Evidence map›Paper›PMID 38613799›Full record

ArticleAging2024

Age and aging process alter the gut microbes.

Qu Zhanbo, Zhuang Jing, Han Shugao, Wu Yinhang, Chu Jian, Yu Xiang, Zhao Feimin, Liu Jian, Wu Xinyue, Wu Wei and 1 more

Open access · greenAbstract read
In one paragraph

Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 5 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

Qu ZhanboFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Zhuang JingFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Han ShugaoThe Second Hospital Affiliated to Zhejiang University School of Medicine, Hangzhou 310017, Zhejiang, China.
Wu YinhangFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Chu JianFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Yu XiangFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Zhao FeiminFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Liu JianFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Wu XinyueFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Wu WeiFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Han ShuwenFifth School of Clinical Medicine of Zhejiang Chinese Medical University (Huzhou Central Hospital), Huzhou 313000, Zhejiang, China.
Zhejiang Chinese Medical University · CNHuzhou University · CNHuzhou Central Hospital · CNSecond Affiliated Hospital of Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGut microbes and age are both factors that influence the development of disease. The community structure of gut microbes is affected by age.

objectiveTo plot time-dependent gut microbe profiles in individuals over 45 years old and explore the correlation between age and gut microbes.

methodsFecal samples were collected from 510 healthy individuals over 45 years old. Shannon index, Simpson index, Ace index, etc. were used to analyze the diversity of gut microbes. The beta diversity analysis, including non-metric multidimensional scaling (NMDS), was used to analyze community distribution. Linear discriminant analysis (LDA) and random forest (RF) algorithm were used to analyze the differences of gut microbes. Trend analysis was used to plot the abundances of characteristic gut microbes in different ages.

resultsThe individuals aged 45-49 had the highest richness of gut bacteria. Fifteen characteristic gut microbes, including

conclusionsThe individuals in different ages have characteristic gut microbes. The changes in community structure of gut microbes may be related to age-induced diseases.

Indexed as

AgingFecesGastrointestinal MicrobiomeAgedAged, 80 and overAge FactorsBacteriaFemaleHumansMaleMiddle Agedagebioinformatics analysisfunctional genesgut microbesmetagenomic sequencing

Identifiers

PMID38613799
PMCPMC11087091
OpenAlexW4394579623

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.