-
1Academic Journal
Συγγραφείς: I. A. Mazerkina, И. А. Мазеркина
Συνεισφορές: The study reported in this publication was carried out as part of publicly funded research project No. 056-00052-23-00 and was supported by the Scientific Centre for Expert Evaluation of Medicinal Products (R&D public accounting No. 121022400082-4)., Работа выполнена в рамках государственного задания ФГБУ «НЦЭСМП» Минздрава России № 056-00052-23-00 на проведение прикладных научных исследований (номер государственного учета НИР 121022400082-4).
Πηγή: Safety and Risk of Pharmacotherapy; Том 11, № 2 (2023); 131-144 ; Безопасность и риск фармакотерапии; Том 11, № 2 (2023); 131-144 ; 2619-1164 ; 2312-7821
Θεματικοί όροι: доклинические исследования, drug-induced liver injury, in vitro studies, cell cultures, cell models, organ-on-a-chip, omics, transcriptomics, proteomics, metabolomics, non-clinical studies, лекарственное повреждение печени, исследования in vitro, клеточные культуры, клеточные модели, орган-на-чипе, омик-технологии, транскриптомика, протеомика, метаболомика
Περιγραφή αρχείου: application/pdf
Relation: https://www.risksafety.ru/jour/article/view/351/722; https://www.risksafety.ru/jour/article/view/351/723; https://www.risksafety.ru/jour/article/view/351/724; https://www.risksafety.ru/jour/article/view/351/725; https://www.risksafety.ru/jour/article/view/351/726; https://www.risksafety.ru/jour/article/view/351/727; https://www.risksafety.ru/jour/article/view/351/728; https://www.risksafety.ru/jour/article/view/351/729; https://www.risksafety.ru/jour/article/view/351/730; https://www.risksafety.ru/jour/article/view/351/780; https://www.risksafety.ru/jour/article/downloadSuppFile/351/341; Onakpoya IJ, Heneghan CJ, Aronson JK. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC Med. 2016;4(14):10. https://doi.org/10.1186/s12916-016-0553-2; Wouters OJ, McKee M, Luyten J. Estimated research and development investment needed to bring a new medicine to market, 2009–2018. JAMA. 2020;323(9):844–53. https://doi.org/10.1001/jama.2020.1166; DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: new estimates of R&D costs. J Health Econ. 2016;47:20–33. https://doi.org/10.1016/j.jhealeco.2016.01.012; Sakai C, Iwano S, Yamazaki Y, Ando A, Nakane F, Kouno M, et al. Species differences in the pharmacokinetic parameters of cytochrome P450 probe substrates between experimental animals, such as mice, rats, dogs, monkeys, and microminipigs, and humans. Drug Metab Toxicol. 2014;5:6. https://doi.org/10.4172/2157-7609.1000173; Spanhaak S, Cook D, Barnes J, Reynolds J. Species concordance for liver injury. In: Safety Intelligence Program Board. Cambridge, UK: BioWisdom, Ltd; 2008.; Hewitt NJ, Gómez Lechón MJ, Houston JB, Hallifax D, Brown HS, Maurel P, et al. Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab Rev. 2007;39(1):159–234. https://doi.org/10.1080/03602530601093489; Vickers AE, Bentley P, Fisher RL. Consequences of mitochondrial injury induced by pharmaceutical fatty acid oxidation inhibitors is characterized in human and rat liver slices. Toxicol In Vitro. 2006;20(7):1173–82. https://doi.org/10.1016/j.tiv.2006.01.021; Edwards RJ, Price RJ, Watts PS, Renwick AB, Tredger JM, Boobis AR, Lake BG. Induction of cytochrome P450 enzymes in cultured precision-cut human liver slices. Drug Metab Dispos. 