Evidence map›Paper›PMID 41971320›Full record

ArticleFrontiers in microbiology2026

Intestinal microbiome gone native: gut microbiome shift and resistome diversity in first homecoming giant panda family.

Yuhang Wu, Linhua Deng, Xiangwang He, Dianyi Zhou, Shanshan Ling, Ming He, Qian Wang, Chengdong Wang, Minglei Wang, Honglin Wu and 3 more

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Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Yuhang Wu *Department of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China.
Linhua Deng *China Conservation and Research Centre for the Giant Panda, Chengdu, China.
Xiangwang He *Department of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China.
Dianyi ZhouDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China.
Shanshan LingChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Ming HeChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Qian WangChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Chengdong WangChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Minglei WangChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Honglin WuChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Linfeng LiSichuan Fire Research Institute of Ministry of Emergency Management, Chengdu, China.
Desheng LiChina Conservation and Research Centre for the Giant Panda, Chengdu, China.
Libing YunDepartment of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The world-famous giant pandas ( Methods: In this study, we have clarified the dynamic microbiome composition and snapshot of ARGs (resistome) of the first panda family returning from overseas. Fecal samples were gathered for high-throughput sequencing for both amplicon and metagenomics sequencing, which were collected on the first day of their quarantine (Admission stage) and 3 days after the quarantine (Release stage). Feces from two native captive pandas were used as controls. Results and discussion: The predominant

Indexed as

16S rRNAantibiotic resistant genesgiant pandasinternational travelmetagenomicsmicrobiome

Identifiers

PMID41971320
PMCPMC13062235

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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.