Relevant bibliographies by topics / Cell/net

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Cell/net'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Cell/net"

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Hurtley, S. "CELL BIOLOGY: Caught in the NET." Science 315, no. 5811 (January 26, 2007): 438a. http://dx.doi.org/10.1126/science.315.5811.438a.

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Boucher, Thomas O., Mohsen A. Jafari, and Glenn A. Meredith. "Petri net control of an automated manufacturing cell." Computers & Industrial Engineering 17, no. 1-4 (January 1989): 459–63. http://dx.doi.org/10.1016/0360-8352(89)90105-8.

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Vitali, Eleonora, Ilena Boemi, Giulia Tarantola, Sara Piccini, Alessandro Zerbi, Giulia Veronesi, Roberto Baldelli, et al. "Metformin and Everolimus: A Promising Combination for Neuroendocrine Tumors Treatment." Cancers 12, no. 8 (August 2, 2020): 2143. http://dx.doi.org/10.3390/cancers12082143.

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Introduction: Treatment options for neuroendocrine tumors (NETs) are rarely curative, as NETs frequently show resistance to medical therapy. The use of everolimus, an mTOR inhibitor, is limited by the development of resistance, probably due to the activation of Akt signaling. In this context, the antidiabetic drug metformin is able to inhibit mTOR, providing a rationale for the use of metformin and everolimus in combination. Methods: We investigated the effects of the metformin and everolimus combination on NET cell proliferation, apoptosis, colony formation, cell viability, NET spheroids growth and the involvement of the Akt and mTOR pathways, and also developed everolimus-resistant NET cells to further study this combination. Results: Metformin and everolimus in combination are more effective than monotherapy in inhibiting pancreatic NET (PAN-NET) cell proliferation (−71% ± 13%, p < 0.0001 vs. basal), whereas no additive effects were observed on pulmonary neuroendocrine tumor (PNT) cell proliferation. The combinatorial treatment is more effective than monotherapy in inhibiting colony formation, cell viability, NET spheroids growth rate and mTOR phosphorylation in both NET cell lines. In a PAN-NET cell line, metformin did not affect Akt phosphorylation; conversely, it significantly decreased Akt phosphorylation in a PNT cell line. Using everolimus-resistant NET cells, we confirmed that metformin maintained its effects, acting by two different pathways: Akt-dependent or independent, depending on the cell type, with both leading to mTOR suppression. Conclusions: Considering the promising effects of the everolimus and metformin combination in NET cells, our results provide a rationale for its use in NET patients.
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Chen, D. S., H. C. Chen, and J. M. Park. "An improved ART neural net for machine cell formation." Journal of Materials Processing Technology 61, no. 1-2 (August 1996): 1–6. http://dx.doi.org/10.1016/0924-0136(96)02457-0.

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Jin, Xi-Feng, Gerald Spöttl, Julian Maurer, Svenja Nölting, and Christoph Josef Auernhammer. "Inhibition of Wnt/β-Catenin Signaling in Neuroendocrine Tumors In Vitro: Antitumoral Effects." Cancers 12, no. 2 (February 4, 2020): 345. http://dx.doi.org/10.3390/cancers12020345.