2003;31(3):282–8. https://doi.org/10.1124/dmd.31.3.282; Starokozhko V, Vatakuti S, Schievink B, Merema MT, Asplund A, Synnergren J, et al. Maintenance of drug metabolism and transport functions in human precision-cut liver slices during prolonged incubation for 5 days. Arch Toxicol. 2017;91(5):2079–92. https://doi.org/10.1007/s00204-016-1865-x; Hadi M, Westra IM, Starokozhko V, Dragovic S, Merema MT, Groothuis GM. Human precision-cut liver slices as an ex vivo model to study idiosyncratic drug-induced liver injury. Chem Res Toxicol. 2013;26(5):710–20. https://doi.org/10.1021/tx300519p; Khetani SR, Kanchagar C, Ukairo O, Krzyzewski S, Moore A, Shi J, et al. Use of micropatterned cocultures to detect compounds that cause drug-induced liver injury in humans. Toxicol Sci. 2013;132(1):107–17. https://doi.org/10.1093/toxsci/kfs326; Burkard A, Dähn C, Heinz S, Zutavern A, Sonn tag-Buck V, Maltman D, et al. Generation of proliferating human hepatocytes using Upcyte® technology: characterisation and applications in induction and cytotoxicity assays. Xenobiotica. 2012;42(10):939–56. https://doi.org/10.3109/00498254.2012.675093; Segovia-Zafra A, Di Zeo-Sánchez DE, López-Gómez C, Pérez-Valdés Z, García-Fuentes E, Andrade RJ, et al. Preclinical models of idiosyncratic drug-induced liver injury (iDILI): moving towards prediction. Acta Pharm Sin B. 2021;11(12):3685–726. https://doi.org/10.1016/j.apsb.2021.11.013; Sison-Young RL, Mitsa D, Jenkins RE, Mottram D, Alexandre E, Richert L, et al. Comparative proteomic characterization of 4 human liver-derived single cell culture models reveals significant variation in the capacity for drug disposition, bioactivation, and detoxication. Toxicol Sci. 2015;147(2):412–24. https://doi.org/10.1093/toxsci/kfv136; Saran C, Fu D, Ho H, Klein A, Fallon JK, Honkakoski P, et al. A novel differentiated HuH-7 cell model to examine bile acid metabolism, transport and cholestatic hepatotoxicity. Sci Rep. 2022;12(1):14333. https://doi.org/10.1038/s41598-022-18174-z; Schwartz RE, Fleming HE, Khetani SR, Bhatia SN. Pluripotent stem cell-derived hepatocyte-like cells. Biotechnol Adv. 2014;32(2):504–13. https://doi.org/10.1016/j.biotechadv.2014.01.003; Imagawa K, Takayama K, Isoyama S, Tanikawa K, Shinkai M, Harada K, et al. Generation of a bile salt export pump deficiency model using patient-specific induced pluripotent stem cell-derived hepatocyte-like cells. Sci Rep. 2017;7:41806. https://doi.org/10.1038/srep41806; Nguyen TV, Ukairo O, Khetani SR, McVay M, Kanchagar C, Seghezzi W, et al. Establishment of a hepatocyte-Kupffer cell coculture model for assessment of proinflammatory cytokine effects on metabolizing enzymes and drug transporters. Drug Metab Dispos. 2015;43(5):774–85. https://doi.org/10.1124/dmd.114.061317; Baze A, Parmentier C, Hendriks DFG, Hurrell T, Heyd B, Bachellier P, et al. Three-dimensional spheroid primary human hepatocytes in monoculture and coculture with nonparenchymal cells. Tissue Eng Part C Methods. 2018;24(9):534–45. https://doi.org/10.1089/ten.TEC.2018.0134; Olsen AL, Bloomer SA, Chan EP, Gaça MD, Georges PC, Sackey B, et al. Hepatic stellate cells require a stiff environment for myofibroblastic differentiation. Am J Physiol Gastrointest Liver Physiol. 