Evidence map›Paper›PMID 34456884›Full record

ArticleFrontiers in microbiology2021

Evaluation of Short-Chain Antimicrobial Peptides With Combined Antimicrobial and Anti-inflammatory Bioactivities for the Treatment of Zoonotic Skin Pathogens From Canines.

Qiyu Tang, Chunyi Yang, Weitian Li, Yuhang Zhang, Xinying Wang, Weixin Wang, Zhiling Ma, Di Zhang, Yipeng Jin, Degui Lin

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. The dynamic interplay betweenFrontiers in cellular and infection microbiology · 2026
    Review
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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

10 authors at 3 institutions in 2 countries.

Qiyu TangDepartment of Veterinary Clinical Science, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Chunyi YangDepartment of Veterinary Clinical Science, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Weitian LiLaboratory of Anatomy of Domestic Animals, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Yuhang ZhangKey Lab of Animal Epidemiology and Zoonosis of Ministry of Agriculture, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Xinying WangModern Animal Research Center, Nanjing University, Nanjing, China.
Weixin WangDepartment of Veterinary Clinical Science, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Zhiling MaResearch and Development Department, Artron BioResearch Inc., Vancouver, BC, Canada.
Di ZhangDepartment of Veterinary Clinical Science, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Yipeng JinDepartment of Veterinary Clinical Science, College of Veterinary Medicine, China Agricultural University, Beijing, China.
Degui LinDepartment of Veterinary Clinical Science, College of Veterinary Medicine, China Agricultural University, Beijing, China.
China Agricultural University · CNArtron Bioresearch (Canada) · CANanjing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incidence of zoonotic

Indexed as

anti-biofilmanti-inflammationantimicrobial peptideMicrosporum canismouse skin infection modelStaphylococcus pseudintermediussynergistic efficacy

Identifiers

PMID34456884
PMCPMC8386128
OpenAlexW3192013843

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.