Evidence map›Paper›PMID 40128566›Full record

ArticleCell death discovery2025

Comprehensive analysis of cellular metrics: From proliferation to mitochondrial membrane potential and cell death in a single sample.

Sirina Sabirova, Gulnaz Sharapova, Aida Budyukova, Marina Gomzikova, Anna Brichkina, Nick A Barlev, Albert Rizvanov, Nikita Markov, Hans-Uwe Simon

Abstract read
In one paragraph

Article in Cell death discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. TiACS omega · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. The essential oil from the rhizomes ofFrontiers in pharmacology · 2025
    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

9 authors.

Sirina SabirovaLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Gulnaz SharapovaLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Aida BudyukovaLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Marina GomzikovaLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Anna BrichkinaLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.ORCID http://orcid.org/0000-0001-8707-9900
Nick A BarlevLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Albert RizvanovOpenLab Gene and Cell Technology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Nikita MarkovInstitute of Pharmacology, University of Bern, Bern, Switzerland. nikita.markov@unibe.ch.ORCID http://orcid.org/0000-0003-1121-973X
Hans-Uwe SimonLaboratory of Molecular Immunology, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia. hans-uwe.simon@unibe.ch.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 310030_184816 (HUS)
6 · The paper itself

Abstract

Changes in cell number during in vitro experiments and pharmacological screenings primarily depend on two factors: cell death and proliferation. The dynamics of these processes determine whether cell populations expand and accumulate or, conversely, decrease over time. Understanding the biological mechanisms governing these changes is crucial for deciphering the mode of action of any pharmacological or genetic treatment in fundamental research and pre-clinical trials. In this context, we introduce a robust and efficient flow cytometry-based methodology that enables comprehensive analysis of key cellular parameters that indicate changes in cell numbers. This approach encompasses the assessment of cell count along with critical maintenance parameters including proliferation, cell cycle dynamics, apoptosis, cell permeability, and mitochondrial depolarization. These parameters are intricately linked, offering a detailed view of the cellular state. The described methodology is versatile and adaptable for analyzing various cell types, whether at steady state or in response to treatments. To develop this workflow, we integrated and optimised multiple flow cytometry-based stainings such as annexin V, propidium iodide, bromodeoxyuridine, CellTrace Violet, and JC-1 into a unified protocol. This article offers a detailed, step-by-step guide to the entire method, covering aspects such as timing, sample preparation techniques, and the reagents used. Additionally, it includes examples of the data that can be obtained with this technique and illustrates its multiparametric visualization. Collectively, this methodology facilitates the rapid acquisition of up to eight different parameters from a single sample in one experiment.

Identifiers

PMID40128566
PMCPMC11933298

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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.