2011;301(1):110–8. https://doi.org/10.1152/ajpgi.00412.2010; Khetani SR, Berger DR, Ballinger KR, Davidson MD, Lin C, Ware BR. Microengineered liver tissues for drug testing. J Lab Autom. 2015;20(3):216–50. https://doi.org/10.1177/2211068214566939; Yokoyama Y, Sasaki Y, Terasaki N, Kawataki T, Takekawa K, Iwase Y, et al. Comparison of drug metabolism and its related hepatotoxic effects in HepaRG, cryopreserved human hepatocytes, and HepG2 cell cultures. Biol Pharm Bull. 2018;41(5):722–32. https://doi.org/10.1248/bpb.b17-00913; Wu X, Wang S, Li M, Li J, Shen J, Zhao Y, et al. Conditional reprogramming: next generation cell culture. Acta Pharm Sin B. 2020;10(8):1360–81. https://doi.org/10.1016/j.apsb.2020.01.011; Su S, Di Poto C, Roy R, Liu X, Cui W, Kroemer A, Ressom HW. Long-term culture and characterization of patient-derived primary hepatocytes using conditional reprogramming. Exp Biol Med (Maywood). 2019;244(11):857–64. https://doi.org/10.1177/1535370219855398; De Bruyn T, Chatterjee S, Fattah S, Keemink J, Nicolaï J, Augustijns P, et al. Sandwich-cultured hepatocytes: utility for in vitro exploration of hepatobiliary drug disposition and drug-induced hepatotoxicity. Expert Opin Drug Metab Toxicol. 2013;9(5):589–616. https://doi.org/10.1517/17425255.2013.773973; Yanni SB, Augustijns PF, Benjamin DK Jr, Brouwer KL, Thakker DR, Annaert PP. In vitro investigation of the hepatobiliary disposition mechanisms of the antifungal agent micafungin in humans and rats. Drug Metab Dispos. 2010;38(10):1848–56. https://doi.org/10.1124/dmd.110.033811; Matsunaga N, Suzuki K, Nakanishi T, Ogawa M, Imawaka H, Tamai I. Modeling approach for multiple transporters-mediated drug-drug interactions in sandwich-cultured human hepatocytes: effect of cyclosporin A on hepatic disposition of mycophenolic acid phenyl-glucuronide. Drug Metab Pharmacokinet. 2015;30(2):142–8. https://doi.org/10.1016/j.dmpk.2014.10.006; Fu D, Cardona P, Ho H, Watkins PB, Brouwer KLR. Novel mechanisms of valproate hepatotoxicity: impaired Mrp2 trafficking and hepatocyte depolarization. Toxicol Sci. 2019;171(2):431–42. https://doi.org/10.1093/toxsci/kfz154; Berger DR, Ware BR, Davidson MD, Allsup SR, Khetani SR. Enhancing the functional maturity of induced pluripotent stem cell-derived human hepatocytes by controlled presentation of cell-cell interactions in vitro. Hepatology. 2015;61(4):1370–81. https://doi.org/10.1002/hep.27621; Takahashi Y, Hori Y, Yamamoto T, Urashima T, Ohara Y, Tanaka H. 3D spheroid cultures improve the metabolic gene expression profiles of HepaRG cells. Biosci Rep. 2015;35(3):e00208. https://doi.org/10.1042/BSR20150034; Bell CC, Dankers ACA, Lauschke VM, Sison-Young R, Jenkins R, Rowe C, et al. Comparison of hepatic 2D sandwich cultures and 3D spheroids for long-term toxicity applications: a multicenter study. Toxicol Sci. 2018;162(2):655–66. https://doi.org/10.1093/toxsci/kfx289; Kostadinova R, Boess F, Applegate D, Suter L, Weiser T, Singer T, et al. A long-term three dimensional liver co-culture system for improved prediction of clinically relevant drug-induced hepatotoxicity. Toxicol Appl Pharmacol. 