Obesogenic diet alters decidual differentiation and cell-cell communication in the mouse uterus
Bibliographic record
Abstract
SUMMARY Maternal obesity is associated with increased risk of infertility, implantation failure, miscarriage, and other pregnancy complications. While prior studies have linked obesity to uterine dysfunction and impaired endometrial biology, how obesity alters the cellular and molecular landscape of the early pregnant endometrium remains poorly understood. Here, we perform single-cell RNA sequencing of embryonic day 5.5 uterus from control and obesogenic mice to generate a cellular atlas of the early decidualizing endometrium. We identify obesity-associated transcriptional changes across multiple Endometrial Stromal Cell (ESC) states and innate immune populations, including uterine natural killer cells and macrophages. Computational modeling reveals that maternal obesity disrupts distinct routes of ESC differentiation during decidualization and leads to shifts in ESC-derived cues known to impact innate immune responses. These findings provide a comprehensive single-cell resource of the post-implantation mouse endometrium while simultaneously generating critical insight into how maternal obesity reprograms the maternal-fetal interface in early pregnancy.
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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".