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Academic literature on the topic 'Metabolom'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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Journal articles on the topic "Metabolom"

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Roos, Martin. "Metabolom gibt Aufschlüsse." Im Focus Onkologie 19, no. 4 (April 2016): 10. http://dx.doi.org/10.1007/s15015-016-2443-z.

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Schütz, Burkhard, Heiko Hofmann, and Ricarda Kuenen. "Intestinales Mikrobiom und humanes Metabolom." Deutsche Zeitschrift für Onkologie 51, no. 04 (December 2019): 165–70. http://dx.doi.org/10.1055/a-1030-2772.

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ZusammenfassungDie mikrobielle Besiedlung des Darmes (intestinales Mikrobiom) beeinflusst die Gesundheit des gesamten Organismus. Je nach Zusammensetzung des Mikrobioms ergeben sich unterschiedliche Stoffwechselprozesse im Darm (Metabolom), die wiederum zu unterschiedlichen Stoffwechselprodukten, den Metaboliten, führen. In Abhängigkeit des intestinalen Mikrobioms und Metaboloms ergibt sich ein bestimmtes Metaboliten-Profil, welches bei der Entstehung und dem Verlauf diverser Erkrankungen eine bedeutende Rolle spielen kann, auch bei onkologischen Erkrankungen. Mit dem Wissen dieser bisher nicht bekannten biochemischen Zusammenhänge eröffnen sich neue und ursachenorientierte therapeutische Möglichkeiten in der Behandlung und Prävention von onkologischen Fällen. In diesem Artikel stellen wir inzwischen gut erforschte Wechselwirkungen zwischen intestinalem Mikrobiom und der humanen Darmmucosa, dem Gallensäuren-Stoffwechsel, der Biotransformation und Ausscheidung von Hormonen, Toxinen und mehr vor. Auch Mikrobiomeinflüsse auf Nahrungsbestandteile (z. B. Lecithin, Carnitin, Cholin u. a.) und Tryptophanmetabolismus werden erörtert.

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Mardin, W. A. "Das Metabolom des kolorektalen Karzinoms." Der Onkologe 20, no. 6 (May 11, 2014): 587–88. http://dx.doi.org/10.1007/s00761-014-2696-0.

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Tillack, J., N. Paczia, S. Leweke, M. Oldiges, W. Wiechert, K. Nöh, and S. Noack. "Modellierung und detaillierte Fehleranalyse der Metabolom-Datenprozessierung." Chemie Ingenieur Technik 82, no. 9 (August 27, 2010): 1556–57. http://dx.doi.org/10.1002/cite.201050353.

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Staiger, Dorothee. "Wie der Mensch das Tomaten-Metabolom verändert." Biologie in unserer Zeit 48, no. 4 (August 2018): 213–14. http://dx.doi.org/10.1002/biuz.201870407.

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MATOUŠEK, Jaroslav. ""Transgenic" metabolome of hop, some aspects of its development and prospects of utilization." Kvasny Prumysl 58, no. 1 (January 1, 2012): 13–19. http://dx.doi.org/10.18832/kp2012003.

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Fritschka, Emanuel. "Gliflozin verbessert Urin-Metabolom auch bei nierengesunden Diabetikern." Info Diabetologie 15, no. 3 (June 2021): 16–17. http://dx.doi.org/10.1007/s15034-021-3701-5.

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Krome, Dr Susanne. "Multiples Myelom." Onkologische Welt 09, no. 05 (December 2018): 218–19. http://dx.doi.org/10.1055/s-0038-1677584.

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Ein Metabolom umfasst die Gesamtheit der Stoffwechseleigenschaften von Zellen. Bislang war wenig über ein spezifisches metabolisches Muster von Myelomzellen bekannt. Die Studie belegt Unterschiede zu gesunden Kontrollen. Die Abgrenzung inner-halb der Myelom-Patientenpopulation war weniger markant.

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Vergara, Daniele, Sara Ravaioli, Eugenio Fonzi, Loredaria Adamo, Marina Damato, Sara Bravaccini, Francesca Pirini, et al. "Carbonic Anhydrase XII Expression Is Modulated during Epithelial Mesenchymal Transition and Regulated through Protein Kinase C Signaling." International Journal of Molecular Sciences 21, no. 3 (January 22, 2020): 715. http://dx.doi.org/10.3390/ijms21030715.