2013;268(1):1–16. https://doi.org/10.1016/j.taap.2013.01.012; Vorrink SU, Zhou Y, Ingelman-Sundberg M, Lauschke VM. Prediction of drug-induced hepatotoxicity using long-term stable primary hepatic 3D spheroid cultures in chemically defined conditions. Toxicol Sci. 2018;163(2):655–65. https://doi.org/10.1093/toxsci/kfy058; Ide I, Nagao E, Kajiyama S, Mizoguchi N. A novel evaluation method for determining drug-induced hepatotoxicity using 3D bio-printed human liver tissue. Toxicol Mech Methods. 2020;30(3):189–96. https://doi.org/10.1080/15376516.2019.1686795; Schmidt K, Berg J, Roehrs V, Kurreck J, Al-Zeer MA. 3D-bioprinted HepaRG cultures as a model for testing long term aflatoxin B1 toxicity in vitro. Toxicol Rep. 2020;7:1578–87. https://doi.org/10.1016/j.toxrep.2020.11.003; Deng J, Wei W, Chen Z, Lin B, Zhao W, Luo Y, et al. Engineered liver-on-a-chip platform to mimic liver functions and its biomedical applications: a review. Micromachines (Basel). 2019;10(10):676. https://doi.org/10.3390/mi10100676; Rubiano A, Indapurkar A, Yokosawa R, Miedzik A, Rosenzweig B, Arefin A, et al. Characterizing the reproducibility in using a liver microphysiological system for assaying drug toxicity, metabolism, and accumulation. Clin Transl Sci. 2021;14(3):1049–61. https://doi.org/10.1111/cts.12969; Picollet-D’hahan N, Zuchowska A, ILemeunier I, Le Gac S. Multiorgan-on-a-chip: a systemic approach to model and decipher inter-organ communication. Trends in Biotechnology. 2021;39(8):788–810. https://doi.org/10.1016/j.tibtech.2020.11.014; Bricks T, Paullier P, Legendre A, Fleury MJ, Zeller P, Merlier F, et al. Development of a new microfluidic platform integrating co-cultures of intestinal and liver cell lines. Toxicol Vitro. 2014;28(5):885–95. https://doi.org/10.1016/j.tiv.2014.02.005; Oleaga C, Bernabini C, Smith AS, Srinivasan B, Jackson M, McLamb W, et al. Multi-organ toxicity demonstration in a functional human in vitro system composed of four organs. Sci Rep. 2016;6(1):20030. https://doi.org/10.1038/srep20030; Weaver RJ, Betts C, Blomme EAG, Gerets HHJ, Gjervig Jensen K, Hewitt PG, et al. Test systems in drug discovery for hazard identification and risk assessment of human drug-induced liver injury. Expert Opin Drug Metab Toxicol. 2017;13(7):767–82. https://doi.org/10.1080/17425255.2017.1341489; Benbow JW, Aubrecht J, Banker MJ, Nettleton D, Aleo MD. Predicting safety toleration of pharmaceutical chemical leads: cytotoxicity correlations to exploratory toxicity studies. Toxicol Lett. 2010;197(3):175–82. https://doi.org/10.1016/j.toxlet.2010.05.016; Roth AD, Lee MY. Idiosyncratic drug-induced liver injury (IDILI): potential mechanisms and predictive assays. Biomed Res Int. 2017;2017:9176937. https://doi.org/10.1155/2017/9176937; Jee A, Sernoskie SC, Uetrecht J. Idiosyncratic drug-induced liver injury: mechanistic and clinical challenges. Int J Mol Sci. 2021;22(6):2954. https://doi.org/10.3390/ijms22062954; Devi SS, Palkar PS, Mehendale HM. Measuring covalent binding in hepatotoxicity. Curr Protoc Toxicol. 2007;14:Unit14.6. https://doi.org/10.1002/0471140856.tx1406s32; Wang Q, Liu H, Slavsky M, Fitzgerald M, Lu C, O’Shea T. A high-throughput glutathione trapping assay with combined high sensitivity and specificity in high-resolution mass spectrometry by applying product ion extraction and data-dependent neutral loss. J Mass Spectrom. 