High Stromal Senescence During the Window of Implantation Is Linked to Plasma Cell Presence and Cluster Formation in the Endometrium
Bibliographic record
Abstract
Successful implantation requires a finely regulated endometrial microenvironment during the window of implantation. Chronic endometritis, defined by plasma cell infiltration, and stromal senescence, indicated by p16 expression, represent separate but potentially interacting mechanisms associated with impaired endometrial receptivity. The relationship between these processes remains poorly understood. We aim to examine whether stromal senescence is associated with plasma cell density and clustering in the human endometrium during the implantation window. Forty mid-luteal (LH+7) endometrial biopsies were retrospectively analyzed and stratified into low-senescence (<0.5% stromal p16+ cells, n = 20) and high-senescence (>3.5%, n = 20) groups. Plasma cells were identified by immunohistochemistry for MUM1 and CD138 and quantified using HALO® software (version 3.4). Group comparisons were performed using Student’s t-test and chi-squared analysis. CD138+ plasma cells were significantly more abundant in high-senescence endometria than in low-senescence controls (0.065 ± 0.10 vs. 0.014 ± 0.027 cells/mm2, p = 0.02). Only MUM1+ cells formed stromal clusters, which were more frequent in high-senescence samples (67% vs. 31%, p = 0.05). High endometrial stromal senescence during the implantation window is associated with increased plasma cell infiltration and clustering. This interplay may contribute to chronic endometritis and impaired receptivity, providing new insights into potential diagnostic and therapeutic strategies for reproductive failure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".