Regulation of functional steroid receptors and ligand-induced responses in telomerase-immortalized human endometrial epithelial cells
Bibliographic record
Abstract
Information on the regulation of steroid hormone receptors and their distinct functions within the human endometrial epithelium is largely unavailable. We have immortalized human primary endometrial epithelial cells (EECs) isolated from a normal proliferative phase endometrium by stably transfecting the catalytic subunit (hTERT) of the human telomerase complex and cultured these hTERT-EECs now for over 350 population doublings. Active hTERT was detected in hTERT-EECs employing the telomerase repeat amplification assay protocol. hTERT-EECs revealed a polarized, non-invasive epithelial phenotype with apical microvilli and production of a basal lamina when grown on a three-dimensional collagen-fibroblast lattice. Employing atomic force microscopy, living hTERT-EECs were shown to produce extracellular matrix (ECM) components and ECM secretion was modified by estrogen and progesterone (P4). hTERT-EECs expressed inducible and functional endogenous estrogen receptor-alpha (ER-alpha) as demonstrated by estrogen response element reporter assays and induction of P4 receptor (PR). P4 treatment down-regulated PR expression, induced MUC-1 gene activity and resulted in increased ER-beta transcriptional activity. Gene activities of cytokines and their receptors interleukin (IL)-6, leukemia inhibitory factor (LIF), IL-11 and IL-6 receptor (IL6-R), LIF receptor and gp130 relevant to implantation revealed a 17 beta-estradiol (E2)-mediated up-regulation of IL-6 and an E2- and P4-mediated up-regulation of IL6-R in hTERT-EECs. Thus, hTERT-EECs may be regarded as a novel in vitro model to investigate the role of human EECs in steroid hormone-dependent normal physiology and pathologies, including implantation failure, endometriosis and endometrial cancer.
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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 | 0.001 |
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".