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Background and aims: Inhibition of Wnt/β-catenin signaling by specific inhibitors is currently being investigated as an antitumoral strategy for various cancers. The role of Wnt/β-catenin signaling in neuroendocrine tumors still needs to be further investigated. Methods: This study investigated the antitumor activity of the porcupine (PORCN) inhibitor WNT974 and the β-catenin inhibitor PRI-724 in human neuroendocrine tumor (NET) cell lines BON1, QGP-1, and NCI-H727 in vitro. NET cells were treated with WNT974, PRI-724, or small interfering ribonucleic acids against β-catenin, and subsequent analyses included cell viability assays, flow cytometric cell cycle analysis, caspase3/7 assays and Western blot analysis. Results: Treatment of NET cells with WNT974 significantly reduced NET cell viability in a dose- and time-dependent manner by inducing NET cell cycle arrest at the G1 and G2/M phases without inducing apoptosis. WNT974 primarily blocked Wnt/β-catenin signaling by the dose- and time-dependent downregulation of low-density lipoprotein receptor-related protein 6 (LRP6) phosphorylation and non-phosphorylated β-catenin and total β-catenin, as well as the genes targeting the latter (c-Myc and cyclinD1). Furthermore, the WNT974-induced reduction of NET cell viability occurred through the inhibition of GSK-3-dependent or independent signaling (including pAKT/mTOR, pEGFR and pIGFR signaling). Similarly, treatment of NET cells with the β-catenin inhibitor PRI-724 caused significant growth inhibition, while the knockdown of β-catenin expression by siRNA reduced NET tumor cell viability of BON1 cells but not of NCI-H727 cells. Conclusions: The PORCN inhibitor WNT974 possesses antitumor properties in NET cell lines by inhibiting Wnt and related signaling. In addition, the β-catenin inhibitor PRI-724 possesses antitumor properties in NET cell lines. Future studies are needed to determine the role of Wnt/β-catenin signaling in NET as a potential therapeutic target.
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Matsui, Mika, Sachie Fujita, Shunichi Suzuki, Hiroshi Matsuno, and Satoru Miyano. "Simulated Cell Division Processes of the Xenopus Cell Cycle Pathway by Genomic Object Net." Journal of Integrative Bioinformatics 1, no. 1 (December 1, 2004): 27–37. http://dx.doi.org/10.1515/jib-2004-3.

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Summary Matsuno et al.[1] modeled and simulated that multicellular patterning by the Drosophila Delta-Notch signaling pathway by using the software “Genomic Object Net” which was developed based on hybrid functional Petri net (HFPN) architecture. In this model, cellular formation is fixed throughout the simulation. This paper constructs an HFPN model of the Xenopus cell cycle pathway, which includes the mechanism for cell division control as well as checkpoint processes. This model simulates dynamic cell division processes of the early Xenopus embryo, including the changes in cell division cycles from synchronous to asynchronous.
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Krieger, Nancy S., Walter R. Parker, Kristen M. Alexander, and David A. Bushinsky. "Prostaglandins regulate acid-induced cell-mediated bone resorption." American Journal of Physiology-Renal Physiology 279, no. 6 (December 1, 2000): F1077—F1082. http://dx.doi.org/10.1152/ajprenal.2000.279.6.f1077.

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Metabolic acidosis induces bone calcium efflux initially by physicochemical dissolution and subsequently by cell-mediated mechanisms involving inhibition of osteoblasts and stimulation of osteoclasts. In rat kidney, acidosis increases endogenous prostaglandin synthesis, and in bone, prostaglandins are important mediators of resorption. To test the hypothesis that acid-induced bone resorption is mediated by prostaglandins, we cultured neonatal mouse calvariae in neutral or physiologically acidic medium with or without 0.56 μM indomethacin to inhibit prostaglandin synthesis. We measured net calcium efflux and medium PGE2 levels. Compared with neutral pH medium, acid medium led to an increase in net calcium flux and PGE2 levels after both 48 h and 51 h, a time at which acid-induced net calcium flux is predominantly cell mediated. Indomethacin inhibited the acid-induced increase in both net calcium flux and PGE2. Net calcium flux was correlated directly with medium PGE2 ( r = 0.879, n = 29, P < 0.001). Exogenous PGE2, at a level similar to that found after acid incubation, induced net calcium flux in bones cultured in neutral medium. Acid medium also stimulated an increase in PGE2levels in isolated bone cells (principally osteoblasts), which was again inhibited by indomethacin. Thus acid-induced stimulation of cell-mediated bone resorption appears to be mediated by endogenous osteoblastic PGE2 synthesis.
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Mura, Ivan, and Attila Csikász-Nagy. "Stochastic Petri Net extension of a yeast cell cycle model." Journal of Theoretical Biology 254, no. 4 (October 2008): 850–60. http://dx.doi.org/10.1016/j.jtbi.2008.07.019.

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Falk, Thorsten, Dominic Mai, Robert Bensch, Özgün Çiçek, Ahmed Abdulkadir, Yassine Marrakchi, Anton Böhm, et al. "U-Net: deep learning for cell counting, detection, and morphometry." Nature Methods 16, no. 1 (December 17, 2018): 67–70. http://dx.doi.org/10.1038/s41592-018-0261-2.

