Evidence map›Paper›PMID 39753028›Full record

ArticleComputers in biology and medicine2025

Mathematical modeling of impacts of patient differences on renin-angiotensin system and applications to COVID-19 lung fibrosis outcomes.

Mohammad Aminul Islam, Ashlee N Ford Versypt

Abstract read
In one paragraph

Article in Computers in biology and medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Mohammad Aminul IslamDepartment of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
Ashlee N Ford VersyptDepartment of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA; Department of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA; Institute for Artificial Intelligence and Data Science, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA; Witebsky Center for Microbial Pathogenesis and Immunology, University at Buffalo, The State University of New York, Buffalo, NY, 14203, USA; Department of Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, 14215, USA. Electronic address: ashleefv@buffalo.edu.

Funding

Quantitative Systems Biomedicine and Pharmacology for Multiscale Tissue DamageR35GM133763 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI Ashlee Nicole Ford Versypt · 2019 to 2026
$2.7M
NIGMS NIH HHS R35 GM133763
6 · The paper itself

Abstract

Patient-specific premorbidity, age, and sex are significant heterogeneous factors that influence the severe manifestation of lung diseases, including COVID-19 fibrosis. The renin-angiotensin system (RAS) plays a prominent role in regulating the effects of these factors. Recent evidence shows patient-specific alterations of RAS peptide homeostasis concentrations with premorbidity and the expression level of angiotensin-converting enzyme 2 (ACE2) during COVID-19. However, conflicting evidence suggests decreases, increases, or no changes in RAS peptides after SARS-CoV-2 infection. A multiscale computational model was developed to quantify the systemic contribution of heterogeneous factors of RAS during COVID-19. Three submodels were connected-an agent-based model for in-host COVID-19 response in the lung tissue, a RAS dynamics model, and a fibrosis dynamics model to investigate the effects of patient-group-specific factors in the systemic alteration of RAS and collagen deposition in the lung. The model results indicated cell death due to inflammatory response as a major contributor to the reduction of ACE and ACE2. The model explained possible mechanisms for conflicting evidence of patient-group-specific changes in RAS peptides in previously published studies. RAS peptides decreased for all virtual patient groups with aging in both sexes. In contrast, large variations in the magnitude of reduction were observed between male and female virtual patients in the older and middle-aged groups. The patient-specific variations in homeostasis RAS peptide concentrations of SARS-CoV-2-negative patients affected the dynamics of RAS during infection. This model may find further applications in patient-specific calibrations of tissue models for acute and chronic lung diseases to develop personalized treatments.

Indexed as

COVID-19Models, BiologicalPulmonary FibrosisRenin-Angiotensin SystemSARS-CoV-2Angiotensin-Converting Enzyme 2FemaleHumansLungMaleMiddle AgedACE2 protein, humanAngiotensin-Converting Enzyme 2Pulmonary fibrosisRenin-angiotensin systemSARS-CoV-2TGF-β

Identifiers

PMID39753028
PMCPMC11932320

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.