2019;54(2):158–66. https://doi.org/10.1002/jms.4320; Ramachandran A, Jaeschke H. Oxidative stress and acute hepatic injury. Curr Opin Toxicol. 2018;7:17–21. https://doi.org/10.1016/j.cotox.2017.10.011; Chen S, Zhang Z, Qing T, Ren Z, Yu D, Couch L, Ning B, Mei N, Shi L, Tolleson WH, Guo L. Activation of the Nrf2 signaling pathway in usnic acid-induced toxicity in HepG2 cells. Arch Toxicol. 2017;91(3):1293–307. https://doi.org/10.1007/s00204-016-1775-y; Mihajlovic M, Vinken M. Mitochondria as the target of hepatotoxicity and drug-induced liver injury: molecular mechanisms and detection methods. Int J Mol Sci. 2022;23:3315. https://doi.org/10.3390/ijms23063315; Nadanaciva S, Will Y. The role of mitochondrial dysfunction and drug safety. IDrugs. 2009;12(11):706–10. PMID: 19844857; Begriche K, Massart J, Robin M, Borgne-Sanchez A, Fromenty B. Drug-induced toxicity on mitochondria and lipid metabolism: mechanistic diversity and deleterious consequences for the liver. J Hepatol. 2011;54(14):773–94. https://doi.org/10.1016/j.jhep.2010.11.006; Fromenty B. Alteration of mitochondrial DNA homeostasis in drug-induced liver injury. Food Chem Toxicol. 2020;135:110916. https://doi.org/10.1016/j.fct.2019.110916; McKee E, Ferguson M, Bentley A, Marks T. Inhibition of mammalian mitocondrial protein synthesis by oxazolidinones. Antimicrobial Agents Chemother. 2006;50(16):2042–9. https://doi.org/10.1128/AAC.01411-05; Kamalian L, Douglas O, Jolly CE, Snoeys J, Simic D, Monshouwer M, et al. Acute metabolic switch assay using glucose/galactose medium in HepaRG cells to detect mitochondrial toxicity. Curr Protoc Toxicol. 2019;80(1):76. https://doi.org/10.1002/cptx.76; Nadanaciva S, Willis J, Barker M, Gharaibeh D, Capaldi R, Marusich M, et al. Assessment of drug-induced mitochondrial dysfunction via altered cellular respiration and acidification measured in a 96-well platform. J Bioenerg Biomembr. 2012;44(14):421–37. https://doi.org/10.1007/s10863-012-9446-z; Marchetti P, Fovez Q, Germain N, Khamari R, Kluza J. Mitochondrial spare respiratory capacity: mechanisms, regulation, and significance in non-transformed and cancer cells. FASEB J. 2020;34(10):13106–24. https://doi.org/10.1096/fj.202000767R; Nadanaciva S, Willis JH, Barker ML, Gharaibeh D, Capaldi RA, Marusich MF, et al. Lateral-flow immunoassay for detecting drug-induced inhibition of mitochondrial DNA replication and mtDNA-encoded protein synthesis. J Immunol Methods. 2009;343(1):1–12. https://doi.org/10.1016/j.jim.2008.12.002; Porceddu M, Buron N, Rustin P, Fromenty B, Borgne-Sanchez A. In vitro assessment of mitochondrial toxicity to predict drug-induced liver injury. In: Chen M, Will Y, eds. Drug-induced liver toxicity. New York: Springer New York; 2018. P. 283–300. https://doi.org/10.1007/978-1-4939-7677-5_14; Perez MJ, Briz O. Bile-acid-induced cell injury and protection. World J Gastroenterol. 2009;15(14):1677–89. https://doi.org/10.3748/wjg.15.1677; Garzel B, Yang H, Zhang L, Huang SM, Polli JE, Wang H. The role of bile salt export pump gene repression in drug-induced cholestatic liver toxicity. Drug Metab Dispos. 