Evidence map›Paper›PMID 36340168›Full record

ArticleACS omega2022

Simple Assessment of Red Blood Cell Deformability Using Blood Pressure in Capillary Channels for Effective Detection of Subpopulations in Red Blood Cells.

Yang Jun Kang, Sami Serhrouchni, Asya Makhro, Anna Bogdanova, Sung Sik Lee

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Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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.

Yang Jun KangDepartment of Mechanical Engineering, Chosun University, Gwangju501-759, Republic of Korea.ORCID https://orcid.org/0000-0002-5047-3012
Sami SerhrouchniInstitute of Veterinary Physiology, University of Zürich, Zürich8057, Switzerland.
Asya MakhroInstitute of Veterinary Physiology, University of Zürich, Zürich8057, Switzerland.
Anna BogdanovaInstitute of Veterinary Physiology, University of Zürich, Zürich8057, Switzerland.
Sung Sik LeeScientific Center for Optical and Electron Microscopy, ETH Zürich, Zürich8093, Switzerland.ORCID https://orcid.org/0000-0001-9267-232X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of red blood cell (RBC) deformability as a biomarker requires expensive equipment to induce and monitor deformation. In this study, we present a simple method for quantifying RBC deformability. We designed a microfluidic channel consisting of a micropillar channel and a coflowing channel connected in series. When blood (loading volume = 100 μL) was injected continuously into the device under constant pressure (1 bar), we monitored the boundary position of the blood and the reference flow in the coflowing channel. A decrease in the deformability of RBCs results in a growing pressure drop in the micropillar channel, which is mirrored by a decrease in blood pressure in the coflowing channel. Analysis of this temporal variation in blood pressure allowed us to define the clogging index (CI) as a new marker of RBC deformability. As a result of the analytical study and numerical simulation, we have demonstrated that the coflowing channel may serve as a pressure sensor that allows the measurement of blood pressure with accuracy. We have shown experimentally that a higher hematocrit level (i.e., more than 40%) does not have a substantial influence on CI. The CI tended to increase to a higher degree in glutaraldehyde-treated hardened RBCs. Furthermore, we were able to resolve the difference in deformability of RBCs between two different RBC density subfractions in human blood. In summary, our approach using CI provides reliable information on the deformability of RBCs, which is comparable to the readouts obtained by ektacytometry. We believe that our microfluidic device would be a useful tool for evaluating the deformability of RBCs, which does not require expensive instruments (e.g., high-speed camera) or time-consuming micro-PIV analysis.

Identifiers

PMID36340168
PMCPMC9631408

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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.