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Enregistrement W2989815900 · doi:10.1071/rdv32n2ab200

200 Maturation method affects lipid accumulation in bovine oocytes

2019· article· en· W2989815900 sur OpenAlexaff
Otávio Augusto Costa de Faria, T. S. Kawamoto, Luzia Renata Oliveira Dias, Andrei Antonioni Guedes Fidelis, L. O. Leme, José Felipe Warmling Sprícigo, Margot Alves Nunes Dode

Notice bibliographique

RevueReproduction Fertility and Development · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueReproductive Biology and Fertility
Établissements canadiensUniversity of Guelph
Organismes subventionnairesnon disponible
Mots-clésOocyteOvulationAndrologyIn vitro maturationEmbryoIn vivoBiologyFollicleIn vitroEmbryo transferFolliculogenesisChemistryCryopreservationEndocrinologyCell biologyBiochemistryBiotechnologyMedicineHormone

Résumé

récupéré en direct d'OpenAlex

In vitro maturation is a key step in in vitro embryo production, since its success will depend on the availability of good quality oocytes. Previous studies have shown that it is during this stage that the greatest accumulation of lipid droplets occurs, which is reflected in the amount of lipid present in embryos produced in vitro. However, this is not observed when maturation is performed in vivo. Therefore, we hypothesised that lipid accumulation would be avoided if oocyte maturation were carried out in ovarian follicles following intrafollicular transfer of immature oocytes (IFIOT). We compared lipid accumulation in oocytes matured in vitro, in vivo, and by IFIOT. A total of 90 Nellore heifers were distributed in 3 experimental groups: donors of immature oocytes (D-IMA), ovulators of IFIOT oocytes (D-OV), and superstimulated donors of in vivo-matured oocytes (D-FSH). All animals rotated through all groups during the experiment. To obtain immature oocytes, the D-IMA were submitted to ovum pickup (OPU), in which aspiration medium was supplemented with 500 μM 3-isobutyl-1-methylxanthine (IBMX), and, after selection, part of the oocytes were cultured in vitro for 22 h (MatF) and part were used for IFIOT (MatT). To perform MatT, the D-OV had their ovulation synchronized by a progesterone and benzoate oestradiol protocol, in which 30 h after the implant removal, the IFIOT was performed on the dominant follicle. The D-FSH oocytes were stimulated with 80 mg of FSH (Folltropin; Vetoquinol) over 4 days, every 12 h, in decreasing doses. At the same time that the immature oocytes were placed in MatF and IFIOT, ovulation was induced with the gonadotrophin releasing hormone (GnRH) analogue (50 µg of lecirelin) in D-OV and D-FSH groups. After 22 h, matured oocytes were either removed from culture (MatF) or recovered from follicles by OPU (MatT and MatS). From the recovered oocytes of all groups, only those with a polar body were used for lipid droplet evaluation. To quantify lipid accumulation, denuded oocytes were fixed and stained with boron-dipyrromethene (Bodipy) 493/503 (20 µg mL−1) and evaluated by confocal microscopy. Captured images were evaluated in the ImageJ program (National Institutes of Health), and lipid content was determined by calculating the ratio of the area of the lipid droplets to total oocyte area. Data were analysed by ANOVA with statistical significance set at P < 0.05. A total of 95 oocytes were evaluated: 25 immature (CT), 24 in vitro (MatF), 30 in vivo (MatS), and 16 in vivo (MatT). The mean area containing lipid droplets in immature oocytes (14% ± 0.9) was similar (P > 0.05) to that observed in both in vivo maturation systems (MatS = 17.26% ± 0.8 and MatT = 14.11% ± 0.9). However, in the MatF oocytes, lipid content (24.34% ± 1) increased during maturation and was higher than in the other groups (P < 0.05). We showed for the first time that oocytes matured by IFIOT are similar to those in vivo matured with regard to lipid content, which may imply their superior quality over those matured in vitro. This new maturation method opens new possibilities for biotechnologies that need to use mature oocytes, such in vitro embryo production, oocyte and embryo cryopreservation, cloning, and transgenesis. This study was supported by FAP-DF and Capes.

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)0,002
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,118
Score d'incertitude au seuil0,547

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
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 Opus0,042
Tête enseignante GPT0,329
Écart entre enseignants0,288 · 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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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