Login Register Cart 0
Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes

Author(s): Yan Xu, Yu-Hang Zhang, JiaRui Li, Xiao Y. Pan, Tao Huang* and Yu-Dong Cai*

Volume 22, Issue 10, 2019

Page: [665 - 674] Pages: 10

DOI: 10.2174/1386207322666191129114741

Price: $65

Abstract

Background: Human rhinovirus has different identified serotypes and is the most common cause of cold in humans. To date, many genes have been discovered to be related to rhinovirus infection. However, the pathogenic mechanism of rhinovirus is difficult to elucidate through experimental approaches due to the high cost and consuming time.

Methods and Results: In this study, we presented a novel approach that relies on machine-learning algorithms and identified two genes OTOF and SOCS1. The expression levels of these genes in the blood samples can be used to accurately distinguish virus-infected and non-infected individuals.

Conclusion: Our findings suggest the crucial roles of these two genes in rhinovirus infection and the robustness of the computational tool in dissecting pathogenic mechanisms.

Keywords: Human Rhinovirus, maximum relevance minimum redundancy, support vector machine, incremental feature selection, OTOF, SOCS1.

« Previous Next »
[1]
Price, W.H. The isolation of a new virus associated with respiratory clinical disease in humans. Proc. Natl. Acad. Sci. USA, 1956, 42(12), 892-896.
[http://dx.doi.org/10.1073/pnas.42.12.892] [PMID: 16589969]
[2]
Palmenberg, A.C.; Rathe, J.A.; Liggett, S.B. Analysis of the complete genome sequences of human rhinovirus. J. Allergy Clin. Immunol., 2010, 125(6), 1190-1199.
[http://dx.doi.org/10.1016/j.jaci.2010.04.010] [PMID: 20471068]
[3]
Bella, J.; Rossmann, M.G. ICAM-1 receptors and cold viruses. Pharm. Acta Helv., 2000, 74(2-3), 291-297.
[http://dx.doi.org/10.1016/S0031-6865(99)00056-4] [PMID: 10812972]
[4]
Vlasak, M.; Roivainen, M.; Reithmayer, M.; Goesler, I.; Laine, P.; Snyers, L.; Hovi, T.; Blaas, D. The minor receptor group of human rhinovirus (HRV) includes HRV23 and HRV25, but the presence of a lysine in the VP1 HI loop is not sufficient for receptor binding. J. Virol., 2005, 79(12), 7389-7395.
[http://dx.doi.org/10.1128/JVI.79.12.7389-7395.2005] [PMID: 15919894]
[5]
Fuchs, R.; Blaas, D. Uncoating of human rhinoviruses. Rev. Med. Virol., 2010, 20(5), 281-297.
[http://dx.doi.org/10.1002/rmv.654] [PMID: 20629045]
[6]
Oliver, B.G.; Lim, S.; Wark, P.; Laza-Stanca, V.; King, N.; Black, J.L.; Burgess, J.K.; Roth, M.; Johnston, S.L. Rhinovirus exposure impairs immune responses to bacterial products in human alveolar macrophages. Thorax, 2008, 63(6), 519-525.
[http://dx.doi.org/10.1136/thx.2007.081752] [PMID: 18245149]
[7]
Kimura, G.; Ueda, K.; Eto, S.; Watanabe, Y.; Masuko, T.; Kusama, T.; Barnes, P.J.; Ito, K.; Kizawa, Y. Toll-like receptor 3 stimulation causes corticosteroid-refractory airway neutrophilia and hyperresponsiveness in mice. Chest, 2013, 144(1), 99-105.
[http://dx.doi.org/10.1378/chest.12-2610] [PMID: 23348232]
[8]