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Dunlop, Stuart, Ben Jones, and Duncan McFarlane. "Petri Net Based Design and Diagnosis for an Assembly Cell." IFAC Proceedings Volumes 30, no. 18 (August 1997): 1107–12. http://dx.doi.org/10.1016/s1474-6670(17)42544-4.

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Dissertations / Theses on the topic "Cell/net"

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Ramnerö, David. "Semi-automatic Training Data Generation for Cell Segmentation Network Using an Intermediary Curator Net." Thesis, Uppsala universitet, Bildanalys och människa-datorinteraktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-332724.

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In this work we create an image analysis pipeline to segment cells from microscopy image data. A portion of the segmented images are manually curated and this curated data is used to train a Curator network to filter the whole dataset. The curated data is used to train a separate segmentation network to improve the cell segmentation. This technique can be easily applied to different types of microscopy object segmentation.
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Melendez, Melendez Roy Kelvin. "Sperm cell segmentation in digital micrographs based on convolutional neural networks using u-net architecture." Master's thesis, Pontificia Universidad Católica del Perú, 2021. http://hdl.handle.net/20.500.12404/19908.

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Human infertility is considered a serious disease of the the reproductive system that affects more than 10% of couples worldwide,and more than 30% of reported cases are related to men. The crucial step in evaluating male in fertility is a semen analysis, highly dependent on sperm morphology. However,this analysis is done at the laboratory manually and depends mainly on the doctor’s experience. Besides,it is laborious, and there is also a high degree of interlaboratory variability in the results. This article proposes applying a specialized convolutional neural network architecture (U-Net),which focuses on the segmentation of sperm cells in micrographs to overcome these problems.The results showed high scores for the model segmentation metrics such as precisión (93%), IoU score (86%),and DICE score of 93%. Moreover,we can conclude that U-net architecture turned out to be a good option to carry out the segmentation of sperm cells.
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Zhang, Xitong. "vU-net: edge detection in time-lapse fluorescence live cell images based on convolutional neural networks." Digital WPI, 2018. https://digitalcommons.wpi.edu/etd-theses/1224.

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Time-lapse fluorescence live cell imaging has been widely used to study various dynamic processes in cell biology. As the initial step of image analysis, it is important to localize and segment cell edges with higher accuracy. However, fluorescence live-cell images usually have issues such as low contrast, noises, uneven illumination in comparison to immunofluorescence images. Deep convolutional neural networks, which learn features directly from training images, have successfully been applied in natural image analysis problems. However, the limited amount of training samples prevents their routine application in fluorescence live-cell image analysis. In this thesis, by exploiting the temporal coherence in time-lapse movies together with VGG-16 [1] pre-trained model, we demonstrate that we can train a deep neural network using a limited number of image frames to segment the entire time-lapse movies. We propose a novel framework, vU-net, which combines the advantages of VGG-16 [1] in feature extraction and U-net [2] in feature reconstruction. Moreover, we design an auxiliary convolutional block at the end of the architecture to enhance edge detection. We evaluate our framework using dice coefficient and the distance between the predicted edge and the ground truth on high-resolution image datasets of an adhesion marker, paxillin, acquired by a Total Internal Reflection Fluorescence (TIRF) microscope. Our results demonstrate that, on difficult datasets: (i) The testing dice coefficient of vU-net is 3.2% higher than U-net with the same amount of training images. (ii) vU-net can achieve the best prediction results of U-net with one third of training images needed by U-net. (iii) vU-net produces more robust prediction than U-net. Therefore, vU-net can be more practically applied to challenging live cell movies than U-net since it requires a small size of training sets and achieved accurate segmentation.
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Liljequist, Viktor. "Development of a Bioreactor Simulator for supporting automation software test and verification." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325959.

