Evidence map›Paper›PMID 39281911›Full record

ArticleACS omega2024

ALTMAN: A Novel Method for Cell Cycle Analysis.

Zining Wang, Tian Wang, Xiaohui Chen, Linxi Lv, Yang Luo, Wei Gu

Abstract read
In one paragraph

Article in ACS omega, 2024. 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

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

6 authors.

Zining WangCenter of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing 400044, People's Republic of China.
Tian WangCenter of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing 400044, People's Republic of China.
Xiaohui ChenDepartment of Clinical Laboratory, Fuling Hospital, Chongqing University, Chongqing 408099, People's Republic of China.
Linxi LvCenter of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing 400044, People's Republic of China.
Yang LuoCenter of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing 400044, People's Republic of China.ORCID https://orcid.org/0000-0002-0166-9027
Wei GuCenter of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing 400044, People's Republic of China.ORCID https://orcid.org/0000-0002-9529-4683

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate analysis of S-phase fraction is crucial for the assessment of cell proliferation levels, tumor malignancy and prognostic effects of treatment. Most of the currently developed methods for S-phase cell analysis rely on flow cytometric analysis of DNA content determination. However, the lack of standardized procedures for sample analysis and interpretation of cell cycle fitting graphs poses a significant limitation in clinical practice for utilizing flow cytometry to measure the cell cycle based on DNA content. Herein, we developed an approach for analyzing S-phase cells based on telomerase activity determination. Briefly, this approach distinguishes S-phase cells in cell populations via direct fluorescence tracking of telomerase activity within individual cells. The dynamic analysis of telomerase activity in different cell cycles was made possible by the ALTMAN strategy developed in our previous studies, which has been successfully employed to distinguish S-phase cells in cultured cells. This method offers a novel avenue for the assessment of cell cycle status and the evaluation of the proliferation status of tumor cells and the prognosis effect of tumor patients via analyzing the differences in telomerase activity during different cell cycle processes.

Identifiers

PMID39281911
PMCPMC11391549

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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.