Evidence map›Paper›PMID 39744996›Full record

ArticleLab on a chip2025

Stepwise isolation of diverse metabolic cell populations using sorting by interfacial tension (SIFT).

Matthew Shulman, Thomas Mathew, Aria Trivedi, Azam Gholizadeh, Charlotte Colcord, Ryan Wiley, Kiron S Allen, Lakshmi Thangam, Kelsey Voss, Paul Abbyad

Abstract read
In one paragraph

Article in Lab on a chip, 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.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Matthew ShulmanDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0009-0004-2407-4503
Thomas MathewDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0009-0009-4253-0580
Aria TrivediDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0009-0009-5150-4966
Azam GholizadehDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0000-0002-6634-758X
Charlotte ColcordDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0009-0007-5108-4194
Ryan WileyDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0009-0009-3996-6025
Kiron S AllenDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.
Lakshmi ThangamDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.
Kelsey VossDepartment of Pharmacology, University of Virginia, Charlottesville, VA, 22903, USA.ORCID 0000-0003-1732-2682
Paul AbbyadDepartment of Chemistry and Biochemistry, Santa Clara University, Santa Clara, CA, 95053, USA. pabbyad@scu.edu.ORCID 0000-0002-8641-8533

Funding

Development of Platform for Passive Cell Selection Based on MetabolismR15GM129674 · NIGMS · SANTA CLARA UNIVERSITY · PI ABBYAD, PAUL · 2018 to 2018
$374k
NIGMS NIH HHS R15 GM129674
6 · The paper itself

Abstract

We present here a passive and label-free droplet microfluidic platform to sort cells stepwise by lactate and proton secretion from glycolysis. A technology developed in our lab, Sorting by Interfacial Tension (SIFT), sorts droplets containing single cells into two populations based on pH by using interfacial tension. Cellular glycolysis lowers the pH of droplets through proton secretion, enabling passive selection based on interfacial tension and hence single-cell glycolysis. The SIFT technique is expanded here by exploiting the dynamic droplet acidification from surfactant adsorption that leads to a concurrent increase in interfacial tension. This allows multiple microfabricated rails at different downstream positions to isolate cells with distinct glycolytic levels. The device is used to correlate sorted cells with three levels of glycolysis with a conventional surface marker for T-cell activation. As glycolysis is associated with both disease and cell state, this technology facilitates the sorting and analysis of crucial cell subpopulations for applications in oncology, immunology and immunotherapy.

Indexed as

Cell SeparationLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesGlycolysisHumansHydrogen-Ion ConcentrationSurface Tension

Identifiers

PMID39744996
PMCPMC11910337

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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.