Serotonin effect on deiodinating activity in the rat
Bibliographic record
Abstract
Serotonin (5-HT) and thyroid hormones are part of a complex system modulating eating behaviour and energy expenditure. 5-Deiodinase (5-D) converts the relatively inactive thyroxine (T4) to triiodothyronine (T3), and its activity is an indirect measure of T3 production in peripheral tissues, particularly in the brain, intrascapular brown adipose tissue (IBAT), heart, liver, and kidney. We evaluated the effect of 5-HT on 5'-D activity during basal conditions and after short (30 min) cold exposure (thyroid stimulating hormone stimulation test, TST). 5'-D activity was assessed in the liver, heart, brain, kidney, and IBAT. TST increases 5'-D activity in the brain, heart, and IBAT and decreases it in kidney, leaving it unchanged in the liver. 5-HT alone did not modify 5'-D activity in the organs under study but decreased it in the IBAT, heart, and brain when injected before the TST was administered. Our results confirm the important role of 5-HT in thermoregulation, given its peripheral site of action, in modulating heat production controlling intracellular T3 production. These effects are more evident when heat production is upregulated during cold exposure in organs containing type II 5'-D, such as the brain, heart, and IBAT, which are able to modify their function during conditions that alter energy balance. In conclusion, 5-HT may also act peripherally directly on the thyroid and organs containing type II 5'-D, thus controlling energy expenditure through heat production.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".