Gene cascade analysis in human granulosa tumor cells (KGN) following exposure to high levels of free fatty acids and insulin
Bibliographic record
Abstract
Abstract Maternal metabolic disorders such as obesity and diabetes are detrimental factors that compromise fertility and the success rates of medically assisted procreation procedures. During metabolic stress, adipose tissue is more likely to release free fatty acids (FFA) in the serum resulting in an increase of FFA levels not only in blood, but also in follicular fluid (FF). In humans, high concentrations of palmitic acid and stearic acid reduced granulosa cell survival and were associated with poor cumulus-oocyte complex (COC) morphology. Obesity and high levels of circulating FFA were also causatively linked to hampered insulin sensitivity in cells and compensatory hyperinsulinemia. To provide a global picture of the principal upstream signaling pathways and genomic mechanisms involved in this metabolic context, human granulosa-like tumor cells (KGN) were treated with a combination of palmitic acid, oleic acid, and stearic acid at the higher physiological concentrations found in the follicular fluid of women with a higher body mass index (BMI) (≥ 30.0 kg/m 2 ). We also tested a high concentration of insulin alone and in combination with high concentrations of fatty acids. Transcription analysis by RNA-seq with a cut off for fold change of 1.5 and p-value 0.05 resulted in thousands of differentially expressed genes for each treatment. Using analysis software such as Ingenuity Pathway Analysis (IPA), we were able to establish that high concentrations of FFA affected the expression of genes mainly related to glucose and insulin homoeostasis, fatty acid metabolism, as well as steroidogenesis and granulosa cell differentiation processes. The combination of insulin and high concentrations of FFA affected signaling pathways related to apoptosis, inflammation, and oxidative stress. Taken together, our results provided new information on the mechanisms that might be involved in human granulosa cells exposed to high concentrations of FFA and insulin in the contexts of metabolism disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".