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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Delayed type I interferon response and the subsequent out-of-sequence cytokine signal inhibit T cell induction in non-surviving Ebola virus-infected patients</dc:title><dc:creator>Zhao,	Gang	(Avtor)
	</dc:creator><dc:creator>Korva,	Miša	(Avtor)
	</dc:creator><dc:creator>Muñoz-Fontela,	César	(Avtor)
	</dc:creator><dc:creator>Günther,	Stephan	(Avtor)
	</dc:creator><dc:creator>Kerber,	Romy	(Avtor)
	</dc:creator><dc:creator>Binder,	Sebastian C.	(Avtor)
	</dc:creator><dc:creator>Meyer-Hermann,	Michael	(Avtor)
	</dc:creator><dc:subject>Ebola virus</dc:subject><dc:subject>cytokine dynamics</dc:subject><dc:subject>innate adaptive immune crosstalk</dc:subject><dc:subject>machine learning - ML</dc:subject><dc:subject>mathematical model</dc:subject><dc:subject>sequential cytokine signaling</dc:subject><dc:subject>type I interferon</dc:subject><dc:description>Introduction: While there is evidence that Ebola virus (EBOV) antagonizes the antiviral type I interferon (IFN-I) response, the role of IFN-I for EBOV disease remains controversial, as initially protective responses may contribute to disease pathogenesis later. 
Methods: We analyzed patient data from the 2014-2016 West Africa epidemic with a combination of machine learning and mathematical modeling to identify predictive immune mediators and reconstruct their temporal dynamics in survivors and non-survivors. 
Results: Our results suggest that IFN-I response in survivors occurs before symptom onset, while non-survivors mount IFN-I responses 3-4 days later, although with a similar strength. This delayed IFN-I response overlaps in time with IL-12 signals in non-survivors. As optimal T cell activation requires a particular temporal sequence in cytokine signals, this impairs the development of T cell-based cellular immunity. 
Discussion: The presented patient data analysis helps reconcile the seemingly contradictory role of IFN-I in EBOV disease from a cytokine dynamics perspective and supports the theory of sequential T cell activation, according to which a dysregulated temporal sequence of cytokine signals keeps T cells unresponsive to the pathogen.</dc:description><dc:date>2026</dc:date><dc:date>2026-06-07 06:14:43</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>183189</dc:identifier><dc:identifier>UDK: 616-097</dc:identifier><dc:identifier>ISSN pri članku: 1664-3224</dc:identifier><dc:identifier>DOI: 10.3389/fimmu.2026.1806697</dc:identifier><dc:identifier>COBISS_ID: 280576771</dc:identifier><dc:language>sl</dc:language></metadata>
