Relationship Between Brown Adipose Tissue and Shivering in Cold‐Exposed Humans
Notice bibliographique
Résumé
Background An inverse relationship between brown adipose tissue (BAT) volume and shivering intensity has previously been reported in humans. Considering its small volume in adult humans, this inverse relationship may be explained by the regional distribution of BAT. It has been postulated that the paraspinal depot may be critical to heating the spinal cord to maintain neural conductivity under cold stimulation. However, this local heating may also suppress the drive to shiver, a phenomenon previously shown in guinea pigs. Objective The research objective was to determine whether the presence of paraspinal BAT can modulate the intensity and pattern of shivering in lean, healthy, adult humans. Hypothesis We propose that paraspinal BAT thermogenesis can supress shivering intensity and modulate the shivering pattern. Methodology The present data includes 23 young women who completed a 3h mild cold exposure protocol, using a liquid‐conditioned suit perfused with water at 18°C. During cold exposure, participants remained supine in a PET/CT scanner. An i.v. bolus of [ 11 C]‐acetate and [ 18 F]FDG were given sequentially, with each injection followed by a 30 min list‐mode dynamic PET acquisition to quantify depot‐specific BAT oxidative metabolism and glucose uptake, respectively. Finally, a whole‐body static PET acquisition was performed to quantify the total BAT volume and distribution. Surface electromyography (sEMG) was used to characterize shivering activity in 8 different muscles. Shivering intensity and shivering pattern were determined using custom‐designed EMG algorithms. In brief, the two distinct shivering patterns (continuous vs burst shivering) are distinguished according to differences in frequency of occurrence (4‐8 Hz for continuous vs. 0.1‐0.2 Hz for bursts) and intensity [2‐5% maximal voluntary contraction (MVC) for continuous vs. 7‐15% MVC for bursts]. Results Total BAT volume was estimated at 53 mL (95% CI: 34 to 72 mL) with paraspinal BAT volume accounting for 9% (95% CI: 5 to 13%) of total BAT. Mean shivering intensity under this cold stimulus was 3.0 % MVC (95% CI: 2.0 to 3.8 %). Shivering bursts occurred at a frequency of 2.8 bursts/min (95% CI: 2.3 to 3.2 bursts/min), eliciting a shivering intensity of 9.6 % MVC (95% CI: 5.9 to 13.3 % MVC), while the more continuous low‐intensity shivering was maintained at 3.0 % MVC (95% CI: 1.6 to 4.4% MVC). Pearson correlations revealed no associations between total BAT volume, shivering intensity or shivering pattern. Similarly, paraspinal BAT volume was not associated with any shivering outcomes. Conclusion The role of BAT in humans is still not clearly elucidated. Here we showed that in premenopausal women, neither total BAT volume nor paraspinal BAT are associated with shivering intensity or shivering pattern. Further studies are required to determine whether BAT plays a more regionalized role, unique to each depot, or more globally on whole‐body energy metabolism.
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 | 0,000 |
| 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 ».