Rescue Ebola Patients in silico
Abstract
Abstract Ebola, one of the most pathogenic and lethal viruses, repeatedly leads to severe outbreaks with large numbers of casualties. By integration of data of fatal, non-fatal and asymptomatic cases, we developed a mathematical model of the immune response to Ebola infections and found that TNF-α can explain subsequent cytokine responses and allows to quantitatively stratify patients into survivors and fatal cases. The model further suggests that antibodies provide the key resolving mechanism in survivors while IFN-γ is the key defense mechanism in fatal cases. Exogenous IFN-γ and inhibition of excessive inflammation have the potential to rescue fatal Ebola infections in silico. In view of the high mortality of this disease, limited real life studies, and the unforeseeable next outbreak, our in silico analysis is meant as a guide for future research by the determination of the most efficient strategies for Ebola treatment.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.