Bibliographic record
Abstract
High-density lipoproteins are involved in reverse cholesterol transport and possess anti-inflammatory and antioxidative properties. Paradoxically, CETP (cholesteryl ester transfer protein) inhibitors have been shown to increase inflammation as revealed by a raised plasma level of high-sensitivity C-reactive protein. CETP inhibitors did not improve clinical outcomes in large-scale clinical trials of unselected patients with coronary disease. Dalcetrapib is a CETP modulator for which effects on cardiovascular outcomes were demonstrated in the dal-OUTCOMES trial to be influenced by correlated polymorphisms in the ADCY9 (adenylate cyclase type 9) gene ( P =2.4×10 −8 for rs1967309). Patients with the AA genotype at rs1967309 had a relative reduction of 39% in the risk of presenting a cardiovascular event when treated with dalcetrapib compared with placebo (95% confidence interval, 0.41–0.92). In contrast, patients with the GG genotype had a 27% increase in risk, whereas heterozygotes (AG) presented a neutral result. Supporting evidence from the dal-PLAQUE-2 study using carotid ultrasonography revealed that the polymorphisms tested in the ADCY9 linkage disequilibrium block were associated with disease regression for patients with the protective genotype, progression for the harmful genotype, and no effect in heterozygotes ( P ≤0.05 and ≤0.01 for 10 and 3 polymorphisms, respectively) when comparing dalcetrapib to placebo. Strikingly concordant and significant genotype-dependent effects of dalcetrapib were also obtained for changes in high-sensitivity C-reactive protein and cholesterol efflux capacity. The Dal-GenE randomized trial is currently being conducted in patients with a recent acute coronary syndrome bearing the AA genotype at rs1967309 in the ADCY9 gene to confirm the effects of dalcetrapib on hard cardiovascular outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.283 | 0.227 |
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".