, A., &amp; Wager, E. (2005). European Medical Writers Association (EMWA) guidelines on the role of medical writers in developing peer-reviewed publications. Current Medical Research and Opinion, 21(2), 317&ndash;321. doi:10.1185/030079905x25578 G&oslash;tzsche, P. C., Hr&oacute;bjartsson, A., Johansen, H. K., Haahr, M. T., Altman, D. G., &amp; Chan, A.-W. (2007). Ghost Authorship in Industry-Initiated Randomised Trials. PLoS Medicine, 4(1), e19. doi:10.1371/journal.pmed.0040019 Lacasse, J. R., &amp; Leo, J. (2010). Ghostwriting at Elite Academic Medical Centers in the United States. PLoS Medicine, 7(2), e1000230. doi:10.1371/journal.pmed.1000230 World Association of Medical Editors. Policy Statements Prepared by the WAME Editorial Policy Committee. URL: https://www.wame.org/policies. Lissoni, F., &amp;Montobbio, F. (2014). Guest Authors or Ghost Inventors? Inventorship and Authorship Attribution in Academic Science. Evaluation Review, 39(1), 19&ndash;45. doi:10.1177/0193841x13517234 DeTora, L. M., Carey, M. A., Toroser, D., &amp; Baum, E. Z. (2019). Ghostwriting in biomedicine: a review of the published literature. Current Medical Research and Opinion, 1&ndash;1. doi:10.1080/03007995.2019.1608101 Matheson, A. (2016). The Disposable Author:How Pharmaceutical Marketing Is Embraced within Medicine&rsquo;s Scholarly Literature. Hastings Center Report, 46(4), 31&ndash;37. doi:10.1002/hast.576 Sismondo, S., &amp;Doucet, M. (2009). Publication Ethics and the Ghost Management of Medical Publication. Bioethics, 24(6), 273&ndash;283. doi:10.1111/j.1467-8519.2008.01702.x

BackgroundMagnetic resonance imaging and histological studies have shown that iron levels are dysregulated in rheumatoid arthritis (RA) patients, with iron accumulation in gray matter and a considerable loss in healthy white matter. Iron accumulation in RA environment is closely related to immune disorders. Deferoxamine (DFO) is an iron complexing agent that has been shown to attenuate RA development. It has previously been reported that the suppression funtction of natural regulatory T cells (nTreg) is impaired in RA patients. It is still unclear how iron disrupts immune cells dysfunction in the RA milieu, and whether regulating iron is beneficial for Treg cell expansion and function maintenance.ObjectivesThe purpose of this work is to identiy the underlying gene expression profile of ferroptotic-induced dysregulatory RA-Treg, and to investigate the possible application of TGF-induced Treg (iTreg) in the treatment of RA.MethodsWe established a collagen-induced arthritis (CIA) mouse model, a typical animal model of autoimmune arthritis, and performed single cell RNA-sequencing (scRNA-seq) to discover different Treg populations in the joints of CIA mouse models. We also analyzed RNA-seq data from imidazole ketone erastin (IKE), a ferroptosis inducer treated nTreg and iTreg.ResultsData from single-cell RNA sequencing further identify two groups of Treg cells that have distinct susceptibility to RA challenges, with the ferroptosis-susceptibility Treg associated with an increased insulin-like growth factor 1 (IGF1)-related transcriptome. Mechanistically, IGF1 receptor (IGF1R) activates the AKT-mTOR pathway, increases aerobic glycolysis, promotes Treg conversion toward Th17 differentiation, and increases pro-inflammatory cytokines production. Moreover, RNA-sequencing analysis indicated that imidazole ketone erastin (IKE), a ferroptosis inducer, increases the expression of ferroptosis-associated genes in nTreg but not iTreg, and iTreg attenuated arthritis progression in the IKE-aggravated CIA model.ConclusionOur findings suggest that increasing IGF1 and glycolysis account for Treg dysfunction and inflammation in RA, and the novel iTreg may serve as a potential candidate for RA therapy.References[1]Miyara M, Ito YSakaguchi S. TREG-cell therapies for autoimmune rheumatic diseases.Nat Rev Rheumatol. 2014;10:543-51.[2]Buckner JH. Mechanisms of impaired regulation by CD4(+)CD25(+)FOXP3(+) regulatory T cells in human autoimmune diseases.Nat Rev Immunol. 2010;10:849-59.[3]Gao X, Song Y, Lu S, Hu L, Zheng M, Jia SZhao M. Insufficient Iron Improves Pristane-Induced Lupus by Promoting Treg Cell Expansion.Front Immunol. 2022;13:799331.[4]Xu C, Sun S, Johnson T, Qi R, Zhang S, Zhang JYang K. The glutathione peroxidase Gpx4 prevents lipid peroxidation and ferroptosis to sustain Treg cell activation and suppression of antitumor immunity.Cell Rep. 2021;35:109235.[5]Wu J, Feng Z, Chen L, Li Y, Bian H, Geng J,... Zhu P. TNF antagonist sensitizes synovial fibroblasts to ferroptotic cell death in collagen-induced arthritis mouse models.Nat Commun. 2022;13:676.[6]DiToro D, Harbour SN, Bando JK, Benavides G, Witte S, Laufer VA,... Weaver CT. Insulin-Like Growth Factors Are Key Regulators of T Helper 17 Regulatory T Cell Balance in Autoimmunity.Immunity. 2020;52:650-667 e10.[7]Laurence D, Benjamin CD, Patricia V, Sylvie R, Yannick J, Anne GFrédéric B. Soluble mannose 6-phosphate/insulin-Like growth factor II (IGF-II) receptor inhibits interleukin-6-type cytokine-dependent proliferation by neutralization of IGF-II.Endocrinology. 2003;5381-9.[8]Delgoffe G, Kole T, Zheng Y, Zarek P, Matthews K, Xiao B,... Powell J. The mTOR kinase differentially regulates effector and regulatory T cell lineage commitment.Immunity. 2009;30:832-44.AcknowledgementsThis work was supported by Scientific and Technological Planning Project of Guangzhou City [202102020150], Guangdong Provincial Basic and Applied Basic Research Fund Project [2021A1515111172], National Natural Science Foundation of China Youth Fund [82201999, 82201998] and Third Affiliated Hospital of Sun Yat-Sen University Cultivating Special Fund Project for National Natural Science Foundation of China [2022GZRPYQN01].Disclosure of InterestsNone Declared.

BackgroundThe Lewis Y (CD174) carbohydrate antigen is widely expressed in primary and metastatic epithelial tumors like colon, lung, ovarian, and breast. Targeting Lewis Y for cancer therapy was pursued before, however, other anti-Lewis Y antibodies tested in clinical trials showed cross-reactivity to related carbohydrate structures expressed on blood cells and mostly failed for efficacy and/or safety reasons.1–4 We have developed a humanized antibody (GT-001) that shows superior fine-specificity and higher affinity compared to clinically tested anti-Lewis Y antibodies BR96 and h3S193.MethodsThe specificity and cross-reactivity of GT-001, BR96 and h3S193 were compared. Cross-reactivity binding to related carbohydrate PAA-conjugates was tested via ELISA and affinity towards Lewis Y-PAA was measured using switchSENSE® technology (DRX2, Dynamic Biosensors). Functional binding to several tumor cell lines and healthy human leukocytes was analyzed via flow cytometry. Binding of GT-001 to different cancer indications was analyzed by immunohistochemistry. Inhibition of tumor cell proliferation was tested using GT-001 coupled to ProtG-MMAE.ResultsGT-001 is strictly specific for Lewis Y and does not cross-react with &gt;90 related carbohydrate structures tested. Our lead candidate shows superior fine-specificity compared to BR96, for which we could confirm the reported cross-reactivity towards Lewis X,5 and stronger binding of Lewis Y compared to h3S193 as shown by affinity measurement. Further, GT-001 shows no/weak binding to blood cells whereas BR96 and h3S193 significantly bind to different leukocyte subsets. IHC studies reveal that GT-001 stains tumor tissue of different cancer indications (breast cancer, colorectal cancer, head and neck cancer, (non) small cell lung cancer and ovarian cancer) at a high percentage of cases. In ADC surrogate assays, GT-001 potently inhibits the proliferation of several tumor cell lines indicating effective internalization.ConclusionsLewis Y is expressed on many epithelial tumor indications of high medical need. However, several approaches of targeting Lewis Y have failed in the past for efficacy and/or safety reasons. We have developed a humanized antibody that shows superior fine-specificity and higher affinity compared to clinically tested anti-Lewis Y antibodies BR96 and h3S193. Due to the superior fine-specificity, GT-001 shows no/reduced binding of healthy leukocytes potentially reducing side effects as observed for BR96 in the clinic. Its strong target binding and internalization properties make GT-001 an ideal candidate for ADC development.ReferencesAjani JA, Kelsen DP, Haller D, Hargraves K, Healey D. A multi-institutional phase II study of BMS-182248-01 (BR96-doxorubicin conjugate) administered every 21 days in patients with advanced gastric adenocarcinoma. Cancer J 2000;6(2):78–81.Saleh MN, Sugarman S, Murray J, Ostroff JB, Healey D, Jones D, Daniel CR, LeBherz D, Brewer H, Onetto N, LoBuglio AF. Phase I trial of the anti-Lewis Y drug immunoconjugate BR96-doxorubicin in patients with lewis Y-expressing epithelial tumors. J Clin Oncol 2000;18(11):2282–92.Scott AM, Tebbutt N, Lee FT, Cavicchiolo T, Liu Z, Gill S, Poon AM, Hopkins W, Smyth FE, Murone C, MacGregor D, Papenfuss AT, Chappell B, Saunder TH, Brechbiel MW, Davis ID, Murphy R, Chong G, Hoffman EW, Old LJ. A phase I biodistribution and pharmacokinetic trial of humanized monoclonal antibody Hu3s193 in patients with advanced epithelial cancers that express the Lewis-Y antigen. Clin Cancer Res 2007;13(11):3286–92.Smaletz O, Diz MD, do Carmo CC, Sabbaga J, Cunha-Junior GF, Azevedo SJ, Maluf FC, Barrios CH, Costa RL, Fontana AG, Madrigal V, Wainstein AJ, Yeda FP, Alves VA, Moro AM, Blasbalg R, Scott AM, Hoffman EW. A phase II trial with anti-Lewis-Y monoclonal antibody (hu3S193) for the treatment of platinum resistant/refractory ovarian, fallopian tube and primary peritoneal carcinoma. Gynecol Oncol 2015;138(2):272–7.Zhang S, Zhang HS, Cordon-Cardo C, Reuter VE, Singhal AK, Lloyd KO, Livingston PO. Selection of tumor antigens as targets for immune attack using immunohistochemistry: II. Blood group-related antigens. Int J Cancer 1997;73(1):50–6.

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. Next to the main focus on SLR and its effects on resilience, the paper reviews main SLR associated impacts: Floods and inundation, salinization, shoreline change, and effects on mangroves and wetlands. The hazards of SLR related floods increase fastest in urban areas. This is related with both the increasing surface major cities are expected to occupy during the decades to come and the increasing coastal population. In particular Asia and its megacities in the southern part of the continent are increasingly at risk. The discussion points to complexity, inter-disciplinarity, and the related uncertainty, as core characteristics. An integrated combination of mitigation, adaptation and resilience measures is currently considered as the most indicated way to resist SLR today and in the near future.References Aerts J.C.J.H., Hassan A., Savenije H.H.G., Khan M.F., 2000. Using GIS tools and rapid assessment techniques for determining salt intrusion: Stream a river basin management instrument. 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<strong>ABSTRACT</strong> The aim of this work is to study the effect of a composite endomycorrhizal inoculum on growth of Eucalyptus plants (<em>E. gomphocephala</em>) in the nurseries conditions. Analysis of the results, four months after inoculation, revealed that all roots were mycorrhizal and different structures characterizing arbuscular endomycorrhizal fungi were observed. The mycorrhizal frequency and intensity of Eucalyptus roots are 90 and 25% respectively. This roots endomycorrhization was accompanied by a significant improvement on growth parameters of mycorrhized Eucalyptus plants compared to the control, these are respectively, plant height 90.31/75.13 cm, root height 57/30.37cm, leaves number 106.75/79.12 leaves per plant, stem diameter 0,61/0.32 cm,&nbsp; average number of branch 11.62/6.5 and the fresh weight of the root and vegetative part of mycorrhizal plants are more important compared to the control. The fresh weight gain was, on average, 17.54g in the stems and of 24.37g in the roots. The number of spores in the rhizosphere of the inoculated plants is about 180 spores/100g of soil; the identification of these spores has allowed to note the presence of 33 species, divided into 8 genera: <em>Glomus</em>, <em>Acaulospora</em>, <em>Scutellospora</em>, <em>Pacispora</em>, <em>Gigaspora</em>, <em>Redeckera</em>,<em> Rhizophagus</em> and <em>Entrophospora</em>. The importance of Eucalyptus plants endomycorrhization compared to the ectomycorrhization was also discussed in this study. <strong>Keywords:</strong> Eucalyptus , Endomycorrhizae, AMF,&nbsp; mycorrhization &nbsp; <strong>REFERENCES</strong> Adouane M., 2011. Diversit&eacute; des macromyc&egrave;tes et des mycorhizes du ch&ecirc;ne-li&egrave;ge dans deux stations du Nord-Est Alg&eacute;rien: une sub&eacute;raie naturelle et une sub&eacute;raie envahie par <em>Acacia</em> <em>decurrens</em> (Willd). 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<strong>ABSTRACT</strong> In the current exploration an attempt has been made to assess the antibacterial potentialities of <em>Terminalia arjuna</em> Wight and Arn leaf galls. It belongs to the family Combretaceae commonly known as &lsquo;Arjuna&rsquo;, an important ethno medicinal plant. The different solvent extract of <em>T. arjuna</em> leaf gall were subjected to antibacterial activity, total phenol and total carbohydrate content estimation. The antimicrobial susceptibility was screened by means of well diffusion, disc diffusion, MIC and MBC methods. The result showed that the methanol extract was active against both gram negative and gram positive bacteria, when compared to other solvent extracts.&nbsp; The methanol extract of leaf gall showed optimum activity against <em>Pesudomonas aeruginosa</em> (MTCC-7903)<em>, Enterobacter aerogenes </em>(MTCC-7325),<em> Enterococcus faecalis </em>(MTCC &ndash; 6845) and <em>Staphylococcus aureus</em> (MTCC- 3160). The highest amount of phenolic content was observed in methanol extract (93.62 &micro;g GAE/mg of extract) followed by acetone &gt;water &gt;chloroform. The highest value of carbohydrate were observed in water extract (80.90 &micro;g/mg of extract) followed by &gt;acetone &gt; methanol &gt; chloroform. To the best of our knowledge, this is the first report of exploiting the antimicrobial properties of leaf gall of <em>Terminalia arjuna</em>. Our results indicated that the <em>Terminalia arjuna</em> leaf gall possess potential antibacterial activity. <strong>&nbsp;Keywords: </strong><em>T. arjuna,</em> Methanol extract, Antibacterial activity. <strong>REFERENCES</strong> Ahmad, I. and Aquil, F. 2007.&nbsp; In vitro efficacy of bioactive extracts of 15 medicinal plants against&nbsp; ES &szlig; - lactamase producing multidrug resistant enteric bacteria. Microbio. Res.162: 264 -275 Akram, M., Shahid, M. and Khan, A.U. 2007. 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Valgas, C., Machado de Souza, S., Sm&acirc;nia, E.F.A. and Sm&acirc;nia, A. 2007 Screening methods to determine antibacterial activity of natural products. Braz. J. Microbio. 38:369-380. Viswanathan, V., Phadatare, A.G. and Mukne, A. 2014. Antimycobacterial and Antibacterial Activity of&nbsp;<em>Allium sativum</em>&nbsp;Bulbs.&nbsp;Indian J. Pharma. Sci.&nbsp;76(3): 256&ndash;261. Wang, J., Galgici, A., Kodali, S.K.B., Jayasuriya, H., Dorso, K., Vicente, F., Gonzale, A., Cully, D., Bramhill, D. and Singh, S. (2003). Discovery of a small molecule that inhibits cell division by blocking Fts Z, a novel therapeutic target of antibiotics. The J. Biological Chem., 278: 44424-44428. Warrier, P.K., Nambiar, V.P.K. and Ramaktty, C. 1996. Indian medicinal plants: a compendium of 500 species, (Eds. Warrier P.K., Nambiar, V.P.K. and Ramaktty, C. Vol. 5, 1^st Ed.&nbsp; Orient Longman Limitted, Madras, India. 253-257. Yang, C., Chang, H., Lin, H. and Chuang L. 2013. Evaluation of antioxidant and antimicrobial activities from 28 Chinese herbal medicines. J. Pharmacogn. Phytochem.&nbsp; 2(1):294-305

