Evidence map›Paper›PMID 39004631›Full record

ArticleScientific reports2024

Quantification of circadian rhythms in mammalian lung tissue snapshot data.

Saskia Grabe, Bharath Ananthasubramaniam, Hanspeter Herzel

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Circadian genesJournal of Zhejiang University. Science. B · 2025
    Review
  4. 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

3 authors.

Saskia GrabeCharité Center for Basic Sciences, Institute for Theoretical Biology, Charité-Universitätsmedizin Berlin, Berlin, Germany. grabesas@hu-berlin.de.
Bharath AnanthasubramaniamDepartment of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.
Hanspeter HerzelCharité Center for Basic Sciences, Institute for Theoretical Biology, Charité-Universitätsmedizin Berlin, Berlin, Germany.

Funding

Deutsche Forschungsgemeinschaft AN 1553/2-1Deutsche Forschungsgemeinschaft RTG2424
6 · The paper itself

Abstract

Healthy mammalian cells have a circadian clock, a gene regulatory network that allows them to schedule their physiological processes to optimal times of the day. When healthy cells turn into cancer cells, the circadian clock often becomes cancer specifically disturbed, so there is an interest in the extraction of circadian features from gene expression data of cancer. This is challenging, as clinical gene expression samples of cancer are snapshot-like and the circadian clock is best examined using gene expression time series. In this study, we obtained lists of intersecting circadian genes in public gene expression time series data of lung tissue of mouse and baboon. We base our circadian gene lists on correlations of gene expression levels of circadian genes, which are closely associated to the phase differences between them. Combining circadian gene expression patterns of diurnal and nocturnal species of different ages provides circadian genes that are also important in healthy and cancerous human lung tissue. We tested the quality of the representation of the circadian clock in our gene lists by PCA-based reconstructions of the circadian times of the mouse and baboon samples. Then we assigned potential circadian times to the human lung tissue samples and find an intact circadian clock in the healthy human lung tissue, but an altered, weak clock in the adjacent cancerous lung tissue.

Indexed as

Circadian ClocksCircadian RhythmLungAnimalsGene Expression ProfilingHumansLung NeoplasmsMicePapio

Identifiers

PMID39004631
PMCPMC11247089

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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.