Evidence map›Paper›PMID 28746858›Full record

ArticleBiophysical journal2017

Modeling of Biomechanics and Biorheology of Red Blood Cells in Type 2 Diabetes Mellitus.

Hung-Yu Chang, Xuejin Li, George Em Karniadakis

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

34 citing papers in PubMed, 77 citations in OpenAlex.

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  13. Microfluidic-based systems for the management of diabetes.Drug delivery and translational research · 2024
    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

3 authors at 1 institution in 1 country.

Hung-Yu ChangDivision of Applied Mathematics, Brown University, Providence, Rhode Island.
Xuejin LiDivision of Applied Mathematics, Brown University, Providence, Rhode Island. Electronic address: xuejin_li@brown.edu.
George Em KarniadakisDivision of Applied Mathematics, Brown University, Providence, Rhode Island. Electronic address: george_karniadakis@brown.edu.
Brown University · US

Funding

Multiscale Modeling of Sickle Cell Anemia: Methods and ValidationU01HL114476 · NHLBI · BROWN UNIVERSITY · PI DAO, MING, HIGGINS, JOHN MATTHEW · 2013 to 2017
$3.9M
Multiscale, Multiphysics Model of Thrombus Biomechanics in Aortic DissectionU01HL116323 · NHLBI · YALE UNIVERSITY · PI HUMPHREY, JAY D., KARNIADAKIS, GEORGE · 2013 to 2017
$2.4M
NHLBI NIH HHS U01 HL114476NHLBI NIH HHS U01 HL116323
6 · The paper itself

Abstract

Erythrocytes in patients with type-2 diabetes mellitus (T2DM) are associated with reduced cell deformability and elevated blood viscosity, which contribute to impaired blood flow and other pathophysiological aspects of diabetes-related vascular complications. In this study, by using a two-component red blood cell (RBC) model and systematic parameter variation, we perform detailed computational simulations to probe the alteration of the biomechanical, rheological, and dynamic behavior of T2DM RBCs in response to morphological change and membrane stiffening. First, we examine the elastic response of T2DM RBCs subject to static tensile forcing and their viscoelastic relaxation response upon release of the stretching force. Second, we investigate the membrane fluctuations of T2DM RBCs and explore the effect of cell shape on the fluctuation amplitudes. Third, we subject the T2DM RBCs to shear flow and probe the effects of cell shape and effective membrane viscosity on their tank-treading movement. In addition, we model the cell dynamic behavior in a microfluidic channel with constriction and quantify the biorheological properties of individual T2DM RBCs. Finally, we simulate T2DM RBC suspensions under shear and compare the predicted viscosity with experimental measurements. Taken together, these simulation results and their comparison with currently available experimental data are helpful in identifying a specific parametric model-the first of its kind, to our knowledge-that best describes the main hallmarks of T2DM RBCs, which can be used in future simulation studies of hematologic complications of T2DM patients.

Indexed as

Models, CardiovascularBiomechanical PhenomenaCell MembraneComputer SimulationDiabetes Mellitus, Type 2ElasticityElastic ModulusErythrocyte DeformabilityErythrocytesHumansMicrofluidicsRheologyViscosity

Identifiers

PMID28746858
PMCPMC5529313
OpenAlexW2952519480

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.