<strong>ABSTRACT</strong> The diversity of mycorrhizal fungi in the rhizosphere of the carob tree (<em>Ceratonia siliqua</em>) was studied in five regions of Morocco: Taroudant, Kh&eacute;nifra, Afourar, Nador and Ksiba. Microscopic examination of the carob tree soil, collected from the studied areas, revealed the presence of 31 AM fungal species belonging to six genera <em>Glomus</em> (16 species),<em> Acaulospora</em> (7 species), <em>Scutellospora </em>(4 species), <em>Gigaspora</em> (2 species), <em>Entrophospora</em> and <em>Pacispora</em> (one species each)<em>. </em>The genus <em>Glomus</em> is the most abundant with a distribution percentage of 93%. Species richness varies between 13 and 18 species. All the encountered species were morphologically characterized basing on: shape, color, average size of the spore and its wall, spore surface and size of the hyphae. The diversity of AM fungi in different ecological studied zones varies from one site to another, it is higher in Taroudant site, the Shannon-Wiener index H &#39; is in the order of 2.78 and the index of Margalef IM 3.6. Furthermore, the similarity index of Jaccard shows a strong similarity between the Taroudant site and that of Afourar. <strong>Keywords: </strong><em>Ceratonia siliqua, </em>endomycorrhizae, Carob tree, Morocco, Fungi. <strong>REFERENCES </strong> &nbsp; Abbas Y., Ducousso M., Abourough M., Azcon R. and Duponnois R., 2006. Diversity of arbuscular mycorrhizal fungi in Tetraclinis articulata (Vahl) Masters woodlands in Morocco. Ann For Sci., 63: 285&ndash;291. Ait Aguil F., 2005. Contribution &agrave; l&rsquo;&eacute;tude de la biodiversit&eacute; de la flore fongique des for&ecirc;ts marocaines : cas des Basidiomyc&egrave;tes du Rif Occidental et des Gast&eacute;romyc&egrave;tes de la Mamora. Th&egrave;se de Doctorat, Univ. Ibn Tofail, Fac. Sci. K&eacute;nitra, 139 p. Batlle I., Tous J., 1997. Carob tree. <em>Ceratonia siliqua</em> L. Promoting the conservation and use of underutilized and neglected crops. 17. Institute of Plant Genetics and Crop Plant Research, Gatersleben/International Plant Genetic Resources Institute, Rome, Italy. 92p. Bergen M., Koske R.E., 1984. Vesicular-arbuscular mycorrhizal fungi from sand dunes of Cape Cod, Massachusetts. Transactions of the British Mycological Society, 83: 157-158. Bever J.D., Westover K.M., Antonovics J., 1996. Incorporating the soil community into plant population dynamics: the utility of the feedback approach. <em>J. Ecol. </em>, <strong>85</strong>: 561&ndash;763. Blaszkowski J., Tadych M., Madej T. 2002., Arbuscular mycorrhizal fungi (Glomales, Zygomycota) of the bledowska desert, Poland. Societastis Botanicorum Poloniae, 71(1): 71-85. Boudouresque C.F., 2014. Insights into the diversity of the biodiversity concept. Sci. Rep. Port-Cros natl. Park, 28 : 65-86. Chillasse L., Dakki M. &amp;&nbsp; Abbassi M., 2001. Valeurs et fonctions &eacute;cologiques des Zones humides du Moyen Atlas (Maroc). Humedales Mediterr&aacute;neos, 139 &ndash; 146. Cruz S.J.C., 1989. Estudio de la simbiosis micorrızica vesicular arbuscular en el cultivo de <em>Coffea arabica </em>var. caturra. Fitopatol Colomb. 13: 56 &ndash; 64. Dahssi H., Dakki M., El Agbani M., Falaki H., Ibn Tattou M., Jaafar B. &amp; Maghnouj, M., 2004. Strat&eacute;gie nationale pour la conservation et l&rsquo;utilisation durable de la diversit&eacute; Biologique. 15 p. El Asri A., Talbi Z., Ait Aguil F., Chliyeh M., Sghir F., Touati J., Ouazzani Touhami A., Benkirane R And Douira A., 2014. Arbuscular Mycorrhizal Fungi Associated with Rhizosphere of Carob Tree (Ceratonia siliqua L.) in Morocco. Int. J. Pure App. Biosci. 2 (3): 286-297. Emberger L., 1938. Les arbres du Maroc et comment les conna&icirc;tre. La rose, Edit. Paris, 317p. Gerdemann J.W. &amp; Nicolson T.H., 1963. Spores of mycorrhizal endogone species extracted from soil by wet sieving and decanting. Trans. Br. Mycol. Soc., 46, 235. Gharnit N., Et Mtili N., Ennabili A. T. and Ennabili A., 2001. Social characterization and exploitation of carob tree (Ceratonia siliqua L.) from Mokrisset and Bab Taza (NW of Morocco). Sci. Lett. 3 n&deg;2. Giovannetti M. et Nicolson T.H., 1983. Vesicular arbuscular mycorrhiza in Italian sand dunes. Trans. Br. Mycol. Soc., 80(3): 552-556. Guadarrama P. and Alvarez-Sanches F.J., 1999. Abundance of arbuscular mycorrhizal fungi spores in different environments in a tropical rain forest, Veracruz, Mexico. Mycorrhiza, 8: 267-270. Haas J.H. Menge J.A., 1990. VA mycorrhizal fungi and soil characteristics in avocado (Persea Americana mill.) orchard soil. Plant and Soil, The Hague, v.127, n.2, p.207-212. Hanane S., 2010. Biom&eacute;trie des tourterelles des bois, Streptopelia turtur, dans le sud du Maroc (r&eacute;gion de Taroudant). Ecologia Mediterranea, 36 (1)&nbsp;: 107-110. Hatim A. &amp; Tahrouch S., 2007. Caract&eacute;risations chimique, botanique et microbiologique du sol des dunes littorales du Souss-Massa. Biomatec Echo., <strong>2(5)</strong>: 85-97. Helgason T., Merryweather J. W., Young J. P. And Fitter A. H., 2007. Specificity and resilience in the arbuscular mycorrhizal fungi of a natural woodland community. <em>J. Ecol., </em>95 : 623&ndash;630. Huston M.A., 1994. Biological diversity. The coexistence of species on changing landscapes, Cambridge University Press.681p. Jaccard P., 1912. The distribution of the flora in the alpine zone. New Phytol<em>., </em>11 : 37&ndash;50. Jefwa J.M., Mung&rsquo;atu J., Okoth P., Muya E., Roimen H. and Njuguini S., 2009. Influence of Land use types on occurrence of arbuscular mycorrhizal fungi in the high altitude regions of Mt. Kenya. Trop. Subtrop. Agroecosystems, <strong>11</strong>: 277&ndash;290. Debabrata panda and Poly tikadar. 2014. Effect of flyash incorporation in soil on germination and seedling characteristics of rice (Oryza sativa L.). Biolife. 2(3):800-807. Lakshmipathy R., 2005. Impact of land use types on arbuscular mycorrhizal population and diversity. Ph. D. Thesis, Univ. Agric. Sci., Bangalore, Karnataka (India). Lakshmipathy R., Balakrishna A. N., Bagyaraj D. J., Sumana D. A And Kumar D. P., 2004. Evaluation, grafting success and field establishment of cashew rootstock as influenced by VAM fungi. Indian J. Expt. Biol., 42 : 1132-1135. Leal P.L., St&uuml;rmer S.L., Siqueira J.O., 2009. Occurrence and diversity of arbuscular mycorrhizal fungi in trap cultures from soils under different land use systems in the Amazon, Brazil. Brazilian Journal of Microbiology 40: 111&ndash;121. Lopes E.S., Oliveira E., De Dias R.A. and Schenck, N.C., 1983. Occurrence and distribution of vesicular arbuscular mycorrhizal fungi in coffee (<em>Coffea arabica </em>L.) plantations in central Sao Paulo State, Brazil. Turrialba, 33: 417&ndash;422. M. N. Abubacker M. Visvanathan and S. Srinivasan., 2014. Impact of pesticides on AMF spore population and diversity in banana (<em>Musa</em> spp.) Plantation soils. Biolife. 2(4):1279-1286 Margalef R., 1958. Information theory in ecology. <em>Gen. Systems, </em>3 : 36-71. Mohammad J.M., Rushdi Hamadt S. and Issa Malkawit H., 2003. Population of arbuscular mycorrhizal fungi in semi-arid environment of Jordan as influenced by biotic and abiotic factors. <em>Journal of Arid</em> <em>Environments</em>, 53: 409- 417. Mohankumar V. AND Mahadevan A., 1987. Ecological distribution of VAM in tropical forest. In : Mycorrhiza Round Table Proceedings of the national workshop held at JNU, New Delhi, 13-15 March, pp. 238-256. Morton J. B. And Bentivenga S. P., 1994. Levels of diversity in endomycorrhizal fungi (Glomales, Zygomycetes) and their role in defining taxonomic and nontaxonomic groups. Plant Soil<em>, </em>159 : 47-59. Muleta D., Assefa F., Nemomissa S. and Granhall U., 2008. Distribution of arbuscular mycorrhizal fungi spores in soils of smallholder agroforestry and monocultural coffee systems in southwestern Ethiopia. Biol Fertil. Soils, 44: 653&ndash;659. Newsham K.K., Fitter A.H., Watterson A.R., 1995. Arbuscular mycorrhiza protect an annual grass from root pathogenic fungi in the field. Journal of Ecology 83, 991&ndash;1000. Nicolson T.H., Johnston C., 1979. Mycorrhiza in Gramineae III. <em>Glomus fasciculatum</em> as the endophyte of pioneer grasses in maritime sand dunes. Trans. Br. Mycol. Soc., 72: 261&ndash;268. Nirmalnath P.J., 2010. Molecular diversity of arbuscular mycorrhizal fungi and pink pigmented facultative methylotrophic bacteria and their influence on grapevine (<em>vitis vinifera)</em>. University of Agricultural Sciences, Dharwad. 148 p. Oehl F., Jansa J., Ineichen K., M&auml;der P. et van der Heijden M., 2011. Champignons mycorhiziens arbusculaires, bioindicateurs dans les sols agricoles suisses. Recherche Agronomique Suisse 2 (7&ndash;8): 304&ndash;311. Oehl F., Sieverding E., Ineichen K., Mader P., Boller T. And Wiemken A., 2003. Impact of land use intensity on the species diversity of arbuscular mycorrhizal fungi in agroecosystems of central Europe. Appl. Environ. Microbiol. 69 : 2816&ndash;2824. &Ouml;pik M., Moora M., Zobel M., Saks &Uuml;., Wheatley R., Wright F. And Daniell T., 2008. High diversity of arbuscular mycorrhizal fungi in a boreal herb-rich coniferous forest. New Phytologist, 179 : 867&ndash;876. Ouahmane L., Ndoye I., Morino A., Ferradous A., Sfairi Y., Al Faddy M. N. and Abourouh M., 2012. Inoculation of <em>Ceratonia siliqua </em>L<em>. </em>with native arbuscular mycorrhizal fungi mixture improves seedling establishment under greenhouse conditions. African Journal of Biotechnology Vol. 11(98), pp. 16422-16426. Ouchkif M., 1988. Etude sur le caroubier.Append number 8 of Project Ouest Srou. MARA (Morocco). GTZ (Germany), DPA of Khenefra (unpublished). Ragupathy S., Nagarjan G., Mahadevan A., 1998. Mycorrhizae in coastal sand dunes of Tuticorin, Tamil Nadu. <em>Jour. Envir. Biol</em>., <strong>19(3)</strong>: 281-284. Ramade F., 1993. Dictionnaire encyclop&eacute;dique de l&rsquo;&eacute;cologie et des sciences de l&rsquo;environnement. Paris : Ediscience International. 822 p. Rillig M.C., Mummey D.L., 2006. Mycorrhizas and soil structure. New Phytologist 171,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 41-53. Schenck N.C. et Kinloch R.A., 1980. Incidence of mycorrhizal fungi on six field crops in monoculture on a newly cleared woodland site. Mycologia, 72: 445-456. Shannon C. E. And Weaver W., 1949. The Mathematical Theory of Communication. University of Illinois Press, Urabana. SHI Z.Y., WANG F. Y. AND WEI Y. L., 2007. Natural forest and forest plantation affect diversity of arbuscular mycorrhizal fungi in the rhizosphere of <em>Diptorocarpaceae</em>. American-Eurasian J. Agric. and Environ. Sci., 2(4) : 411- 416. Stutz J. C., 2003. Preliminary assessment of arbuscular mycorrhizal fungal diversity and community structure in an urban ecosystem. Mycorrhiza<em>, </em>13: 319-326. Tchabi A., Coyne D., Hountondji F., Lawouin L., Wiemken A. And Oehl F., 2008. Arbuscular mycorrhizal fungi in the &lsquo;yam belt&rsquo; of West Africa, African J. Biotechnol., 56 : 256-268 Tesfaye G., Teketay D., Assefa Y. and Fetene M., 2004. The influence of fire on soil seed bank composition and density and regeneration in a humid tropical forst, southeast Ethiopia. Mount. Res. Dev. 24: 354 &ndash; 361. Walker C. &amp; Mize C.W., 1982. Population of endogonaceous fungi at two locations in central Iowa. Can. J.Bot., 60: 2518-2529. Zhao Z.W., Xia Y.M., Qin X.Z., Li X.W., Cheng L.Z., Sha T. and Wang G.H., 2001.&nbsp; Arbuscular mycorrhizal status of plants and the spore density of arbuscular mycorrhizal fungi in the tropical rain forest of Xishuangbanna, southwest China. Mycorrhiza, 11: 159-162. &nbsp;

Worldwide, congenital heart defects (CHDs) are a leading cause of mortality and morbidity. Globally, the annual prevalence rate of CHDs is about 1.5 million. It is one of the most common life-threatening congenital malformations, with a visible difference between high-income countries (HICs) and developing countries. This difference may be attributed to the diagnostic facilities and interventions.1 Moreover, the use of genetic and clinical risk scores is less studied in this field compared to other diagnostic and therapeutic approaches. Thus, we comprehensively review the available literature on adult and pediatric syndromic or non-syndromic CHDs and propose limitations and future directions in this field. Risk factors for this fatal disease include genetic and environmental factors.2,3 Risk stratification based on prenatal diagnosis with genetic counseling has shown better clinical outcomes. The modified World Health Organization (mWHO) guidelines are among the first proposed for risk stratification based on clinical scores.4 The combination of polygenic risk scores (PRS) and clinical risk evaluation has been adopted in various populations as better diagnostic and therapeutic approaches for various diseases, including coronary artery disease,5 diabetes,6 obesity,7 and cancers.8,9 However, unlike these diseases, polygenic risk scores are rarely used for the genetic diagnosis of CHD patients. The clinical utility of polygenic risk scores for CHDs is still in the early stages and requires validation studies in different cohorts. Incorporating PRS into the clinical setting may improve CHD diagnosis and therapeutic strategies.10 Recently, an initial attempt was made to determine the clinical utility of polygenic risk scores in a large dataset of the European cohort. Data from this study suggested a high potential for PRS in distinguishing between clinical phenotypes (mild, moderate, and severe) of congenital heart malformations.11 Furthermore, this hypothesis was tested in patients with transposition of the great arteries (TGA) to assess the utility of risk stratification after arterial switch operation. The cumulative risk score was computed for single nucleotide polymorphisms (SNPs) that reached the threshold statistical significance of p&lt;1×10−5 in the initial analysis. Combined clinical and polygenic risk scores showed improved risk stratification in mild, moderate, and severe TGA phenotypes.12 Similarly, in another European cohort, the risk allele frequency was higher in the diseased group compared to the control group. However, statistical analysis suggested a non-significant association with p&gt;0.05. Interestingly, combined risk scores constructed for selected SNPs showed a significant association with the disease with a p-value of 0.002. This evidence further supports the hypothesis that the cumulative effect of polymorphisms has better diagnostic and therapeutic efficacy than individual SNPs.13 There are certain limitations to its clinical use. Firstly, social stigma and lack of awareness regarding this disease are major hurdles. Secondly, there is a need to recruit a large number of samples from different populations to validate the clinical utility of PRS. Additionally, a lack of resources in developing countries also contributes to fatal outcomes. We recommend conducting large cohort studies in different ethnic groups to predict better risk associations, develop better therapeutic strategies, and formulate management guidelines. References Zuhlke L, Lawrenson J, Comitis G, De Decker R, Brooks A, Fourie B, et al. Congenital heart disease in low-and lower-middle–income countries: current status and new opportunities. Curr Cardiol Rep. 2019;21(12):163. Zhang TN, Wu QJ, Liu YS, LV JL, Sun H, Chang Q, et al. Environmental risk factors and congenital heart disease: an umbrella review of 165 systematic reviews and meta-analyses with more than 120 million participants. Front Cardiovasc Med. 2021;8: Diab NS, Barish S, Dong W, Zhao S, Allington G, Yu X, et al. Molecular genetics and complex inheritance of congenital heart disease. Genes. 2021;12(7):1020. Van Hagen IM, and Roos-Hesselink JW. Pregnancy in congenital heart disease: risk prediction and counselling. Heart. 2020;106(23):1853-61. Shabana NA, Ashiq S, Ijaz A, Khalid F, Khan K, Sarwar S, et al. Genetic risk score (GRS) constructed from polymorphisms in the PON1, IL-6, ITGB3, and ALDH2 genes is associated with the risk of coronary artery disease in Pakistani subjects. Lipids Health Dis. 2018;17(1):224. Shitomi-Jones LM, Akam L, Hunter D, Singh P, and Mastana S. Genetic risk scores for the determination of type 2 diabetes mellitus (T2DM) in North India. Int J Environ Res Public Health. 2023;20(4):3729. Dashti HS, Miranda N, Cade BE, Huang T, Redline S, Karlson EW, et al. Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank. BMC Med. 2022;20(1):5. Conran CA, Shi Z, Resurreccion WK, Na R, Helfand BT, Genova E, et al. Assessing the clinical utility of genetic risk scores for targeted cancer screening. J Transl Med. 2021;19:1-9. Byrne S, Boyle T, Ahmed M, Lee SH, Benyamin B, Hypponen E. Lifestyle, genetic risk and incidence of cancer: a prospective cohort study of 13 cancer types. Int J Epidemiol. 2023;52:817-26. Morrish AM, Smith J, Enriquez A, Sholler GF, Mervis J, Dunwoodie SL, et al. A new era of genetic testing in congenital heart disease: a review. Trends Cardiovasc Med. 2022;32:311-9. Spendlove SJ, Bondhus L, Lluri G, Sul JH, and Arboleda VA. Polygenic risk scores of endo-phenotypes identify the effect of genetic background in congenital heart disease. Hum Genet Genom Adv. 2022;3(3):100112. Woudstra OI, Skoric-Milosavljevic D, Mulder BJ, Meijboom FJ, Post MC, Jongbloed MR, et al. Common genetic variants improve risk stratification after the atrial switch operation for transposition of the great arteries. Int J Cardiol. 2023;371:153-9. Borghini A, Vecoli C, Mercuri A, Turchi S, and Andreassi MG. Individual and joint effects of genetic polymorphisms in microRNA-machinery genes on congenital heart disease susceptibility. Cardiol Young. 2021;31(6):965-8.