Hatchwell, L.; Collison, A.; Girkin, J.; Parsons, K.; Li, J.; Zhang, J.; Phipps, S.; Knight, D.; Bartlett, N.W.; Johnston, S.L.; Foster, P.S.; Wark, P.A.; Mattes, J. Toll-like receptor 7 governs interferon and inflammatory responses to rhinovirus and is suppressed by IL-5-induced lung eosinophilia. Thorax, 2015, 70(9), 854-861.
[http://dx.doi.org/10.1136/thoraxjnl-2014-205465] [PMID: 26108570]
[9]
Kuo, C.; Lim, S.; King, N.J.; Bartlett, N.W.; Walton, R.P.; Zhu, J.; Glanville, N.; Aniscenko, J.; Johnston, S.L.; Burgess, J.K.; Black, J.L.; Oliver, B.G. Rhinovirus infection induces expression of airway remodelling factors in vitro and in vivo. Respirology, 2011, 16(2), 367-377.
[http://dx.doi.org/10.1111/j.1440-1843.2010.01918.x] [PMID: 21199160]
[10]
Triantafilou, K.; Vakakis, E.; Richer, E.A.; Evans, G.L.; Villiers, J.P.; Triantafilou, M. Human rhinovirus recognition in non-immune cells is mediated by Toll-like receptors and MDA-5, which trigger a synergetic pro-inflammatory immune response. Virulence, 2011, 2(1), 22-29.
[http://dx.doi.org/10.4161/viru.2.1.13807] [PMID: 21224721]
[11]
Slater, L.; Bartlett, N.W.; Haas, J.J.; Zhu, J.; Message, S.D.; Walton, R.P.; Sykes, A.; Dahdaleh, S.; Clarke, D.L.; Belvisi, M.G.; Kon, O.M.; Fujita, T.; Jeffery, P.K.; Johnston, S.L.; Edwards, M.R. Co-ordinated role of TLR3, RIG-I and MDA5 in the innate response to rhinovirus in bronchial epithelium. PLoS Pathog., 2010, 6(11)e1001178
[http://dx.doi.org/10.1371/journal.ppat.1001178] [PMID: 21079690]
[12]
Alper, C.M.; Doyle, W.J.; Skoner, D.P.; Buchman, C.A.; Cohen, S.; Gwaltney, J.M. Prechallenge antibodies moderate disease expression in adults experimentally exposed to rhinovirus strain hanks. Clin. Infect. Dis., 1998, 27(1), 119-128.
[http://dx.doi.org/10.1086/514634] [PMID: 9675465]
[13]
Message, S.D.; Johnston, S.L. Host defense function of the airway epithelium in health and disease: clinical background. J. Leukoc. Biol., 2004, 75(1), 5-17.
[http://dx.doi.org/10.1189/jlb.0703315] [PMID: 12972516]
[14]
Kelly, J.T.; Busse, W.W. Host immune responses to rhinovirus: mechanisms in asthma. J. Allergy Clin. Immunol., 2008, 122(4), 671-682.
[http://dx.doi.org/10.1016/j.jaci.2008.08.013] [PMID: 19014757]
[15]
Çalışkan, M.; Baker, S.W.; Gilad, Y.; Ober, C. Host genetic variation influences gene expression response to rhinovirus infection. PLoS Genet., 2015, 11(4)e1005111
[http://dx.doi.org/10.1371/journal.pgen.1005111] [PMID: 25874939]
[16]
Peng, H.; Long, F.; Ding, C. Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell., 2005, 27(8), 1226-1238.
[http://dx.doi.org/10.1109/TPAMI.2005.159] [PMID: 16119262]
[17]
Li, J.; Lu, L.; Zhang, Y.H.; Liu, M.; Chen, L.; Huang, T.; Cai, Y-D. Identification of synthetic lethality based on a functional network by using machine learning algorithms. J. Cell. Biochem., 2019, 120(1), 405-416.
[http://dx.doi.org/10.1002/jcb.27395] [PMID: 30125975]
[18]
Chen, L.; Wang, S.; Zhang, Y-H.; Li, J.; Xing, Z-H.; Yang, J.; Huang, T.; Cai, Y-D. Identify key sequence features to improve CRISPR sgRNA efficacy. IEEE Access, 2017, 5, 26582-26590.
[http://dx.doi.org/10.1109/ACCESS.2017.2775703]
[19]
Chen, L.; Chu, C.; Huang, T.; Kong, X.; Cai, Y-D. Prediction and analysis of cell-penetrating peptides using pseudo-amino acid composition and random forest models. Amino Acids, 2015, 47(7), 1485-1493.
