Suppression of Niacin-induced Vasodilation with an Antagonist to Prostaglandin D2 Receptor Subtype 1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Niacin (nicotinic acid) reduces cardiovascular events in patients with dyslipidemia. However, symptoms associated with niacin-induced vasodilation (e.g., flushing) have limited its use. Laropiprant is a selective antagonist of the prostaglandin D2 receptor subtype 1 (DP1), which may mediate niacin-induced vasodilation. The aim of this proof-of-concept study was to evaluate the effects of laropiprant (vs placebo) on niacin-induced cutaneous vasodilation. Coadministration of laropiprant 30, 100, and 300 mg with extended-release (ER) niacin significantly lowered flushing symptom scores (by approximately 50% or more) and also significantly reduced malar skin blood flow measured by laser Doppler perfusion imaging. Laropiprant was effective after multiple doses in reducing symptoms of flushing and attenuating the increased malar skin blood flow induced by ER niacin. In conclusion, the DP1 receptor antagonist laropiprant was effective in suppressing both subjective and objective manifestations of niacin-induced vasodilation. Clinical Pharmacology & Therapeutics (2007) 81, 849–857. doi:10.1038/sj.clpt.6100180; published online 28 March 2007 TRIAL REGISTRATION: This study has been registered at clinicaltrials.gov on 9/19/2007 (NCT00533312).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it