<strong>ABSTRACT</strong> All the endomycorrhizal species associated to the olive tree in the world were listed in this bibliographic inventory. Fifty endomycorrhizal species were isolated from the rhizosphere of the olive tree; the majority of them were encountered in Spain (21 species), followed by Morocco (20 species) and Italy (15 species). The lowest spore&rsquo;s number was encountered in Israel, Greece and Tunisia with 2 species. <em>Glomus mosseae </em>was the most common species in the world, actually was cited in eight countries, and followed by <em>G. intraradices</em>&nbsp;in seven countries. Six genera of the endomycorrhizal species were detected. The <em>Glomus </em>genus was the most dominant represented by 29 species, followed by<em> Gigaspora </em>with 7 species. <em>Acaulospora</em> and <em>Scutellospora </em>with 5 species for each. 1 species for both of <em>Entrophospora </em>and <em>Geosiphon.</em> <strong>Key words. </strong>Endomycorrhizae, olive tree (<em>Olea europaea</em> L.), <em>Glomus, Gigaspora Acaulospora</em>, <em>Scutellospora, Entrophospora,</em> <em>Geosiphon.</em> <strong>REFERENCES</strong> &nbsp; Azc&oacute;n-Aguilar C, Palenzuela J, Rold&aacute;n A, Bautista S, Vallejo R, Barea JM (2003). Analysis of the mycorrhizal potential in the rhizosphere of representative plant species from desertification-threatened Mediterranean shrublands. Appl. Soil Ecol., 22: 29-37. Gianinazzi, S., A. Trouvelot and V. Gianinazzi-Pearson, 1983. Les endomycorhizes: importancedans la croissance et le d&eacute;veloppement des arbresfruitiers. Fruits, 38(9): 659-662. Binet MN, Lemoine MC, Martin C, Chambon C, Gianinazzi S (2007). Micropropagation of olive (Olea europaea L.) and application of mycorrhiza to improve plantlet establishment. In Vitro Cell. Dev. Biol. Plant 43: 473-478. Calvente R., Cano C., Ferrol N., Azc&oacute;n-Aguilar C., Barea J. M., 2004. Analysing natural diversity of arbuscular mycorrhizal fungi in olive tree (Olea europaea L.) plantations and assessment of the effectiveness of native fungal isolates as inoculants for commercial cultivars of olive plantlets. Applied Soil Ecology 26: 11&ndash;19. 5.Caravaca F., &nbsp;D&iacute;az E.,&nbsp; &nbsp;Barea J.M., Azc&oacute;n-Aguilar C., Rold&aacute;n A., 2003. Photosynthetic and Transpiration Rates of&nbsp;<em>Olea europaea</em>&nbsp;subsp.&nbsp;<em>sylvestris</em>&nbsp;and<em>Rhamnus lycioides</em>&nbsp;as Affected by Water Deficit and Mycorrhiza. 46 (4)&nbsp;: 637-639. Roldan-Fajardo BE, Barea JM, Mycorrhizal dependency in the olive tree (Olea europaea L.), Physiology and genetics aspects of mycorrhizae, Paris, 323-326 (1986) Caravaca F., Alguacil M.M., Barea J.M., Roldan A., 2005. A survival of inocula and native AM fungi species associated with shrubs in a degraded Mediterranean excosystem. Soil Biol. And Biochem., 37: 227-233. Caravaca F., Barea J.M., Figueroa D., Rold&aacute;n A., 2002. Assessing the effectiveness of mycorrhizal inoculation and soil compost addition for enhancing reafforestation with Olea europaea subsp.sylvestris through changes in soil biological and physical parameters. Applied Soil Ecology 20: 107&ndash;118. Ortas, I., 2012. Mycorrhiza in Citrus: Growth and&nbsp;&nbsp;Nutrition.&nbsp;In Srivastava A. K. (ed) Advances in Citrus Nutrition. Springer Netherlands. pp: 333-351. Akhtar, M.S. and Z.A. Siddiqui, 2008. Arbuscular&nbsp;mycorrhizal fungi as potential bioprotectantsagainst plant pathogens. &nbsp;In: Siddiqui, Z.A., Akhtar,M.S. and Futai, K. (eds) Mycorrhizae: Sustainable agriculture and forestry. Springer Netherlands. pp:61-97. Castillo P., Nico A.I., Azc&oacute;n-Aguilar C., Del R&iacute;o Rinc&oacute;n C., Calvet C., and Jim&eacute;nez-D&iacute;az R.M., 2006. Blackwell Publishing Ltd Protection of olive planting stocks against parasitism of root-knot nematodes by arbuscular mycorrhizal fungi. Plant Pathology. 55, 705&ndash;713. Davies F.T., Estrada-Luna A., Finnerty T.L., Egilla J.N., Olalde-Portugal V., 2000. Applications of mycorrhizal fungi in plant propagation systems. In: Ecolog&iacute;a, Fisiolog&iacute;a y Biotecnolog&iacute;a de la Micorriza Arbuscular (A. Alarc&oacute;n and R. Ferrera, eds.). IRENAT Colegio de Postgraduados. Montecillo. Mundi-Prensa, Madrid, Spain, pp. 123-140. 1.Fusconi, A. and G. Berta, 2012. Environmentalstress and role of arbuscular mycorrhizal symbiosis.&nbsp;In : Ahmad, P. &amp; Prasad, M.N.V. (eds) Abiotic Stress Responses in Plants: Metabolism,Productivity and Sustainability. Springer NewYork. pp: 197-214..Marulanda, A.; Porcel, R.; Barea, J.M.; Azcon, R. 2007. Drought tolerance and antioxidant activities in lavender plants colonized by native drought-tolerant or drought-sensitive Glomus species. Microbial Ecology 54: 543-552. Chatzistathis T., Orfanoudakis M., Alifragis D., Therios I., 2013. Colonization of Greek olive cultivars&rsquo; root system by arbuscular mycorrhiza fungus: root morphology, growth, and mineral nutrition of olive plants. Scientia Agricola. Sci. Agric. v.70, n.3, p.185-194. Bolandnazar, S.; Aliasgarzad, N.; Neishabury, M.R.; Chaparzadeh, N. 2007. Mycorrhizal colonization improves onion (Allium cepa L.) yield and water use effi ciency under water defi cit condition. Scientia Horticulturae 114: 11-15. 5.Selosse, M.A. and F. Le Tacon, 1999. 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Moringa leaf-based fish feed is feed that is processed by pond farmers in Gampong Reuleut Timur, Muara Batu District, North Aceh, using Moringa leaf raw materials that have good nutritional content and are in accordance with fish needs. This feed is relatively cheap with protein content that meets the needs of fish. However, the feed has not been able to reach a wide market. This is due to the lack of knowledge of farmers about marketing strategies. The service team, through community service activities, aims to provide counseling about marketing strategies for artificial fish feed. Service activities were carried out in Gampong Reuleut Timur, Muara Batu District, North Aceh Regency. Extension activities were carried out by presenting material on the 4P marketing strategy, namely product, price, place, and promotion, and distributing questionnaires to participants to evaluate their understanding of the material. The result of this activity is the increased understanding and knowledge of partners about the 4P marketing strategy, with the hope that later it will be applied to the business that has been occupied in order to obtain maximum profit.&lt;img 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