[http://dx.doi.org/10.1007/s00726-015-1974-5] [PMID: 25894890]
[20]
Zhao, X.; Chen, L.; Lu, J. A similarity-based method for prediction of drug side effects with heterogeneous information. Math. Biosci., 2018, 306, 136-144.
[http://dx.doi.org/10.1016/j.mbs.2018.09.010] [PMID: 30296417]
[21]
Chen, L.; Zhang, Y-H.; Huang, G.; Pan, X.; Wang, S.; Huang, T.; Cai, Y-D. Discriminating cirRNAs from other lncRNAs using a hierarchical extreme learning machine (H-ELM) algorithm with feature selection. Mol. Genet. Genomics, 2018, 293(1), 137-149.
[http://dx.doi.org/10.1007/s00438-017-1372-7] [PMID: 28913654]
[22]
Zhang, Y.H.; Chu, C.; Wang, S.; Chen, L.; Lu, J.; Kong, X.; Huang, T.; Li, H.; Cai, Y.D. The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life. PLoS One, 2016, 11(10)e0165496
[http://dx.doi.org/10.1371/journal.pone.0165496] [PMID: 27780226]
[23]
Chen, L.; Pan, X.; Hu, X.; Zhang, Y-H.; Wang, S.; Huang, T.; Cai, Y-D. Gene expression differences among different MSI statuses in colorectal cancer. Int. J. Cancer, 2018, 143(7), 1731-1740.
[http://dx.doi.org/10.1002/ijc.31554] [PMID: 29696646]
[24]
Wang, S.; Zhang, Y-H.; Huang, G.; Chen, L.; Cai, Y-D. Analysis and prediction of myristoylation sites using the mRMR method, the IFS method and an extreme learning machine algorithm. Comb. Chem. High Throughput Screen., 2017, 20(2), 96-106.
[http://dx.doi.org/10.2174/1386207319666161220114424] [PMID: 28000567]
[25]
Wang, S.; Zhang, Q.; Lu, J.; Cai, Y-D. Analysis and prediction of nitrated tyrosine sites with the mRMR method and support vector machine algorithm. Curr. Bioinform., 2018, 13(1), 3-13.
[http://dx.doi.org/10.2174/1574893611666160608075753]
[26]
Zhang, Q.; Sun, X.; Feng, K.; Wang, S.; Zhang, Y.H.; Wang, S.; Lu, L.; Cai, Y.D. Predicting citrullination sites in protein sequences using mRMR method and random forest algorithm. Comb. Chem. High Throughput Screen., 2017, 20(2), 164-173.
[http://dx.doi.org/10.2174/1386207319666161227124350] [PMID: 28029071]
[27]
Chen, L.; Zhang, Y.H.; Lu, G.; Huang, T.; Cai, Y.D. Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways. Artif. Intell. Med., 2017, 76, 27-36.
[http://dx.doi.org/10.1016/j.artmed.2017.02.001] [PMID: 28363286]
[28]
Liu, L.; Chen, L.; Zhang, Y.H.; Wei, L.; Cheng, S.; Kong, X.; Zheng, M.; Huang, T.; Cai, Y.D. Analysis and prediction of drug-drug interaction by minimum redundancy maximum relevance and incremental feature selection. J. Biomol. Struct. Dyn., 2017, 35(2), 312-329.
[http://dx.doi.org/10.1080/07391102.2016.1138142] [PMID: 26750516]
[29]
Huang, T.; Cui, W.; Hu, L.; Feng, K.; Li, Y.X.; Cai, Y.D. Prediction of pharmacological and xenobiotic responses to drugs based on time course gene expression profiles. PLoS One, 2009, 4(12)e8126
[http://dx.doi.org/10.1371/journal.pone.0008126] [PMID: 19956587]
[30]
Cortes, C.; Vapnik, V. Support-vector networks. Mach. Learn., 1995, 20(3), 273-297.
[http://dx.doi.org/10.1007/BF00994018]
[31]
Duan, K-B.; Keerthi, S.S. Which is the Best Multiclass SVM Method? An Empirical Study. In: Multiple Classifier Systems; Oza, N.; Polikar, R.; Kittler, J.; Roli, F., Eds.; Springer: Berlin, Heidelberg, 2005; Vol. 3541, pp. 278-285.
