Modelling sex-specific whole-body metabolic responses to feeding and fasting
Notice bibliographique
Résumé
Abstract Men exhibit a preference for carbohydrate metabolism, whereas women tend to favor lipid metabolism. Significant sex-based differences in energy oxidation are evident across various metabolic states, including fasting and feeding. While some of these differences can be attributed to variations in body composition—such as increased fat mass in women and higher muscle mass in men—there are also inherent disparities in metabolic fluxes. For instance, women exhibit increased rates of lipolysis independent of body composition. However, there remain gaps in our understanding of how sex influences the metabolism of specific organs and how these differences manifest at the systemic level. To address some of these gaps, we developed a sex-specific, whole-body, multi-scale model of metabolism during feeding and fasting. Our model represents healthy young adults (male and female) and integrates cellular metabolism in organs with whole-body responses following various mixed meals, particularly high-carbohydrate and high-fat meals. We explored sex-related variations in metabolic responses during both the absorptive and postabsorptive phases following meals. Our model predicted that sex-related metabolic differences observed at the systemic level are driven by variations in nutrient storage and oxidation patterns in the liver, skeletal muscle, and adipose tissue. We hypothesized that sex differences in hepatic glucose output during short-term fasts are partly influenced by variations in free fatty acids, glycerol, and glycogen handling. We also identified a candidate mechanism, possibly more prevalent in the female liver, where lipids are redirected toward carbohydrate metabolism to support hepatic glucose production. Integrating sex-specific data and parameters into multi-scale frameworks holds promise for enhancing our understanding of human metabolism and its modulation by sex. Author summary Men and women exhibit different metabolic preferences, with men favoring carbohydrate metabolism and women favoring lipid metabolism. These differences impact energy usage during fasting and feeding, influenced by body composition and inherent metabolic variations. However, there remain gaps in our understanding of how sex influences the metabolism of specific organs and how these differences manifest at the systemic level. To address these gaps, we developed a sex-specific whole-body metabolic model, representing healthy young adults. Our model explores how men and women metabolize mixed meals, especially high-carbohydrate and high-fat meals. We found that sex-related metabolic variations arise from differences in nutrient storage and utilization in key organs like the liver, muscles, and fat tissue. We propose that variations in free fatty acids and glycogen handling contribute to differences in hepatic glucose output between men and women during short-term fasting. Integrating sex-specific data into metabolic models can enhance our understanding of human metabolism and its modulation by sex.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».