<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Yang YF</submitter><funding>National Science and Technology Council</funding><pagination>1215</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12474022</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>17(9)</volume><pubmed_abstract>Long COVID, characterized by persistent symptoms following acute SARS-CoV-2 infection, has emerged as a significant public health challenge with wide-ranging clinical and socioeconomic implications. Developing an effective risk assessment strategy is essential for the early identification and management of individuals susceptible to prolonged symptoms. This study uses a quantitative approach to characterize the dose-response relationships between spike protein concentrations and effects, including Long COVID symptom numbers and the release of proinflammatory mediators. A mathematical model is also developed to describe the time-dependent change in spike protein concentrations post diagnosis in twelve Long COVID patients with a cluster analysis. Based on the spike protein concentration-Long</pubmed_abstract><journal>Viruses</journal><pubmed_title>Biomarker-Based Risk Assessment Strategy for Long COVID: Leveraging Spike Protein and Proinflammatory Mediators to Inform Broader Postinfection Sequelae.</pubmed_title><pmcid>PMC12474022</pmcid><funding_grant_id>NSTC 113-2313-B-002-032</funding_grant_id><pubmed_authors>Yang YF</pubmed_authors><pubmed_authors>Wang WM</pubmed_authors><pubmed_authors>Chen CY</pubmed_authors><pubmed_authors>Chen SY</pubmed_authors><pubmed_authors>You SH</pubmed_authors><pubmed_authors>Chen SC</pubmed_authors><pubmed_authors>Lin YJ</pubmed_authors><pubmed_authors>Hsiao HA</pubmed_authors><pubmed_authors>Lai IH</pubmed_authors><pubmed_authors>Ling MP</pubmed_authors><pubmed_authors>Lu TH</pubmed_authors><pubmed_authors>Liao CM</pubmed_authors></additional><is_claimable>false</is_claimable><name>Biomarker-Based Risk Assessment Strategy for Long COVID: Leveraging Spike Protein and Proinflammatory Mediators to Inform Broader Postinfection Sequelae.</name><description>Long COVID, characterized by persistent symptoms following acute SARS-CoV-2 infection, has emerged as a significant public health challenge with wide-ranging clinical and socioeconomic implications. Developing an effective risk assessment strategy is essential for the early identification and management of individuals susceptible to prolonged symptoms. This study uses a quantitative approach to characterize the dose-response relationships between spike protein concentrations and effects, including Long COVID symptom numbers and the release of proinflammatory mediators. A mathematical model is also developed to describe the time-dependent change in spike protein concentrations post diagnosis in twelve Long COVID patients with a cluster analysis. Based on the spike protein concentration-Long</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Sep</publication><modification>2026-05-02T03:19:22.434Z</modification><creation>2026-05-02T03:11:37.868Z</creation></dates><accession>S-EPMC12474022</accession><cross_references><pubmed>41012643</pubmed><doi>10.3390/v17091215</doi></cross_references></HashMap>