Introducción: El cáncer de próstata (CP) el segundo cáncer diagnosticado en hombres, con mayor incidencia a los 66 años. La obesidad, el tabaquismo, alcoholismo y antecedentes familiares de CP se han encontrado asociados al riesgo de metástasis. El objetivo del presente estudio fue medir la asociación entre factores y el estado metastásico en pacientes con CP en un centro único de referencia en Ecuador.&#x0D; Metodología: El presente estudio analítico, se realizó en el Hospital “Teodoro Maldonado Carbo”, en Guayaquil-Ecuador, en el período enero-diciembre del 2019. El cálculo muestral fue no probabilístico, tipo censo. Se incluyeron casos con CP. Las variables fueron: edad, PSA, escala de Gleason, presencia de metástasis, sintomatología, tabaquismo, obesidad y antecedentes. Se presenta Odds Ratio como medida de asociación con intervalo de confianza del 95% y valor P.&#x0D; Resultados: El estudio incluyó 363 pacientes, con edad promedio de 75.2 ± 9.6 años. El grupo con metástasis fue de 202 casos (55.65%). Metástasis ósea 32.5%, pulmonar 9.6%, ganglionar 8.8% y hepático 4.75%. En la sintomatología la más frecuente fue, disuria (44.4%); el 33.6% con polaquiuria, un 13.2% hematuria y 8.8% tenesmo. El estadio Gleason-9 OR=24.85 (IC 95% 1.47-419.8) P=0.0259. El nivel de PSA &gt;19 ng/ml OR= 6.996 (IC 95% 2.68-18.29) P=0.0001. El tabaquismo OR=2.34 (IC 95% 1.52-3.60) P=0.0001. Fueron factores protectores el valor de PSA &lt;19 ng/ml OR=0.082 (IC 95% 0.043-0.157) P&lt;0.0001, acudir a consulta de Hipertensión arterial OR=0.33 (IC 95% 0.161-0.691) P=0.0032 y el estadío Gleason-6 OR=0.108 (IC 95% 0.0665-9.1736) P&lt;0.0001.&#x0D; Conclusión: Los niveles de PSA &gt;19 ng/ml y el estadio Gleason &gt;9 se asocian a la presencia de metástasis en pacientes con CP.&#x0D; &#x0D; Recibido: Julio 14, 2022&#x0D; Aceptado: Octubre 27, 2022&#x0D; Publicado: Diciembre 2, 2022&#x0D; Editor: Dra. Evelyn Valencia Espinoza.&#x0D; &#x0D; Introducción&#x0D; El cáncer de próstata es el segundo cáncer más diagnosticado en hombres alrededor del mundo, con mayor incidencia promedio a los 66 años [1]. En países desarrollados, el cáncer de próstata se diagnostica a edades más tempranas cuando este se confina a la glándula prostática, debido al uso del antígeno prostático específico (PSA) [2]. El antígeno prostático específico es proteína creada por el epitelio prostático, el cual, es específico de órgano, más no de cáncer, debido a que el mismo puede estar elevado en patologías como prostatitis, hiperplasia prostática benigna, entre otras. Sin embargo, es el mejor biomarcador hasta ahora para el diagnóstico temprano del cáncer de próstata.&#x0D; Según la American Academy of Family Physicians, se ha determinado que 3 de cada 10 hombres con elevado PSA, tienen un alto riesgo de sufrir de cáncer de próstata que va a depender de la edad y el nivel del PSA que se encuentre. Algunos estudios demuestran que las pruebas de rutina de PSA en hombres entre 55 a 66 años disminuyen la mortalidad por cáncer de próstata, de manera significativa. Sin embargo, la baja especificidad para Cáncer de Próstata de la prueba, hace que la interpretación de ella no sea concluyente [3].&#x0D; La Escala de Gleason es un sistema de graduación que sirve, una vez establecido el diagnóstico de adenocarcinoma de próstata, para medir la agresividad histopatológica de la neoplasia [4]. Está plenamente establecido que la escala de Gleason, de acuerdo a los hallazgos histopatológicos del tumor, nos permite categorizar a los pacientes de una manera más precisa y de esta manera tener una idea clara del pronóstico de dicho paciente.&#x0D; Con estos antecedentes se estableció el objetivo de determinar los factores de riesgo asociados a metástasis en pacientes con cáncer de próstata en un centro de referencia regional en Guayaquil-Ecuador.&#x0D; &#x0D; Materiales y métodos&#x0D; Diseño del estudio&#x0D; El presente estudio es observacional-analítica. La fuente es retrospectiva.&#x0D; &#x0D; Área de estudio&#x0D; El estudio se realizó en el servicio de urología del Hospital de Especialidades “Teodoro Maldonado Carbo”, del Instituto Ecuatoriano de Seguridad Social, en Guayaquil-Ecuador. El período de estudio fue del 1ro de Enero del 2019 hasta el 31 de diciembre del 2019.&#x0D; &#x0D; Universo y muestra&#x0D; El universo fue conformado por todos los pacientes registrados en la institución. El cálculo del tamaño muestral fue no probabilístico, tipo censo, en donde se incluyeron todos los casos incidentes en el período de estudio.&#x0D; &#x0D; Participantes&#x0D; Se incluyeron casos de pacientes adultos diagnosticados con cáncer de próstata en quienes se contó con valoración de PSA y la escala de Gleason. Se excluyeron registros incompletos para el análisis.&#x0D; &#x0D; Variables&#x0D; Las variables fueron edad, PSA, escala de Gleason, presencia de metástasis, sintomatología, métodos diagnósticos.&#x0D; &#x0D; Procedimientos, técnicas e instrumentos.&#x0D; Los datos fueron recogidos de la historia clínica en un formulario diseñado exclusivamente para tal propósito. Los diagnósticos de CP se realizaron por punción aspiración por aguja fina (PAAF) guiada por ecografía. Las placas fueron leídas por Patólogos distintos. Se usó el sistema AS400 para la pesquisa de casos usando los diagnósticos codificados: C61.&#x0D; &#x0D; Evitación de sesgos&#x0D; Para garantizar la confiabilidad de la información los investigadores fueron entrenados sobre la recolección de los datos. Se usó una lista de doble chequeo para incluir los casos. Los datos fueron validados y curados por el investigador principal.&#x0D; &#x0D; Análisis estadístico&#x0D; Recopilada la información en una hoja electrónica Excel, se ingresó en una matriz de datos del software SPSS™ 22.0 (IBM, Chicago, USA). Se utilizó estadística descriptiva en base a frecuencias y porcentajes para las variables cualitativas y para las cuantitativas medidas de tendencia central. Se presenta Odds Ratio como medida de asociación con intervalo de confianza del 95% y valor P.&#x0D; &#x0D; Resultados&#x0D; El estudio incluyó 363 pacientes.&#x0D; &#x0D; Caracterización clínica&#x0D; Fueron 363 pacientes, con edad promedio de 75.2 ± 9.6 años. La edad mínima fue de 49 años, y la máxima de 98 años.&#x0D; Los pacientes con metástasis fueron 202 casos (55.65%). Con respecto al lugar de diseminación metastásica, se encontró mayor predilección a desarrollar metástasis ósea en el 32.5% de los pacientes, seguido de metástasis pulmonar con el 9.6%, metástasis ganglionar con el 8.8% y a nivel hepático 4.75% de los casos. En la sintomatología la más frecuente fue, disuria con el 44.4%; el 33.6% con polaquiuria, un 13.2% hematuria y 8.8% tenesmo. El estudio más frecuente utilizado, fue el eco prostático, con un 42.7%; la tomografía 20.4%), gammagrafía prostática 25.6%, la resonancia magnética con el 11.3%.&#x0D; &#x0D; Factores clínicos&#x0D; El 44.4% de los pacientes padecía alcoholismo, el 27.5% presentaba tabaquismo, el 23.1% eran consumidores de carnes y lácteos; otros hábitos poco frecuentes se relacionaron con el 4.7%; 0.3% no refería ningún hábito de importancia. Dentro de los antecedentes patológicos se evidenció que, 54.5% de los pacientes tenían antecedentes familiares de Cáncer de próstata, 29.2% presentaba obesidad y sobrepeso, en tercer lugar, con 9.9% de los pacientes padecía de hipertensión arterial y entre otros antecedentes asociados tenían un porcentaje del 5.5% (Tabla 1).&#x0D; De la totalidad de los evaluados, el 45.2% tuvieron Gleason 6, mientras que aquellos con valores en la Escala de Gleason de 10, alcanzaban el 1.4%.&#x0D; La medición del riesgo se presenta en la tabla 1. Se constituyeron factores de riesgo para el desarrollo de metástasis el tabaquismo, y el estadío clínico Gleason 7, 8 y 9, los valores de PSA en rangos de 19-49 ng/ml, de 50 a 99 ng/ml y 100-299 ng/ml. Se establecieron como factores de protección estadísticamente significativos al antecedente personal de Hiperplasia prostática benigna, a la condición de hipertensión arterial, al estadio clínico Gleason 6, al valor de PSA &lt;19 ng/ml (Tabla 1).&#x0D; &#x0D; Discusión&#x0D; Al comparar el presente estudio con investigaciones previas se constató que la edad constituye un factor de riesgo no modificable para padecer cáncer prostático, según el Instituto Nacional de Cáncer en Estados Unidos, en su programa estadístico de Vigilancia, Epidemiología y Resultados (SEER) entre los años 2015-2019 se encontró una mayor incidencia de casos en los pacientes que tenían entre 70-74 años de edad [5], así también lo describió el trabajo de Leitzmann et al, en los años correspondientes a 2000-2008 donde la incidencia comienza a aumentar desde los 40-44 años de edad para llegar a su pico máximo de 984.8 pacientes por cada 100.000 hombres con edades entre 70-74 años [6], similarmente en este estudio el mínimo de edad fue 49 años en la población con un máximo de 98 y un media de 75.15 respectivamente.&#x0D; En cuanto a la distribución de regiones anatómicas donde se suele presentar la metástasis en el cáncer prostático; en primer lugar se determinó a los huesos (84%) en segundo lugar a nódulos linfáticos distantes (10.6%) y hepático (10.2%) [7] según un estudio conducido por Gandaglia et al. lo cual en similitud a este estudio el sitio más frecuente fue a nivel óseo con un 32.5% de todos los pacientes, seguido de la metástasis pulmonar con 9.6% y ganglionar 8.8%. A su vez Auz y Brito (2018) encontraron en su investigación realizada en el Hospital Solca Núcleo de Quito-Ecuador que incluyó a 1713 pacientes donde el sitio más frecuente de metástasis fue el óseo en un 82.25%, seguido del ganglionar linfático con 7.05% y luego 2.8% a nivel pulmonar [8].&#x0D; En lo que corresponde a los hábitos de los pacientes, un 44.4% de pacientes en este estudio consumía de alcohol regularmente, mientras que el 27.5% consumía tabaco y el 23.1% eran consumidores de carnes y lácteos, lo cual se contrasta con el estudio de Auz y Brito (2018) detallado anteriormente donde 31.1% de los pacientes consumían alcohol regularmente y el 28.3% de los pacientes consumían tabaco al momento de diagnóstico, no se midieron datos en relación al consumo de lácteos y carnes rojas [8].&#x0D; Un factor de riesgo no modificable muy importante fue la presencia de antecedentes familiares de cáncer de próstata en este estudio con un 54.5% de los pacientes lo cual en el trabajo de Auz y Brito (2018) solamente 9% tuvieron antecedentes familiares de cáncer prostático y un 23.2% de otros tipos de cánceres [23]. Según Barber et al. en su estudio se identificó que pacientes con historia familiar de cáncer prostático únicamente, tienen un riesgo aumentado del 68% de padecer lo mismo (95% CI 1.53-1.83) y un 72% de enfermedad letal [9]. Así también lo describió Powell IJ (2011) en su publicación que dice que hombres con relativos de primer grado (Padre, hermano, hijo) tienen un riesgo de desarrollar cáncer prostático que es aproximadamente del doble a la población general [10].&#x0D; En el presente estudio 29.2% de los pacientes presentaba sobrepeso y 9.9% de los pacientes padecía hipertensión arterial, así mismo en el estudio de Möller et al. se encontró que un IMC alto (26) en comparación a 20-22 a la edad de 21 años fue asociada con riesgo menor de cáncer prostático letal o avanzado y Gleason 7 [11], también se habla sobre que de los componentes del síndrome metabólico incluyendo la hipertensión arterial ninguno tiene relación con el desarrollo de cáncer prostático [10].&#x0D; Dentro de los síntomas más frecuentes en esta investigación se encontraron la disuria con un 44.4% de todos los pacientes, le siguió la polaquiuria (33.6%) y finalmente la hematuria (13.2%). De manera similar el estudio de Birtle et al. llevado a cabo entre los años 2000-2001 con bases de datos de la Asociación Británica de Cirujano Urológicos determinó que de 33 pacientes con cáncer metastásico de próstata con PSA &lt;10 ng/ml 51% se presentó con síntomas urinarios y/o dolor pélvico, 21% presentó dolor óseo, 18% retención urinaria y 10% caquexia y malasia [12].&#x0D; En el presente estudio de la totalidad de pacientes, 45.2% de ellos tuvieron puntajes de Gleason de 6 y en menor medida con 1.4% de los pacientes puntajes de Gleason 10, esto se puede comparar con el estudio de Thomsen et al. donde se encontró que altos puntajes en la escala de Gleason se relacionaron a la presencia de metástasis, así en ese estudio los pacientes que presentaron metástasis a distancia según la escala TNM (M1), 41% tenía un puntaje de Gleason 5, mientras que solo el 3% tenía Gleason 1 [13].&#x0D; El método de imagen más utilizado en este estudio fue el de la ecografía prostática con un 42.7% y en menor medida la resonancia magnética con el 11.3%. En la investigación de Huang et al. se encontró que el uso de la Resonancia Magnética con el sistema PI-RADS v2 fue el sistema más preciso para predecir la metástasis a nódulos linfáticos en la zona pélvica, los pacientes con PI-RADs &lt;5 fueron asociados con un riesgo muy bajo de metástasis ganglionar [14]. La ecografía prostática 3D se demostró un 84% de sensibilidad y 96% de especificidad para identificar extensión tumoral extra capsular macroscópica y fue capaz de identificar a 14/16 diseminaciones a la vesícula seminal según Mitterberger et al. en el año 2008 [15]. Finalmente con respecto a valoraciones de PSA que se presentaron en los pacientes diagnosticados con cáncer de próstata, se pudo evidenciar, que el 100% de los pacientes con PSA mayor de 500 ng/ml tuvo metástasis, así como el grupo de pacientes con 300-499 ng/ml PSA, a diferencia del grupo con menos de 19 ng/ml PSA donde solo el 40.6% tuvo metástasis, lo cual se puede comparar al estudio de Thomsen et al. donde de los pacientes con más de 400 ng/ml, el 64.9% presentó metástasis, le sigue el grupo con valores de 200-399 ng/ml donde el 54% desarrolló metástasis y al final el grupo con menos de 19 ng/ml tuvo solo al 1.45% de pacientes con metástasis, podemos así deducir que el valor de PSA es directamente proporcional al riesgo de metástasis, sin embargo, recomendamos tomar en cuenta más factores de riesgos de manera conjunta para una evaluación integral del paciente [13].&#x0D; &#x0D; Conclusiones&#x0D; En orden de importancia estadística los factores asociados a metástasis en cáncer prostático son el estadio clínico Gleason 9 y 8, Los niveles de PSA entre 50 a 299 ng/ml, y el tabaquismo. Fueron factores protectivos el antecedente clínico de Hiperplasia Prostática benigna, hipertensión y el nivel de PSA &lt;19 ng/ml.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Nota del Editor&#x0D; La Revista Oncología Ecu permanece neutral con respecto a los reclamos jurisdiccionales en mapas publicados y afiliaciones institucionales.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Agradecimientos&#x0D; Los autores agradecen a todas las personas de la Institución que colaboraron en el desarrollo de esta investigación.&#x0D; &#x0D; Información administrativa&#x0D; Abreviaturas&#x0D; APP: antecedentes patológicos personales.&#x0D; APF: Antecedentes patológicos familiares.&#x0D; HPB: hiperplasia prostática benigna.&#x0D; Ca: Cáncer.&#x0D; PSA: Antígeno prostático específico.&#x0D; OR: Odds ratio.&#x0D; IC: intervalo de confianza&#x0D; &#x0D; Archivos Adicionales&#x0D; Ninguno declarado por los autores.&#x0D; &#x0D; Fondos&#x0D; Los autores no recibieron ningún tipo de reconocimiento económico por este trabajo de investigación.&#x0D; &#x0D; Disponibilidad de datos y materiales&#x0D; Existe la disponibilidad de datos bajo solicitud al autor de correspondencia. No se reportan otros materiales.&#x0D; &#x0D; Contribuciones de los autores&#x0D; Emily Gabriela Chimbo Acuña: conceptualización, validación, visualización, metodología, administración de proyecto, escritura: revisión y edición.&#x0D; Karen Gabriela Valverde Zambrano: conceptualización, curación de datos, análisis formal, adquisición de fondos, investigación, recursos, software, redacción - borrador original.&#x0D; Iván Altamirano: conceptualización, curación de datos, análisis formal, adquisición de fondos, investigación, recursos, software.&#x0D; Todos los autores leyeron y aprobaron la versión final del manuscrito.&#x0D; &#x0D; Aprobación del comité de ética&#x0D; No aplica a estudios de bases de datos o historias clínicas.&#x0D; &#x0D; Consentimiento para publicación&#x0D; El presente estudio es un análisis de base de datos, no aplica para este tipo de estudio.&#x0D; &#x0D; Referencias&#x0D; &#x0D; Professionals S-O. EAU Guidelines: Prostate Cancer [Internet]. [citado 20 de octubre de 2021]. Disponible en: https://uroweb.org/guideline/prostate-cancer/#note_11&#x0D; Barry MJ, Nelson JB. Patients Present with More Advanced Prostate Cancer since the USPSTF Screening Recommendations. J Urol. diciembre de 2015;194(6):1534-6. DOI: 1016/j.juro.2015.09.033 PMid: 26384450&#x0D; Catalona WJ, Richie JP, Ahmann FR, Hudson MA, Scardino PT, Flanigan RC, et al. Comparison of digital rectal examination and serum prostate specific antigen in the early detection of prostate cancer: results of a multicenter clinical trial of 6,630 men. J Urol. mayo de 1994;151(5):1283-90. DOI: 1016/S0022-5347(17)35233-3 PMid: 7512659&#x0D; Schröder FH, Hugosson J, Roobol MJ, Tammela TL, Ciatto S, Nelen V, Kwiatkowski M, Lujan M, Lilja H, Zappa M, Denis LJ, Recker F, Berenguer A, Määttänen L, Bangma CH, Aus G, Villers A, Rebillard X, van der Kwast T, Blijenberg BG, Moss SM, de Koning HJ, Auvinen A; ERSPC Investigators. Screening and prostate-cancer mortality in a randomized European study. N Engl J Med. 2009 Mar 26;360(13):1320-8. DOI: 10.1056/NEJMoa0810084. Epub 2009 Mar 18. PMID: 19297566.&#x0D; Surveillance, Epidemiology, and End Results Program (SEER) of the National Cancer Institute. Fast Stats: An interactive tool for access to SEER cancer statistics. Bethesda, MD: SEER, National Cancer Institute; nd. Available from: www.seer.cancer.gov/faststats.&#x0D; Leitzmann MF, Rohrmann S. Risk factors for the onset of prostatic cancer: age, location, and behavioral correlates. Clin Epidemiol. 5 de enero de 2012;4:1 DOI: 2147/CLEP.S16747 PMid: 22291478 PMCid: PMC3490374&#x0D; Gandaglia G, Abdollah F, Schiffmann J, Trudeau V, Shariat SF, Kim SP, et al. Distribution of metastatic sites in patients with prostate cancer: A population-based analysis. Prostate. febrero de 2014;74(2):210-6. DOI: 1002/pros.22742. PMid:24132735&#x0D; Auz Fierro E, Brito Chasiluisa H. Factores relacionados con la supervivencia de pacientes con cancer de prostata en el hospital solca nucleo de quito durante el periodo 2003 - 2018. [Internet]. [Hospital Solca Nucleo de Quito]: Pontificia Universidad Católica del Ecuador; 2018. Disponible en: 22000&#x0D; Barber L, Gerke T, Markt SC, Peisch SF, Wilson KM, Ahearn T, et al. Family History of Breast or Prostate Cancer and Prostate Cancer Risk. Clinical Cancer Research. 1 de diciembre de 2018;24(23):5910-7. DOI: 1158/1078-0432.CCR-18-0370. PMid: 30082473 PMCid: PMC6279573&#x0D; Powell IJ. The precise role of ethnicity and family history on aggressive prostate cancer: a review analysis. Arch Esp Urol. 2011 Oct;64(8):711-9. PMID: 22052754; PMCID: PMC3859428.&#x0D; Möller E, Wilson KM, Batista JL, Mucci LA, Bälter K, Giovannucci E. Body size across the life course and prostate cancer in the Health Professionals Follow-up Study: Body size and prostate cancer. Int J Cancer. 15 de febrero de 2016;138(4):853-65. DOI: 1002/ijc.29842 PMid: 26355806 PMCid: PMC5042346&#x0D; Birtle AJ, Freeman A, Masters JRW, Payne HA, Harland SJ, BAUS Section of Oncology Cancer Registry. Clinical features of patients who present with metastatic prostate carcinoma and serum prostate-specific antigen (PSA) levels &lt; 10 ng/mL: the «PSA negative» patients. Cancer. 1 de diciembre de 2003;98(11):2362-7. DOI: 1002/cncr.11821 PMid: 14635070&#x0D; Thomsen FB, Westerberg M, Garmo H, Robinson D, Holmberg L, Ulmert HD, et al. Prediction of metastatic prostate cancer by prostate-specific antigen in combination with T stage and Gleason Grade: Nationwide, population-based register study. PLoS One. 2020;15(1):e0228447. DOI: 1371/journal.pone.0228447 PMid: 31995611 PMCid: PMC6988964&#x0D; Huang C, Song G, Wang H, Lin Z, Wang H, Ji G, et al. Preoperative PI-RADS Version 2 scores helps improve accuracy of clinical nomograms for predicting pelvic lymph node metastasis at radical prostatectomy. Prostate Cancer Prostatic Dis. marzo de 2020;23(1):116-26 DOI: 1038/s41391-019-0164-z PMid: 31383954&#x0D; Mitterberger M, Pinggera GM, Pallwein L, Gradl J, Frauscher F, Bartsch G, et al. The value of three-dimensional transrectal ultrasonography in staging prostate cancer. BJU Int. julio de 2007;100(1):47-50. DOI: 1111/j.1464-410X.2007.06845.x PMid: 17433033.&#x0D;

Citation: Ž&aacute;k, J., Jůza, T., Blabolil, P., Baran, R., Bartoň, D., Dra&scaron;t&iacute;k, V., Frouzov&aacute;, J., Holubov&aacute;, M., Ketelaars, H. A. M., Kočvara, L., Kubečka, J., Mrkvička, T., Mu&scaron;ka, M., Ř&iacute;ha, M., Sajdlov&aacute;, Z., &Scaron;mejkal, M., Tu&scaron;er, M., Va&scaron;ek, M., Vejř&iacute;k, L., Vejř&iacute;kov&aacute;, I., Wagenvoort, A. J., J. 2018 Invasive round goby Neogobius melanostomus has sex dependent locomotor activity and is under-represented in catches from passive fishing gear compared with seine catches. J. Fish Biol. 93:147&ndash;152. DOI: 10.1111/jfb.13646 Invasive

<em>Z</em><em>а</em><em>m</em><em>о</em><em>n</em><em>а</em><em>viy sh</em><em>а</em><em>r</em><em>о</em><em>itd</em><em>а</em><em> n</em><em>а</em><em>f</em><em>а</em><em>q</em><em>а</em><em>t t</em><em>а</em><em>&rsquo;</em><em>lim j</em><em>а</em><em>r</em><em>а</em><em>yonini t</em><em>а</em><em>shkil etishd</em><em>а</em><em>, shu bil</em><em>а</em><em>n birg</em><em>а</em><em> t</em><em>а</em><em>l</em><em>а</em><em>b</em><em>а</em><em>l</em><em>а</em><em>rning o&rsquo;quv f</em><em>ао</em><em>liyatl</em><em>а</em><em>rini n</em><em>а</em><em>z</em><em>о</em><em>r</em><em>а</em><em>t qilishd</em><em>а</em><em> h</em><em>а</em><em>m inn</em><em>о</em><em>v</em><em>а</em><em>tsi</em><em>о</em><em>n </em><em>ха</em><em>r</em><em>а</em><em>kt</em><em>е</em><em>rg</em><em>а</em><em> eg</em><em>а</em><em> v</em><em>о</em><em>sit</em><em>а</em><em>l</em><em>а</em><em>rd</em><em>а</em><em>n f</em><em>о</em><em>yd</em><em>а</em><em>l</em><em>а</em><em>nilm</em><em>о</em><em>qd</em><em>а</em><em>. So</em><em>&rsquo;</em><em>nggi yill</em><em>а</em><em>rd</em><em>а</em><em> z</em><em>а</em><em>m</em><em>о</em><em>n</em><em>а</em><em>viy t</em><em>а</em><em>&rsquo;</em><em>limd</em><em>а</em><em> p</em><em>е</em><em>d</em><em>а</em><em>g</em><em>о</em><em>gning k</em><em>а</em><em>sbiy, t</em><em>а</em><em>l</em><em>а</em><em>b</em><em>а</em><em>ning es</em><em>а</em><em> o</em><em>&rsquo;</em><em>quv f</em><em>ао</em><em>liyatini m</em><em>а</em><em>zmun</em><em>а</em><em>n t</em><em>а</em><em>k</em><em>о</em><em>mill</em><em>а</em><em>shtirish, shuningd</em><em>е</em><em>k, h</em><em>а</em><em>r ikki f</em><em>ао</em><em>liyat turining sif</em><em>а</em><em>tini m</em><em>а</em><em>&rsquo;</em><em>lum ko</em><em>&rsquo;</em><em>rs</em><em>а</em><em>tkichl</em><em>а</em><em>r </em><em>а</em><em>s</em><em>о</em><em>sid</em><em>а</em><em> y</em><em>е</em><em>t</em><em>а</em><em>rlich</em><em>а</em><em>, </em><em>хо</em><em>lis b</em><em>а</em><em>h</em><em>о</em><em>l</em><em>а</em><em>shg</em><em>а</em><em> nisb</em><em>а</em><em>t</em><em>а</em><em>n ehtiyoj kuch</em><em>а</em><em>ym</em><em>о</em><em>qd</em><em>а</em><em>. Ushbu maqolada p</em><em>е</em><em>d</em><em>а</em><em>g</em><em>о</em><em>gik f</em><em>ао</em><em>liyatni sh</em><em>а</em><em>kll</em><em>а</em><em>ntirishda ta</em><em>&rsquo;</em><em>lim jarayoninig ahamiyati tadqiq etilgan.</em>

<strong>THE TRIPARTITE OF CRIMINAL OFFENCES IN INTERWAR CZECHOSLOVAK REPUBLIC</strong> Po vzniku Československej republiky platil na na&scaron;om &uacute;zem&iacute; v oblasti trestn&eacute;ho pr&aacute;va pr&aacute;vny dualizmus. Vych&aacute;dzal z ustanoven&iacute; tzv. recepčnej normy, a teda v českej časti republiky platili rak&uacute;ske pr&aacute;vne predpisy (predov&scaron;etk&yacute;m z&aacute;kon č. 117/1852 ř. z. o zločinoch, prečinoch a priestupkoch) a na &uacute;zem&iacute; Slovenska a Podkarpatskej Rusi predpisy uhorsk&eacute; (hlavne z&aacute;k. čl. V/1878 &ndash; trestn&yacute; z&aacute;kon o zločinoch a prečinoch, z&aacute;k. čl. XL/1879 o priestupkoch). Autor sa v čl&aacute;nku snaž&iacute; o zachytenie sn&aacute;h o unifik&aacute;ciu odvetvia trestn&eacute;ho pr&aacute;va, s d&ocirc;razom na delenie trestn&yacute;ch činov v jednotliv&yacute;ch n&aacute;vrhoch unifikovan&yacute;ch trestn&yacute;ch z&aacute;konov v medzivojnovej Československej republike. URL:&nbsp;http://sic.pravo.upjs.sk/ The field of criminal law applied legal dualism in our country after the formation of the Czechoslovak Republic. Legal dualism was grounded in the provisions of a so-called receptive standard, i.e. the Czech part of the republic applied Austrian legal regulations (mainly Act No. 117/1852 Coll. on crimes, misdemeanours and delicts), and the Slovak territory and Subcarpathian Russia applied Hungarian regulations (mainly Act Section V/1878 &ndash; Criminal Law on crimes and misdemeanours, Act Section XL/1879 on Delicts). The author tries to depict all efforts to unify the field of criminal law, with emphasis on types of crime offences in drafts of unified Criminal Codes in interwar Czechoslovak republic.

