Evidence map›Paper›PMID 39506977›Full record

ReviewProgress in biomedical engineering (Bristol, England)2024

Antibiofilm approaches as a new paradigm for treating infections.

Fany Reffuveille, Yasser Dghoughi, Marius Colin, Marcelo D T Torres, Cesar de la Fuente-Nunez

Abstract readReview
In one paragraph

Review in Progress in biomedical engineering (Bristol, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

5 authors.

Fany ReffuveilleUniversité de Reims Champagne-Ardenne, Biomatériaux et Inflammation en Site Osseux, BIOS EA 4691, SFR Cap Santé, 51097 Reims, France.ORCID 0000-0002-0753-3761
Yasser DghoughiUniversité de Reims Champagne-Ardenne, Biomatériaux et Inflammation en Site Osseux, BIOS EA 4691, SFR Cap Santé, 51097 Reims, France.
Marius ColinUniversité de Reims Champagne-Ardenne, Biomatériaux et Inflammation en Site Osseux, BIOS EA 4691, SFR Cap Santé, 51097 Reims, France.ORCID 0000-0002-9841-6711
Marcelo D T TorresMachine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.ORCID 0000-0002-6165-9138
Cesar de la Fuente-NunezMachine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.ORCID 0000-0002-2005-5629

Funding

Combining chemical and computational tools for predictive models of microbiome communitiesR35GM138201 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI DE LA FUENTE, CESAR · 2020 to 2024
$1.8M
Defense Threat Reduction Agency HDTRA11810041Defense Threat Reduction Agency HDTRA1-21-1-0014Defense Threat Reduction Agency HDTRA1-23-1-0001NIGMS NIH HHS R35 GM138201
6 · The paper itself

Abstract

The lack of effective antibiotics for drug-resistant infections has led the World Health Organization to declare antibiotic resistance a global priority. Most bacterial infections are caused by microbes growing in structured communities called biofilms. Bacteria growing in biofilms are less susceptible to antibiotics than their planktonic counterparts. Despite their significant clinical implications, bacterial biofilms have not received the attention they warrant, with no approved antibiotics specifically designed for their eradication. In this paper, we aim to shed light on recent advancements in antibiofilm strategies that offer compelling alternatives to traditional antibiotics. Additionally, we will briefly explore the potential synergy between computational approaches, including the emerging field of artificial intelligence, and the accelerated design and discovery of novel antibiofilm molecules in the years ahead.

Indexed as

Anti-Bacterial AgentsBacterial InfectionsBiofilmsArtificial IntelligenceBacteriaHumansAnti-Bacterial Agentsantibiofilm moleculesantibiofilm strategiesbiofilm modelscomputational approachesengineering approaches

Identifiers

PMID39506977
PMCPMC11540418

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.