Abnormal Pathways in Endometriosis in Relation to Progesterone Resistance: A Review
Bibliographic record
Abstract
Introduction Endometriosis is an estrogen-dependent disorder, and recent studies suggest that progesterone resistance may contribute to the development and pathophysiology of the disorder. Based on this, identification of genetic and molecular perturbations in the endometrium of women with endometriosis is an important step towards understanding the pathogenesis of the disease, and the development of novel treatment and diagnostic strategies. Methods A systematic literature search in PubMed and Embase was performed, and 118 articles were identified for further screening. Two reviewers performed article screening independently using Covidence, and 16 studies fulfilled the inclusion criteria. The Newcastle-Ottawa Scale was used to assess the quality of these studies. Results This review presents data from eutopic endometrial biopsies from women with and without endometriosis. Several biomarkers related to a downregulated progesterone response were identified and discussed in detail. Conclusions Our review demonstrates significant results concerning the biomarkers investigated, which may substantiate the theory of progesterone resistance in women with endometriosis. However, further research is necessary to determine their specific role and relevance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| 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) | 0.003 | 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".