FOXO1 and c-jun transcription factors mRNA are modulated in endometriosis
Bibliographic record
Abstract
Endometriosis is a polygenic gynaecological condition affecting 5-15% of women of childbearing age. Major symptoms of the disease are pelvic pain and infertility. No clear link has been established between symptoms and the stage of the disease. Although some aspects have begun to be clarified, clinical understanding of endometriosis remains partial at the molecular level. In this perspective, we targeted isolation of differentially expressed genes in the eutopic endometrial tissue. Our assumption was that the endometrial cells of patients presented an unusual gene expression profile, allowing their implantation and survival in an ectopic site, leading to endometriotic lesions. Here, we report that mRNA steady-state levels of two key transcription factors are modulated in endometriosis. FOXO1 (also known as FKHR) levels were 1.6-fold lower in endometriosis compared to the control group at the onset of the secretory phase (day 15-21), while c-jun mRNA was present at higher amounts in endometriosis (1.5-fold) at the proliferative phase of the menstrual cycle. These results were derived from a large sample composed of 157 control subjects and 209 patients with endometriosis. Gene profiling was conducted by real-time quantitative PCR, and data were quality controlled before statistical analysis. Whether protein levels are affected as well remains to be investigated.
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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) | 0.001 | 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".