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The GE Healthcare Life sciences organization develop and manufacture bioreactors, mixers, filtration skids and chromatography systems used together in a biomanufacturing platform. The platform is monitored and controlled by a distributed control system through a Programmable Logic Controller (PLC). The automation software controlling the platform is today tested and verified together with the physical units. The software use PROFIBUS, an industry standard for industrial automation, for communication and control of the units. Limited access to the physical units is usually a bottleneck and it's difficult to test abnormal situations to make sure the correct alarms are triggered. To reduce the hardware dependency and to provide support during test and verification, a virtual environment is developed to simulate the behavior of a bioreactor during execution. A .NET application has been developed together with a mathematical framework to simulate a cell culture and to return relevant process parameters such as pH, dissolved oxygen, temperature and weight. The results show that it's possible to simulate a bioreactor and to communicate with the control system. The software can be a valuable tool when developing and testing automation software but should not be used for process optimization or tuning of control parameters.
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Lundin, Johan. "EROI of crystalline silicon photovoltaics : Variations under different assumptions regarding manufacturing energy inputs and energy output." Thesis, Uppsala universitet, Institutionen för fysik och astronomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-199639.

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Installed photovoltaic nameplate power have been growing rapidly around the worldin the last few years. But how much energy is returned to society (i.e. net energy) by this technology, and which factors contribute the most to the amount of energy returned? The objective of this thesis was to examine the importance of certain inputs and outputs along the solar panel production chain and their effect on the energy return on (energy) investment (EROI) for crystalline wafer-based photovoltaics. A process-chain model was built using publicly available life-cycle inventory (LCI) datasets. This model has been kept simple in order to ensure transparency. Univariate sensitivity analysis for processes and multivariate case studies was then applied to the model. The results show that photovoltaic EROI values are very sensitive to assumptions regarding location and efficiency. The ability of solar panels to deliver net energy in northern regions of the earth is questionable. Solar cell wafer thickness have a large impact on EROI, with thinner wafers requiring less silicon material. Finding an alternative route for production of solar-grade silicon is also found to be of great importance, as is introduction of kerf loss recycling. Equal system sizes have been found to yield an primary EROI between approximately 5.5-19 depending on location and assumptions. This indicates that a generalized absolute EROI for photovoltaics may be of little use for decision-makers. Using the net energy cliff concept in relation to primary EROI found in this thesis shows that primary EROI rarely decreases to less than the threshold of 8:1 in univariate cases. Crystalline photovoltaics under similar system boundaries as those in the thesis model does not necessarily constrain economic growth on an energetic basis.
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Amghar, Bilal. "Modélisation, observabilité et commande de convertisseurs multicellulaires parallèles dans un environnement dédié." Phd thesis, Université de Cergy Pontoise, 2013. http://tel.archives-ouvertes.fr/tel-00880757.

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Les convertisseurs de puissance multicellulaires trouvent une place privilégiée dans le contrôle des systèmes de très forte puissance. Dans ce travail de thèse une nouvelle classe de convertisseurs de puissance est étudiée les Convertisseurs Multicellulaires Parallèles (CMP). La topologie de ces convertisseurs repose sur une association de n cellules de commutationinterconnectées par l'intermédiaire d'inductances indépendantes, appelées aussiinductances de liaison. Le CMP permet d'atteindre un courant de sortie égal à n fois le courant d'entrée du convertisseur, l'inconvénient majeur de ce type de convertisseur est le déséquilibrage des courants de branches . Dans le but de réduire et d'économiser le nombre de capteurs, nous avons proposé dans la première partie de la thèse une analyse d'observabilité spécifique à une classe de système dynamique hybride appelée Z(TN)-Observability et synthétisé un observateur hybride en utilisant l'algorithme super twisting. La deuxièmepartie du travail a été consacrée à la synthèse d'une loi de commande pour la régulation des courants de branches. En effet, le régulateur proposé est un régulateur hybride en basant sur la modélisation par réseaux de pétri de l'algorithme de contrôle. Enfin, Les deux parties théoriques sont suivies par une réalisation pratique d'un CMP à trois cellules de commutation pour valider les deux approches proposées. Les résultats expérimentaux nous ont montré les performances de l'observateur et le régulateur de courant et de tension de sortie.
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Scott, Lena. "Plasticity in the dopamine 1 receptor system : behavior and cell biological studies /." Stockholm, 2004. http://diss.kib.ki.se/2004/91-7140-060-5/.

