Evidence map›Paper›PMID 37020171›Full record

ArticleAnnals of biomedical engineering2023

A Multiscale Model for Shear-Mediated Platelet Adhesion Dynamics: Correlating In Silico with In Vitro Results.

Peineng Wang, Jawaad Sheriff, Peng Zhang, Yuefan Deng, Danny Bluestein

Abstract read
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In one paragraph

Article in Annals of biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 1 institution in 1 country.

Peineng Wang *Department of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA.
Jawaad Sheriff *Department of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA.
Peng ZhangDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
Yuefan DengDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
Danny BluesteinDepartment of Biomedical Engineering, T08-50 Health Sciences Center, Stony Brook University, Stony Brook, NY, 11794-8084, USA. danny.bluestein@stonybrook.edu.ORCID http://orcid.org/0000-0002-4014-2308
Stony Brook University · US

Funding

Multiscale Modeling of Blood Flow and Platelet Mediated ThrombosisU01HL131052 · NHLBI · STATE UNIVERSITY NEW YORK STONY BROOK · PI BLUESTEIN, DANNY · 2016 to 2020
$3.6M
NHLBI NIH HHS R01 HL131052NHLBI NIH HHS U01 HL131052
6 · The paper itself

Abstract

Platelet adhesion to blood vessel walls is a key initial event in thrombus formation in both vascular disease processes and prosthetic cardiovascular devices. We extended a deformable multiscale model (MSM) of flowing platelets, incorporating Dissipative Particle Dynamics (DPD) and Coarse-Grained Molecular Dynamics (CGMD) describing molecular-scale intraplatelet constituents and their interaction with surrounding flow, to predict platelet adhesion dynamics under physiological flow shear stresses. Binding of platelet glycoprotein receptor Ibα (GPIbα) to von Willebrand factor (vWF) on the blood vessel wall was modeled by a molecular-level hybrid force field and validated with in vitro microchannel experiments of flowing platelets at 30 dyne/cm

Indexed as

Thrombosisvon Willebrand FactorBlood PlateletsHumansMolecular Dynamics SimulationPlatelet AdhesivenessProtein Bindingvon Willebrand FactorDissipative particle dynamicsGPIbα-vWF bondMachine learningMolecular dynamicsPlatelet kinematics

Identifiers

PMID37020171
OpenAlexW4362632915

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.