Lipid Metabolic Process Involved in Oocyte Maturation During Folliculogenesis
Bibliographic record
Abstract
Oocyte maturation is a complex and dynamic process regulated by the coordination of ovarian cells and numerous extraovarian signals. From mammal studies, it is learnt that lipid metabolism provides sufficient energy for morphological and cellular events during folliculogenesis, and numerous lipid metabolites, including cholesterol, lipoproteins, and 14-demethyl-14-dehydrolanosterol, act as steroid hormone precursors and meiotic resumption regulators. Endogenous and exogenous signals, such as gonadotropins, insulin, and cortisol, are the upstream regulators in follicular lipid metabolic homeostasis, forming a complex and dynamic network in which the key factor or pathway that plays the central role is still a mystery. Though lipid metabolites are indispensable, long-term exposure to a high-fat environment will induce irreversible damage to follicular cells and oocyte meiosis. This review specifically describes the transcriptional expression patterns of several lipid metabolism-related genes in human oocytes and granulosa cells during folliculogenesis, illustrating the spatiotemporal lipid metabolic changes in follicles and the role of lipid metabolism in female reproductive capacity. This study aims to elaborate the impact of lipid metabolism on folliculogenesis, thus providing guidance for improving the fertility of obese women and the clinical outcome of assisted reproduction.
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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) | 0.001 | 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) | 0.002 | 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".