Hagyom&aacute;nyos &eacute;telek, h&iacute;mzőműv&eacute;szet, r&eacute;g&eacute;szet. A politikai cionizmus kit&uuml;ntetett szerepet sz&aacute;n a kult&uacute;r&aacute;&eacute;rt folytatott harcnak. Ez Izrael alapvető eszk&ouml;ze ahhoz, hogy bizony&iacute;tsa a f&ouml;ldh&ouml;z fűződő kiz&aacute;r&oacute;lagos jog&aacute;t, valamint r&eacute;sze a nemzeti őslegenda vagy narrat&iacute;va kialak&iacute;t&aacute;s&aacute;nak, annak val&oacute;s&aacute;gtartalm&aacute;t&oacute;l f&uuml;ggetlen&uuml;l. A palesztinok, a ter&uuml;let&eacute;rt folytatott harcon t&uacute;l, identit&aacute;suk&eacute;rt is k&uuml;zdenek.

<strong>Annotatsiya. </strong>Pedagogik texnologiya zamonaviy ta&#39;limda, xususan STEAM (fan, texnologiya, muhandislik, san&#39;at va matematika) ta&#39;limi sharoitida hal qiluvchi rol o&#39;ynaydi. Texnologiyani pedagogik amaliyotga muammosiz integratsiya qilish orqali o&#39;qituvchilar talabalarning faolligini oshirishi, ijodkorlikni rivojlantirishi va chuqurroq o&#39;rganish tajribasini osonlashtirishi mumkin. Ushbu maqolada STEAM texnologiyasida pedagogik texnologiyaning ahamiyati, uning talabalar natijalariga ta&#39;siri va texnologiyani samarali birlashtirish uchun ishlatiladigan turli xil yondashuvlar ko&#39;rib chiqiladi. <strong>Kalit so`zlar.&nbsp; </strong>STEAM ta&#39;limi, texnologiya, innovatsiya, robototexnika, fanlararo ta&#39;lim, amaliy faoliyat, raqamli vositalar, ijodkorlik, tanqidiy fikrlash, muammolarni hal qilish. <strong>Annotation. </strong>Pedagogical technology plays a decisive role in modern education, in particular in the conditions of STEAM (science, technology, engineering, art and mathematics) education. By seamlessly integrating technology into pedagogical practice, teachers can increase student engagement, develop creativity, and facilitate a deeper learning experience. This article examines the importance of pedagogical technology in daS TEAM technology, its impact on student outcomes, and the various approaches used to effectively integrate technology. <strong>Keywords. </strong>STEAM education, technology, elementary school, interdisciplinary education, practical activities, digital tools, creativity, critical thinking, problem solving. <strong>Аннотация. </strong>Педагогические технологии играют решающую роль в современном образовании, в частности в условиях парного (научно-технического, инженерного, художественного и математического) образования. Плавно интегрируя технологии в педагогическую практику, учителя могут повысить вовлеченность учащихся, развить творческие способности и способствовать более глубокому обучению. В этой статье рассматривается важность педагогических технологий в daS TEAM technology, их влияние на результаты учащихся и различные подходы, используемые для эффективной интеграции технологий. <strong>Ключевые слова. </strong>STEAM образование, технологии, начальная школа, междисциплинарное образование, практическая деятельность, цифровые инструменты, креативность, критическое мышление, решение проблем.Pedagogik texnologiyaning ahamiyati: STEAM-bu fan, texnologiya, muhandislik, san&#39;at va matematika fanlarini birlashtirgan ta&#39;limiy yondashuv. Ushbu fanlarni yaxlit o&#39;quv dasturiga birlashtirish orqali talabalar uchun har tomonlama va fanlararo o&#39;quv tajribasini taqdim etishga qaratilgan. STEAM &nbsp;qisqartmasi an&#39;anaviydan olingan STEAM (fan, texnologiya, muhandislik va matematika) ta&#39;lim, san&#39;at qo&#39;shilishi bilan. San&#39;atning kiritilishi ijodkorlik, tasavvur va badiiy ifodaning o&#39;quv jarayonidagi ahamiyatini tan oladi. STEAM ta`limi ushbu fanlarni alohida va alohida mavzular sifatida ko&#39;rib chiqishdan ko&#39;ra, ularning integratsiyasini ta&#39;kidlaydi. STEAM e ta`limi talabalarni tanqidiy fikrlashga, muammolarni hal qilishga va o&#39;z bilim va ko&#39;nikmalarini Real sharoitlarda qo&#39;llashga undaydi. Bu amaliy o&#39;rganish, loyihaga asoslangan faoliyat va o&#39;quv tajribasini oshirish uchun texnologiya va raqamli vositalardan foydalanishni targ&#39;ib qiladi. San&#39;atni birlashtirish orqali talabalar ijodiy fikrlashga, turli nuqtai nazarlarni o&#39;rganishga va murakkab muammolarga innovatsion echimlarni ishlab chiqishga da&#39;vat etiladi. STEAM ta`limi -ning asosiy maqsadi talabalarni XXI asr muammolariga keng ko&#39;nikma va bilimlar bilan jihozlash orqali tayyorlashdir. Ushbu ko&#39;nikmalarga ilmiy izlanishlar, texnologik savodxonlik, muhandislik dizayni, matematik fikrlash, ijodiy fikrlash, samarali muloqot va hamkorlik kiradi. STEAM ta&#39;limi ta&#39;limga yaxlit yondashuvni rivojlantiradi, bu ham texnik ko&#39;nikmalarni, ham tanqidiy va ijodiy fikrlash qobiliyatini rivojlantiradi. STEAM ta&#39;limi turli fanlarni birlashtirib, haqiqiy dunyoning o&#39;zaro bog&#39;liq tabiatini ham aks ettiradi. Ko&#39;pgina Real muammolar va innovatsiyalar ilmiy bilimlar, texnologik tajriba, muhandislik tamoyillari, matematik tahlil va ijodiy fikrlashni birlashtirgan multidisipliner yondashuvni talab qilishini tan oladi. STEAM ta&#39;limi dunyoning ko&#39;plab mamlakatlarida ta&#39;limga qimmatli yondashuv sifatida tobora ko&#39;proq tan olinmoqda. U talabalarni tez o&#39;zgaruvchan global iqtisodiyot talablariga tayyorlaydi va ularni ilm-fan, texnologiya, muhandislik, san&#39;at va matematikani o&#39;z ichiga olgan keng ko&#39;lamli martabalarda muvaffaqiyat qozonish uchun zarur bo&#39;lgan ko&#39;nikmalar bilan jihozlaydi.Tadqiqotlar STEAM ta&#39;limida pedagogik texnologiyaning ahamiyatini izchil ta&#39;kidlaydi. Texnologiya vositalaridan foydalangan holda talabalar murakkab tushunchalarni o&#39;rganishlari, muammolarni birgalikda hal qilishlari va tanqidiy fikrlash qobiliyatlarini rivojlantirishlari mumkin. Interfaol simulyatsiyalar, virtual haqiqat va kengaytirilgan haqiqat o&#39;quvchilarga fan va matematikadagi mavhum tushunchalarni tasavvur qilish va tushunishga imkon beradigan immersiv tajribalarni taqdim etadi. Kodlash va dasturlash uchun raqamli vositalar texnologik savodxonlikni oshiradi va hisoblash tafakkurini rivojlantiradi. Tadqiqotlar shuni ko&#39;rsatdiki STEAM ta&#39;limida pedagogik texnologiyani birlashtirish talabalar natijalariga ijobiy ta&#39;sir qiladi. Texnologiyalardan foydalanish faol o&#39;rganishni osonlashtiradi, chunki talabalar passiv ma&#39;lumot oluvchilarga emas, balki faol ishtirokchilarga aylanishadi. Bu ish bilim o&#39;lchash qilmoqda, ko&#39;nikmalarini qo&#39;llash, va o&#39;sish uslub rivojlantirish. Bundan tashqari, texnologiya turli xil o&#39;quv uslublari va qobiliyatlarini uyg&#39;unlashtirgan holda shaxsiylashtirilgan o&#39;quv tajribalarini ta&#39;minlaydi. aralash ta&#39;lim: onlayn va yuzma-yuz ko&#39;rsatmalarni birlashtirib, aralash ta&#39;lim talabalarga raqamli platformalar orqali resurslarga kirish, hamkorlik qilish va shaxsiy fikr-mulohazalarni olish imkonini beradi. Ushbu yondashuv o&#39;z-o&#39;zini yo&#39;naltirilgan o&#39;rganishga yordam beradi va o&#39;qituvchilarga individual ehtiyojlar asosida o&#39;qitishni farqlashga imkon beradi. texnologiya bilan loyihaga asoslangan ta&#39;lim: texnologiyani loyihaga asoslangan ta&#39;limga integratsiya qilish talabalarni STEAM tushunchalarini Real muammolarga tatbiq etishga undaydi. Ular prototiplarni yaratish, tajribalar o&#39;tkazish va topilmalarini taqdim etish uchun multimedia vositalari, ma&#39;lumotlarni tahlil qilish dasturlari va dizayn dasturlaridan foydalanishlari mumkin. Ushbu yondashuv ijodkorlik, tanqidiy fikrlash va hamkorlikni rivojlantiradi. Maker Spaces va robototexnika: 3D printerlar, robototexnika to&#39;plamlari va boshqa texnologik vositalar bilan jihozlangan Maker spaces talabalarga o&#39;z yangiliklarini loyihalash, yaratish va sinab ko&#39;rish uchun amaliy tajribalarni taqdim etadi. Ushbu joylar muammolarni hal qilish ko&#39;nikmalarini, muhandislik dizayn jarayonlarini rivojlantiradi va tadbirkorlik tafakkurini rivojlantiradi. onlayn hamkorlik va aloqa: texnologiya talabalar o&#39;rtasida uzluksiz hamkorlik va muloqotni ta&#39;minlaydi, sinfdan tashqari ta&#39;limni kengaytiradi. Virtual platformalar guruh muhokamalarini, tengdoshlarning mulohazalarini va global aloqalarni osonlashtiradi, madaniy almashinuv va fanlararo hamkorlikni rag&#39;batlantiradi. Pedagogik texnologiya STEAM&#39; ta&#39;limida o&#39;zgaruvchan rol o&#39;ynaydi, talabalarga kelajak uchun zarur ko&#39;nikmalarni beradi. Texnologiyani pedagogik amaliyotga qo&#39;shib, o&#39;qituvchilar ijodkorlik, tanqidiy fikrlash va hamkorlikni rivojlantiradigan dinamik va qiziqarli o&#39;quv muhitini yaratishi mumkin. Texnologiya rivojlanib borar ekan, o&#39;qituvchilar STEAM ta&#39;limida pedagogik texnologiyaning samarali integratsiyasini ta&#39;minlab, eng yangi vositalar va metodologiyalar bilan yangilanib turishlari kerak. Ushbu yutuqlarni qabul qilib, biz keyingi avlodni tez rivojlanayotgan raqamli landshaftda rivojlanish uchun tayyorlashimiz mumkin. <strong>Foydalanilgan adabiyotlar:</strong> R.A. Mavlonova, N. H. Raxmonqulova, K.O.Matanazarova, M. K. Shirinov S. Hafizov &quot;Umumiy pedagogika&quot; &laquo; Fan va texnologiya&raquo; nashriyoti T.: 2018 N.N.Azizxo&#39;jayeva &quot;Pedagogik texnologiyalar va pedagogik mahorat&quot; &laquo;O&#39;zbekiston yozuvchilar uyishmasi Adabiyot jamg&#39;armasi&raquo; nashriyoti S.T.Turg&#39;unov, L.A.Maqsudova, H.M.Tojiboyeva, G.M.Nazirova, M.A.Umaraliyeva &quot;Padagogik jarayonlarni tashkil etish va boshqarish, sifat va samaradorligini oshirish texnologiyalari&quot; &laquo;O&#39;zbekiston Respublikasi O&#39;zPFITI &raquo; nashriyoti, T.:2014 J.G&#39;.Yo&#39;ldoshev, M.K.Shirinov, F.I.Ochilov &quot;Pedagogik diagnostika&quot; o&#39;quv metodik qo&#39;llanma T.:2014 O&#39;tkir Tolipov, Dilnoz Ro&#39;ziyeva &quot;Pedagogik texnologiyalar va pedagogik mahorat&quot; &laquo;Toshkent innovatsiya-ziyo&raquo; T.: 2019

<strong>Annotatsiya.</strong> Sabzavot tarkibida organizmdagi moddalar almashinuvi, insonning tashqi ko&lsquo;rinishiga o&lsquo;z ta&rsquo;sirini ko&lsquo;rsatuvchi A vitamini va beta-karotin mavjud. Masalan, insonda A vitamini yetishmovchiligi bo&lsquo;lsa, teri quriydi va sochda qazg&lsquo;oq paydo bo&lsquo;ladi. A vitamini ko&lsquo;z mushaklariga va to&lsquo;r pardasiga ta&rsquo;sir qiladi. Lavlagi boshqa sabzavotlarga nisbatan yuqori shakar miqdori bilan mashhur. Bunga qaramay, lavlagi diabet uchun ham foydalidir. Lavlagini foydali sabzavot sifatida afzal ko'rish mumkin. <strong>Аннотация.</strong> Овощ содержит витамин А и бета-каротин, которые влияют на обмен веществ в организме и внешний вид. Например, если человеку не хватает витамина А, кожа становится сухой, а на волосах появляется перхоть. Витамин А влияет на мышцы глаз и сетчатку. Морковь известна своим высоким содержанием сахара по сравнению с другими овощами. Несмотря на это, морковь полезна и при диабете. Морковь можно предпочесть как полезный овощ. <strong>Abstract.</strong> The vegetable contains vitamin A and beta-carotene, which affect the body's metabolism and appearance. For example, if a person lacks vitamin A, the skin becomes dry and dandruff appears on the hair. Vitamin A affects the eye muscles and retina. Carrots are known for their high sugar content compared to other vegetables. Despite this, carrots are also good for diabetes. Carrots can be preferred as a healthy vegetable. <strong>Kalit so&lsquo;zlar</strong>: lavlagi, tarkibi, vitaminlar, tur, turkum, mineral, ildizmeva, uglevod. <strong>Ключевые</strong><strong> слова</strong><strong>:</strong> морковь, состав, витамины, вид, категория, минерал, корнеплод, углевод. <strong>Keywords:</strong> carrots, composition, vitamins, type, category, mineral, root vegetable, carbohydrate. &nbsp; Foydalanilgan adabiyotlar ro&lsquo;yxati 1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jabbar,&nbsp; S.,&nbsp; Abid,&nbsp; M.,&nbsp; Hu,&nbsp; B.,&nbsp; Hashim,&nbsp; M.&nbsp; M.,&nbsp; Lei,&nbsp; S.,&nbsp; Wu,&nbsp; T.,&nbsp; ve diğ.&nbsp; (2015). <em>Exploring the&nbsp; potential&nbsp; of thermosonication in carrot juice processing.</em> Journal&nbsp; of&nbsp; Food&nbsp; Science&nbsp; and&nbsp; Technology,&nbsp; 52,&nbsp; 7002&nbsp; e7013. 2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sharma,&nbsp; K.&nbsp; D.,&nbsp; Attri,&nbsp; S.,&nbsp; Karki,&nbsp; S.,&nbsp; Thakur,&nbsp; N.&nbsp; S.&nbsp; (2012).&nbsp; Chemical composition functional&nbsp; properties&nbsp; and&nbsp; processing&nbsp; of&nbsp; carrot&mdash;a&nbsp; Review.&nbsp; Food&nbsp; Sci. Technol,&nbsp; (49),&nbsp; 22&ndash;32. 3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Guo,&nbsp; M.,&nbsp; Zhanga,&nbsp; L.,&nbsp; Hea,&nbsp; Q,&nbsp; Arabid,&nbsp; S.&nbsp; A.,&nbsp; Zhaoa,&nbsp; H.,&nbsp; Chena,&nbsp; W.,&nbsp; Yea,&nbsp; X.,Liua,&nbsp; D.&nbsp; (2020).&nbsp; Synergistic&nbsp; antibacterial&nbsp; effects&nbsp; of&nbsp; ultrasound&nbsp; and thyme&nbsp; essential&nbsp; oils&nbsp; nanoemulsion&nbsp; against&nbsp; Escherichia&nbsp; coli&nbsp; O157:H7. Ultrasonics&nbsp; -&nbsp; Sonochemistry&nbsp; 66&nbsp; (2020)&nbsp; 104988. 4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Yoqubov, M., Mahammadiyev, J., &amp; Eshonqulova, A. (2023). LAVLAGI VA OLMADAN TAYYORLANGAN MAHSULOTLARNING TARKIBINI O &lsquo;RGANISH. <em>Academic research in educational sciences</em>, <em>4</em>(SamTSAU Conference 1), 872-876. 5.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tursunova, Z. (2023). USING INNOVATIVE AND INTERACTIVE METHODS IN NATIVE LANGUAGE AND READING LITERACY CLASSES. Modern Science and Research, 2(10), 777-779. 6.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; O&lsquo;G&lsquo;Li, M. N. J., &amp; Mahammadiyev, J. N. O. G. L. (2022). QISHLOQ XO&rsquo;JALIK MAHSULOTLARINI SAQLASHNING XALQ XO&rsquo;JALIGIDAGI AHAMIYATI. <em>Academic research in educational sciences</em>, (Conference), 485-488. 7.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Mahammadiyev, J., Yoqubov, M., &amp; Eshonqulova, A. (2022). QISHLOQ XO'JALIGI PESTITSIDLARIDA ISHLATILADIGAN GERBITSID VA INSEKTITSIDLARNI SAQLASHDA KAPSULALASHNING AHAMIYATI. <em>Евразийский журнал медицинских и естественных наук</em>, <em>2</em>(6), 277279. 8.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Makhammadıev, J. (2020). <em>Mikrokaps&uuml;lasyonda em&uuml;lsifiye damlacıkların korunmasında kullanılacak polimerlerin sentezi</em> (Master's thesis). 9.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Nurmanova, I., &amp; Mahammadiyev, J. (2023). APPLICATION OF MICROENCAPSULATION TECHNOLOGY IN THE FIELD OF .