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Members of the carbonic anhydrase family are functionally involved in the regulation of intracellular and extracellular pH in physiological and pathological conditions. Their expression is finely regulated to maintain a strict control on cellular homeostasis, and it is dependent on the activation of extracellular and intracellular signaling pathways. Combining RNA sequencing (RNA-seq), NanoString, and bioinformatics data, we demonstrated that the expression of carbonic anhydrase 12 (CAXII) is significantly different in luminal and triple negative breast cancer (BC) models and patients, and is associated with the activation of an epithelial mesenchymal transition (EMT) program. In BC models, the phorbol ester 12-myristate 13-acetate (PMA)-mediated activation of protein kinase C (PKC) induced a down-regulation of CAXII with a concomitant modulation of other members of the transport metabolon, including CAIX and the sodium bicarbonate cotransporter 3 (NBCn1). This is associated with a remodeling of tumor glycolytic metabolism induced after PKC activation. Overall, this analysis highlights the dynamic nature of transport metabolom and identifies signaling pathways finely regulating this plasticity.

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Nenko, N. I., I. A. Ilina, M. A. Sundyreva, G. K. Kiseleva, and Т. V. Skhalyakho. "Metabolom characteristics of grape plant stability to low temperature stress." Scientific Works of North Caucasian Federal Scientific Center of Horticulture, Viticulture, Wine-making 15 (June 2018): 39–49. http://dx.doi.org/10.30679/2587-9847-2018-15-39-49.

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Dissertations / Theses on the topic "Metabolom"

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Daub, Carsten O. "Analysis of integrated transcriptomics and metabolomics data a systems biology approach /." [S.l. : s.n.], 2004. http://pub.ub.uni-potsdam.de/2004/0025/daub.pdf.

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Jungnickel, Arne [Verfasser]. "Einfluss bariatrischer Chirurgie auf das Metabolom des Urins / Arne Jungnickel." Greifswald : Universitätsbibliothek Greifswald, 2013. http://d-nb.info/1037811844/34.

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Daniel, Christina. "Identifizierung und Nachweis pflanzlicher Substanzen über ITS-Sequenzen und Fingerprint-Analyse des Metaboloms." München Verl. Dr. Hut, 2009. http://d-nb.info/994105606/04.

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Bader, Matthias [Verfasser]. "Einfluss von Chemosensorika auf Metabolom, Proteom und Funktionalität des Speichels beim Menschen / Matthias Bader." München : Verlag Dr. Hut, 2019. http://d-nb.info/1188516361/34.

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Kaspar, Hannelore. "Amino acid analysis in biological fluids by GC-MS." kostenfrei, 2009. http://www.opus-bayern.de/uni-regensburg/volltexte/2009/1316/.

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Orland, Annika [Verfasser]. "Metabolomic and Transcriptomic Analyses in the Characterization of Herbal Substances and their Preparations = Metabolom- und Transkriptom-Analysen zur Charakterisierung von pflanzlichen Substanzen und daraus hergestellten Zubereitungen / Annika Orland." Bonn : Universitäts- und Landesbibliothek Bonn, 2014. http://d-nb.info/1077290357/34.

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Timischl, Birgit. "Hyphenated mass spectrometric methods for quantitative metabolomics in E. coli and human cells." kostenfrei, 2008. http://www.opus-bayern.de/uni-regensburg/volltexte/2008/1028/.

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Bergner, Elena [Verfasser], Sacha [Gutachter] Baginsky, Udo [Gutachter] Johannigmeier, and Thomas [Gutachter] Pfannschmidt. "Molekulare und funktionelle Charakterisierung der Casein Kinase 2 : vergleichende Phosphoproteom- und Metabolom-Analysen / Elena Bergner ; Gutachter: Sacha Baginsky, Udo Johannigmeier, Thomas Pfannschmidt." Halle (Saale) : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2020. http://d-nb.info/1210727811/34.

