Local network regulation of orexin neurons in the lateral hypothalamus
Bibliographic record
Abstract
Obesity and inadequate sleep are among the most common causes of health problems in modern society. Thus, the discovery that orexin (hypocretin) neurons play a pivotal role in sleep/wake regulation, energy balance, and consummatory behaviors has sparked immense interest in understanding the regulatory mechanisms of these neurons. The local network consisting of neurons and astrocytes within the lateral hypothalamus and perifornical area (LH/PFA), where orexin neurons reside, shapes the output of orexin neurons and the LH/PFA. Orexin neurons not only send projections to remote brain areas but also contribute to the local network where they release multiple neurotransmitters to modulate its activity. These neurotransmitters have opposing actions, whose balance is determined by the amount released and postsynaptic receptor desensitization. Modulation and negative feedback regulation of excitatory glutamatergic inputs as well as release of astrocyte-derived factors, such as lactate and ATP, can also affect the excitability of orexin neurons. Furthermore, distinct populations of LH/PFA neurons express neurotransmitters with known electrophysiological actions on orexin neurons, such as melanin-concentrating hormone, corticotropin-releasing factor, thyrotropin-releasing hormone, neurotensin, and GABA. These LH/PFA-specific mechanisms may be important for fine tuning the firing activity of orexin neurons to maintain optimal levels of prolonged output to sustain wakefulness and stimulate consummatory behaviors. Building on these exciting findings should shed further light onto the cellular mechanisms of energy balance and sleep-wake regulation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".