Binding Domain‐Driven Intracellular Trafficking of Sterols for Synthesis of Steroid Hormones, Bile Acids and Oxysterols
Bibliographic record
Abstract
Steroid hormones, bioactive oxysterols and bile acids are all derived from the biological metabolism of lipid cholesterol. The enzymatic pathways generating these compounds have been an area of intense research for almost a century, as cholesterol and its metabolites have substantial impacts on human health. Owing to its high degree of hydrophobicity and the chemical properties that it confers to biological membranes, the distribution of cholesterol in cells is tightly controlled, with subcellular organelles exhibiting highly divergent levels of cholesterol. The manners in which cells maintain such sterol distributions are of great interest in the study of steroid and bile acid synthesis, as limiting cholesterol substrate to the enzymatic pathways is the principal mechanism by which production of steroids and bile acids is regulated. The mechanisms by which cholesterol moves within cells, however, remain poorly understood. In this review, we examine the subcellular machinery involved in cholesterol metabolism to steroid hormones and bile acid, relating it to both lipid- and protein-based mechanisms facilitating intracellular and intraorganellar cholesterol movement and delivery to these pathways. In particular, we examine evidence for the involvement of specific protein domains involved in cholesterol binding, which impact cholesterol movement and metabolism in steroidogenesis and bile acid synthesis. A better understanding of the physical mechanisms by which these protein- and lipid-based systems function is of fundamental importance to understanding physiological homeostasis and its perturbation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".