Endpoints of drug discovery for menopausal vasomotor symptoms
Bibliographic record
Abstract
OBJECTIVE: Estrogen supplementation is considered a reliable therapeutic approach to symptoms of vasomotor dysregulation (hot flashes) associated with the menopausal transition and sex hormone deprivation. Implication of changes in central neurotransmission in the pathogenesis of hot flashes has prompted the off-label use of serotonergic and γ-aminobutyric acid-ergic drugs as a therapeutic alternative, claiming similarity of outcomes to those of estrogen treatment. METHODS: Using telemetric recordings in a rat model of estrogen deficit-induced vasomotor dysregulation, we compared the long- and short-term effects of estrogen supplementation and treatment with neuropharmaceuticals (venlafaxine, desvenlafaxine, fluoxetine, agomelatine, gabapentin) on endpoints of thermoregulation. RESULTS: Among the tested drugs, only fluoxetine was capable to emulate the restorative action of estradiol on the diurnal oscillations in skin temperature and control of heat dissipation. Unlike estradiol, several of the tested compounds produced marked transient decreases in skin temperature within the first 2 hours of application while being unable to restore physiological diurnal patterns of thermoregulation. CONCLUSIONS: Our findings suggest that in this animal model of impaired thermoregulation, neuropharmaceuticals may simulate therapeutic effects by eliciting immediate but transient hypothermia, which is not associated with the recovery of physiological control of heat dissipation. Therefore, short-term monitoring of drug actions in this disease model may considerably bias readouts of drug discovery for menopausal vasomotor symptoms.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".