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Enregistrement W1681568060

Prebiotic mechanisms, functions and applications - A review

2013· review· en· W1681568060 sur OpenAlex

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Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

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Notice bibliographique

RevueTNO Repository · 2013
Typereview
Langueen
DomaineNursing
ThématiqueMicrobial Metabolites in Food Biotechnology
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésPrebioticMicrobiomeComputational biologyBiologyHuman microbiomeImmune systemFunction (biology)ProbioticGut floraBiotechnologyBioinformaticsImmunologyGeneticsBacteria
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In October 2012, a group of scientists met at the 10th Meeting of the International Scientific Association of Probiotics and Prebiotics (ISAPP) in Cork, Ireland to discuss issues surrounding prebiotics and their development. This article summarises outputs from the meeting. Various prebiotic definitions were discussed and how the concept has evolved from targeting the colonic microbiome, through to the entire gastrointestinal tract and finally the ISAPP definition, which specifies fermentation as a key criterion. Structure and function relationships are becoming clearer with effects upon microbial diversity, determinations of selectivity and enhanced biological activity being major outcomes. Immune modulation and metal chelation were further facets. Biomass can be a useful, and economic, means of generating new prebiotics. Pectic oligomers from citrus are model examples. Testing aspects range from in vitro batch culture fermenters to multiple stage models, immobilized systems, animal, cellular studies and human trials. Analytical processes around microbiota characterization and functionality were compared. Human studies were seen as the definitive outcome, including 13C labeling of key interventions. For extra intestinal effects, atopic disease, respiratory infections, vaginal issues, oral disease, adiposity, liver damage and skin infections are all feasible. The general outcome was that microbiota modulation was the key mechanism that linked these interactions. In pet food applications, the market potential for prebiotics is huge. Health targets are similar to those of humans. Issues include monomeric composition, chain length, linkages, branching, microbiota beyond bifidobacteria, metabolic function, mechanisms of health effects. Molecular biology has unraveled some of the explanations for prebiotic influences e.g. gene clusters to show transporters, regulators, permeases, hydrolases, lacS. In Lactobacillus ruminis, fermentation studies have been aligned to genome annotations, showing an energy efficient and rapid transport of GOS. In bifidobacteria, functional genome analyses have demonstrated uptake of trisaccharides. Questions relating to patients were then raised. For example, are prebiotics related to disease treatment or health maintenance? If a prebiotic does not change the microbiota, then how does it operate? Case study trials in Inflammatory Bowel Disease were presented on patient access to prebiotics and information. These showed that their knowledge of prebiotics was poor, compared to probiotics. The group then discussed the next generation of prebiotics (e.g. anti-adhesive activities). The comparator was Human Milk Oligosaccharides, which both reduce adherence of pathogens and act as prebiotics. Studies with galactooligosacchardes (GOS) have used pyrosequencing to demonstrate varying species level effects. This has relevance for infant formulae. Prebiotic aspects of whole foods and their complexity was covered. Trials were described where cross feeding and co-metabolism had been investigated. Suggestions on other prebiotic influences, aside from bifidobacteria, were made and included metagenomics, metabonomics, gene expression, mRNA global sequencing, bile deconjugation, enzyme profiles, lipids, phenolics. The discussion suggested how prebiotics could move forward with a wider expansion of the concept, target populations, expanded microorganisms, health benefits, application of new technologies and improved consumer understanding being the main goals. Copyright © 2013 by New Century Health Publishers, LLC. Chemicals/CAS: pectin, 9000-69-5

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,959
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

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 Opus0,023
Tête enseignante GPT0,294
Écart entre enseignants0,271 · 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