Evidence map›Paper›PMID 37429969›Full record

ArticleScientific reports2023

Comparative transcriptome analysis of unfractionated peripheral blood leukocytes after exercise in human.

Mingkun Nie, Qingling Liu, Ruoling Jia, Zhuoyi Li, Xiaoru Li, Xiangtao Meng

Abstract read
In one paragraph

Article in Scientific reports, 2023. 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. Article
  4. Review
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.

Mingkun NieSchool of Physical Education, Xinxiang University, Xinxiang, 453000, Henan, China.
Qingling LiuSchool of Pharmacy, Xinxiang University, Xinxiang, 453000, Henan, China.
Ruoling JiaSchool of Pharmacy, Xinxiang University, Xinxiang, 453000, Henan, China. jiaruoling2010@163.com.
Zhuoyi LiSchool of Pharmacy, Xinxiang University, Xinxiang, 453000, Henan, China.
Xiaoru LiSchool of Pharmacy, Xinxiang University, Xinxiang, 453000, Henan, China.
Xiangtao MengSchool of Pharmacy, Xinxiang University, Xinxiang, 453000, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exercise has profound but variable effects on the immune system. However, only limited information exists about the changes of exercise-induced gene expression in whole immune cells. The aim of this study is to unravel the potential molecular changes of genes which are related to immunity after exercise. The raw expression data and corresponding clinical of GSE18966 were downloaded from Gene Expression Omnibus database. The differentially expressed genes between control group and treat groups were performed by in-house developed perl scripts. A total of 83 differentially expressed genes (DEGs) (|log2 FC|> 1, FDR < 0.05) were identified between control and treat group 1 (0 h after exercise), 128 DEGs (|log2 FC|> 1, FDR < 0.05) between control and treat group 2 (4 h after exercise), and there was no significant difference between control and treat group 3 (20 h after exercise). Next, we identified 51 overlapping genes between treat group 1 (0 h after exercise) and treat group 2 (4 h after exercise) using Venn analysis. Protein-protein interaction (PPI) network was constructed by Cytoscape 3.7.2, and nine hub genes (S100A12, FCGR3B, FPR1, VNN2, AQP9, MMP9, OSM, NCF4, HP) were identified. Finally, 9 hub genes were identified as the potential biomarkers of exercise using validation set (GSE83578) verification analysis. These hub genes might serve as potential molecular targets of monitoring exercise and training processes in the further.

Indexed as

Gene Expression ProfilingTranscriptomeDatabases, FactualGenes, OverlappingHumansLeukocytes

Identifiers

PMID37429969
PMCPMC10333281

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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.