Artificial intelligence-enabled microfluidic cytometer using gravity-driven slug flow for rapid CD4

Desh Deepak Dixit, Tyler P Graf, Kevin J McHugh, Peter B Lillehoj

Abstract read

In one paragraph

Article in Microsystems & nanoengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2026
Article

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

4 authors.

Desh Deepak Dixit *Department of Mechanical Engineering, Rice University, Houston, TX, USA.ORCID http://orcid.org/0000-0003-2148-1803

Tyler P Graf *Department of Bioengineering, Rice University, Houston, TX, USA.

Kevin J McHughDepartment of Bioengineering, Rice University, Houston, TX, USA.

Peter B LillehojDepartment of Mechanical Engineering, Rice University, Houston, TX, USA. lillehoj@rice.edu.ORCID http://orcid.org/0000-0002-0289-2634

Funding

Unbiased electrothermal flow-enhanced identification of antigen-specific T cells in lung cancerR21CA283852 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LILLEHOJ, PETER B, REUBEN, ALEXANDRE · 2023 to 2023

$413k

NCI NIH HHS R21 CA283852U.S. Department of Health & Human Services | National Institutes of Health (NIH) R21CA283852

6 · The paper itself

Abstract

The quantification of immune cell subpopulations in blood is important for the diagnosis, prognosis and management of various diseases and medical conditions. Flow cytometry is currently the gold standard technique for cell quantification; however, it is laborious, time-consuming and relies on bulky/expensive instrumentation, limiting its use to laboratories in high-resource settings. Microfluidic cytometers offering enhanced portability have been developed that are capable of rapid cell quantification; however, these platforms involve tedious sample preparation and processing protocols and/or require the use of specialized/expensive instrumentation for flow control and cell detection. Here, we report an artificial intelligence-enabled microfluidic cytometer for rapid CD4

Identifiers

PMID40016189

DOI10.1038/s41378-025-00881-y

PMCPMC11868388

What OpenQuestion holds

Textmetadata

LicenceCC BY

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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.