Evidence map›Paper›PMID 38136728›Full record

ReviewAntibiotics (Basel, Switzerland)2023

Antibiotic Resistance: Do We Need Only Cutting-Edge Methods, or Can New Visions Such as One Health Be More Useful for Learning from Nature?

Maria Vitale

Open access · goldAbstract readReview
In one paragraph

Review in Antibiotics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Maria VitaleGenetics of Microorganisms Laboratory, Molecular Biology Department, Istituto Zooprofilattico Sperimentale della Sicilia "A. Mirri", 90129 Palermo, Italy.ORCID 0000-0003-2084-2718
Istituto Zooprofilattico Sperimentale Della Sicilia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance is an increasing global problem for public health, and focusing on biofilms has provided further insights into resistance evolution in bacteria. Resistance is innate in many bacterial species, and many antibiotics are derived from natural molecules of soil microorganisms. Is it possible that nature can help control AMR diffusion? In this review, an analysis of resistance mechanisms is summarized, and an excursus of the different approaches to challenging resistance spread based on natural processes is presented as "lessons from Nature". On the "host side", immunotherapy strategies for bacterial infections have a long history before antibiotics, but continuous new inputs through biotechnology advances are enlarging their applications, efficacy, and safety. Antimicrobial peptides and monoclonal antibodies are considered for controlling antibiotic resistance. Understanding the biology of natural predators is providing new, effective, and safe ways to combat resistant bacteria. As natural enemies, bacteriophages were used to treat severe infections before the discovery of antibiotics, marginalized during the antibiotic era, and revitalized upon the diffusion of multi-resistance. Finally, sociopolitical aspects such as education, global action, and climate change are also considered as important tools for tackling antibiotic resistance from the One Health perspective.

Indexed as

antibiotic resistanceantimicrobial peptidesbacterial predatorsbiofilm and quorum sensingclimate changeeducational and socio-political aspectsmonoclonal antibodiesOne Health perspectivephage therapysepsis

Identifiers

PMID38136728
PMCPMC10740918
OpenAlexW4389286780

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.