Evidence map›Paper›PMID 37254548›Full record

ReviewCombinatorial chemistry & high throughput screening2024

Recent Advances in Biologically Active Ingredients from Natural Drugs for Sepsis Treatment.

Zhenzhen Zheng, Xiayinan Song, Yanmei Shi, Xiaofeng Long, Jie Li, Min Zhang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Combinatorial chemistry & high throughput screening, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 45% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 at 3 institutions in 1 country.

Zhenzhen ZhengAffiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China.
Xiayinan SongInnovation Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China.
Yanmei ShiDepartment of Cardiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
Xiaofeng LongAffiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China.
Jie LiInnovation Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China.
Min ZhangAffiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China.
Affiliated Zhongshan Hospital of Dalian University · CNShandong University of Traditional Chinese Medicine · CNAffiliated Hospital of Shandong University of Traditional Chinese Medicine · CN

Funding

China Postdoctoral Science Foundation 2022T150393,2021M690099National Natural Science Foundation of China (NSFC) ZR2020QH309,82004277
6 · The paper itself

Abstract

Sepsis refers to the dysregulated host response to infection; its incidence and mortality rates are high. It is a worldwide medical problem but there is no specific drug for it. In recent years, clinical and experimental studies have found that many monomer components of traditional Chinese medicine have certain effects on the treatment of sepsis. This paper reviews the advances in research on the active ingredients of traditional Chinese medicine involved in the treatment of sepsis in recent years according to their chemical structure; it could provide ideas and references for further research and development in Chinese materia medica for the treatment of sepsis.

Indexed as

Biological ProductsDrugs, Chinese HerbalMedicine, Chinese TraditionalSepsisAnimalsHumansBiological ProductsDrugs, Chinese Herbalactive ingredientschemical structuremonomers.natural drugssepsisTraditional Chinese Medicine

Identifiers

PMID37254548
OpenAlexW4378782230

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.