[http://dx.doi.org/10.1007/11494683_28]
[32]
Lecun, Y.; Jackel, L.D.; Bottou, L.; Cortes, C.; Denker, J.S.; Drucker, H.; Guyon, I.; Muller, U.A.; Sackinger, E.; Simard, P. Learning Algorithms For Classification: A Comparison On Handwritten Digit Recognition. In: Neural Networks: The Statistical Mechanics Perspective; Oh, J-H.; Cho, S.; Kwon, C., Eds.; Pohang University of Science and Technology: South Korea, 1995.
[33]
Platt, J.C. Sequential minimal optimization: A fast algorithm for training support vector machine., Technical Report MSR-TR-98-14 April 21,. 1998.
[34]
Witten, I.H.; Frank, E. Data Mining: Practical Machine Learning Tools and Techniques; Morgan, Kaufmann: San Francisco, 2005.
[35]
Kohavi, R. A study of cross-validation and bootstrap for accuracy estimation and model selection. In: International Joint Conference on Artificial Intelligence; , 2010; pp. 1137-1143.
[36]
Matthews, B.W. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim. Biophys. Acta, 1975, 405(2), 442-451.
[http://dx.doi.org/10.1016/0005-2795(75)90109-9] [PMID: 1180967]
[37]
Chen, L.; Chu, C.; Zhang, Y-H.; Zheng, M-Y.; Zhu, L.; Kong, X.; Huang, T. Identification of drug-drug interactions using chemical interactions. Curr. Bioinform., 2017, 12(6), 526-534.
[http://dx.doi.org/10.2174/1574893611666160618094219]
[38]
Chen, L.; Zhang, S.; Pan, X.; Hu, X.; Zhang, Y-H.; Yuan, F.; Huang, T.; Cai, Y-D. HIV infection alters the human epigenetic landscape. Gene Ther., 2019, 26(1-2), 29-39.
[http://dx.doi.org/10.1038/s41434-018-0051-6] [PMID: 30443044]
[39]
Zhao, X.; Chen, L.; Guo, Z-H.; Liu, T. Predicting drug side effects with compact integration of heterogeneous networks. Curr. Bioinform., 2019, 14(8), 709-720.
[http://dx.doi.org/10.2174/1574893614666190220114644]
[40]
Cui, H.; Chen, L. A binary classifier for the prediction of EC numbers of enzymes. Curr. Proteomics, 2019, 16(5), 383-391.
[http://dx.doi.org/10.2174/1570164616666190126103036]
[41]
Ben-Ari Fuchs, S.; Lieder, I.; Stelzer, G.; Mazor, Y.; Buzhor, E.; Kaplan, S.; Bogoch, Y.; Plaschkes, I.; Shitrit, A.; Rappaport, N.; Kohn, A.; Edgar, R.; Shenhav, L.; Safran, M.; Lancet, D.; Guan-Golan, Y.; Warshawsky, D.; Shtrichman, R. GeneAnalytics: An integrative gene set analysis tool for next generation sequencing, RNAseq and microarray data. OMICS, 2016, 20(3), 139-151.
[http://dx.doi.org/10.1089/omi.2015.0168] [PMID: 26983021]
[42]
Khsheibun, R.; Paperna, T.; Volkowich, A.; Lejbkowicz, I.; Avidan, N.; Miller, A. Gene expression profiling of the response to interferon beta in Epstein-Barr-transformed and primary B cells of patients with multiple sclerosis. PLoS One, 2014, 9(7)e102331
[http://dx.doi.org/10.1371/journal.pone.0102331] [PMID: 25025430]
[43]
Sykes, A.; Edwards, M.R.; Macintyre, J.; del Rosario, A.; Bakhsoliani, E.; Trujillo-Torralbo, M.B.; Kon, O.M.; Mallia, P.; McHale, M.; Johnston, S.L. Rhinovirus 16-induced IFN-alpha and IFN-beta are deficient in bronchoalveolar lavage cells in asthmatic patients. J. Allergy Clin. Immunol, 2012, 126(6), 1506-1514 e6.
[44]
