Evidence map›Paper›PMID 39654893›Full record

ArticleFrontiers in immunology2024

Jin Li, Lantao Wang, Bin Yu, Jie Su, Shimin Dong

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. 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

5 authors.

Jin LiDepartment of Emergency, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Lantao WangDepartment of Emergency, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Bin YuDepartment of Emergency, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Jie SuDepartment of Emergency, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Shimin DongDepartment of Emergency, Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. However, the relationship between biomarkers and sepsis remains unclear. This study aimed to find potential molecular biomarkers, which could do some help to patients with sepsis. Methods: The sepsis dataset GSE28750, GSE57065 was downloaded from the GEO database, and ten patients with or without sepsis from our hospital were admitted for RNA-seq and the differentially expressed genes (DEGs) were screened. The Metascape database was used for functional enrichment analysis and was used to found the differential gene list. Protein-protein interaction network was used and further analyzed by using Cytoscape and STRING. Logistic regression and Correlation analysis were used to find the potential molecular biomarkers. Results: Taking the intersection of the three datasets yielded 287 differential genes. The enrichment results included Neutrophil degranulation, leukocyte activation, immune effectors process, positive regulation of immune response, regulation of leukocyte activation. The top 10 key genes of PPI connectivity were screened using cytoHubba plugin, which were Conclusion:

Indexed as

BiomarkersComputational BiologyProtein Interaction MapsSepsisDatabases, GeneticGene Expression ProfilingHumansInterleukin-7 Receptor alpha SubunitReceptors, Interleukin-7BiomarkersIL7R protein, humanInterleukin-7 Receptor alpha SubunitReceptors, Interleukin-7bioinformatics analysisCD8AemergencyGZMAIL7Rsepsis

Identifiers

PMID39654893
PMCPMC11625646

What OpenQuestion holds

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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.