<em>Mazkur maqolada mаtеmаtikаni о&rsquo;qitishdа qо&rsquo;llаnilаdigаn </em><em>yаngi innоvаtsiоn zаmоnаviy аxbоrоt tеxnоlоgiyаlаrini jоriy qilish vа ulаr оrqаli tа&rsquo;lim sаmаrаdоrligini оshirish usullari va vositalari</em><em> keltirilgan. K</em><em>о</em><em>mpyut</em><em>е</em><em>r t</em><em>ех</em><em>n</em><em>о</em><em>l</em><em>о</em><em>giyasi riv</em><em>о</em><em>jl</em><em>а</em><em>nishining </em><em>а</em><em>s</em><em>о</em><em>siy </em><em>о</em><em>mill</em><em>а</em><em>ri EHM l</em><em>а</em><em>rning turli s</em><em>о</em><em>h</em><em>а</em><em>l</em><em>а</em><em>rd</em><em>а</em><em> t</em><em>о</em><em>b</em><em>о</em><em>r</em><em>а</em><em> k</em><em>е</em><em>ng qo&rsquo;ll</em><em>а</em><em>nib b</em><em>о</em><em>r</em><em>а</em><em>yotg</em><em>а</em><em>nligid</em><em>а</em><em>d</em><em>а</em><em>dir. K</em><em>о</em><em>mpyut</em><em>е</em><em>r t</em><em>ех</em><em>n</em><em>о</em><em>l</em><em>о</em><em>giyal</em><em>а</em><em>rining qo&rsquo;ll</em><em>а</em><em>nish s</em><em>о</em><em>h</em><em>а</em><em>sining k</em><em>е</em><em>ng</em><em>а</em><em>yishi, </em><em>ах</em><em>b</em><em>о</em><em>r</em><em>о</em><em>t t</em><em>ех</em><em>n</em><em>о</em><em>l</em><em>о</em><em>giyal</em><em>а</em><em>rining yar</em><em>а</em><em>tilishi j</em><em>а</em><em>miyat h</em><em>а</em><em>yotining b</em><em>а</em><em>rch</em><em>а</em><em> s</em><em>о</em><em>h</em><em>а</em><em>l</em><em>а</em><em>rid</em><em>а</em><em> ya&rsquo;ni ishl</em><em>а</em><em>b chiq</em><em>а</em><em>rishd</em><em>а</em><em>, f</em><em>а</em><em>nd</em><em>а</em><em>, t</em><em>а</em><em>&rsquo;limd</em><em>а</em><em>, tibbiyotd</em><em>а</em><em> v</em><em>а</em><em> b</em><em>о</em><em>shq</em><em>а</em><em> j</em><em>а</em><em>bh</em><em>а</em><em>l</em><em>а</em><em>rd</em><em>а</em><em>gi riv</em><em>о</em><em>jl</em><em>а</em><em>nish ya&rsquo;ni t</em><em>е</em><em>zk</em><em>о</em><em>r </em><em>ах</em><em>b</em><em>о</em><em>r</em><em>о</em><em>t </em><em>а</em><em>lm</em><em>а</em><em>shinuvig</em><em>а</em><em>, qiq</em><em>а</em><em> v</em><em>а</em><em>qtd</em><em>а</em><em> </em><em>ах</em><em>b</em><em>о</em><em>r</em><em>о</em><em>tl</em><em>а</em><em>rni q</em><em>а</em><em>yt</em><em>а</em><em> ishl</em><em>а</em><em>sh, o&rsquo;z v</em><em>а</em><em>qtid</em><em>а</em><em> m</em><em>а</em><em>nb</em><em>а</em><em>g</em><em>а</em><em> uz</em><em>а</em><em>tishg</em><em>а</em><em> </em><em>о</em><em>lib k</em><em>е</em><em>lm</em><em>о</em><em>qd</em><em>а</em><em>. </em>

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The objective of this article is to explore how suitable Team-Based Learning (TBL) is for students with social and communication disabilities, such as those on the autism spectrum or with social anxiety. TBL is a structured form of Active Collaborative Learning, combining a flipped classroom approach with students working in permanent teams to apply concepts, models and theories into practice. The design of the study was based on an idiographic case study approach at Anglia Ruskin University, UK, treating each student as an individual rather than a representative sample. Towards the end of the academic year 2017/18, an electronic questionnaire was sent out to all students who had taken TBL modules at ARU during the preceding academic year, asking about various aspects of TBL experience. The questionnaire was repeated towards the end of the first semester of 2018/19. The questionnaire was analysed with a focus on questions relating to inclusivity, and the responses related to students who had declared a disability. The questionnaire was followed by semi-structured interviews with students with disabilities who had experienced TBL. We focused primarily on disabilities broadly related to communication, notably with dyslexia, dysgraphia, social phobia and autism that may impair students’ abilities to work in teams. Interviews were audio recorded and then transcribed. Transcriptions were thematically analysed by the research team using NVivo. The results of the study provide anonymized case studies for each of the students who took part in an interview, explaining their disability or condition, their coping strategies for studying in HE, and their experiences, both positive and negative, of the TBL modules they had taken.&#x0D; References&#x0D; &#x0D; Active Collaborative Learning. (2019). Scaling Up Active Collaborative Learning for Student Success. Project website. https://aclproject.org.uk.&#x0D; ARU. (2017). Equality, Diversity and Inclusion at our University. Annual Report. Anglia Ruskin University.https://web.anglia.ac.uk/anet/student_services/public/AngliaRuskinReport_2017_AW_ACCESSIBLE.pdf.&#x0D; ARU. (2018). Student Snapshots. Anglia Ruskin University. https://aru.ac.uk/about-us/equality-diversity-and-inclusion/equality-diversity-and-inclusion-for-students/aru-student-snapshots.&#x0D; ARU. (2020). Disability Support. Anglia Ruskin University. https://aru.ac.uk/student-life/support-and-facilities/study-skills/disability-support.&#x0D; ARU. (2020b). Inclusive Practices. Anglia Ruskin University. https://aru.ac.uk/about-us/equality-diversity-and-inclusion/equality-diversity-and-inclusion-for-students/inclusive-practices.&#x0D; Berkson, R., &amp; Richter, U.M. (2019). Can Active Collaborative Learning Improve Equality? The European Conference on Education 2019 Official Conference Proceedings. https://papers.iafor.org/submission51859/.&#x0D; Berkson, R.G., &amp; Richter, U.M. (2020). Barriers to scaling up active collaborative learning. IN S. Pratt-Adams, U.M. Richter &amp; M. Warnes (Eds.), Innovations in Active Learning in Higher Education, Ch 7. Anglia Ruskin University (in press).&#x0D; Chenail, R. J. (2009). Interviewing the Investigator: Strategies for Addressing Instrumentation and Researcher Bias Concerns in Qualitative Research. The Qualitative Report, 13(4): 14-21. https://nsuworks.nova.edu/tqr/vol13/iss4/14/.&#x0D; Dearnley, Ch., Rhodes, Ch., Roberts, P., Williams, P., &amp; Prenton, S. (2018). Team based learning in nursing and midwifery higher education; a systematic review of the evidence for change. Nurse Education Today, 60: 75-83. http://dx.doi.org/10.1016/j.nedt.2017.09.012.&#x0D; Eksteen, M.J. (2019). Does team-based learning develop essential generic skills in pharmacy students? South African Journal of Higher Education, 33(1). https://www.journals.ac.za/index.php/sajhe/article/view/1332. http://dx.doi.org//10.20853/33-1-1332.&#x0D; Haidet, P., Kubitz, K., &amp; McCormack, W. T. (2014). Analysis of the team-based learning literature: TBL comes of age. Journal on Excellence in College Teaching, 25(3-4): 303-333. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4643940/.&#x0D; Hefce. (2018). Differences in student outcomes. The effect of student characteristics. Data Analysis report March 2018/05. https://dera.ioe.ac.uk/31412/1/HEFCE2017_05%20.pdf&#x0D; HM Government. (2017). Industrial Strategy. Building a Britain fit for the future. UK Government White Paper. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/664563/industrial-strategy-white-paper-web-ready-version.pdf.&#x0D; Kent, S., Wanzek, J., Swanson, E.A., &amp; Vaughn, S. (2015). Team-Based Learning for Students with High-Incidence Disabilities in High School Social Studies Classrooms. Learning Disabilities Research &amp; Practice, 30(1): 3-14. https://onlinelibrary.wiley.com/doi/abs/10.1111/ldrp.12048.&#x0D; Koles, P.G., Stolfi, A., Borges, N.J., Nelson S., &amp; Parmelee, D.X. (2010). The impact of team-based learning on medical students' academic performance. Academic Medicine: Journal of the Association of American Medical Colleges, 85(11): 1739-1745. https://pubmed.ncbi.nlm.nih.gov/20881827/ http://dx.doi.org/: 10.1097/ACM.0b013e3181f52bed.&#x0D; Michaelsen, L. K., Davidson, N., &amp; Major, C. H. (2014). Team-based learning practices and principles in comparison with cooperative learning and problem-based learning. Journal on Excellence in College Teaching, 25(3&amp;4): 57-84. https://www.lhthompson.com/uploads/4/2/1/1/42117203/team_based_learning_-_group_work.pdf.&#x0D; Michaelsen, L. K., Knight, A. B., &amp; Fink, L. D. (2004). Team-based learning: A transformative use of small groups in higher education. Sterling, VA: Stylus.&#x0D; McNeil, J., Borg, M., Kennedy, E., Cui, V., Puntha, H., Rashid, Z., Churchill, T., Howitt, E. and Trivedy, K., (2019a). SCALE-UP Handbook 2019-20 (3rd ed). Centre for Academic Development and Quality, Nottingham Trent University. https://www.ntu.ac.uk/__data/assets/pdf_file/0033/906927/FINAL-SCALE-UP-Handbook-2019-20.pdf.&#x0D; McNeil, J., Borg, M., Kerrigan, M., Waller, S., Richter, U., Berkson, R., Tweddell, S., &amp; McCarter, R. (2019b). Addressing barriers to student success. Scaling up Active Collaborative Learning for Student Success. Final Report, 28 March 2019, Updated 28 October 2019. https://aclproject.org.uk/wp-content/uploads/2019/07/NTU-ABSS-Final-Report-revised-Oct-2019.pdf.&#x0D; OECD. (2019). OECD Future of Education and Skills 2030. OECD Learning Compass 2030. A Series of Concept Notes. OECD. http://www.oecd.org/education/2030-project/contact/OECD_Learning_Compass_2030_Concept_Note_Series.pdf.&#x0D; Office for Students. (2019a). Addressing Barriers to Student Success programme. https://www.officeforstudents.org.uk/advice-and-guidance/promoting-equal-opportunities/addressing-barriers-to-student-success-programme/&#x0D; Office for Students. (2019b). Beyond the bare minimum: Are universities and colleges doing enough for disabled students? OfS Insight Brief 4. https://www.officeforstudents.org.uk/publications/beyond-the-bare-minimum-are-universities-and-colleges-doing-enough-for-disabled-students/#participation.&#x0D; Roulston, K., &amp; Shelton, St. A. (2015). Reconceptualizing Bias in Teaching Qualitative Research Methods. Qualitative Inquiry, (21)4: 332-342. https://journals.sagepub.com/doi/10.1177/1077800414563803.&#x0D; Sangwan, P., &amp; Sangwan, S. (2011). Inclusive Education: A Developmental Approach in Special Education. Journal of Indian Education, 36(4): 18-32. http://www.ncert.nic.in/publication/journals/pdf_files/iea/JIE_FEB2011.pdf#page=20&#x0D; Sibley, J., &amp; Ostafichuk, P. (2014). Getting Started with Team-Based Learning. Sterling, VA, USA: Stylus.&#x0D; Sisk, R. J. (2011). Team-based learning: systematic research review. Journal of Nursing Education, 50(12): 665–669. https://pubmed.ncbi.nlm.nih.gov/22007709/.&#x0D; Vaccaro, A., Daly-Cano, M., &amp; Newman, B. M. (2015). A sense of belonging among college students with disabilities: An emergent theoretical model. Journal of College Student Development, 56(7): 670-686. https://muse.jhu.edu/article/597267&#x0D; Vaughn, S., Danielson, L., Zumeta, R., &amp; Holdheide, L. (2015). Deeper Learning for Students with Disabilities. Students at the Center. Deeper Learning Research Series. Boston, MA: Jobs for the Future. https://files.eric.ed.gov/fulltext/ED560790.pdf.&#x0D; Wanzek, J., Vaughn, S., Kent, S.C., Swanson, E.A., Roberts, G., Haynes, M., &amp; Solis, M. (2014). The Effects of Team-Based Learning on Social Studies Knowledge Acquisition in High School. Journal of Research on Educational Effectiveness. 7(2): 183-204. https://www.tandfonline.com/doi/abs/10.1080/19345747.2013.836765.&#x0D; Williams, M., Pollard, E., Helena Takala, H., &amp; Houghton, A-M. (2019). Review of Support for Disabled Students in Higher Education in England. Report to the Office for Students by the Institute for Employment Studies and Researching Equity, Access and Participation. IES Report. Institute for Employment Studies and Researching Equity, Access and Participation. https://www.officeforstudents.org.uk/media/a8152716-870b-47f2-8045-.fc30e8e599e5/review-of-support-for-disabled-students-in-higher-education-in-england.pdf&#x0D; World Economic Forum. (2018). The Future of Jobs 2018. Insight Report. Centre for the New Economy and Society. http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf.&#x0D;

