Revisiting Human Cholesterol Synthesis and Absorption: The Reciprocity Paradigm and its Key Regulators
Bibliographic record
Abstract
Hypercholesterolemia is a major risk factor for cardiovascular disease. Cholesterol homeostasis in the body is governed by the interplay between absorption, synthesis, and excretion or conversion of cholesterol into bile acids. A reciprocal relationship between cholesterol synthesis and absorption is known to regulate circulating cholesterol in response to dietary or therapeutic interventions. However, the degree to which these factors affect synthesis and absorption and the extent to which one vector shifts in response to the other are not thoroughly understood. Also, huge inter-individual variability exists in the manner in which the two systems act in response to any cholesterol-lowering treatment. Various factors are known to account for this variability and in light of recent experimental advances new players such as gene-gene interactions, gene-environmental effects, and gut microbiome hold immense potential in offering an explanation to the complex traits of inter-individual variability in human cholesterol metabolism. In this context, the objective of the present review is to provide an overview on cholesterol metabolism and discuss the role of potential factors such as genetics, epigenetics, epistasis, and gut microbiome, as well as other regulators in modulating cholesterol metabolism, especially emphasizing the reciprocal relationship between cholesterol synthesis and absorption. Furthermore, an evaluation of the implications of this push-pull mechanism on cholesterol-lowering strategies is presented.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".