TRPM8 thermosensation in ectotherms mediates both skin colour and locomotor performance responses to cold temperature
Bibliographic record
Abstract
Thermoregulation is a homeostatic process to maintain an organism’s internal temperature within a physiological range compatible with life. In ectotherms, body temperature fluctuates with that of the environment, with both physiological and behavioral responses employed to modify body temperature. Changing skin colour/reflectance and locomotor activity are both well-recognized temperature regulatory mechanisms, but little is known of the participating thermosensor/s. We find that Xenopus laevis tadpoles put in the cold exhibit a temperature-dependent and rapid melanosome aggregation in melanophores, which lightens the skin. To identify the cold-sensor, we focused on transient receptor potential (trp) channel genes from group 1 (TRPA, TRPM, TRPV and TRPC families). Of particular interest were TRPM family members, known as cold sensors. mRNAs for several TRPMs are present in Xenopus tails, and TRPM8 protein is present in skin melanophores. Temperature-induced melanosome aggregation is mimicked by the Trpm8 agonist menthol (WS12) and blocked by the Trpm8 antagonist PF05105679. The degree of skin lightening induced by cooling or the WS12 TRPM8 agonist correlates with the extent of alterations in locomotor performance. We propose that TRPM8 serves as a cool thermosensor in ectotherms that helps coordinate skin lightening and behavioural locomotor performance as adaptive thermoregulatory responses to cold.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.024 |
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".