Lee, C.; Kolesnik, T.B.; Caminschi, I.; Chakravorty, A.; Carter, W.; Alexander, W.S.; Jones, J.; Anderson, G.P.; Nicholson, S.E. Suppressor of cytokine signalling 1 (SOCS1) is a physiological regulator of the asthma response. Clin. Exp. Allergy, 2009, 39(6), 897-907.
[http://dx.doi.org/10.1111/j.1365-2222.2009.03217.x] [PMID: 19309352]
[45]
Gielen, V.; Sykes, A.; Zhu, J.; Chan, B.; Macintyre, J.; Regamey, N.; Kieninger, E.; Gupta, A.; Shoemark, A.; Bossley, C.; Davies, J.; Saglani, S.; Walker, P.; Nicholson, S. E.; Dalpke, A. H.; Kon, O. M.; Bush, A.; Johnston, S. L.; Edwards, M. R. Increased nuclear suppressor of cytokine signaling 1 in asthmatic bronchial epithelium suppresses rhinovirus induction of innate interferons. J.Allergy Clin. Immunol.,, 2015, 136(1), 177-188 e11..
[http://dx.doi.org/10.1016/j.jaci.2014.11.039]
[46]
Doran, E.; Choy, D.F.; Shikotra, A.; Butler, C.A.; O’Rourke, D.M.; Johnston, J.A.; Kissenpfennig, A.; Bradding, P.; Arron, J.R.; Heaney, L.G. Reduced epithelial suppressor of cytokine signalling 1 in severe eosinophilic asthma. Eur. Respir. J., 2016, 48(3), 715-725.
[http://dx.doi.org/10.1183/13993003.00400-2015] [PMID: 27338192]
[47]
Shikotra, A.; Choy, D.F.; Ohri, C.M.; Doran, E.; Butler, C.; Hargadon, B.; Shelley, M.; Abbas, A.R.; Austin, C.D.; Jackman, J.; Wu, L.C.; Heaney, L.G.; Arron, J.R.; Bradding, P. Increased expression of immunoreactive thymic stromal lymphopoietin in patients with severe asthma. J. Allergy Clin. Immunol.,, 2012, 129(1), 104-11 e1-9..
[http://dx.doi.org/10.1016/j.jaci.2011.08.031]
[48]
Baraldo, S.; Saetta, M.; Barbato, A.; Contoli, M.; Papi, A. Rhinovirus-induced interferon production in asthma. Thorax, 2014, 69(8), 772.
[http://dx.doi.org/10.1136/thoraxjnl-2013-204922] [PMID: 24695636]
[49]
Sykes, A.; Macintyre, J.; Edwards, M.R.; Del Rosario, A.; Haas, J.; Gielen, V.; Kon, O.M.; McHale, M.; Johnston, S.L. Rhinovirus-induced interferon production is not deficient in well controlled asthma. Thorax, 2014, 69(3), 240-246.
[http://dx.doi.org/10.1136/thoraxjnl-2012-202909] [PMID: 24127021]
[50]
Becker, T.M.; Durrani, S.R.; Bochkov, Y.A.; Devries, M.K.; Rajamanickam, V.; Jackson, D.J. Effect of exogenous interferons on rhinovirus replication and airway inflammatory responses. Ann. Allergy Asthma Immunol., 2013, 111(5), 397-401.
[http://dx.doi.org/10.1016/j.anai.2013.07.029] [PMID: 24125148]
[51]
Souto, F.O.; Alves-Filho, J.C.; Turato, W.M.; Auxiliadora-Martins, M.; Basile-Filho, A.; Cunha, F.Q. Essential role of CCR2 in neutrophil tissue infiltration and multiple organ dysfunction in sepsis. Am. J. Respir. Crit. Care Med., 2011, 183(2), 234-242.
[http://dx.doi.org/10.1164/rccm.201003-0416OC] [PMID: 20732989]
[52]
Rajan, D.; McCracken, C.E.; Kopleman, H.B.; Kyu, S.Y.; Lee, F.E.; Lu, X.; Anderson, L.J. Human rhinovirus induced cytokine/chemokine responses in human airway epithelial and immune cells. PLoS One, 2014, 9(12)e114322
[http://dx.doi.org/10.1371/journal.pone.0114322] [PMID: 25500821]
[53]
Mercer, P.F.; Williams, A.E.; Scotton, C.J.; José, R.J.; Sulikowski, M.; Moffatt, J.D.; Murray, L.A.; Chambers, R.C. Proteinase-activated receptor-1, CCL2, and CCL7 regulate acute neutrophilic lung inflammation. Am. J. Respir. Cell Mol. Biol., 2014, 50(1), 144-157.
