Evidence map›Paper›PMID 39203524›Full record

ArticleMicroorganisms2024

Antimicrobial Peptide Identified via Machine Learning Presents Both Potent Antibacterial Properties and Low Toxicity toward Human Cells.

Qifei Wang, Junlin Yang, Malcolm Xing, Bingyun Li

Abstract read
In one paragraph

Article in Microorganisms, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

4 authors.

Qifei WangDepartment of Orthopaedics, School of Medicine, West Virginia University, Morgantown, WV 26506, USA.
Junlin YangSpine Center, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200082, China.ORCID 0000-0001-9809-1219
Malcolm XingDepartment of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T2N2, Canada.
Bingyun LiDepartment of Orthopaedics, School of Medicine, West Virginia University, Morgantown, WV 26506, USA.ORCID 0000-0002-5766-5666

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preventing infection is a critical clinical challenge; however, the extensive use of antibiotics has resulted in remarkably increased antibiotic resistance. A variety of antibiotic alternatives including antimicrobial peptides (AMPs) have been studied. Unfortunately, like most conventional antibiotics, most current AMPs have shown significantly high toxicity toward the host, and therefore induce compromised host responses that may lead to negative clinical outcomes such as delayed wound healing. In this study, one of the AMPs with a short length of nine amino acids was first identified via machine learning to present potentially low cytotoxicity, and then synthesized and validated in vitro against both bacteria and mammalian cells. It was found that this short AMP presented strong and fast-acting antimicrobial properties against bacteria like

Indexed as

antimicrobial peptidecytotoxicityinfectionorthopedicviability

Identifiers

PMID39203524
PMCPMC11356914

What OpenQuestion holds

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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.