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Hammerl, Richard [Verfasser]. "Differenzielle off-line LC-NMR Kopplung (DOLC-NMR) zur molekularen Kartierung Nährstoff-induzierter Metabolom-Veränderungen in Saccharomyces cerevisiae und Penicillium roqueforti / Richard Hammerl." München : Verlag Dr. Hut, 2020. http://d-nb.info/1219478563/34.

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Birkemeyer, Claudia Sabine. "Signal-metabolome interactions in plants." Phd thesis, Universität Potsdam, 2005. http://opus.kobv.de/ubp/volltexte/2006/714/.

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From its first use in the field of biochemistry, instrumental analysis offered a variety of invaluable tools for the comprehensive description of biological systems. Multi-selective methods that aim to cover as many endogenous compounds as possible in biological samples use different analytical platforms and include methods like gene expression profile and metabolite profile analysis. The enormous amount of data generated in application of profiling methods needs to be evaluated in a manner appropriate to the question under investigation. The new field of system biology rises to the challenge to develop strategies for collecting, processing, interpreting, and archiving this vast amount of data; to make those data available in form of databases, tools, models, and networks to the scientific community.

On the background of this development a multi-selective method for the determination of phytohormones was developed and optimised, complementing the profile analyses which are already in use (Chapter I). The general feasibility of a simultaneous analysis of plant metabolites and phytohormones in one sample set-up was tested by studies on the analytical robustness of the metabolite profiling protocol. The recovery of plant metabolites proved to be satisfactory robust against variations in the extraction protocol by using common extraction procedures for phytohormones; a joint extraction of metabolites and hormones from plant tissue seems practicable (Chapter II).

Quantification of compounds within the context of profiling methods requires particular scrutiny (Chapter II). In Chapter III, the potential of stable-isotope in vivo labelling as normalisation strategy for profiling data acquired with mass spectrometry is discussed. First promising results were obtained for a reproducible quantification by stable-isotope in vivo labelling, which was applied in metabolomic studies.

In-parallel application of metabolite and phytohormone analysis to seedlings of the model plant Arabidopsis thaliana exposed to sulfate limitation was used to investigate the relationship between the endogenous concentration of signal elements and the ‘metabolic phenotype’ of a plant. An automated evaluation strategy was developed to process data of compounds with diverse physiological nature, such as signal elements, genes and metabolites – all which act in vivo in a conditional, time-resolved manner (Chapter IV). Final data analysis focussed on conditionality of signal-metabolome interactions.
Die instrumentelle Analytik stellt mit ihrem unschätzbaren Methodenreichtum Analysenwerkzeuge zur Verfügung, die seit ihrem Einzug in die Biologie die Aufzeichnung immer komplexerer ‚Momentaufnahmen’ von biologischen Systemen ermöglichen. Konkret hervorzuheben sind dabei vor allem die sogenannten ‚Profilmethoden’. Die Anwendung von Profilmethoden zielt darauf ab, aus einer bestimmten Stoffklasse so viele zugehörige Komponenten wie nur möglich gleichzeitig zu erfassen.

Für die Auswertung derart komplexer Daten müssen nun auch entsprechende Auswertungsmethoden bereit gestellt werden. Das neu entstandene Fachgebiet der Systembiologie erarbeitet deshalb Strategien zum Sammeln, Auswerten und Archivieren komplexer Daten, um dieses gesammelte Wissen in Form von Datenbanken, Modellen und Netzwerken der allgemeinen Nutzung zugänglich zu machen.

Vor diesem Hintergrund wurde den vorhandenen Profilanalysen eine Methode zur Erfassung von Pflanzenhormonen hinzugefügt. Verschiedene Experimente bestätigten die Möglichkeit zur Kopplung von Pflanzenhormon- und Pflanzeninhaltsstoff(=metabolit)-Profilanalyse. In weiteren Untersuchungen wurde das Potential einer innovativen Standardisierungstechnologie für die mengenmässige Erfassung von Pflanzeninhaltsstoffen in biologischen Proben betrachtet (in vivo labelling mit stabilen Isotopen).

