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Enregistrement W4398165537 · doi:10.1152/physiol.2024.39.s1.1464

The effect of high intensity interval training on muscle contractile function 8 weeks following chemically-induced ovarian failure

2024· article· en· W4398165537 sur OpenAlexaff
Parastoo Mashouri, Avery Hinks, Benjamin E. Dalton, Luke D. Flewwelling, W. Glen Pyle, Arthur J. Cheng, Geoffrey A. Power

Notice bibliographique

RevuePhysiology · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueReproductive Biology and Fertility
Établissements canadiensYork UniversityUniversity of Guelph
Organismes subventionnairesnon disponible
Mots-clésHigh-intensity interval trainingInterval trainingIntensity (physics)Internal medicineEndocrinologyFunction (biology)CardiologyMedicineChemistryBiologyAndrologyCell biologyPhysics

Résumé

récupéré en direct d'OpenAlex

The negative effects of ovariectomy on muscle contractile function have been well-characterized, however, the effects of gradual ovarian failure (i.e., perimenopausal transition into late-stage menopause) on muscle function over the lifespan have received less attention. Furthermore, whether exercise training can mitigate changes in muscle contractile function associated with menopause is unclear. The objective of this study, using a chemically-induced ovarian failure mouse model (4-vinylcyclohexene diepoxide; VCD), was to investigate time-course changes in muscle contractility of sedentary controls and the potential of high intensity interval training to mitigate any deleterious effects of ovarian failure. Starting at 11wks old, mice were injected with 160mg/kg/day of VCD for 15 days. Twenty-eight (VCD-trained: n=10, VCD-sedentary: n=10, control: n=8) CD1 female mice were used in this study, with the VCD-trained group beginning training at the onset of ovarian failure for a total of 8 weeks. Contractile properties of the plantar flexors were assessed using an in-vivo set-up 8 weeks following the onset of ovarian failure. As well, a fatigue task (repeated maximal isometric contractions until torque decreased by 60%) was performed. Recovery was measured immediately after, and up to 10min following task termination. Upon completion of mechanical testing, mice were sacrificed and intact muscle fibres were isolated from the flexor digitorum brevis, and myoplasmic free Ca 2+ (tetanic [Ca 2+ ] i ) concentrations were measured across stimulation frequencies of 10-200 Hz and throughout 50 tetanic contractions (70Hz) to replicate our fatigue task. There was no difference in pre-fatigue values across groups for peak twitch torque, peak 100Hz torque, RTD, 10:100Hz torque, tetanic [Ca 2+ ] i during low (10Hz) and high Hz (100Hz) stimulation, and all were reduced similarly immediately following the fatigue task. Repetitions to task failure was similar across groups and tetanic [Ca 2+ ] i during repetitive contractions (n=50) was reduced similarly across groups. As well, all groups recovered similarly across these measures. Torque and RTD did not recover fully by 10min for either measure, while 10Hz, 100Hz and 10:100Hz tetanic [Ca 2+ ] i was recovered immediately following the fatigue task. Given 10Hz torque was relatively maintained following the fatigue task, and there was a ~40% decline in 100Hz torque, the 10:100Hz ratio increased throughout recovery — this, combined with the [Ca 2+ ] data indicate that calcium sensitivity and release are unlikely contributors to impaired force production following the fatigue task across groups. The present study aimed to assess the impact of training on muscle contractility using a mouse model of gradual ovarian failure. Unlike other models of ovarian failure, there does not seem to be any impairment in muscular performance at the joint level in our VCD-mice, and they responded similarly across groups in response to repetitive fatiguing contractions and exercise training. Supported by NSERC. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,766
Score d'incertitude au seuil0,321

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
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 recherche0,0000,001
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 Opus0,018
Tête enseignante GPT0,274
Écart entre enseignants0,256 · 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'étudeExpérimental (laboratoire)
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
Publié2024
Routes d'admission1
Résumé présentoui

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