Adrenergic stimulation as a means to determine in vivo brown adipose tissue thermogenic capacity
Bibliographic record
Abstract
Determination of the capacity for adaptive nonshivering thermogenesis is of importance in a broad range of metabolic studies, including investigations of the effects of cold acclimation, preparation for and arousal from hibernation, diet-induced thermogenesis, and metabolic balance. Adaptive nonshivering thermogenesis is understood as being mediated through the activity of uncoupling-protein-1 (UCP1). Norepinephrine and the β3-adrenergic agonist CL-316,423 have long been used to assess the capacity for nonshivering thermogenesis in intact mammals. Here we examine whether in mice ( Mus musculus Linnaeus, 1758) the acclimation-induced thermogenic effect of the β3-adrenergic agent CL-316,243 underestimates true adrenergically (norepinephrine-)induced capacity for nonshivering thermogenesis, whether anesthesia partly masks true thermogenic capacity, and to what degree adrenergic responses are proportional to and dependent upon the presence of UCP1. All conditions yielded significant differences between cold- and thermoneutral-acclimated mice and between wild-type and uncoupling protein 1 knockout mice. The cold-acclimation-recruited thermogenesis elicited by CL-316,243 was not statistically significantly lower than that elicited by norepinephrine, and the level of cold acclimation-recruited adrenergically induced thermogenesis was not statistically significantly affected by anesthesia. The absence of UCP1 practically eliminated cold acclimation-recruited adrenergically induced thermogenesis. Cold acclimation-recruited adrenergically-induced thermogenesis is positively associated with UCP1 amount. Qualitatively and quantitatively comparable results are thus obtained irrespective of which adrenergic activator is used.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".