ATP‐sensitive potassium channels mediate the thermosensory response of orexin neurons
Bibliographic record
Abstract
Key points High body temperature accompanies sleepiness, and loss of appetite and motivation. Suppression of orexin neurons has been suggested to be involved in such behavioural responses. In this study we determined that orexin neurons are inhibited by an increase in temperature itself. The effect of warming is mediated by a novel temperature sensing mechanism involving ATP‐sensitive potassium (KATP) channels. As KATP channels are also sensitive to energy balance, our results suggest that orexin neurons play an important role in regulating energy balance by inducing sickness behaviour when body temperature is elevated. Abstract High body temperatures are generally associated with somnolence, lethargy, hypophagia and anhedonia. Orexin neurons have been suggested to play a role in such sickness behaviours due to their known functions in appetite, behavioural and autonomic activation. Furthermore, the activity of orexin neurons is inhibited by lipopolysaccharide that induces fever. However, the cellular mechanism(s) underlying this suppression of orexin neurons was unknown. We used patch‐clamp recordings in acute rat brain slices to demonstrate that orexin neurons, including those projecting to the wake‐promoting locus coeruleus, are inhibited by increasing the ambient temperature by a 2–4°C increment between 26 and 40°C. This effect was not mediated by conventional thermosensing mechanisms but instead involved the activation of ATP‐sensitive potassium (KATP) channels. Since KATP channels can also sense energy substrate levels and cellular metabolism, our results suggest that orexin neurons can integrate the state of energy balance and body temperature, and adjust their output accordingly. Thus, the thermosensitivity of orexin neurons may be an important part of maintaining energy homeostasis during hyperthermia and fever.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
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".