Hormon- und Metabolitprofilanalyse wurden dann parallel angewandt, um Wechselwirkungen zwischen der Konzentration von Signalkomponenten und der Ausprägung des Stoffwechsels in Keimlingen der Modellpflanze Arabidopsis thaliana zu untersuchen. Es wurde eine Prozessierungsmethode entwickelt, die es auf einfache Art und Weise erlaubt, Daten oder Komponenten verschiedenen Ursprungs wie Signalelemente, Gene und Metabolite, die in biologischen Systemen zeitlich versetzt aktiv oder verändert erscheinen, im Zusammenhang zu betrachten. Die abschließende Analyse aller Daten richtet sich auf die Abschätzung der Bedingtheit von Signal-Metabolismus Interaktionen.

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Books on the topic "Metabolom"

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McCandless, David W., ed. Cerebral Energy Metabolism and Metabolic Encephalopathy. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-1209-3.

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Verpoorte, Robert, and A. W. Alfermann, eds. Metabolic Engineering of Plant Secondary Metabolism. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-015-9423-3.

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Verpoorte, Robert. Metabolic Engineering of Plant Secondary Metabolism. Dordrecht: Springer Netherlands, 2000.

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Robertson, R. Paul, ed. Translational Endocrinology & Metabolism: Metabolic Surgery Update. 8401 Connecticut Avenue, Suite 900, Chevy Chase, Maryland 20815: The Endocrine Society, 2012. http://dx.doi.org/10.1210/team.9781936704071.

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Reeves, Sue L. Biological variation in basal metabolic rate and energy metabolism. Oxford: Oxford Brookes University, 1997.

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Surgical metabolism: The metabolic care of the surgical patient. New York: Springer, 2014.

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Guest, Paul C., ed. Reviews on Biomarker Studies of Metabolic and Metabolism-Related Disorders. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12668-1.

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Rigden, Scott. The ultimate metabolism diet: Eat right for your metabolic type. Alameda, CA: Hunter House Publishers, 2009.

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Lutz, Norbert, Jonathan V. Sweedler, and Ron Wevers. Methodologies for metabolomics: Experimental strategies and techniques. Cambridge: Cambridge University Press, 2012.

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American Society for Bone and Mineral Research, ed. Primer on the metabolic bone diseases and disorders of mineral metabolism. 4th ed. Philadelphia: Lippincott Williams & Wilkins, 1999.

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Book chapters on the topic "Metabolom"

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Sackmann-Sala, Lucila, D. R. Bailey Miles, and John J. Kopchick. "Metabolism and Metabolic Regulation." In Laron Syndrome - From Man to Mouse, 451–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11183-9_52.

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Guo, Shenghao, Yanni Gu, Jiayin Qu, and Anne Le. "Bridging the Metabolic Parallels Between Neurological Diseases and Cancer." In The Heterogeneity of Cancer Metabolism, 229–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_17.

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AbstractDespite the many recent breakthroughs in cancer research, oncology has traditionally been seen as a distinct field from other diseases. Recently, more attention has been paid to repurposing established therapeutic strategies and targets of other diseases towards cancer treatment, with some of these attempts generating promising outcomes [1, 2]. Recent studies using advanced metabolomics technologies [3] have shown evidence of close metabolic similarities between cancer and neurological diseases. These studies have unveiled several metabolic characteristics shared by these two categories of diseases, including metabolism of glutamine, gamma-aminobutyric acid (GABA), and N-acetyl-aspartyl-glutamate (NAAG) [4–6]. The striking metabolic overlap between cancer and neurological diseases sheds light on novel therapeutic strategies for cancer treatment. For example, 2-(phosphonomethyl) pentanedioic acid (2-PMPA), one of the glutamate carboxypeptidase II (GCP II) inhibitors that prevent the conversion of NAAG to glutamate, has been shown to suppress cancer growth [6, 7]. These promising results have led to an increased interest in integrating this metabolic overlap between cancer and neurological diseases into the study of cancer metabolism. The advantages of studying this metabolic overlap include not only drug repurposing but also translating existing knowledge from neurological diseases to the field of cancer research. This chapter discusses the specific overlapping metabolic features between cancer and neurological diseases, focusing on glutamine, GABA, and NAAG metabolisms. Understanding the interconnections between cancer and neurological diseases will guide researchers and clinicians to find more effective cancer treatments.

