0144 ACTIVATION OF GLUTAMATE CELLS IN THE SUBCOERLEUS NUCLEUS TRIGGERS CATAPLEXY-LIKE ATTACKS IN WILD-TYPE MICE
Bibliographic record
Abstract
Cataplexy is characterized by the sudden uncontrollable loss in skeletal muscle tone during wakefulness and is hypothesized to be triggered by the same brainstem circuits that generate REM sleep. Recently, we determined that glutamate neurons in the subcoeruleus nucleus (SubC) are an important neural substrate for controlling REM sleep. Here, we aimed to determine if optogenetic activation of glutamate neurons in the SubC could produce cataplexy in wild-type mice. To manipulate glutamate neurons of the SubC we bilaterally infused 200nL of an adeno-associated viral vector (AAV) containing a stabilized step-function opsin (AAV-EF1a-DIO-hChR2(C128S/D156A)-mCherry) into the SubC of mice expressing cre-recombinase in glutamate cells (vglut-cre). Animals were instrumented with EEG and EMG electrodes in order to monitor sleep-wake behaviors. SubC neurons were stimulated with brief pulses of blue light (50ms) applied every 10s for 1 hour, after which a single pulse of green light (50ms) was applied to terminate neuronal activation. Only animals with opsin expression and optic fibres targeted to the SubC were used for analysis. Under baseline conditions mice exhibited typical amounts of wake, non-REM and REM sleep and showed no evidence of cataplexy. However, activation of glutamate cells in the SubC triggered repeated behavioural arrests that strongly resembled cataplexy attacks in narcoleptic mice. During the 1-hour stimulation period mice experienced 42 ± 4 (n=2) cataplexy-like attacks that were 65 ± 5s in length. However, cataplexy-like attacks disappeared, and normal sleep-wake behaviours resumed, after SubC stimulation was optically terminated. Our results suggest that glutamate cells in the SubC are a potential neural substrate for triggering muscle paralysis during 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".