Cholesterol esterification by ACAT2 is essential for efficient intestinal cholesterol absorption: evidence from thoracic lymph duct cannulation
Bibliographic record
Abstract
The hypothesis tested in this study was that cholesterol esterification by ACAT2 would increase cholesterol absorption efficiency by providing cholesteryl ester (CE) for incorporation into chylomicrons. The assumption was that absorption would be proportional to Acat2 gene dosage. Male ACAT2⁺/⁺, ACAT2⁺/⁻, and ACAT2⁻/⁻ mice were fed a diet containing 20% of energy as palm oil with 0.2% (w/w) cholesterol. Cholesterol absorption efficiency was measured by fecal dual-isotope and thoracic lymph duct cannulation (TLDC) methods using [³H]sitosterol and [¹⁴C]cholesterol tracers. Excellent agreement among individual mice was found for cholesterol absorption measured by both techniques. Cholesterol absorption efficiency in ACAT2⁻/⁻ mice was 16% compared with 46-47% in ACAT2⁺/⁺ and ACAT2⁺/⁻ mice. Chylomicrons from ACAT2⁺/⁺ and ACAT2⁺/⁻ mice carried ∼80% of total sterol mass as CE, whereas ACAT2⁻/⁻ chylomicrons carried >90% of sterol mass in the unesterified form. The total percentage of chylomicron mass as CE was reduced from 12% in the presence of ACAT2 to ∼1% in ACAT2⁻/⁻ mice. Altogether, the data demonstrate that ACAT2 increases cholesterol absorption efficiency by providing CE for chylomicron transport, but one copy of the Acat2 gene, providing ∼50% of ACAT2 mRNA and enzyme activity, was as effective as two copies in promoting 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".