Evidence map›Paper›PMID 40519058›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2025

SCO-ph: Microfluidic Dynamic Phenotyping Platform for High-Throughput Screening of Single Cell Acidification.

Hyejoong Jeong, Emilia A Leyes Porello, Jean G Rosario, Da Kuang, Syung Hun Han, Jai-Yoon Sul, Bomyi Lim, Daeyeon Lee, Junhyong Kim

Abstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Hyejoong JeongDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Emilia A Leyes PorelloDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Jean G RosarioDepartment of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID 0000-0002-6116-5058
Da KuangDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Syung Hun HanDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Jai-Yoon SulDepartment of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Bomyi LimDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Daeyeon LeeDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID 0000-0001-6679-290X
Junhyong KimDepartment of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Funding

Center for Sub-Cellular GenomicsRM1HG010023 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI EBERWINE, JAMES H, KIM, JUNHYONG · 2018 to 2022
$11.0M
National Human Genome Research Institute of the National Institutes of Health RM1HG010023NHGRI NIH HHS RM1 HG010023
6 · The paper itself

Abstract

Studies on the dynamics of single cell phenotyping have been hampered by the lack of quantitative high-throughput metabolism assays. Extracellular acidification, a prominent phenotype, yields significant insights into cellular metabolism, including tumorigenicity. Here, it is developed a versatile microfluidic system for single cell optical pH analysis (SCO-pH), which compartmentalizes single cells in 140-pL droplets and immobilizes ≈40,000 droplets in a 2D array for temporal extracellular pH analysis. SCO-pH distinguishes cells undergoing hyperglycolysis induced by oligomycin A from untreated cells by monitoring their extracellular acidification. To facilitate pH sensing in each droplet, a cell-impermeable pH probe is encapsulated and its fluorescence intensities are quantified. Using this approach, hyperglycolytic cells can be differentiated, and single-cell heterogeneity in extracellular acidification dynamics can be concurrently observed. This high-throughput system will be useful in applications that require dynamic phenotyping of single cells with significant heterogeneity.

Indexed as

High-Throughput Screening AssaysMicrofluidic Analytical TechniquesMicrofluidicsSingle-Cell AnalysisHumansHydrogen-Ion ConcentrationPhenotypeextracellular acidificationglycolysis, high‐throughputmicrofluidicsphenotypingsingle cell

Identifiers

PMID40519058
PMCPMC12366287

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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.