[PMID: 23972264]
[54]
Yoneyama, M.; Kikuchi, M.; Natsukawa, T.; Shinobu, N.; Imaizumi, T.; Miyagishi, M.; Taira, K.; Akira, S.; Fujita, T. The RNA helicase RIG-I has an essential function in double-stranded RNA-induced innate antiviral responses. Nat. Immunol., 2004, 5(7), 730-737.
[http://dx.doi.org/10.1038/ni1087] [PMID: 15208624]
[55]
Loisel, D.A.; Du, G.; Ahluwalia, T.S.; Tisler, C.J.; Evans, M.D.; Myers, R.A.; Gangnon, R.E.; Kreiner-Møller, E.; Bønnelykke, K.; Bisgaard, H.; Jackson, D.J.; Lemanske, R.F., Jr; Nicolae, D.L.; Gern, J.E.; Ober, C. Genetic associations with viral respiratory illnesses and asthma control in children. Clin. Exp. Allergy, 2016, 46(1), 112-124.
[http://dx.doi.org/10.1111/cea.12642] [PMID: 26399222]
[56]
Fintini, D.; Salvatori, R.; Salemi, S.; Otten, B.; Ubertini, G.; Cambiaso, P.; Mullis, P.E. Autosomal-dominant isolated growth hormone deficiency (IGHD type II) with normal GH-1 gene. Horm. Res., 2006, 65(2), 76-82.
[PMID: 16424673]
[57]
Bedke, N.; Sammut, D.; Green, B.; Kehagia, V.; Dennison, P.; Jenkins, G.; Tatler, A.; Howarth, P.H.; Holgate, S.T.; Davies, D.E. Transforming growth factor-beta promotes rhinovirus replication in bronchial epithelial cells by suppressing the innate immune response. PLoS One, 2012, 7(9)e44580
[http://dx.doi.org/10.1371/journal.pone.0044580] [PMID: 22970254]
[58]
Granados, A.; Peci, A.; McGeer, A.; Gubbay, J.B. Influenza and rhinovirus viral load and disease severity in upper respiratory tract infections. J. Clin. Virol., 2017, 86, 14-19.
[http://dx.doi.org/10.1016/j.jcv.2016.11.008] [PMID: 27893998]
[59]
Perreira, J.M.; Aker, A.M.; Savidis, G.; Chin, C.R.; McDougall, W.M.; Portmann, J.M.; Meraner, P.; Smith, M.C.; Rahman, M.; Baker, R.E.; Gauthier, A.; Franti, M.; Brass, A.L. RNASEK is a V-ATPase-associated factor required for endocytosis and the replication of rhinovirus, influenza a virus, and dengue virus. Cell Rep., 2015, 12(5), 850-863.
[http://dx.doi.org/10.1016/j.celrep.2015.06.076] [PMID: 26212330]
[60]
Bønnelykke, K.; Coleman, A.T.; Evans, M.D.; Thorsen, J.; Waage, J.; Vissing, N.H.; Carlsson, C.J.; Stokholm, J.; Chawes, B.L.; Jessen, L.E.; Fischer, T.K.; Bochkov, Y.A.; Ober, C.; Lemanske, R.F., Jr; Jackson, D.J.; Gern, J.E.; Bisgaard, H. Cadherin-related family member 3 genetics and rhinovirus C respiratory illnesses. Am. J. Respir. Crit. Care Med., 2018, 197(5), 589-594.
[http://dx.doi.org/10.1164/rccm.201705-1021OC] [PMID: 29121479]
[61]
Lötzerich, M.; Roulin, P.S.; Boucke, K.; Witte, R.; Georgiev, O.; Greber, U.F. Rhinovirus 3C protease suppresses apoptosis and triggers caspase-independent cell death. Cell Death Dis., 2018, 9(3), 272.
[http://dx.doi.org/10.1038/s41419-018-0306-6] [PMID: 29449668]
[62]
Cerps, S.C.; Menzel, M.; Mahmutovic Persson, I.; Bjermer, L.; Akbarshahi, H.; Uller, L. Interferon-β deficiency at asthma exacerbation promotes MLKL mediated necroptosis. Sci. Rep., 2018, 8(1), 4248.
[http://dx.doi.org/10.1038/s41598-018-22557-6] [PMID: 29523863]

Rights & Permissions Print Cite
Article Metrics
17
© 2024 Bentham Science Publishers | Privacy Policy