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Paro, Renato, Ueli Grossniklaus, Raffaella Santoro, and Anton Wutz. "Epigenetics and Metabolism." In Introduction to Epigenetics, 179–201. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68670-3_9.

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AbstractMost chromatin-modifying enzymes use metabolites as cofactors. Consequently, the cellular metabolism can influence the capacity of the cell to write or erase chromatin marks. This points to an intimate relationship between metabolic and epigenetic regulation. In this chapter, we describe the biosynthetic pathways of cofactors that are implicated in epigenetic and chromatin regulation and provide examples of how metabolic pathways can influence chromatin and epigenetic processes as well as their interplay in developmental and cancer biology.

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Li, Ting, Christopher Copeland, and Anne Le. "Glutamine Metabolism in Cancer." In The Heterogeneity of Cancer Metabolism, 17–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_2.

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AbstractMetabolism is a fundamental process for all cellular functions. For decades, there has been growing evidence of a relationship between metabolism and malignant cell proliferation. Unlike normal differentiated cells, cancer cells have reprogrammed metabolism in order to fulfill their energy requirements. These cells display crucial modifications in many metabolic pathways, such as glycolysis and glutaminolysis, which include the tricarboxylic acid (TCA) cycle, the electron transport chain (ETC), and the pentose phosphate pathway (PPP) [1]. Since the discovery of the Warburg effect, it has been shown that the metabolism of cancer cells plays a critical role in cancer survival and growth. More recent research suggests that the involvement of glutamine in cancer metabolism is more significant than previously thought. Glutamine, a nonessential amino acid with both amine and amide functional groups, is the most abundant amino acid circulating in the bloodstream [2]. This chapter discusses the characteristic features of glutamine metabolism in cancers and the therapeutic options to target glutamine metabolism for cancer treatment.

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Borén, Jan, and Martin Adiels. "Lipid Metabolism in Metabolic Syndrome." In A Systems Biology Approach to Study Metabolic Syndrome, 157–70. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01008-3_8.

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Behrends, Volker, Huw D. Williams, and Jacob G. Bundy. "Metabolic Footprinting: Extracellular Metabolomic Analysis." In Methods in Molecular Biology, 281–92. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0473-0_23.

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Alleyne, George A. O., Jose A. Lupianez, Norma McFarlane-Anderson, Paloma Hortelano, Jacqueline Benjamin, Jennifer Barnswell, and Barbara Scott. "Glutamine Metabolism in Metabolic Acidosis." In Ciba Foundation Symposium 87 - Metabolic Acidosis, 101–19. Chichester, UK: John Wiley & Sons, Ltd., 2008. http://dx.doi.org/10.1002/9780470720691.ch6.

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Günther, Ulrich L., Mei G. Chong, Tatiana Volpari, Katarzyna M. Koczula, Karen Atkins, Christopher M. Bunce, and Farhat L. Khanim. "Metabolic Fluxes in Cancer Metabolism." In Tumor Cell Metabolism, 315–48. Vienna: Springer Vienna, 2015. http://dx.doi.org/10.1007/978-3-7091-1824-5_14.

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Hoang, Giang, Kiet Nguyen, and Anne Le. "Metabolic Intersection of Cancer and Cardiovascular Diseases: Opportunities for Cancer Therapy." In The Heterogeneity of Cancer Metabolism, 249–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_18.

