Cocultured porcine granulosa cells respond to excess non-esterified fatty acids during in vitro maturation
Bibliographic record
Abstract
BACKGROUND: Non-esterified fatty acids (NEFAs) are one of the main lipid components of follicular fluid at concentrations that depend on circulating levels. Elevated levels of NEFAs impair oocyte quality, development potential, and may subsequently influence the metabolism and reproductive fitness of offspring. Granulosa cells (GCs) are the follicular cells that are closely communicating with the oocyte. However, the responses of GCs exposed to high levels of NEFAs when cocultured with cumulus-oocyte complexes (COCs), and how they attenuate the negative effects of NEFAs on oocytes, are unclear. RESULTS: To better understand this protective effect, monolayers of porcine GCs were cocultured with COCs during in vitro maturation (IVM) in the presence of elevated levels of NEFAs. Genomic expression analysis was conducted to explore the responses of the GCs to the elevated levels of NEFAs. After limma algorithm analysis, 1,013 genes were differentially expressed between GCs cultured with and without elevated NEFAs. Among them, 438 genes were upregulated and 575 were downregulated. The differentially expressed genes were enriched in pathways related to metabolism, inflammation, and epithelial-mesenchymal transition. CONCLUSIONS: The pathways and upstream regulators suggested that the cocultured GCs responded to the elevated NEFAs with (1) inhibition of the transition from granulosa to luteal cell, (2) interactions of metabolism change, anti-inflammation, mitochondrial function, and cell transition, (3) intercommunication with cocultured COCs of anti-inflammatory factors.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".