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Verhoog, Nicolette Jeanette Dorothy. "Investigation of differential TNFα-induced interleukin-6 gene regulation by synthesis progestins medroxyprogesterone acetate (MPA) and norethindrone acetate (NET-A) in human endocervical epithelial cells and the role of the unliganded glucocorticoid receptor." Doctoral thesis, University of Cape Town, 2010. http://hdl.handle.net/11427/22025.

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Includes bibliographical references (pages 127-171).
The endocervical mucosae of the female reproductive tract (FRT) not only serve as a physical barrier against microbial infection, but they also express a wide variety of immune mediators. The endocervical epithelial cells express a distinct profile of immune-regulators, which is higher than vaginal and ectocervical epithelial cells. Constant cytokine production would ensure rapid responses to infections and maintenance of the sterility of the upper genital tract. However, overproduction of cytokines could inhibit normal reproductive processes and stimulate excess growth and cell proliferation. The synthetic progestins medroxyprogesterone acetate (MPA) and norethisterone (NET) and its derivatives (norethisterone enanthate (NET-EN); norethisterone acetate (NET-A)) are synthetic steroidal hormones designed to elicit progestational effects similar to those of the endogenous hormone progesterone (P4). They are extensively used as contraceptives and in hormone replacement therapy (HRT). Numerous studies, however, have reported that synthetic progestins affect immune function, increase the risk of sexually transmitted infections (STIs) and also change the morphology of the cervicovaginal mucosa. Despite these findings little is known about the molecular mechanisms of action of MPA and NET, in particular their differential effects on gene expression.
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Kubín, David. "Životní cyklus solární elektrárny, efektivita a návratnost." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220166.

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This master’s thesis named “The Life Cycle of Solar Power, Efficiency and Return” is divided into seven chapters and focuses on the utilization of solar radiation in photovoltaic power stations and solar thermal power stations. The first chapter of this thesis familiarizes the reader with issues concerning renewable resources of energy and presents an overview of the focus of each chapter. The following second chapter is occupied with a topical research of renewable resources of energy utilization in Europe. Further the author presents a brief glance back at the past of solar energy utilization and also a prediction of future solar energy utilization in the Czech Republic. The chapter named “Specification and parameterization of individual technologies” contains an overview of today’s most utilized photovoltaic cells and panels together with an overview of utilized solar collectors and solar thermal power stations. In the following chapter named “Concretization of typical applications and realizations of photovoltaic and solar thermal power stations and determination of all related parameters” the author describes further components of photovoltaic and solar thermal systems. The economical aspect of photovoltaic component production together with an overview of utilized photovoltaic technologies is presented in this chapter. The problem of recycling photovoltaic applications and the current legislative situation regarding this issue in the Czech Republic is also outlined within this chapter. In the fifth chapter of this master’s thesis the author presents mathematical models of a photovoltaic and a solar thermal power station with the focus on economic aspects of investment efficiency assessment. Within this master’s thesis a simulation program in the computational software program Mathematica was created by the author. This program allows a calculation of economic efficiency and return of photovoltaic power station investments. The results of executed simulations are presented in the sixth chapter of this thesis. The last chapter contains an appraisal and summary of results achieved by the author of this thesis.
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Peterson, Emily. "Proteoliposome Proton Flux Assays Establish Net Conductance, pH-Sensitivity, and Functional Integrity of a Novel Truncate of the M2 Ion "Channel" of Influenza A." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2420.

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A novel truncate of Influenza A M2 protein (residues 22-62), incorporated into a uniquely tailored proteoliposome proton uptake assay, demonstrated proton flux more characteristic of an ion transporter than a traditional ion "channel." The liposome paradigm was essential for testing the conductance activity of this M2 truncate at a range of extraphysiological pHs appropriate for channel vs. transport function determination. In addition to transporter-typical proton flux, M2(22-62) showed the key characteristics of functional integrity: selective proton uptake into liposomes and block of uptake by amantadine. Two sets of proteoliposome proton flux assays were carried out, Set 1 at pH values of 6.5, 6.0. 5.5, 5.0, and 4.5; Set 2 at pH values of 6.25, 6.0, 5.75, 5.5, 5.25, 5.0, and 4.75. Observed flux rates followed a proton transport saturation curve similar to that observed in mouse erythroleukemia cells1. Proton transport was maximal at pH 5.5 in Set 1 (139 H+/second/tetramer) and at pH 5.75 in Set 2 (43 H+/second/tetramer). Amantadine block was strongest at pH 5.5 in Set 1 and 6.25 in Set 2, and apparent desensitization of the protein severely reduced proton flux and amantadine sensitivity below pH 5.5 in both sets of experiments. Decreased external pH increased proton uptake with an apparent pKa of 6 (Set 1) or 6.5 (Set 2). These data indicate acid activation of M2(22-62) between pH 5.5-6, optimal amantadine block between pH 5.5-6.25, and a loss of peptide functionality between pH 5.9-4.7.
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Books on the topic "Cell/net"

