Notice bibliographique
Résumé
Around menopause, women experience several physiological changes including fat redistribution, and cognitive decline. These symptoms have been attributed to changes in the hormonal milieu that accompany menopause, specifically the loss of ovarian estradiol (E2). Ovariectomy (OVX) a standard rodent model of menopause, results in chronically low levels of E2. E2 supplementation reinstates cognition, and body composition to pre-OVX states in mice and rats. Post-menopausal E2 replacement in women has yielded mixed results for cognition and body weight. E2 replacement has also been linked to an increased risk of breast cancer. Thus, effective and safe treatments for post-menopause are currently lacking. Two years preceding menopause, the reproductive hormone, follicle-stimulating hormone (FSH), begins to rise. FSH and E2 levels are inversely related; as E2 levels fall, FSH rises. Chronically elevated FSH was recently implicated in post-menopausal bone loss, weight gain, and cognitive decline. It was suggested that blocking FSH action may represent a novel means to prevent or treat these conditions. Compelling experiments in favour of this hypothesis are, however, lacking. In Chapter 1, I review the literature linking E2 loss or elevated FSH to post-menopausal weight gain, and cognitive decline. In Chapter 2, I investigated FSH actions in fat. Specifically, I examined FSH effects on lipid accumulation and adipocyte gene expression in vitro, as well as the effects of ablating the FSH receptor (FSHR) in adipocytes in OVX mice. FSH treatment did not alter expression levels of adipogenesis or thermogenesis markers, nor did it affect lipid accumulation in white adipocytes differentiated from 3T3-L1 cells or from primary mouse pre-adipocytes. Though I successfully disrupted the FSHR gene (Fshr) in adipocytes using the Cre/lox recombination system, I did not observe changes in body weight or composition, or glucose metabolism in OVX mice on normal chow or high fat diet. Finally, using a newly developed FSHR-3xHA knockin mouse model, I detected FSHR protein expression in mouse ovaries, but not in adipose depots of female mice. Collectively, my results do not show FSH effects on adipogenesis in vitro and challenge the hypothesis that FSH acts through FSHR in adipocytes in vivo. In Chapter 3, I investigated the effects of FSH in the brain. First, I examined Fshr expression in mouse brains using RNAscope in situ hybridization, a highly sensitive assay for detecting mRNA with single transcript resolution. I detected low levels of Fshr in several brain regions. To determine whether these rare transcripts were translated into protein, I used our FSHR-3xHA knockin mouse model. I was unable to detect FSHR protein in these mice. In contrast, I detected another HA-tagged transmembrane protein, NPR2, in brains of HA-Npr2 mice, providing a critical methodological control in these experiments. In preliminary experiments, I assessed the ability of fluorescently labeled FSH to enter the brain following i.v. injection in mice. Thus far, I have been unable to detect FSH in the brain. Collectively, the data suggest that FSH is unlikely to act via its receptor in the brain to mediate its effects, if any.Taken together, my data do not support the hypotheses that FSH acts in adipocytes or the brain. These observations suggest that blocking FSH action will not represent an effective means to prevent or treat post-menopausal bone loss, weight redistribution, or cognitive decline.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».