Evidence map›Paper›PMID 32814061›Full record

ArticleBiophysical journal2020

Quantifying Fibrinogen-Dependent Aggregation of Red Blood Cells in Type 2 Diabetes Mellitus.

Yixiang Deng, Dimitrios P Papageorgiou, Xuejin Li, Nikolaos Perakakis, Christos S Mantzoros, Ming Dao, George Em Karniadakis

Open access · hybridAbstract read
In one paragraph

Article in Biophysical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.7field-weighted citation impact, top 5% 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

27 citing papers in PubMed, 45 citations in OpenAlex.

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  10. Biomechanics of phagocytosis of red blood cells by macrophages in the human spleen.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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  12. Review
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  15. Pathophysiology of Red Blood Cell Dysfunction in Diabetes and Its Complications.Pathophysiology : the official journal of the International Society for Pathophysiology · 2023
    Review
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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

7 authors at 4 institutions in 2 countries.

Yixiang DengDivision of Applied Mathematics, Brown University, Providence, Rhode Island; School of Engineering, Brown University, Providence, Rhode Island.
Dimitrios P PapageorgiouDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Xuejin LiDepartment of Engineering Mechanics and Center for X-Mechanics, Zhejiang University, Hangzhou, People's Republic of China.
Nikolaos PerakakisDivision of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
Christos S MantzorosDivision of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts; Boston VA Healthcare System, Boston, Massachusetts.
Ming DaoDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts.
George Em KarniadakisDivision of Applied Mathematics, Brown University, Providence, Rhode Island. Electronic address: george_karniadakis@brown.edu.
Beth Israel Deaconess Medical Center · USBrown University · USMassachusetts Institute of Technology · USZhejiang University · CN

Funding

Multiscale Modeling of Sickle Cell Anemia: Methods and ValidationU01HL114476 · NHLBI · BROWN UNIVERSITY · PI DAO, MING, HIGGINS, JOHN MATTHEW · 2013 to 2017
$3.9M
Multimodality imaging-driven multifidelity modeling of aortic dissectionU01HL142518 · NHLBI · YALE UNIVERSITY · PI HUMPHREY, JAY D., KARNIADAKIS, GEORGE · 2018 to 2022
$2.8M
Leptin and Adipokine PhysiologyK24DK081913 · NIDDK · BETH ISRAEL DEACONESS MEDICAL CENTER · PI MANTZOROS, CHRISTOS S · 2008 to 2020
$1.5M
NHLBI NIH HHS U01 HL142518NIDDK NIH HHS K24 DK081913
6 · The paper itself

Abstract

Fibrinogen is regarded as the main glycoprotein in the aggregation of red blood cells (RBCs), a normally occurring phenomenon that has a major impact on blood rheology and hemodynamics, especially under pathological conditions, including type 2 diabetes mellitus (T2DM). In this study, we investigate the fibrinogen-dependent aggregation dynamics of T2DM RBCs through patient-specific predictive computational simulations that invoke key parameters derived from microfluidic experiments. We first calibrate our model parameters at the doublet (a rouleau consisting of two aggregated RBCs) level for healthy blood samples by matching the detaching force required to fully separate RBC doublets with measurements using atomic force microscopy and optical tweezers. Using results from companion microfluidic experiments that also provide in vitro quantitative information on cell-cell adhesive dynamics, we then quantify the rouleau dissociation dynamics at the doublet and multiplet (a rouleau consisting of three or more aggregated RBCs) levels for obese patients with or without T2DM. Specifically, we examine the rouleau breakup rate when it passes through microgates at doublet level and investigate the effect of rouleau alignment in altering its breakup pattern at multiplet level. This study seamlessly integrates in vitro experiments and simulations and consequently enhances our understanding of the complex cell-cell interaction, highlighting the importance of the aggregation and disaggregation dynamics of RBCs in patients at increased risk of microvascular complications.

Indexed as

Diabetes Mellitus, Type 2Erythrocyte AggregationErythrocytesFibrinogenHumansOptical TweezersFibrinogen

Identifiers

PMID32814061
PMCPMC7474208
OpenAlexW3048299856

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.