Active chromatin marks and up-regulation of FOXC1 in uterine epithelial cells demarcate the onset of reproductive decline in aging females
Bibliographic record
Abstract
Abstract Advanced maternal age increases the risk of pregnancy complications due, in part, to changes in the uterine environment. Here, we show that uterine aging in mice is associated with a progressive increase in transcriptional variation, accompanied by a notable accumulation of activating histone marks at multiple genomic loci. Importantly, the transcriptional signatures of uterine aging differ substantially from senescence markers associated with organismal aging. We demonstrate that maternal age-induced effects largely originate in the epithelial compartment and entail a dramatic up-regulation of the pioneer transcription factor FOXC1, combined with a hyper-enrichment for H3K27ac and H3K4me3 across the locus. FOXC1 over-expression in human endometrial epithelial cells causes profound transcriptomic shifts and increased proliferation, recapitulating the aging phenotype. Using endometrial epithelial organoids of young and aged mice, we find that aging hallmarks including Foxc1 up-regulation and epithelial H3K27ac hyper-enrichment are conserved in vitro. Recapitulating the epithelial hyperplasia phenotype seen in vivo, endometrial epithelial organoids from aged mice are larger and mis-express key factors, such as SOX9, critical for uterine gland maturity and function. Collectively, our data highlight the susceptibility of uterine epithelial cells to early-onset aging, demarcated by an increase in activating epigenetic marks that converge on the mis-regulation of FOXC1.
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 | 0.000 | 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".