Non‐responsiveness to plant sterol treatment and possible polymorphisms: ABCG5, ABCG8 and NPC1L1
Bibliographic record
Abstract
Plant sterols (PS) have been shown to decrease low‐density lipoprotein cholesterol (LDL‐C); however, high variability of responsiveness of lipids levels to PS treatment has been observed. We hypothesized that common variants in ATP binding cassette protein G5 (ABCG5) and G8 (ABCG8) or Nieman‐Pick C1‐like 1 (NPC1L1) would underline these large inter‐individual variations in the plasma lipids in response to PS treatment. Twenty‐six hyperlipidemic subjects completed the randomized trial of three PS (1.6 g/d in low‐fat yogurt) and control phase. Twenty‐three subjects consistency lowered their LDL‐C and total cholesterol (TC) during the three PS phases compared to control. Yet, three non‐responders were identified as constantly failed to decrease both TC and LDL‐C in all three PS phases vs. control. However, none of the polymorphisms tested: ABCG8 (V632A, D19H, T400K); ABCG5 (A478T, Q604E); and NPC1L1 showed an association between the top three responders and non‐responders. Results indicate that non‐responsive subjects to PS treatment may explain large heterogeneity in lipid data; however, no recognizable pattern in polymorphisms was detected. Still, their remains the possible link between other different or combination of haplotypes may demonstrate a non‐response phenotype that may establish subjects for which PS treatment would be an ineffective therapeutic strategy. Funding by Danone Research.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".