Impacts of Non- and Whole-fat Milk Supplementation on Metabolism-Associated Fatty Liver Disease (MAFLD) in C57BL/6 Mice
Notice bibliographique
Résumé
Background: Metabolism-associated fatty liver disease (MAFLD) is a widespread metabolic disease affecting 25% of the global adult population following Westernized lifestyles. Lifestyle modifications, specifically adherence to healthy dietary patterns, are pivotal in preventing and mitigating this disease. Consuming milk and dairy products is considered a cornerstone of a healthy dietary pattern, gathering significant attention due to compelling evidence from observational studies. These studies suggest that a higher intake of milk and certain dairy products is associated with a reduced risk of MAFLD. However, the relative health benefits of high- compared to lower-fat milk is a current topic of interest, with ongoing debates about their equivalency in promoting metabolic health. Aims & Hypothesis: In a MAFLD mouse model, we aim to determine the dependence of milk’s fat content on hepatic steatosis and lipid metabolic pathways by comparing whole- (WFM) to non-fat (NFM) milk supplementation in high-fat diet-fed mice (HFD). We hypothesize that both WFM and NFM will significantly improve HFD-induced hepatic lipid accumulation but via differential molecular mechanisms. Methods: Two cohorts of n=24 and n=36 6-week-old male C57BL/6 mice were acclimatized for one week, then randomly assigned to a HFD (45 kcal% fat) or a low-fat diet (LFD; 10 kcal% fat) control group. The HFD mice were randomized to either a WFM or NFM treatment of 0.425 mL milk for 8 weeks. At the end of the study, mice underwent an insulin tolerance and pyruvate tolerance test and body composition was measured. The animals were then euthanized, tissues were collected, and hepatic lipid metabolism was compared using western blot, histology, hepatic lipid assays, gas chromatography, and qPCR. Statistics were then completed using GraphPad Prism software 7.0, utilizing T-test, one-way ANOVA, and Tukey’s post-hoc tests with a p-value ≤ 0.05 considered as statistically significant. Results: Body weight gain was significantly reduced in NFM groups compared to HFD and WFM, accounted for by a significant reduction in fat mass. ITT was unaltered when corrected to baseline, but NFM groups had significantly higher PTT values when corrected to baseline. Overnight-fasted blood glucose was significantly reduced in NFM animals compared to WFM animals, suggesting an altered metabolic state between the two treatment groups. Histological results indicate a significant reduction in lipid accumulation by the NFM group compared to the HFD group (p<0.05), with WFM trending towards a similar reduction (p=0.051). Hepatic triglyceride concentrations were significantly reduced in NFM animals compared to WFM and HFD animals, suggesting a greater effect of NFM in reducing hepatic steatosis. Hepatic molecular results display an enhancement of enzymes involved in fatty acid oxidation and export pathways in the NFM group. In contrast, WFM displays an enhancement of de novo lipogenesis, fatty acid uptake, and fatty acid oxidation. Conclusion: The findings suggest that NFM may be more effective at reducing hepatic steatosis through enhanced fatty acid oxidation and export. WFM may reduce steatosis less effectively because of counteractive effects on fatty acid uptake and de novo lipogenesis versus beta-oxidation. These results provide mechanistic evidence of the protective effects of milk on MAFLD. The funding sources for this project include the Alberta Diabetes Institute Studentship Grant, CIHR Canadian Graduate Studentship, and Dairy Farmers of Canada. 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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».