Evidence map›Paper›PMID 42746154›Full record

ArticleChina CDC weekly2026

Metagenomic Next-Generation Sequencing Analysis of Pathogens in Infected Wounds from Dog and Cat Bites - China, 2021-2025.

Lisong Huang, Lianfu Wang, Xudong Wang, Xiaojing Zhang, Xinyue Yu, Jinhong Yang, Wang Zhang, Jingxian Yang, Weijia Ji, Yun Cao and 4 more

Abstract read
In one paragraph

Article in China CDC weekly, 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

14 authors.

Lisong Huang *Aerospace Center Hospital, Beijing, China.
Lianfu Wang *Taikang Yanyuan Rehabilitation Hospital Beijing, Beijing, China.
Xudong Wang *Hunan Aerospace Hospital, Changsha City, Hunan Province, China.
Xiaojing ZhangWillingmed Technology Beijing Co., Ltd, Beijing, China.
Xinyue YuWillingmed Technology Beijing Co., Ltd, Beijing, China.
Jinhong YangAerospace Center Hospital, Beijing, China.
Wang ZhangAerospace Center Hospital, Beijing, China.
Jingxian YangAerospace Center Hospital, Beijing, China.
Weijia JiAerospace Center Hospital, Beijing, China.
Yun CaoAerospace Center Hospital, Beijing, China.
Yafeng ZhengWillingmed Technology Beijing Co., Ltd, Beijing, China.
Wei GaiWillingmed Technology Beijing Co., Ltd, Beijing, China.
Minghong JiangState Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.
Yonghui LiangAerospace Center Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known about this topic?: Dog and cat bites frequently develop polymicrobial wound infections requiring prompt and appropriate antimicrobial treatment. However, conventional culture-based methods often fail to identify all pathogens, particularly anaerobic and fastidious microorganisms. What is added by this report?: This study used metagenomic next-generation sequencing (mNGS) to analyze infected dog- and cat-bite wounds. Distinct microbial profiles were identified between dog and cat bites, and between domestic and stray animals. Anaerobes were predominant in both groups. What are the implications for public health practice?: These findings highlight the value of mNGS and support empirical antimicrobial strategies to improve infection management and reduce complications.

Indexed as

anaerobic bacteriacat bitedog bitemetagenomic next-generation sequencingwound infection

Identifiers

PMID42746154
PMCPMC13575574

What OpenQuestion holds

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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.