Lipoprotein receptor expression during luteinization of the ovarian follicle
Bibliographic record
Abstract
Ovarian follicles luteinize after ovulation, requiring structural and molecular remodeling along with exponential increases in steroidogenesis. Cholesterol substrates for luteal steroidogenesis are imported via scavenger receptor-BI (SR-BI) and the low-density lipoprotein (LDL) receptor from circulating high-density lipoproteins and LDL. SR-BI mRNA is expressed in pig ovaries at all stages of folliculogenesis and in the corpus luteum (CL). An 82-kDa form of SR-BI predominates throughout, is weakly present in granulosa cells, and is robustly expressed in the CL, along with the less abundant 57-kDa form. Digestion of N-linked carbohydrates substantially reduced the SR-BI mass in luteal cells, indicating that differences between forms is attributable to glycosylation. Immunohistochemistry revealed SR-BI to be concentrated in the cytoplasm of follicular granulosa cells, although found mostly at the periphery of luteal cells. To examine receptor dynamics during gonadotropin-induced luteinization, pigs were treated with an ovulatory stimulus, and ovaries were collected at intervals to ovulation. SR-BI in granulosa cell cytoplasm increased through the periovulatory period, with migration to the cell periphery as the CL matured. In vitro culture of follicles with human chorionic gonadotropin induced time-dependent upregulation of 82-kDa SR-BI in granulosa cells. SR-BI and LDL receptor were reciprocally expressed, with the latter highest in follicular granulosa cells, declining precipitously with CL formation. We conclude that luteinization causes upregulation of SR-BI expression, its posttranslational maturation by glycosylation, and insertion into luteal cell membranes. Expression of the LDL receptor is extinguished during luteinization, indicating dynamic regulation of cholesterol importation to maintain elevated steroid output by the CL.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
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".