Evidence map›Paper›PMID 39546494›Full record

ArticlePLoS computational biology2024

A new look at TFPI inhibition of factor X activation.

Fabian Santiago, Amandeep Kaur, Shannon Bride, Dougald Monroe, Karin Leiderman, Suzanne Sindi

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Fabian SantiagoDepartment of Applied Mathematics, University of California Merced, Merced, California, United States of America.ORCID 0000-0002-5369-4128
Amandeep KaurDepartment of Applied Mathematics, University of California Merced, Merced, California, United States of America.
Shannon BrideDepartment of Applied Mathematics & Statistics, Colorado School of Mines, Golden, Colorado, United States of America.
Dougald MonroeUNC Blood Research Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-0493-2943
Karin LeidermanUNC Blood Research Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-4188-1305
Suzanne SindiDepartment of Applied Mathematics, University of California Merced, Merced, California, United States of America.ORCID 0000-0003-2742-4332

Funding

An integrated computational and experimental approach to understanding the hemostatic response during treatment of bleedingR01HL151984 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FOGELSON, AARON L, LEIDERMAN, KARIN · 2020 to 2023
$2.8M
NHLBI NIH HHS R01 HL151984
6 · The paper itself

Abstract

Blood coagulation is a vital physiological process involving a complex network of biochemical reactions, which converge to form a blood clot that repairs vascular injury. This process unfolds in three phases: initiation, amplification, and propagation, ultimately leading to thrombin formation. Coagulation begins when tissue factor (TF) is exposed on an injured vessel's wall. The first step is when activated factor VII (VIIa) in the plasma binds to TF, forming complex TF:VIIa, which activates factor X. Activated factor X (Xa) is necessary for coagulation, so the regulation of its activation is crucial. Tissue Factor Pathway Inhibitor (TFPI) is a critical regulator of the initiation phase as it inhibits the activation of factor X. While previous studies have proposed two pathways-direct and indirect binding-for TFPI's inhibitory role, the specific biochemical reactions and their rates remain ambiguous. Many existing mathematical models only assume an indirect pathway, which may be less effective under physiological flow conditions. In this study, we revisit datasets from two experiments focused on activated factor X formation in the presence of TFPI. We employ an adaptive Metropolis method for parameter estimation to reinvestigate a previously proposed biochemical scheme and corresponding rates for both inhibition pathways. Our findings show that both pathways are essential to replicate the static experimental results. Previous studies have suggested that flow itself makes a significant contribution to the inhibition of factor X activation. We added flow to this model with our estimated parameters to determine the contribution of the two inhibition pathways under these conditions. We found that direct binding of TFPI is necessary for inhibition under flow. The indirect pathway has a weaker inhibitory effect due to removal of solution phase inhibitory complexes by flow.

Indexed as

Blood CoagulationFactor XLipoproteinsComputational BiologyFactor XaHumansModels, BiologicalThromboplastinFactor XFactor Xalipoprotein-associated coagulation inhibitorLipoproteinsThromboplastin

Identifiers

PMID39546494
PMCPMC11567595

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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.