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W.E. Heraeus Seminar (63rd 1990 Friedrichsdorf, Hesse, Germany). Nonlinear dynamics and neuronal networks: Proceedings of the 63rd W.E. Heraeus Seminar, Friedrichsdorf, 1990. Weinheim: VCH, 1991.

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Professional Microsoft Smartphone Programming. Wrox, 2007.

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An Autobiography for my Wife and Four Daughters - Book Two. Cary, U.S.: Author, 2010.

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Houillier, Pascal. Magnesium homeostasis. Edited by Robert Unwin. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0027.

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Magnesium is critically important in the process of energy release. Although most magnesium is stored outside the extracellular fluid compartment, the regulated concentration appears in blood. Urinary magnesium excretion can decrease rapidly to low values when magnesium entry rate into the extracellular fluid volume is low, which has several important implications: cell and bone magnesium do not play a major role in the defence of blood magnesium concentration; while a major role is played by the kidney and especially the renal tubule, which adapts to match the urinary magnesium excretion and net entry of magnesium into extracellular fluid. In the kidney, magnesium is reabsorbed in the proximal tubule, the thick ascending limb of the loop of Henle (TALH), and the distal convoluted tubule (DCT). Magnesium absorption is mainly paracellular in the proximal tubule and TALH, whereas it is transcellular in the DCT. The hormone(s) regulating renal magnesium transport and blood magnesium concentration are not fully understood. Renal tubular magnesium transport is altered by a number of hormones, mainly in the TALH and DCT. Parathyroid hormone, calcitonin, arginine vasopressin, ß-adrenergic agonists, and epidermal growth factor, all increase renal tubular magnesium reabsorption; in contrast, prostaglandin E2 decreases magnesium reabsorption. Non-hormonal factors also influence magnesium reabsorption: it is decreased by high blood concentrations of calcium and magnesium, probably via the action of divalent cations on the calcium-sensing receptor; metabolic acidosis decreases, and metabolic alkalosis increases, renal magnesium reabsorption.
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(Editor), T. Kumazawa, L. Kruger (Editor), and K. Mizumura (Editor), eds. The Polymodal Receptor - A Gateway to Pathological Pain (Progress in Brain Research). Elsevier Science, 1996.

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Takao, Kumazawa, Kruger Lawrence, and Mizumura Kazue, eds. The polymodal receptor: A gateway to pathological pain. Amsterdam: Elsevier, 1996.

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Book chapters on the topic "Cell/net"

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Bizon, Nicu. "Fuel Cell Net Power Maximization Strategies." In Optimization of the Fuel Cell Renewable Hybrid Power Systems, 185–241. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40241-9_5.

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Minchinton, P. R., J. M. Bishop, and R. J. Mitchell. "The Minchinton Cell — Analog Input to the N-Tuple Net." In International Neural Network Conference, 599. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0643-3_16.

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Hagos, Yeman Brhane, Priya Lakshmi Narayanan, Ayse U. Akarca, Teresa Marafioti, and Yinyin Yuan. "ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection in Multiplex Immunohistochemistry Images." In Lecture Notes in Computer Science, 667–75. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32239-7_74.

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Ding, Chunling, Guosun Zeng, and Fuhuan Wang. "Modeling and Analysis for Reconfigurable Cell Based on Stochastic Petri Net." In Communications in Computer and Information Science, 390–400. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22418-8_55.

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Huang, Jinghan, Yiqing Shen, Dinggang Shen, and Jing Ke. "CA2.5-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 445–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87237-3_43.