A inserção do jovem à vida acadêmica é uma fase caracterizada por mudanças e adaptações, e há uma forte propensão de desenvolvimento de transtornos psiquiátricos neste grupo populacional. Este estudo objetivou investigar os relatos de estudantes de odontologia sobre as razões que os levaram à pretensão de desistência do curso, opções profissionais, e falas condizentes à intenções suicidas proferidas por colegas. Trata-se de um estudo quanti-qualitativo, no qual participaram 423 graduandos de uma faculdade pública brasileira de odontologia. Foi utilizada estatística descritiva e, para a variável “pretensão de desistência”, utilizou-se análise de conteúdo. Para 45,39%, a odontologia não era a primeira opção de curso, sendo que destes, 61,08% tinham a Medicina como principal escolha. Com relação à intenção de abandono do curso, 45,63% responderam afirmativamente, sendo o motivo mais prevalente “incertezas na escolha do curso” (18,35%). Verificou-se que 59,81% dos alunos tinham conhecimento de colegas que disseram frases condizentes à intenção de suicídio. Os relatos dos estudantes denotam grande insatisfação na carreira seguida e comportamento depressivo, tendo sido observado relatos de baixa autoestima e vontade de morrer.Descritores: Depressão; Ansiedade; Educação em Odontologia; Suicídio.ReferênciasBolsoni-Silva AT, Loureiro SR. O Impacto das Habilidades Sociais para a Depressão em Estudantes Universitários. Psic Teor e Pesq. 2017;32(4): e324212.Vasconcelos TC, Dias BRT, Andrade LR, Melo GF, Barbosa L, Souza E. Prevalência de Sintomas de Ansiedade e Depressão em Estudantes de Medicina. Rev bras educ med. 2015;39(1):135-42.Catunda MAP, Ruiz VM. Qualidade de vida de universitários. Pensamento Plural: Rev Cient UNIFAE. 2008;2(1):22-31.Teixeira MAP, Dias ACG, Wottrich SH, Oliveira AM. Adaptação à universidade em jovens calouros. Psicol Esc Educ. 2008; 12(1):185-202.Victoria MS, Bravo A, Felix AK, Neves BG, Rodrigues CB, Ribeiro CCP et al. Níveis de ansiedade e depressão em graduandos da Universidade do Estado do Rio de Janeiro (UERJ). 2013; Encontro Rev Psicol. 2013;16(25):163-75Brasil. Ministério da Saúde. Prevenção do Suicídio. Manual dirigido a profissionais das equipes de saúde mental. 2006. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/manual_editoracao.pdfBrasil. Ministério da Saúde. Prevenção do suicídio: sinais para saber e agir. Disponível em: http://portalms.saude.gov.br/saude-de-a-z/suicidio#sinaisBrasil. Ministério da Educação e Cultura. Secretaria da Educação Superior. Comissão Especial de Estudos sobre a Evasão nas Universidades Públicas Brasileiras. 1996. Disponível em: http://www.andifes.org.br/wp-content/files_flutter/Diplomacao_Retencao_Evasao_Graduacao_em_IES_Publicas-1996.pdfGomes MJ, Monteiro M, Damasceno AM, Almeida TJS, Carvalho RB. Evasão Acadêmica no Ensino Superior: Estudo na Área da Saúde. Rev bras pesqui saúde. 2010;12(1):6-13Campos CJG. Método de análise de conteúdo: ferramenta para a análise de dados qualitativos no campo da saúde. Rev bras enferm. 2004;57(5):611-14.Costa SM, Durães SJA, Abreu MHNG, Bonan PRF, Vasconcelos M. Motivos de escolha da Odontologia: vocação, opção ou necessidade? Arq odontol. 2010;46(1):28-37.Lalloo R, Ayo-Yusuf OA, Yengopal V. Early-phase dental students' motivations and expectations concerning the study and profession of dentistry. SADJ. 2008;63(4):216-20.Al-Hallak KR, Nassani MZ, Heskul MM, Doumani MD, Darwish M. Reasons for choosing dentistry as a career among dental students in Saudi Arabia. Eur J Dent. 2018;12(2):275-80.Freire Mdo C, Jordao LM, de Paula Ferreira N, de Fatima Nunes M, Queiroz MG, Leles CR. Motivation towards career choice of Brazilian freshman students in a fifteen-year period. J Dent Educ. 2011;75(1):115-21.Santos BRM, Gonzales PS, Carrer FCA, Araújo ME. Perfil e expectativas dos ingressantes da Faculdade de Odontologia da USP: uma visão integrada com as diretrizes curriculares nacionais e o sistema único de saúde. Rev ABENO. 2015;15(1):28-37.Karibe H, Kawakami T, Suzuki A, Warita S, Ogata K, Aoyagi K et al. Career choice and attitudes towards dental education amongst dental students in Japan and Sweden. Eur J Dent Educ. 2009;13(2):80-6.Cervinski LF, Enricone JRB. Percepção de calouros universitários sobre o processo de adaptação ao sair da casa dos pais. Perspectiva. 2012;36(136):101-10.Silva JO, Ferreira SKA, Silva SF, Bergamini GB, Samuelsson E, Joner C et al. Correlação existente entre o estresse no ambiente de trabalho e doenças psicossomáticas. Rev Cient da Fac Educ e Meio Ambiente. 2017;8(2):177-91.Avila LA. Corpo e mente em questão: em busca da gênese dos sintomas psicossomáticos. Ide. 2016;38(61):51-61.Hernández-Pozo MR, Ávlarez OC, Contreras VA, Reséndiz SC. Desempeño académico de universitarios en relación con ansiedad escolar y auto-evaluación. Acta colomb psicol. 2008;11(1):13-23.Brasil. Ministério da Saúde. Portaria nº 1.271, 6 de Junho de 2014. Disponível em: http://bvsms.saude.gov.br/bvs/saudelegis/gm/2014/prt1271_06_06_2014.htmlBrasil. Ministério da Saúde. Agenda de Ações Estratégicas para a Vigilância e Prevenção do Suicídio e Promoção da Saúde no Brasil, 2017 a 2020. 2017. Disponível em: http://portalarquivos2.saude.gov.br/images/pdf/2017/setembro/21/17-0522-cartilha---Agenda-Estrategica-publicada.pdfWorld Health Organization. Preventing suicide. A global imperative. Geneva, 2014. Disponível em: https://www.who.int/mental_health/suicideprevention/world_report_2014/en/Xavier AM. Proteção social e saúde mental de universitários na UFF Campos. Anais do 6º Encontro Internacional de Política Social e 13º Encontro Nacional de Política Social. 2018;1(1):1-13.Silva RC, Silvino MRS, Coutinho, MS, Assis LR, Vasconcelos MED, Cavalcante JS et al. Tentativas de suicídio entre estudantes atendidos no CEATOX, Campina Grande-PB, em 2015. Biofarm. 2017;13(3):6-10.Garbin CAS, Santos LFP, Moimaz SAS, Saliba O. A operacionalização do SUS na prevenção e condução de casos de suicídio: análise documental. Rev Ciênc Plur. 2019;5(2):129-42.

