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Enregistrement W2885039808 · doi:10.3168/jds.2017-14115

Exposure to an unpredictable and competitive social environment affects behavior and health of transition dairy cows

2018· article· en· W2885039808 sur OpenAlexafffund
Kathryn L. Proudfoot, Daniel M. Weary, S.J. LeBlanc, L.K. Mamedova, M.A.G. von Keyserlingk

Notice bibliographique

RevueJournal of Dairy Science · 2018
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueReproductive Physiology in Livestock
Établissements canadiensUniversity of GuelphUniversity of British Columbia
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaNovus InternationalZoetisDairy Farmers of Canada
Mots-clésIce calvingAnimal scienceMorningDairy cattleBiologyLactationPregnancy

Résumé

récupéré en direct d'OpenAlex

Social factors are important determinants of disease in humans and and laboratory animals, but less research has been done using farm animals. The objective of this study was to determine if an unpredictable and competitive social environment affects behavior and health during the transition period when dairy cows are at high risk of disease. Five weeks before calving, 64 cows were assigned to a predictable and noncompetitive social environment (predictable) or an unpredictable and competitive social environment (unpredictable) using 8 groups of 4 animals per treatment. Each group consisted of 3 multiparous and 1 primiparous cow. At first enrollment (baseline; 5 wk before calving), all groups had access to 4 electronic feed bins. At 4 wk before calving, cows in the predictable groups were given access to 6 feed bins, and cows in the unpredictable groups were moved into a new pen with 4 resident cows each trained to consume feed from one bin. Each cow in the unpredictable group was then provided access to only 1 of the 4 feed bins which they shared with 1 resident cow (resulting in 2 cows/bin), creating a competitive feeding environment. To create an unpredictable environment, access to morning feed was delayed 0, 1, 2, or 3 h every other day. On alternate days, the cows in unpredictable groups were assigned to feed from a new feed bin (and thus had to compete with a new resident partner). Feeding and social behavior were collected electronically from the feed bins. Blood was sampled at baseline (wk -5), wk -2, wk -1, and wk +1 relative to calving to measure inflammatory (haptoglobin and tumor necrosis factor-α) and metabolic (nonesterified fatty acids, β-hydroxybutyrate, calcium, and glucose) biomarkers. Uterine cytology was performed 3 to 5 wk after calving to diagnose cytological endometritis. Data were analyzed using mixed models including baseline data as a covariate, week as a repeated measure, treatment as a main effect, and a treatment by week interaction. The probability of cytological endometritis at the group level was analyzed using Mann-Whitney U tests. Parity was included in separate models to determine any parity × treatment interactions. Cows from both treatments consumed the same amount of feed, but cows in the unpredictable group spent less time feeding and had a higher rate of feed intake. Cows in the unpredictable groups also visited the feed bins less often, consumed more feed during each visit, and were involved in more social replacements at the feed bin compared with predictable groups. Cows in the unpredictable groups had higher serum concentrations of nonesterified fatty acids and tumor necrosis factor-α, but lower β-hydroxybutyrate compared with predictable groups. Multiparous cows in unpredictable groups were more likely to be diagnosed with cytological endometritis after calving compared with cows in the predictable groups, but primiparous cows in unpredictable groups showed a tendency for the opposite response. These results suggest that an unpredictable and competitive social environment before calving causes changes in feeding and social behavior, some physiological indicators of metabolism and inflammation, and increases the risk of uterine disease in multiparous cows after calving.

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 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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,973
Score d'incertitude au seuil0,365

Scores Codex et Gemma par catégorie

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

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 Opus0,026
Tête enseignante GPT0,271
Écart entre enseignants0,245 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations31
Publié2018
Routes d'admission2
Résumé présentoui

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