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Zhang, Mo, Xiang Li, Mengjia Xu, and Quanzheng Li. "RBC Semantic Segmentation for Sickle Cell Disease Based on Deformable U-Net." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, 695–702. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00937-3_79.

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Park, Inho, Dokyun Na, Kwang H. Lee, and Doheon Lee. "Fuzzy Continuous Petri Net-Based Approach for Modeling Helper T Cell Differentiation." In Lecture Notes in Computer Science, 331–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11536444_25.

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Pati, Pushpak, Guillaume Jaume, Lauren Alisha Fernandes, Antonio Foncubierta-Rodríguez, Florinda Feroce, Anna Maria Anniciello, Giosue Scognamiglio, et al. "HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification." In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 208–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60365-6_20.

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Bashir, Raja Muhammad Saad, Talha Qaiser, Shan E. Ahmed Raza, and Nasir M. Rajpoot. "HydraMix-Net: A Deep Multi-task Semi-supervised Learning Approach for Cell Detection and Classification." In Interpretable and Annotation-Efficient Learning for Medical Image Computing, 164–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61166-8_18.

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Ou, Kai, Ya-Xiong Wang, Wei-Wei Yuan, and Young-Bae Kim. "Net Power Output of Open Cathode Fuel Cell Optimization Based on the Over-Temperature Protection." In Advanced Mechanical Science and Technology for the Industrial Revolution 4.0, 235–48. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4109-9_25.

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Conference papers on the topic "Cell/net"

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Shibuya, Eisuke, and Kazuhiro Hotta. "Feedback U-net for Cell Image Segmentation." In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2020. http://dx.doi.org/10.1109/cvprw50498.2020.00495.

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Pawanekar, Sameer, and Gaurav Trivedi. "Net weighing based timing driven standard cell placer." In 2015 19th International Symposium on VLSI Design and Test (VDAT). IEEE, 2015. http://dx.doi.org/10.1109/isvdat.2015.7208114.

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Lukashevich, Marina, and Natalia Iskra. "U-Net Architecture Application to Nuclei Cell Detection." In 2019 International Conference on Information Science and Communications Technologies (ICISCT). IEEE, 2019. http://dx.doi.org/10.1109/icisct47635.2019.9011982.

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Akbas, Cem Emre, and Michal Kozubek. "Condensed U-Net (Cu-Net): An Improved U-Net Architecture for Cell Segmentation Powered by 4x4 Max-Pooling Layers." In 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). IEEE, 2020. http://dx.doi.org/10.1109/isbi45749.2020.9098351.

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Kumar, C. Akshay, Mahesh Kumar T. N, and A. V. Narasimhadhan. "Cell Segmentation by Modified U-Net Architecture for Biomedical Images." In 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2020. http://dx.doi.org/10.1109/conecct50063.2020.9198530.

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Bakir, Mehmet Emin, and ve Hacer Yalim Keles. "Deep Learning Based Cell Segmentation Using Cascaded U-Net Models." In 2021 29th Signal Processing and Communications Applications Conference (SIU). IEEE, 2021. http://dx.doi.org/10.1109/siu53274.2021.9477937.

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Fujii, Haruki, Hayato Tanaka, Momoko Ikeuchi, and Kazuhiro Hotta. "X-net with Different Loss Functions for Cell Image Segmentation." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2021. http://dx.doi.org/10.1109/cvprw53098.2021.00420.

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Gong, Mingmin, Aijun Chen, and Hao Feng. "U-net gland cell image segmentation method combined with spatial attention." In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2021. http://dx.doi.org/10.1109/icaica52286.2021.9498180.

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Kwon, Jason, Xiaohua Wang, Rajesh K. Ahluwalia, and Aymeric Rousseau. "Impact of fuel cell system design used in series fuel cell HEV on net present value (NPV)." In 2011 IEEE Vehicle Power and Propulsion Conference (VPPC). IEEE, 2011. http://dx.doi.org/10.1109/vppc.2011.6043039.

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D'Souza, Kelwyn A., and Suresh K. Khator. "Petri Net based simulation of controls for a computer-integrated assembly cell." In the 24th conference. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/167293.167793.

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