Endometrial microbiome during early pregnancy among women with and without chronic endometritis: a pilot study
Bibliographic record
Abstract
Introduction Although chronic endometritis (CE) is strongly associated with infertility and adverse pregnancy outcomes, the specific microbiome of women with CE who can conceive remain unclear. Methods This study recruited 100 participants aged 18 to 45 years with spontaneously conceived pregnancy who opted for pregnancy termination, detected their endometrial microbiome by 16S rRNA, and made a diagnosis of CE. Results Among them, 19 were diagnosed with CE. There was a comparable microbial composition within the endometrium between women with and without CE. The relative abundance of Sphingomonas (21%) and Pseudomonas (8%) were the same in both groups. Compared to women without CE, women with CE exhibited higher abundance of Faecalibacterium (6.5% vs 3.8%), Escherichia-Shigella (3.3% vs 2.6%), Akkermansia (1.65% vs 1.1%), and lower abundance of Lactobacillus (10% vs 14%), and Corynebacterium (1.35% vs 2.15%) at the genus level. Streptococcus, Escherichia-Shigella, Akkermansia and Finegoldia exhibited significant interactions with other microbiome in participants with CE. Discussion In women with CE, reproductive potential may be associated with the compositional stability of the endometrial microbiome, whereas an imbalance in the abundance of these microbes may be linked to their pregnancy outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".