2014;42(3):318–22. https://doi.org/10.1124/dmd.113.054189; Stieger B, Mahdi ZM. Model systems for studying the role of canalicular efflux transporters in drug-induced cholestatic liver disease. J Pharm Sci. 2017;106(9):2295–301. https://doi.org/10.1016/j.xphs.2017.03.023; Schaefer M, Morinaga G, Matsui A, Schänzle G, Bischoff D, Süssmuth RD. Quantitative expression of hepatobiliary transporters and functional uptake of substrates in hepatic two-dimensional sandwich cultures: a comparative evaluation of upcyte and primary human hepatocytes. Drug Metab Dispos. 2018;46(2):166–77. https://doi.org/10.1124/dmd.117.078238; Funk C, Pantze M, Jehle L, Ponelle C, Scheuermann G, Lazendic M, et al. Troglitazone-induced intrahepatic cholestasis by an interference with the hepatobiliary export of bile acids in male and female rats. Correlation with the gender difference in troglitazone sulfate formation and the inhibition of the canalicular bile salt export pump (Bsep) by troglitazone and troglitazone sulfate. Toxicology. 2001;167(1):83–98. https://doi.org/10.1016/s0300-483x(01)00460-7; Chan R, Benet LZ. Measures of BSEP inhibition in vitro are not useful predictors of DILI. Toxicol Sci. 2018;162(2):499–508. https://doi.org/10.1093/toxsci/kfx284; LeCluyse EL, Witek RP, Andersen ME, Powers MJ. Organotypic liver culture models: meeting current challenges in toxicity testing. Crit Rev Toxicol. 2012;42(6):501–48. https://doi.org/10.3109/10408444.2012.682115; Ogese MO, Faulkner L, Jenkins RE, French NS, Copple IM, Antoine DJ, et al. Characterization of drug-specific signaling between primary human hepatocytes and immune cells. Toxicol Sci. 2017;158(1):76–89. https://doi.org/10.1093/toxsci/kfx069; Persson M. High content screening for prediction of human drug-induced liver injury. In: Chen M, Will Y, eds. Drug-induced liver toxicity. New York: Springer New York; 2018. P. 331–43. https://doi.org/10.1007/978-1-4939-7677-5_16; O’Brien PJ, Irwin W, Diaz D, Howard-Cofield E, Krejsa CM, Slaughter MR, et al. High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening. Arch Toxicol. 2006;80(9):580–604. https://doi.org/10.1007/s00204-006-0091-3; Hong S, Song JM. A 3D cell printing-fabricated HepG2 liver spheroid model for high-content in situ quantification of drug-induced liver toxicity. Biomater Sci. 2021;9(17):5939–50. https://doi.org/10.1039/d1bm00749a; Donato M, Tolosa L. High-content screening for the detection of drug-induced oxidative stress in liver cells. Antioxidants (Basel). 2021;10(1):106. https://doi.org/10.3390/antiox10010106; Kozak K, Rinn B, Leven O, Emmenlauer M. Strategies and solutions to maintain and retain data from high content imaging, analysis, and screening assays. Methods Mol Biol. 2018;1683:131–48. https://doi.org/10.1007/978-1-4939-7357-6_9; Lowe R, Shirley N, Bleackley M, Dolan S, Shafee T. Transcriptomics technologies. PLoS Comput Biol. 2017;13(5):1005457. https://doi.org/10.1371/journal.pcbi.1005457; Gupta R, Schrooders Y, Hauser D, van Herwijnen M, Albrecht W, Ter Braak B, et al. Comparing in vitro human liver models to in vivo human liver using RNA-Seq. Arch Toxicol. 