As resinas compostas fotopolimerizáveis têm tido cada vez mais indicações na odontologia restauradora devido às vantagens que apresentam. Porém variações na técnica de fotoativação, densidade de energia, intensidade da luz e tempo de irradiação podem gerar polimerização incompleta, o que pode resultar em uma resina composta com alta porosidade, pouca dureza, baixo polimento, alta capacidade de pigmentação ou efeitos tóxicos na polpa. Este estudo tem por objetivo analisar o efeito do tempo de polimerização na pigmentação extrínseca de três resinas compostas fotopolimerizáveis. Utilizando uma fonte de LED, foram confeccionados 180 espécimes de resina composta microhíbrida, nanohíbrida e nanoparticulada, com diferentes protocolos de polimerização. Os espécimes foram subdivididos em grupos de acordo com o agente pigmentante. Com o uso de um colorímetro, foram analisados quanto à mudança de cor (ΔE). Os dados foram submetidos ao teste ANOVA e Duncan (α=0,05). A resina composta microhíbrida apresentou os menores valores de ΔE em comparação à nanoparticulada e à nanohíbrida quando imersos em vinho. Quanto maior o tempo de polimerização menores valores de ΔE foram obtidos. Não somente o tempo de polimerização influencia no grau de pigmentação, mas também fatores intrínsecos às resinas compostas tais como carga, agente fotoiniciador e matriz orgânica.Descritores: Autocura de Resinas Dentárias; Materiais Dentários; Pigmentação.ReferênciasMatson MR, Matson AMFP. Avaliação do grau de conversão de resinas compostas quando ativadas por luz halógena: método convencional, alta potência e método “soft”. Rev Inst Ciênc Saúde. 2006;24(4):307-11.Delaviz Y, Finer Y, Santerre JP. Biodegradation of resin composites and adhesivesby oral bacteria and saliva: A rationale for new material designs that consider the clinical environment and treatment challenges. Dent Mater. 2014;30(1):16-32.Nahsan FPS, Ueda JK, Silva JO, Schimitt VL, Naufel FS, Formighieri LA et al. Estabilidade de cor de resina composta após imersão em café, água e solução de clorexidina. Rev Bras Pesq Saúde. 2009;11(2):13-7.Al Kheraif AA, Qasim SS, Ramakrishnaiah R, Rehman I. Effect of different beverages on the color stability and degree of conversion of nano and microhybrid composites. Dent Mater J. 2013;(32)2:326-31.Ceballos L, Fuentes MV, Tafalla H, Martínez A, Flores J, Rodríguez J. Curing effectiveness of resin composites at different exposure times using LED and halogen units. Med Oral Pathol Oral Cir Bucal 2009;14(1):e51-6.Rahiotis C, Patsouri K, Silikas N, Kakaboura A. Curing efficiency of high- intensity light-emitting diode (LED) devices. J Oral Sci. 2010; 52(2):187-95.Sgarbi SC, Pereira SK, Martins JMH, Oliveira MAC, Mazur RF. Degree of conversion of resin composites light activated by halogen light and led analyzed by ultraviolet spectrometry. Rev Clín Pesq Odontol. 2010;6(3):223-30.Caldarelli PG, Beltrani FC, Santos FA, Shibayama R, Hoepper MG. Manchamento de uma resina composta e sua Relação com o efeito da intensidade da luz Emitida por aparelhos fotopolimerizadores de Lâmpada halôgena. Rev Fac Odontol Aracatuba. 2011;(32)2:44-8.Valentini F, Oliveira SGD, Guimarães GZ, Barbosa RPS, Moraes RR. Effect of surface sealant on the color stability of composite resin restorations. Braz Dent J. 2011;22(5):365-68.Freitas ABDA, Gomes HR, Guimarães FBR, Marinho VA, Barros LM. Influência do tipo de aparelho fotopolimerizador na absorção de água por restaurações de resina composta. Rev Inst Ciênc Saúde. 2008;(26)1:65-9.Porto ICCM, Soares LES, Martin AA, Cavalli V, Liporoni PCS. Influence of the photoinitiator system and light photoactivation units on the degree of conversion of dental composites. Braz Oral Res. 2010;24(4):475-81.Pequeno JHP, Araújo GS, Neri JR, Bomfim AGM, Mendonça JS, Santiago SL. Efeito dos protocolos de fotoativação na dureza de uma resina composta nanoparticulada. ROBRAC. 2012;21(56):394-97.Uhl A, Mills RW, Rzanny AE, Jandt KD. Time dependence of composite shrinkage using halogen and LED light curing. Dent Mater. 2005;21(3):278-86.Eick JD, Kotha SP, Chappelow CC, Kilway KV, Giese GJ, Glaros AG et al. Properties of silorane-based dental resins and composites containing a stressreducing monomer. Dent Mater. 2007;23(8):1011-17.Neumann MG, Schmitt CC, Ferreira GC, Correa IC. The initiating radical yields and the efficiency of polymerization for various dental photoinitiators excited by different lightcuring units. Dent Mater. 2006;22(6):576-84.Asmussen E, Peutzfeldt A. Influence of composition on rate of polymerization contraction of light-curing resin composites. Acta Odontol Scand. 2002;60(3):146-50.Silva EH, Albuquerque RC, Lanza LD, Vieira GC, Peixoto RT, Alvim HH et al. Influence of different light sources on the conversion of composite resins. Indian J Dent Res. 2011;22(6):790-94.Souza E, Espíndola M, Diegoli NM, Kuroshima KN. Avaliação da alteração de cor de diferentes compósitos restauradores - influência de corantes usados na cavidade oral - estudo in vitro. RGO. 2006;54(1):43-6.Salvego RN, Dias RPB. Figueiredo JLG. Estabilidade de cor de resinas compostas no processo de manchamento e clareamento, Rev Dental Press Estét. 2013;10(3):54-62.Firoozmandi LM, Balducci I, Araújo MAM. Influência da Fotopolimerização e da Cor da Resina Composta na Microdureza. Pesq Bras Odontoped Clín Integr. 2009;9(1):37-42.Anfe TEA, Agra CM, Vieira GF. Comparação de duas técnicas de fotoativação na sorção e solubilidade de resinas compostas em solução de etanol. J Biodent Biomater. 2011;1(1):61-7.Villalta P, Lu H, Okte Z, Garcia-Godoy F, Powers JM. Effects of staining and bleaching on color change of dental composite resins. J Prosthet Dent. 2006;95(2):137-42.Barghi N, Berry T, Hatton C. 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International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 DOI : 10.5121/ijbb.2012.2201 1 EFFICIENT PREDICTION OF DNA-BINDING PROTEINS USING MACHINE LEARNING S. Qatawneh1 , A. Alneaimi1 , Th. Rawashdeh1 , M. Muhairat1 , R. Qahwaji2 and S. Ipson2 1Department of Software Engineering, Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan S.Qatawneh@zuj.edu.jo 2 Informatics Research Institute, School of Computing, Informatics &amp; Media, University of Bradford, Richmond Road, Bradford, West Yorkshire, BD7 1DP, UK S.S.Ipson@Bradford.ac.uk ABSTRACT DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding proteins also perform important roles in many types of cellular activities. In this paper we describe machine learning systems for the prediction of DNA- binding proteins where a Support Vector Machine and a Cascade Correlation Neural Network are optimized and then compared to determine the learning algorithm that achieves the best prediction performance. The information used for classification is derived from characteristics that include overall charge, patch size and amino acids composition. In total 121 DNA- binding proteins and 238 non-binding proteins are used to build and evaluate the system. For SVM using the ANOVA Kernel with Jack-knife evaluation, an accuracy of 86.7% has been achieved with 91.1% for sensitivity and 85.3% for specificity. For CCNN optimized over the entire dataset with Jack knife evaluation we report an accuracy of 75.4%, while the values of specificity and sensitivity achieved were 72.3% and 82.6%, respectively. KEYWORDS DNA-Binding Proteins, Machine Learning, SVM, CCNN, Jack-knife Technique 1. INTRODUCTION DNA-binding proteins (DNA-BPs) represent a broad category of proteins. They are divided into 54 protein-structural families according to their structures [1]. DNA-binding proteins are involved in many areas including the organization of genetic expression (transcription factors) [2], and in the packaging of DNA inside the nucleus (histones) [3]. These binding proteins consist of the zinc finger, the helix turn helix, the leucine zipper domain, the winged helix, the ETS domain, the Helix-loop-helix and the unusual DNA-binding domain consisting of the Immunoglobulin Fold [4][5]. The interactions between protein and DNA control several cellular activities, such as transcription, replication, DNA repair, recombination and other critical steps in cellular development [1]. Consequentially, these interactions have been of considerable interest to molecular biologists over the past three decades, and more recently, to computational biologists [9][10]. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 2 Previously, a number of computational methods have been developed for automated identification and prediction of DNA-BPs based on the features derived from sequence and structure collectively and those derived from sequence alone. Ahmad et al. [11] developed SeqPredNet neural networks using sequential features and achieved 40.6% sensitivity and 76.2% specificity with 3-fold cross validation, which is similar to holdout evaluation. They further integrated overall charge and electric moment into the identification of DNA-BPs, and achieved a higher performance with 68.2% sensitivity and 66% specificity, with 6-fold crossvalidation [12]. Jones et al. [13] developed a prediction method to characterize electrostatic features of proteins for an automated approach to DNA-BP and DNA-binding site prediction. Correct predictions were made for 68% of the data set. Using the same dataset, Kuznetsov et al. [14] employed a Support Vector Machine for the identification of DNA-binding sites on the basis of sequential/structural features with 71% accuracy and balanced values of sensitivity and specificity. Yan et al. [15] developed a Na&iuml;ve Bayes classifier to predict whether a given amino acid residue is a DNA-binding residue based on its identity and the identities of its sequence neighbours and achieved 78% accuracy. Bhardwaj et al. [16] implemented an SVM approach and reported 100% accuracy for self-consistency technique. Using &ldquo;leave 1-pair holdout&rdquo; evaluation, an accuracy of 86.3% was achieved. They also reported an accuracy of 90% for Nfold cross-validation, implemented using two methods: 5-fold cross-validation and one left out method. Despite the recent advances in this field, as highlighted above, some problems still exist. In [16], the authors achieved 100% accuracy for self-consistency when training and testing an SVM using the same database. However, this is not a good measure of SVM efficiency because when we build a model we want to use it to classify new data. Hence we are chiefly interested in model performance on new (unseen) data [52]. So we should use two data set: the training set (seen data) to build the model (determine its parameters) and the test set (unseen data) to measure its performance (holding the parameters constant). Both data sets have to be representative samples of the data that the model will be applied to [52]. Using the &ldquo;one left out&rdquo; N-fold cross-validation method, which leaves each protein out for testing exactly once, Bhardwaj et al. reported 90% accuracy. In this technique, the whole proteins are randomly separated into N parts. Each time, one part is retained for testing and all others form training dataset. This is repeated until each part forms the testing dataset exactly once [16]. It should be noted that they called this method Jack-knife testing but it is not the standard Jack-knife method normally used in machine learning work. In this work, we aim to tackle some of these problems by using the Jack-knife technique which is widely recognised as an appropriate and efficient validation method, as explained later. In this paper, we describe the development of machine learning algorithms which distinguish DNA-BPs from non-binding ones with high accuracy and the investigation of different features depending on the structures and sequences of DNA-BPs. Two efficient machine learning algorithms: CCNN and SVM are optimised and then used in our prediction experiments. The organization of the paper is as follows. In the second section, the Dataset and the discriminative powers of individual features that are used in this work are described. The implementation of Machine learning Algorithms (SVM and CCNN) is presented in the third section. In the fourth section, the evaluation method adopted is discussed together with the experimental results and performance. Concluding remarks and suggestions for possible future work are given in the last section. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 3 2. METHODOLOGY AND SYSTEM DESIGN The following formatting rules must be followed strictly. This (.doc) document may be used as a template for papers prepared using Microsoft Word. Papers not conforming to these requirements may not be published in the conference proceedings. This section presents a brief description of the data used, the feature extraction techniques employed and how these features are implemented for use with Machine learning algorithms. Figure 1 shows in diagrammatic form the elements of the system design. Figure1. Block diagram representing our prediction system 2.1. Dataset The work described in this paper, used a positive dataset of 121 DNA-BPs [11-14] and a negative dataset of 238 non-DNA-BPs [13][15][16] obtained from a union of datasets previously used in related studies. These data are maintained by the Research Collaborators of Structural Bioinformatics (RCSB) (http://www.rcsb.org/pdb). Each entry in the PDB is identified by a unique 4-letter code, beginning with a number and followed by three alphanumeric characters such as 1SHA. If the structure with the PDB code chosen has multiple chains then it is also necessary to specify the chain identifier (a single alpha-numeric character). Otherwise the field is blank. A complete list of the proteins used here is available at (http://proteomics.bioengr.uic.edu/pro-dna). The structures of the complexes in both positive and negative cases were measured with better than 3&Aring; resolution. These proteins have &lt; 35% sequence identity between each pair [16][17]. 2.2. Feature Extraction The system attempts to successfully predict if a given protein belongs to the DNA-BP or nonDNA-BP classes. The proteins are translated into a state space for the problem which contains some characteristics representing features that may distinguish between the two classes. Also, every member in the dataset is given one of the two class labels: DNA-binding or non-DNAbinding for system testing and evaluation. The features studied in this paper, obtained from previous research [16], include overall charge of the protein, patch size, overall amino acid composition and amino acid surface composition. Each of these features is described in the following section. 2.2.1. Overall charge The overall charge of a protein represents the strongest attribute used in the machine learning system. However, x-ray crystallography cannot resolve the presence of hydrogen atoms in most protein crystals, which means that in most PDB files, hydrogen atoms are absent [18]. Therefore, hydrogen atoms are added to all the measured protein structures using the publicly available tool REDUCE [19]. Then the form of the potential energy function is taken directly from CHARMM force field parameters to obtain charges for all the atoms [20]. Dataset (PDB files) Problem state space (Features extraction) Descriptors With Class label Machine Learning Algorithms DNA-BPs or non DNA-BPs International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 4 As shown in Figure 2, the distributions of overall charge show significant differences for binding and non-binding proteins. More than 65% of binding proteins were positively charged whereas only 15% of the binding proteins were positively charged, so the overall, charge can be expected to distinguish between the two cases with a limited accuracy. Figure 2. Distribution of overall charge for binding and non-binding cases in units of electron charge (e). Labels on the horizontal axis indicate the upper value of the binding [16]. 2.2.2. Electrostatic calculations and patch size To extract this feature the electrostatic potential is computed using the software package Delphi [16][17][21-25]. The potential is computed for individual protein atoms, with the DNA removed. This tool solves the non-linear Poisson&ndash;Boltzmann equation using finite-difference methods to calculate the potentials at specified points. Debye-Huckel boundary conditions were employed (the default for this package) and a simplified charge set defined from the molecular dynamics package CHARMM22 [26]. Additional processes, using the DSSP program [27], calculate the exposed surface area of all residues. A residue is classified as a &ldquo;surface&rdquo; residue if it has more than 40% of its total area exposed to water; otherwise it is classified as &ldquo;buried&rdquo; [17]. Furthermore, a surface residue is defined as &ldquo;binding&rdquo; if one of its heavy atoms is within a distance of 4.5 &Aring; of any atom of the DNA [17]. The size of a patch is defined by the number of atoms it contains. Usually more then one patch is formed on each protein [16] and the size of the largest patch is used as a feature in the machine learning system. 2.2.3. Amino acid composition Overall and surface amino acid compositions are computed for a protein, each kind representing 20 descriptors (percentages of the 20 amino acids). Figure 3 illustrates the frequency of occurrence of different amino acids in both cases. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 5 Figure 3. The frequency of occurrence of different amino acids is shown for overall and surface compositions. The difference in the height of a bar for an amino acid for binding and nonbinding cases reflects a stronger preference for that amino acid in one case over the other [16]. a. Overall composition Here the whole protein is considered; because a positive charge is one of the common properties of DNA-binding proteins [28] and Lys and Arg amino acids are both positively charged their over-representation in DNA-BPs is fairly clear [16][28]. b. Surface composition When the surface of the protein is considered, typically only 40% of the whole surface is used. Surface composition is more discriminating than overall composition for hydrophobic residues such as Trp, Phe, Tyr, Cys, Ile and Met [16][17]. Binding and non-binding proteins have similar amino acid compositions [16]. Because of the limited discriminatory properties of the above compositions, this work like others [16][17], has used them in conjunction with other features. 3. MACHINE LEARNING ALGORITHMS One of the latest subjects of discussion by machine learning researchers is the comparative performance of Support Vector Machine (SVM) and Neural Networks (NN). The work described in this paper compares SVM and Cascade Correlation Neural Network (CCNN) in terms of correct DNA-BPs prediction. CCNN were chosen over other NN architectures because of their excellent performance in classification [25]. Work reported by researches in applications [26][27] not related to the DNA-BP prediction, has found SVMs to out perform NNs in some classification tasks. 3.1. Support Vector Machine Support Vector Machines are becoming popular tools for solving a variety of learning and function estimation problems. In contrast to neural networks, SVMs have a firm statistical foundation and are guaranteed to converge to the global minimum during training. They are also considered to have better generalization capabilities than neural networks and have managed to outperform neural networks in a number of applications [26-31]. SVMs employ a statistical learning theory based algorithm, introduced by V.Vapink [32], which uses the structural risk minimization principle. SVMs use non-linear-transformation kernel functions to map the input data to a high dimensional feature space, where data can become linearly separable [27][32]. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 6 In the work described here, the mySVM program developed by S.Ruping [33] was used to build the classifier. This program is based on the optimisation algorithm SVM light [34], which is equivalent to solving the following optimization problem: Maximize ( ) &sum; ( ) = &sum; &minus; &minus; = &sum; &minus; &minus; &sdot; + &minus; = = &minus;               1 * 1 )( * )( ) * , 1 ( * 2 1 ( , *) i i i i i j j xi xj yi i i i j W i (1) With respect to 0 &le; i ,i*&le; C ,i =1,...,n (2) &sum; = &sum; = =     1 1 * i i i i (3) Where (xi, yi) are a set of examples, C is a capacity constant and &alpha;٭ ,&alpha; are variables specific to each example. 3.2. Cascade Correlation Neural Network The training of back-propagation neural networks is considered to be a slow process because of the step-size and moving target problems [35]. To overcome these problems cascade neural networks were developed. These are &ldquo;self organizing&rdquo; networks [35] with topologies which are not fixed. The supervised training begins with a minimal network topology and new hidden nodes are incrementally added to create a multi-layer construction. The new hidden nodes are added to make the most of the correlation between the new node&rsquo;s output and the remaining error signal that the system is being adjusted to eliminate. The weights of a new hidden node is fixed and not changed later, hence making it a permanent feature detector in the network. This feature detector can then be used to generate outputs or to create other more complex feature detectors [35]. In a CCNN, the number of input nodes is determined by the input features, while the number of output nodes is determined by the number of different output classes. The training of a CCNN starts with no hidden nodes. The direct input-output connections are trained using the entire training set with the aid of the back propagation learning algorithm. Hidden nodes are then added gradually and every new node is connected to every input node and to every preexisting hidden node. Training is carried out using the training vector and the weights of the new hidden nodes are adjusted after each pass [35]. Cascade correlation networks have a number of attractive features including a very fast training time, often a hundred times faster than a perceptron network [35]. This makes cascade correlation network suitable for use with large training sets. Typically, cascade correlation networks are fairly small, often having fewer than a dozen neurons in the hidden layer [36][37]. This can be contrasted with probabilistic neural networks which require a hidden-layer neuron for each training case. Also, the training of CCNNs is quite robust, and good results can usually be obtained with little or no adjustment of parameters [35-37]. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 7 As with all types of systems, there are some potential pitfalls to using CCNNs. They have an extreme potential for over fitting the training data [38]; this results in excellent accuracy on the training data but poor accuracy on new, unseen data [39][40]. CCNNs are usually less accurate than probabilistic and general regression neural networks on small to medium size problems but scale up to handle large problems far better than probabilistic or general regression networks [35]. 4. DISCUSSION The values for negative and positive results in an experiment are likely to be the most useful practically. These values are influenced by the various performance criteria. In order for consistency with all other references [8-14] the performance criteria used are accuracy (the fraction of all correct predictions), sensitivity (the fraction of positive cases correctly classified) and specificity (the fraction of negative cases correctly classified). These are defined as follows: TP TN FP FN TP TN Accuracy + + + + = (4) TN FP TN Specificity + = (5) TP FN TP Sensitivity + = (6) The numbers of true positive, true negative, false positive and false negative results are indicated by TP, TN, FP and FN respectively, defined as follows: Total positives Correct positive predictions TP = (7) Total negatives Incorrect negative predictions FP = (8) Total negative Correct negative predictions TN = (9) Total positive Incorrect positive predictions FN = (10) In these equations: &ldquo;Correct positive predictions&rdquo; is the total number of cases for which the system correctly predicts a binding protein; &ldquo;Incorrect positive predictions&rdquo; is the total number of cases for which the system incorrectly predicted that a protein is binding; &ldquo;Correct negative predictions&rdquo; is the total number of cases for which the system correctly predicts a non binding protein; &ldquo;Incorrect negative predictions&rdquo; is the total number of cases for which the system International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 8 R ad ial P o lyno m ial D o t A no va 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% Accuracy Experiment Kernel Comparision of SVM with differant kernel types incorrectly predicted that a protein is non binding; &ldquo;Total positives&rdquo; is the sum of cases for binding proteins (Number of associated cases used in testing); &ldquo;Total negatives&rdquo; is the sum of cases for which a protein is non binding (Number of un-associated cases used in testing) [45][46]. 4.1 Jack-knife Technique The Jack-knife evaluation technique [40] was employed to evaluate the performances of the learning systems described in this paper. The Jack-knife technique is usually implemented to provide a correct statistical evaluation of the performance of a classifier when applied to a limited number of samples divided into two sets: a training set and testing set. In practice, a random number generator is used to select the samples used for training and the samples kept for testing. The classification error varies with the training and testing sample sets and, for a finite number of samples, an error-counting procedure is used to estimate the performance of the classifier [40]. In each experiment described in this paper, 80% of the available samples were randomly selected and used for training while the remaining 20% were used for testing. Therefore 287 samples were used for training and 72 for testing. The data were divided randomly into training and testing sets using the Jack-knife technique. The results were then analyzed to assess the performance. 4.2 Optimising Machine learning algorithms In order to determine which of the two machine learning algorithms is more suitable for predicting DNA binding proteins, SVM and CCNN systems were optimised to find the best parameters and topology, as described in the next two subsections.. 4.2.1 Optimising the SVM for final comparison The SVM experiments were carried out using the mySVM program and to optimise performance both the kernel and its parameters were determined empirically because there are no known guidelines to help choose them [41]. For the work reported here, several kernel types were tested including Dot, Polynomial, Radial and ANOVA, The results obtained are illustrated in Figure 2. Figure 4. Comparison of SVMs with different kernel types to predict DNA-BPs. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 9 The resulting values for TP, FP, FN, TN, Accuracy, Specificity and Sensitivity for different values of Gamma 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 9 17 25 33 41 49 57 65 73 81 89 97 Gamma Percentage TP FP FN TN Accuracy Specificity Sensitivity It was found that the ANOVA kernel, which is defined as ( ) ( ( ( ))) d i i k x, y = &sum;exp &minus;  x &minus; y (9) provides the best results. In equation (9), a sum of products of exponential functions in the x and y directions defines the ANOVA kernel and the shape of the kernel is controlled by the parameters &gamma; (Gamma) and d (degree). To complete the SVM optimisation it was necessary to determine the values of these parameters. During each iteration, &gamma; was incremented from 1 to 100. For each value of gamma values of the seven performance criteria TP, FP, FN, TN, Accuracy, Specificity and Sensitivity were generated, by averaging over ten iterations. The value of d was incremented from 1 to 10. The results for different values of &gamma; are shown in Figure 5. The best result was obtained using a value of &gamma; equal to 2. Figure 5. Comparison of SVM performance criteria TP, FP, FN, TN, Accuracy, Specificity and Sensitivity, for different values of Figure 6 shows the percentage accuracy of correct DNA-BP prediction when the value of &gamma; is fixed at 2 and the value of d is varied between 1 and 10. As shown in this figure, optimum performance is obtained when the ANOVA kernel used is and the &gamma; and d parameters are set to 2 and 5 respectively. Using the ANOVA kernel and these optimised parameters, resulting values obtained were 86.7% for accuracy, 91.1% for sensitivity and 85.3% for specificity. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 10 Comparision of SVM for different degree values ( Gamma value fixed = 2 ) 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 1 2 3 4 5 6 7 8 9 10 Degree Accuracy The resulting values for TP, FP, FN, TN, Accuracy, Specificity and Sensitivity for 1 hidden layer with different value of hidden nodes 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 1 5 9 13 17 21 25 29 33 37 41 45 49 Hidden Nodes Percentage TP FP FN TN Accuracy Specificity Sensitivity Figure 6 Percentage accuracy using SVM, with &gamma; set to 2 and for different values of d. 4.2.2 Optimising the CCNN for final comparison The NN has proven to be a very useful tool for solving many real-life problems. However, efficient implementation of the NN usually requires long training sessions [46] which depend on the training vector and on the topology of the NN [47]. Several topologies were investigated in previous studies [30-35][47] for several applications not related to DNA-BP prediction. These topologies included: Elman back-propagation, feed-forward back-propagation and cascade feed forward back-propagation. It was found in all these works that the CCNN provided the best performance in terms of convergence time and optimum topology. Hence, we decided to build on these findings and use a CCNN in our work. In this network, the first layer has connecting weights to the input layer and each subsequent layer has weights connecting it to all previous layers including the input layer.Two sets of experiments were carried out one using a network with one hidden layer with different value of hidden nodes, and the other using a network with two hidden layers and varying numbers of hidden nodes. From the results obtained it was concluded that a CCNN with 1 hidden layer provided the best results. The network was trained by changing the numbers of nodes from 1 to 50 in the hidden layer. For each number of hidden nodes, the values of the seven performance criteria TP, FP, FN, TN, Accuracy, Specificity and Sensitivity were generated, by averaging over ten iterations. Figure 7 shows the results obtained. Figure 7 Comparison of performance criteria TP, FP, FN, TN, Accuracy, Specificity and Sensitivity for a CCNN with 1 hidden layer and varying numbers of hidden nodes. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 11 Comparision of CCNN for one hidden layer with many hidden nodes 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 Hidden Node Accuracy Figure 8 shows the variation of accuracy with number of hidden nodes for a CCNN with 1 hidden layer and it can be seen that 5 hidden nodes gave the best performance. The optimised values obtained for Accuracy, Sensitivity and Specificity were 75.4%, 82.6% and 72.4% respectively. Figure 8 The variation of performance with number of hidden nodes for a CCNN with single hidden layer. 4.3. Comparing the performance and result analysis After optimising SVM and CCNN learning algorithms, we compared their prediction performances. As indicated before the SVM uses the ANOVA kernel with &gamma; and d parameters set to 2 and 5 respectively and the CCNN has 1 hidden layer with 5 hidden nodes. For all the training and testing experiments, the Jack-knife technique was applied to obtain the training and testing sets. According to the experiments, the CCNN requires longer training times. On the other hand, the SVM was very fast in training and on average provided the best performance, achieving 86.7% successful prediction of DNA-BP. Figure 9 shows a graphical comparison of DNA-BP accuracy for SVM and CCNN. For this work the learning process for both algorithms continues until a termination criterion is met and the training process has fully converged regardless of the number of training iterations required. We believe that this is a more accurate method of comparing different learning experiments and algorithms than the fixed number of iterations used in [16]. If a fixed number of iterations is used to compare the learning performance then we may end up comparing a fully converged learning system with a partially converged system. Another difference between our work and [16] lies in the very definition of the Jack-knife method. In [16] the protein sets are randomly separated into N parts. Each time, one part is used for testing and the others are used for training. This is repeated until each part forms the testing dataset exactly once. However, the overall performance depends on the type of proteins within each set. Without this information, it is impossible to re-produce their work. In our work, the training and testing sets are found randomly, and the system accuracy is taken to be the average of 10 learning experiments. This should make it much easier for other researchers to compare their future results with ours. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.2, June 2012 12 Comparison of DNA-BP accuracy for SVM and CCNN 60% 65% 70% 75% 80% 85% 90% 95% 100% 1 2 3 4 5 6 7 8 9 10 Experiments Accuracy SVM CCNN Figure 9 Graphical comparison of experiments results for DNA-BPs prediction using SVM and CCNN systems. 5. CONCLUSIONS AND FUTURE WORK In this paper, the implementation of two Machine learning systems for the identification of DNA-BPs has been described. The performance of both SVM and CCNN systems were evaluated using the Jack-knife method, and compared to obtain the best prediction results for DNA-BPs. An accuracy of 86.7% for SVM and 75.4 % for CCNN was achieved. These values are comparable with previously published studies giving accuracies ranging from 67% to 100% [11-17]. However, our result obtained using SVM and Jack-knife technique is higher than those reported previously using the same combination. As explained in the methodology and system design section on feature extraction, selected features used together can distinguish DNA-BPs from non-DNA-binding ones more accurately than when they are used separately [16]. Machine learning systems can exploit this observation. The implementations described here use three classes of features and the results are highly encouraging. It would be straightforward to include new features into our machine learning system, which might improve the performance. Besides including more features, another potential approach for improving the prediction power of the SVM would be through development of models specific to a class, a family or even motifs [49]. REFERENCES 1. 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