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AbstractAccording to data from the World Health Organization, cardiovascular diseases and cancer are the two leading causes of mortality in the world [1]. Despite the immense effort to study these diseases and the constant innovation in treatment modalities, the number of deaths associated with cardiovascular diseases and cancer is predicted to increase in the coming decades [1]. From 2008 to 2030, due to population growth and population aging in many parts of the world, the number of deaths caused by cancer globally is projected to increase by 45%, corresponding to an annual increase of around four million people [1]. For cardiovascular diseases, this number is six million people [1]. In the United States, treatments for these two diseases are among the most costly and result in a disproportionate impact on low- and middleincome people. As the fight against these fatal diseases continues, it is crucial that we continue our investigation and broaden our understanding of cancer and cardiovascular diseases to innovate our prognostic and treatment approaches. Even though cardiovascular diseases and cancer are usually studied independently [2–12], there are some striking overlaps between their metabolic behaviors and therapeutic targets, suggesting the potential application of cardiovascular disease treatments for cancer therapy. More specifically, both cancer and many cardiovascular diseases have an upregulated glutaminolysis pathway, resulting in low glutamine and high glutamate circulating levels. Similar treatment modalities, such as glutaminase (GLS) inhibition and glutamine supplementation, have been identified to target glutamine metabolism in both cancer and some cardiovascular diseases. Studies have also found similarities in lipid metabolism, specifically fatty acid oxidation (FAO) and synthesis. Pharmacological inhibition of FAO and fatty acid synthesis have proven effective against many cancer types as well as specific cardiovascular conditions. Many of these treatments have been tested in clinical trials, and some have been medically prescribed to patients to treat certain diseases, such as angina pectoris [13, 14]. Other metabolic pathways, such as tryptophan catabolism and pyruvate metabolism, were also dysregulated in both diseases, making them promising treatment targets. Understanding the overlapping traits exhibited by both cancer metabolism and cardiovascular disease metabolism can give us a more holistic view of how important metabolic dysregulation is in the progression of diseases. Using established links between these illnesses, researchers can take advantage of the discoveries from one field and potentially apply them to the other. In this chapter, we highlight some promising therapeutic discoveries that can support our fight against cancer, based on common metabolic traits displayed in both cancer and cardiovascular diseases.

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Kiran, Usha, Athar Ali, Kamaluddin, and Malik Zainul Abdin. "Metabolic Engineering of Secondary Plant Metabolism." In Plant Biotechnology: Principles and Applications, 173–90. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2961-5_6.

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Conference papers on the topic "Metabolom"

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Occhipinti, Annalisa, and Claudio Angione. "A Computational Model of Cancer Metabolism for Personalised Medicine." In Building Bridges in Medical Science 2021. Cambridge Medicine Journal, 2021. http://dx.doi.org/10.7244/cmj.2021.03.001.3.

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Cancer cells must rewrite their ‘‘internal code’’ to satisfy the demand for growth and proliferation. Such changes are driven by a combination of genetic (e.g., genes’ mutations) and non-genetic factors (e.g., tumour microenvironment) that result in an alteration of cellular metabolism. For this reason, understanding the metabolic and genomic changes of a cancer cell can provide useful insight on cancer progression and survival outcomes. In our work, we present a computational framework that uses patient-specific data to investigate cancer metabolism and provide personalised survival predictions and cancer development outcomes. The proposed model integrates patient-specific multi-omics data (i.e., genomic, metabolomic and clinical data) into a metabolic model of cancer to produce a list of metabolic reactions affecting cancer progression. Quantitative and predictive analysis, through survival analysis and machine learning techniques, is then performed on the list of selected reactions. Since our model performs an analysis of patient-specific data, the outcome of our pipeline provides a personalised prediction of survival outcome and cancer development based on a subset of identified multi-omics features (genomic, metabolomic and clinical data). In particular, our work aims to develop a computational pipeline for clinicians that relates the omic profile of each patient to their survival probability, based on a combination of machine learning and metabolic modelling techniques. The model provides patient-specific predictions on cancer development and survival outcomes towards the development of personalised medicine.

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El-fadl, Rihab, Nasser Rizk, Amena Fadel, and Abdelrahman El Gamal. "The Profile of Hepatic Gene Expression of Glucose Metabolism in Mice on High Fat Diet." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0213.

