Neurobiological and immunogenetic aspects of narcolepsy: Implications for pharmacotherapy
Bibliographic record
Abstract
Excessive daytime sleepiness (EDS) and cataplexy are common symptoms of narcolepsy, a sleep disorder associated with the loss of hypocretin/orexin (Hcrt) neurons. Although only a few drugs have received regulatory approval for narcolepsy to date, treatment involves diverse medications that affect multiple biochemical targets and neural circuits. Clinical trials have demonstrated efficacy for the following classes of drugs as narcolepsy treatments: alerting medications (amphetamine, methylphenidate, modafinil/armodafinil, solriamfetol [JZP-110]), antidepressants (tricyclic antidepressants, selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors), sodium oxybate, and the H3-receptor inverse agonist/antagonist pitolisant. Enhanced catecholamine availability and regulation of locus coeruleus (LC) norepinephrine (NE) neuron activity is likely central to the therapeutic activity of most of these compounds. LC NE neurons are integral to sleep/wake regulation and muscle tone; reduced excitatory input to the LC due to compromise of Hcrt/orexin neurons (likely due to autoimmune factors) results in LC NE dysregulation and contributes to narcolepsy/cataplexy symptoms. Agents that increase catecholamines and/or LC activity may mitigate EDS and cataplexy by elevating NE regulation of GABAergic inputs from the amygdala. Consequently, novel medications and treatment strategies aimed at preserving and/or modulating Hcrt/orexin–LC circuit integrity are warranted in narcolepsy/cataplexy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".