2021;95(2):573–89. https://doi.org/10.1007/s00204-020-02937-6; Russo MW, Steuerwald N, Norton HJ, Anderson WE, Foureau D, Chalasani N, et al. Profiles of miRNAs in serum in severe acute drug induced liver injury and their prognostic significance. Liver Int. 2017;37(5):757–64. https://doi.org/10.1111/liv.13312; De Abrew KN, Overmann GJ, Adams RL, Tiesman JP, Dunavent J, Shan YK, Carr GJ, et al. A novel transcriptomics based in vitro method to compare and predict hepatotoxicity based on mode of action. Toxicology. 2015;328:29–39. https://doi.org/10.1016/j.tox.2014.11.008; Ware BR, McVay M, Sunada WY, Khetani SR. Exploring chronic drug effects on microengineered human liver cultures using global gene expression profiling. Toxicol Sci. 2017;157(2):387–98. https://doi.org/10.1093/toxsci/kfx059; Cha HJ, Ko MJ, Ahn SM, Ahn JI, Shin HJ, Jeong HS, et al. Identification of classifier genes for hepatotoxicity prediction in non-steroidal anti-inflammatory drugs. Mol Cell Toxicol. 2010;6:247–53. https://doi.org/10.1007/s13273-010-0034-1; Ölander M, Wiśniewski JR, Artursson P. Cell-type-resolved proteomic analysis of the human liver. Liver Int. 2020;40(7):1770–80. https://doi.org/10.1111/liv.14452; Aebersold R, Mann M. Mass-spectrometric exploration of proteome structure and function. Nature. 2016;537(7620):347–55. https://doi.org/10.1038/nature19949; Alvergnas M, Rouleau A, Lucchi G, Heyd B, Ducoroy P, Richert L, et al. Proteomic mapping of bezafibrate-treated human hepatocytes in primary culture using two-dimensional liquid chromatography. Toxicol Lett. 2011;201(2):123–9. https://doi.org/10.1016/j.toxlet.2010.12.015; Ramirez T, Daneshian M, Kamp H, Bois FY, Clench MR, Coen M et al. Metabolomics in toxicology and preclinical research. ALTEX. 2013;30(2):209–25. https://doi.org/10.14573/altex.2013.2.209; Cuykx M, Rodrigues RM, Laukens K, Vanhaecke T, Covaci A. In vitro assessment of hepatotoxicity by metabolomics: a review. Arch Toxicol. 2018;92(10):3007–29. https://doi.org/10.1007/s00204-018-2286-9; Ruiz-Aracama A, Peijnenburg A, Kleinjans J, Jennen D, van Delft J, Hellfrisch C, et al. An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin. BMC Genomics. 2011;12:251. https://doi.org/10.1186/1471-2164-12-251; Krajnc E, Visentin M, Gai Z, Stieger B, Samodelov SL, Häusler S, Kullak-Ublick GA. Untargeted metabolomics reveals anaerobic glycolysis as a novel target of the hepatotoxic antidepressant nefazodone. J Pharmacol Exp Ther. 2020;375(2):239–46. https://doi.org/10.1124/jpet.120.000120; Rodrigues RM, Kollipara L, Chaudhari U, Sachinidis A, Zahedi RP, Sickmann A, et al. Omics-based responses induced by bosentan in human hepatoma HepaRG cell cultures. Arch Toxicol. 2018;92(6):1939–52. https://doi.org/10.1007/s00204-018-2214-z; https://www.risksafety.ru/jour/article/view/351
-
2Academic Journal
Συγγραφείς: Сазонова, Евгения
Θεματικοί όροι: ФАРМАКОМЕТРИКА, «ОМИК»-ТЕХНОЛОГИИ, БИОМЕДИЦИНА, МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ, ВЕНЧУРНЫЕ ФОНДЫ, ПРОГНОЗИРОВАНИЕ
Περιγραφή αρχείου: text/html
-
3Academic Journal
Πηγή: Вестник Марийского государственного университета.
Θεματικοί όροι: ФАРМАКОМЕТРИКА, «ОМИК»-ТЕХНОЛОГИИ, БИОМЕДИЦИНА, МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ, ВЕНЧУРНЫЕ ФОНДЫ, ПРОГНОЗИРОВАНИЕ
Περιγραφή αρχείου: text/html
