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dc.contributor.authorSasaki, Karin
dc.contributor.authorBruder, Dunja
dc.contributor.authorHernandez-Vargas, Esteban A
dc.date.accessioned2022-06-13T11:09:44Z
dc.date.available2022-06-13T11:09:44Z
dc.date.issued2020-02-15
dc.date.submitted2019-10-07
dc.identifier.issn1007-5704
dc.identifier.pmid32288422
dc.identifier.doi10.1016/j.cnsns.2020.105228
dc.identifier.urihttp://hdl.handle.net/10033/623214
dc.description.abstractCo-infections by multiple pathogens have important implications in many aspects of health, epidemiology and evolution. However, how to disentangle the non-linear dynamics of the immune response when two infections take place at the same time is largely unexplored. Using data sets of the immune response during influenza-pneumococcal coinfection in mice, we employ here topological data analysis to simplify and visualise high dimensional data sets. We identified persistent shapes of the simplicial complexes of the data in the three infection scenarios: single viral infection, single bacterial infection, and co-infection. The immune response was found to be distinct for each of the infection scenarios and we uncovered that the immune response during the co-infection has three phases and two transition points. During the first phase, its dynamics is inherited from its response to the primary (viral) infection. The immune response has an early shift (few hours post coinfection) and then modulates its response to react against the secondary (bacterial) infection. Between 18 and 26 h post co-infection the nature of the immune response changes again and does no longer resembles either of the single infection scenarios.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectComplex data analysisen_US
dc.subjectImmune system dynamicsen_US
dc.subjectInfluenza infectionsen_US
dc.subjectTopological data analysisen_US
dc.titleTopological data analysis to model the shape of immune responses during co-infections.en_US
dc.typeArticleen_US
dc.identifier.journalCommunications in nonlinear science & numerical simulationen_US
dc.source.volume85
dc.source.beginpage105228
dc.source.endpage
refterms.dateFOA2022-06-13T11:09:45Z
dc.source.journaltitleCommunications in nonlinear science & numerical simulation
dc.source.countryChina


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Attribution-NonCommercial-ShareAlike 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International