Accessible and accurate cytometry analysis of adherent cells using fluorescence microscopes.

Daniel Foyt, Yiming Kuang, Samma Rehem, Klaus Yserentant, Bo Huang

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

Update of
Accessible and accurate cytometry analysis using fluorescence microscopes.2025

5 · Who and what money

Authors and funding

5 authors.

Daniel FoytUCSF-UC Berkeley Joint Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA, 94143, USA. daniel_foyt@berkeley.edu.

Yiming KuangDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94143, USA.

Samma RehemBarnard College of Columbia University, New York City, NY, 10027, USA.

Klaus YserentantDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94143, USA.

Bo HuangDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94143, USA. bo.huang@ucsf.edu.

Funding

Mapping endogenous protein dynamics in living cellsR01GM131641 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Bo Huang · 2019 to 2026

$2.6M

NIGMS NIH HHS R01 GM131641NIH HHS R01GM131641

6 · The paper itself

Abstract

We have developed a method along with a Python-based analysis tool to capture images and produce flow-cytometry-like data for adherent cell culture utilizing simple accessible microscopes. Leveraging the recently developed generalist algorithms for cell segmentation, our approach efficiently quantifies single-cell fluorescence signals. We demonstrated the utility of this method by screening a set of 88 prime editing conditions using the integration of mNeonGreen2

Indexed as

Flow CytometrySingle-Cell AnalysisAlgorithmsCell AdhesionHumansImage Processing, Computer-AssistedMicroscopy, Fluorescence

Identifiers

PMID40436920

DOI10.1038/s41598-025-01957-5

PMCPMC12120079

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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.