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Enregistrement W4321456855 · doi:10.3389/fvets.2023.1149010

Editorial: Antimicrobial use, antimicrobial resistance, and the microbiome in animals, volume II

2023· editorial· en· W4321456855 sur OpenAlexafffundabout
Moussa S. Darria, Xin Zhao, Patrick Butaye

Notice bibliographique

RevueFrontiers in Veterinary Science · 2023
Typeeditorial
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGut microbiota and health
Établissements canadiensMcGill UniversityAgriculture and Agri-Food Canada
Organismes subventionnairesAgriculture and Agri-Food Canada
Mots-clésAntimicrobialMicrobiomeAntibiotic resistanceVeterinary medicineMicrobiologyMedicineBiologyAntibioticsBioinformatics

Résumé

récupéré en direct d'OpenAlex

As demonstrated by the COVID-19 pandemic, endemic diseases or epidemic outbreaks represent a significant financial risk to the society. In veterinary medicine, these include also loss of animals, reduction of productivity and market access. Antimicrobials contribute to the treatment and prevention of infectious diseases in both animals and humans while improving farm animals' productivity and welfare. However, antimicrobial resistance (AMR) is becoming an important and growing economic and social problem inducing annual costs estimated at US$1 trillion to US$3.4 trillion worldwide (Ahmad et al., 2019;WHO, 2017), and is regarded as the silent pandemic. Even though AMR, a global threat to humans, animals, and the environment, is complex, wide use of antibiotics has been linked to the emergence and spread of AMR in all ecosystems (One Health). This Research Topic presents 12 studies on antimicrobial use (AMU) and AMR as well as on antimicrobial impacts on the microbiota and epidemiology, dissemination-transmission and the surveillance of AMR.It is well known that AMR is selected mainly by antibiotic/antimicrobial use (AMU). In conventional production, antibiotics (although "antibiotics" and "antimicrobials" are sometimes used interchangeably, antibiotics are actually a subset of antimicrobials) have been used to prevent infectious diseases. However, this practice is discontinued in more and more countries due to restrictions of antibiotic use. Antibiotics as feed additives to promote growth and eventually prevent diseases in healthy production animals has been banned by the European Union in 2006. In 2018, the European Parliament approved new restrictions on the use of antimicrobials in healthy livestock. The Government of Canada (and also many other countries) has developed a Federal Framework and This is a provisional file, not the final typeset article Optimization of therapeutic doses by a better knowledge of the pharmacokinetic/pharmacodynamic (PK/PD) could reduced the burden on AMR of therapeutic use of antimicrobials. . This concept has been presented for danofloxacin in pigs by Zhou et al.The microbiota play critical roles in the gut and establish general health in the animal by maintaining/improving organ integrity and functions, provision and absorptions of nutrients, and protecting against pathogens including promoting immunity. A well-established microbiota, plays particularly in youth age an important role in the animal. Feed additives including alternative to antibiotics received attention since the ban or restriction of in-feed antibiotics as growth promoters.Few studies have investigated the effects of antimicrobials on animal's metabolism, physiology and Editorial: Antimicrobial Use, Antimicrobial Resistance, and the Microbiome in Animals Volume II This is a provisional file, not the final typeset article immunity. In the contrast, several studies reported their effects on microbiota and microbiome.However, many other factors such as genetic (line), physiological status, sex (male, female), health (clinical and sub-clinical) and housing/husbandry influence the microbiota. Microbes respond to antimicrobials by developing and acquiring resistance mechanisms, change gene expression pater which alter their metabolism, nutrients uptake and transport (Brown et al., 2017). The elimination and reduction of multiplication bacteria by the antibiotics result in changes of the bacterial community structure and diversity.In this Research Topic, the analysis of the fecal microbiota in healthy, diarrheal and treated weaned piglets showed differences between these three animal groups (Kong et al. It is important to intensify research to understand circumstances leading to the emergence of pathogenic bacteria and of antibiotic resistance. In animal production industries, better practices in respect to food and environmental safety as well as public and animal health and welfare still need to be developed. Microorganisms living in changing environmental conditions adapt and evolve.Bacterial resistance determinants can be spread through horizontal gene transfer (HGT) which could This is a provisional file, not the final typeset article be in function of the temperature (Burnham 2021). Therefore, climate change and AMR are interlinked, and both should be addressed to protect humans, animals and the environment."One Health" approaches, using "omics" and well structured surveillance under government control, Antimicrobial resistance is a "One Health" issue because AMR genes can be spread across humans, animals and the environment. Surveillance, whole genome sequencing, microbiota/microbiome and antibiotic stewardship research are needed to determine important ARM drivers. Identification of hot spots and the ability to predict phenotype and transmission pathways along with adoption of best AMU practices will contribute to mitigate AMR. New knowledge contributing to the improvement of animal health and production as well as studies providing science-based evidences on AMR transmission Editorial: Antimicrobial Use, Antimicrobial Resistance, and the Microbiome in Animals Volume II This is a provisional file, not the final typeset article through the food chain and the environment are needed. Due to the high load of ARGs in animal manure and their potential spread to the environment when manures are used as soil fertilizers, the effects of different treatments of raw manures, such as composting (thermophilic composting and vermicomposting) and anaerobic digestion should be investigated.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,106

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,017
Méta-épidémiologie (sens strict)0,0050,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0040,002
Études des sciences et des technologies0,0020,002
Communication savante0,0080,006
Science ouverte0,0040,002
Intégrité de la recherche0,0110,012
Charge utile insuffisante (le modèle a refusé de juger)0,0320,020

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,257
Écart entre enseignants0,248 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission3
Résumé présentoui

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