Spatial transcriptomics unveils estrogen-modulated immune responses and structural alterations in the ectocervical mucosa of depot medroxyprogesterone acetate users
Bibliographic record
Abstract
Abstract The injectable contraceptive, depot medroxyprogesterone acetate (DMPA), is associated with compromised cervical mucosal barriers. High-resolution spatial transcriptomics is applied here to reveal the spatial localization of these altered molecular markers. Ectocervical tissue samples from Kenyan sex workers using DMPA, or non-hormonal contraceptives, underwent spatial transcriptomics and gene set enrichment analyses. Integrated systemic estradiol levels and bulk tissue gene expression data from a larger cohort enhanced the study’s scope. Unsupervised clustering unveiled four epithelial and seven submucosal layers, showcasing spatially restricted and diverse functional epithelial responses, and a less structured submucosal spatial ordering. DMPA associated with mucosal-wide immunoglobulin gene upregulation, verified by CD20+ B-cell immunostaining, and upregulated immune markers adjacent to the basal membrane. Downregulated genes represented spatially restricted disrupted epithelial barrier integrity and submucosal extracellular matrix dysfunction. The transcriptional profile was associated with markers of estrogen regulation. Collectively, our findings reveal estrogen-modulated distinct ectocervical transcriptional profiles associated with DMPA usage. While upregulation of immunoglobulin genes occurs throughout the mucosa, activation of innate immune responses and dysregulation of barrier integrity markers are spatially restricted. These results extend previous analyses using bulk transcriptomics and provide insights into the molecular landscape influenced by DMPA, shedding light on contraceptive effects and health implications.
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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".