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Obesity is a growing problem worldwide, and recent data indicated that 20% of the populations would be obese. Obesity arises as a multifactorial disease caused by inherited traits that interact with lifestyle factors such as diet and physical activity. The liver plays an essential role in the gluco-regulation via regulating glucose, lipid and protein metabolism. The process of glucose metabolism is controlled by a range of molecular mechanisms and genes which affect the metabolism of the liver during intake of high fat diet (HFD). The objective of this research is to investigate the profile of hepatic gene expression of glucose metabolism in mice on HFD treated with leptin (5 mg/kg BW Ip injection). Ten wild type CD1 mice fed on HFD is used for this study, where groups are control (vehicle - leptin) and test group (vehicle + leptin). Body weight (BW) was measured, and blood chemistry, insulin and leptin were measured at the end of the experiments. Total RNA was isolated from the liver tissue, and RTPCR profiler array technology was used to evaluate the mRNA expression of 84 essential genes of hepatic glucose metabolism. The data of the BW and blood chemistry are not significantly different between the two groups. Leptin treatment enhanced the metabolic pathways and the candidate genes of the different metabolic pathway; glycogen metabolism such as Gys1, Gys2 and Pygm, pentose phosphate shunt such as Rpia and suppressed the glycolysis such as Aldob, and TCA cycle such as Mdh1b. In conclusion, this study has shown that leptin could affect the profile of the hepatic mouse genes of glucose metabolism in the early stages of HFD to induce obesity

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Kamareddine, Layla, Hoda Najjar, Abeer Mohbeddin, Nawar Haj Ahmed, and Paula Watnick. "Between Immunity, Metabolism, and Development: A story of a Fly Gut!" In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0141.

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In addition to its role in initiating immune response in the body, the innate immune system seems to also play a critical role in maintaining homeostatic balance in the gut epithelium. Our recent studies in the Drosophila melanogaster fruit fly model suggest that different innate immune pathways contribute to this homeostatic balance through activating the transcription of genes encoding antimicrobial peptides. We provide evidence that several metabolic parameters are altered in immune deficient flies. We also highlight a role of the gut flora, particularly through its short chain fatty acid, in contributing to this metabolic balance. Interestingly, our data suggest that impaired immunity and metabolic alteration, in turn, exhibit an effect on host development. Collectively, these findings provide evidence that innate immune pathways not only provide the first line of defense against infection but also contribute to host metabolism and development.

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Fessel, Joshua P., Rizwan Hamid, Eric D. Austin, Yuji Tada, Bryan Wittmann, Anna Hemnes, and James West. "Metabolomic Analysis Reveals Widespread Metabolic Derangements In Pulmonary Arterial Hypertension." In American Thoracic Society 2012 International Conference, May 18-23, 2012 • San Francisco, California. American Thoracic Society, 2012. http://dx.doi.org/10.1164/ajrccm-conference.2012.185.1_meetingabstracts.a6512.

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Pacheco-Torres, Jesus, Marie-France Penet, Yelena Mironchik, Sridhar Nimmagadda, Balaji Krishnamachary, and Zaver M. Bhujwalla. "Abstract 1680: The immune checkpoint metabolome and its relationship with choline metabolism." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-1680.

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Santos, Lucas, Gabriel Yarmush, and Timothy Maguire. "A metabolic flux analyis to quantify the hepatic metabolism during defatting." In 2014 40th Annual Northeast Bioengineering Conference (NEBEC). IEEE, 2014. http://dx.doi.org/10.1109/nebec.2014.6972929.

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Putluri, Nagireddy, Vihas T. Vasu, Ali Shojaie, Gagan Singh Thangjam, Shaiju K. Vareed, Vasanta Putluri, Charles Butler, et al. "Abstract A52: Metabolomic profiling reveals impaired xenobiotic metabolism in bladder cancer." In Abstracts: AACR International Conference on the Science of Cancer Health Disparities‐‐ Sep 30-Oct 3, 2010; Miami, FL. American Association for Cancer Research, 2010. http://dx.doi.org/10.1158/1055-9965.disp-10-a52.

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"PREDICTED RELATIVE METABOLOMIC TURNOVER - Predicting Changes in the Environmental Metabolome from the Metagenome." In Metagenomic Sequence Data Analysis. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003314803370345.

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Yuan, Tai-Yi, Hanan N. Fernando, Jessica Czamanski, Chong Wang, Wei Yong Gu, and Chun-Yuh Huang. "Effects of Static Compression on Energy Metabolism of Porcine Intervertebral Disc." In ASME 2010 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2010. http://dx.doi.org/10.1115/sbc2010-19600.

