Evidence map›Paper›PMID 33751272›Full record

ArticleBulletin of mathematical biology2021

Modeling and Parameter Subset Selection for Fibrin Polymerization Kinetics with Applications to Wound Healing.

Katherine J Pearce, Kimberly Nellenbach, Ralph C Smith, Ashley C Brown, Mansoor A Haider

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Bayesian inference informed by parameter subset selection for a minimal PBPK brain model.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Katherine J PearceDepartment of Mathematics, North Carolina State University, Box 8205, Raleigh, NC, 27695-8205, USA.
Kimberly NellenbachJoint Department of Biomedical Engineering, North Carolina State University and The University of North Carolina at Chapel Hill, Raleigh, NC, 27695, USA.
Ralph C SmithDepartment of Mathematics, North Carolina State University, Box 8205, Raleigh, NC, 27695-8205, USA.
Ashley C BrownJoint Department of Biomedical Engineering, North Carolina State University and The University of North Carolina at Chapel Hill, Raleigh, NC, 27695, USA.
Mansoor A HaiderDepartment of Mathematics, North Carolina State University, Box 8205, Raleigh, NC, 27695-8205, USA. mahaider@ncsu.edu.ORCID 0000-0002-3096-1203

Funding

Targeted treatment of thrombotic occlusions using a dual-delivery microgel therapeuticR01HL146701 · NHLBI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI BROWN, ASHLEY CARSON · 2019 to 2023
$2.0M
NHLBI NIH HHS R01 HL146701
6 · The paper itself

Abstract

During the hemostatic phase of wound healing, vascular injury leads to endothelial cell damage, initiation of a coagulation cascade involving platelets, and formation of a fibrin-rich clot. As this cascade culminates, activation of the protease thrombin occurs and soluble fibrinogen is converted into an insoluble polymerized fibrin network. Fibrin polymerization is critical for bleeding cessation and subsequent stages of wound healing. We develop a cooperative enzyme kinetics model for in vitro fibrin matrix polymerization capturing dynamic interactions among fibrinogen, thrombin, fibrin, and intermediate complexes. A tailored parameter subset selection technique is also developed to evaluate parameter identifiability for a representative data curve for fibrin accumulation in a short-duration in vitro polymerization experiment. Our approach is based on systematic analysis of eigenvalues and eigenvectors of the classical information matrix for simulations of accumulating fibrin matrix via optimization based on a least squares objective function. Results demonstrate robustness of our approach in that a significant reduction in objective function cost is achieved relative to a more ad hoc curve-fitting procedure. Capabilities of this approach to integrate non-overlapping subsets of the data to enhance the evaluation of parameter identifiability are also demonstrated. Unidentifiable reaction rate parameters are screened to determine whether individual reactions can be eliminated from the overall system while preserving the low objective cost. These findings demonstrate the high degree of information within a single fibrin accumulation curve, and a tailored model and parameter subset selection approach for improving optimization and reducing model complexity in the context of polymerization experiments.

Indexed as

FibrinModels, BiologicalWound HealingAnimalsCells, CulturedHumansKineticsPolymerizationFibrinFibrin polymerizationKinetics modelParameter identifiabilitySubset selectionWound healing

Identifiers

PMID33751272
PMCPMC8237246

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Registered trials

None linked

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.