Evidence map›Paper›PMID 38076060›Full record

ArticleHeliyon2023

Evaluation of toxicological effects of chemical substances by gut microbiota: The example of adenine damage to the kidney and gut.

Xiaoya Li, Bo Qiao, Yueying Wu, Na Deng, Zhoujin Tan

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 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
0.8field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  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

5 authors at 2 institutions in 1 country.

Xiaoya LiSchool of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Bo QiaoSchool of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Yueying WuCollege of Basic Medicine, Yunnan University of Chinese Medicine, Kunming, Yunnan, China.
Na DengSchool of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Zhoujin TanSchool of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Hunan University of Traditional Chinese Medicine · CNYunnan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explored the effects of different doses of adenine intake on mice in terms of kidney function, oxidative stress and gut content microbiota to elucidate interactions between adenine-induced kidney function impairment and gut content microbiota disorder. Mice were gavaged with low-dosage adenine suspension (NML), middle-dosage adenine suspension (NMM), high-dosage adenine suspension (NMH) and sterile water (NC). Behaviour, kidney structure and function, colonic structure, oxidative stress and gut content microbiota were detected. Mice in NML, NMM, and NMH groups had significantly lower body weight, anal temperature and food intake, increased water intake, the mice had loose and deformed feces with obvious water stains through the paper. NMM mice presented significantly structural damage to kidney and colonic tissues, considerably higher BUN and Cr, MDA and lower SOD. MDA and SOD levels in NMM and NMH groups were closely associated with Cr and BUN. Moreover, different doses of adenine intake effected the mice gut content microbiota, and enriched the different characteristic bacteria. Characteristic bacteria

Indexed as

AdenineCharacteristic bacteriaDiarrheaKidney functionKidney-gut axisOxidative stress

Identifiers

PMID38076060
PMCPMC10703711
OpenAlexW4389117596

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.