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Degeneration of the intervertebral disc (IVD) has been associated with low back pain, which is one of the major socio-economic problems in the United States. Since IVD is the largest avascular cartilaginous structure in the human body, poor nutrient supply has been suggested as a potential mechanism for IVD degeneration. Biosynthesis of extracellular matrix is an energy demanding process which is required to maintain tissue integrity [1]. Cells consume glucose and oxygen to produce adenosine triphosphate (ATP), the main energy form in cells. Glycolysis, the primary metabolic pathway for production of ATP in IVD cells, is strongly regulated by local oxygen concentration and pH (which is governed by lactate concentration) [2]. Therefore, energy metabolism may play an important role in the malnutrition pathway leading to IVD degeneration. The objective of this study was to investigate the effect of mechanical loading on cellular energy metabolism in whole disc and in agarose gels.

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Huang, Chun-Yuh, and Wei Yong Gu. "Effects of Compression on Glucose Consumption in Intervertebral Disc." In ASME 2008 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2008. http://dx.doi.org/10.1115/sbc2008-192812.

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Nutrition supply is a concern for the health of avascular cartilaginous tissues such as intervertebral disc (IVD). Maintaining tissue integrity relies on cellular biosynthesis of extracellular matrix, which is an energy demanding process [1]. In the IVD, energy is mainly generated through glycolysis (i.e., glucose consumption). Metabolism of nutrients (e.g., oxygen and glucose) within the IVD depends on local concentrations of nutrients, and coupling effects between nutrient level and metabolic rate [2,3]. Our previous theoretical study had developed a new theoretical formulation by incorporating the metabolic rates of solutes into the mechano-electrochemical mixture theory [4,5]. By using this new theoretical model, the distribution of oxygen and lactate can be predicted within the IVD under static and dynamics compressions [4]. However, the effect of compression on glucose consumption in the IVD has not been studied. The objective of this study was to examine the effects of compression on glucose consumption in the IVD under static and dynamic unconfined compression numerically.

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Reports on the topic "Metabolom"

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Starr, Robert C., Brennon R. Orr, M. Hope Lee, and Mark Delwiche. Final Project Report - Coupled Biogeochemical Process Evaluation for Conceptualizing Trichloriethylene Co-Metabolism: Co-Metabolic Enzyme Activity Probes and Modeling Co-Metabolism and Attenuation. Office of Scientific and Technical Information (OSTI), February 2010. http://dx.doi.org/10.2172/972652.

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Lovley, Derek R. Diagnosis of In Situ Metabolic State and Rates of Microbial Metabolism During In Situ Uranium Bioremediation with Molecular Techniques. Office of Scientific and Technical Information (OSTI), November 2012. http://dx.doi.org/10.2172/1097098.

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Lovley, Derek R. Diagnosis of In Situ Metabolic State and Rates of Microbial Metabolism During In Situ Uranium Bioremediation with Molecular Techniques. Office of Scientific and Technical Information (OSTI), November 2012. http://dx.doi.org/10.2172/1055767.

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Popov, V. S., N. V. Vorobeva, and G. A. Svazlian. The relationship of energy metabolism and metabolism in pigs. Вестник Курской государственной сельскохозяйственной академии, 2019. http://dx.doi.org/10.18411/issn1997-0749.2019-03-74-79.

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Glaser, M. Cellular energy metabolism. Office of Scientific and Technical Information (OSTI), June 1991. http://dx.doi.org/10.2172/5714213.

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Flach, Evan. Metabolic Engineering X Conference. Office of Scientific and Technical Information (OSTI), May 2015. http://dx.doi.org/10.2172/1179131.

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Croteau, Rodney. Regulation of Terpene Metabolism. Office of Scientific and Technical Information (OSTI), March 2004. http://dx.doi.org/10.2172/822599.

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Croteau, R. [Regulation of terpene metabolism]. Office of Scientific and Technical Information (OSTI), January 1991. http://dx.doi.org/10.2172/6984681.

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Croteau, R. [Regulation of terpene metabolism]. Office of Scientific and Technical Information (OSTI), November 1989. http://dx.doi.org/10.2172/6984921.

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Croteau, R. [Regulation of terpene metabolism]. Office of Scientific and Technical Information (OSTI), January 1992. http://dx.doi.org/10.2172/6687649.

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