Validation of a single‐isotope‐labeled cholesterol tracer approach for measuring human cholesterol absorption
Bibliographic record
Abstract
Cholesterol absorption is frequently determined using the plasma dual stable-isotope ratio method (PDSIRM). However, this method involves intravenous injection of stable-isotope-labeled cholesterol with simultaneous oral administration of differently labeled cholesterol, which results in high study costs and involves additional ethical considerations. The objective of the present study was to validate a simpler single-isotope method for determining cholesterol absorption against PDSIRM by using data from two previous studies. Enrichments of carbon-13 (13C and deuterium in red blood cells were analyzed by using differential isotope ratio MS. The area under the curve of 13C-enrichment in the plasma free-cholesterol pool was found to be significantly correlated with cholesterol absorption measured by using PDSIRM for study 1 (r = 0.85, P < 0.0001) and study 2 (r = 0.81, P < 0.0001). Average 13C-enrichment correlated with the area under the curve of 13C-enrichment in the plasma free cholesterol for both study 1 (r = 0.98, P < 0.0001) and study 2 (r = 1.00, P < 0.0001). Study 1 examined the efficacy and mechanisms of unesterified plant sterols and stanols on lipid profiles in hypercholesterolemic men and women, while study 2 investigated the effects of phytosterol vs. phytostanol esters on plasma lipid levels and cholesterol kinetics in hyperlipidemic men. Experimental approaches to determine cholesterol absorption were identical between the two studies. Consequently, in both studies, correlations (r = 0.88, P < 0.0001 for study 1, and r = 0.82, P < 0.0001 for study 2) were found between the average 13C-enrichment of plasma free cholesterol and cholesterol absorption measured by PDSIRM. These results suggest that a single-isotope-labeled cholesterol tracer approach can be used as a reliable noninvasive method to replace PDSIRM for examining changes in cholesterol absorption.
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".