Evidence map›Paper›PMID 39234104›Full record

ArticleFrontiers in pharmacology2024

The therapeutic targets and signaling mechanisms of ondansetron in the treatment of critical illness in the ICU.

Lili Tao, Zhenhui Zhang, Chuang Li, Minxuan Huang, Ping Chang

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 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. Frontiers in pharmacology · 2025
    Article
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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.

Lili Tao *Department of Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Zhenhui Zhang *Department of Critical Care Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Chuang Li *Department of Emergency Department, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Minxuan HuangDepartment of Critical Care Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Ping ChangDepartment of Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is accumulating evidence regarding the benefits of the 5-HT Methods: A bioinformatics analysis of network pharmacology was conducted to demonstrate screening targets and the signaling pathways of ondansetron action against the most common critical illnesses such as acute kidney injury (AKI), sepsis, and acute respiratory distress syndrome (ARDS). Experiments of LPS-stimulated rat neutrophils with ondansetron treatment were conducted to further validate the relevant hypothesis. Results: A total of 198, 111, and 26 primary causal targets were identified from the data for the action of ondansetron against AKI, sepsis, and ARDS respectively. We found that the pathway of neutrophil extracellular traps (NETs) formation is statistically significantly involved in the action of ondansetron against these three critical illnesses. In the pathway of NETs formation, the common drug-disease intersection targets in these three critical illnesses were toll-like receptor 8 ( Conclusion: The excessive formation of NETs may have important research value in the development and progression of critical illness. Ondansetron may reduce excessive inflammatory injury in critical diseases by reducing the formation of NETs via influencing the five targets:

Indexed as

AKIARDSNETsnetwork pharmacologyondansetronsepsis

Identifiers

PMID39234104
PMCPMC11372243

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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.