The reproductive cycle is a pathogenic determinant during gonococcal pelvic inflammatory disease in mice
Bibliographic record
Abstract
Women with asymptomatic Neisseria gonorrhoeae infection are at risk of developing pelvic inflammatory disease (PID) if the bacteria ascend from the endocervix into the uterus and oviducts. Factors that affect disease severity, ranging from mild discomfort to severe inflammation, pain, and infertility, remain elusive. Herein we perform direct transcervical inoculation of N. gonorrhoeae into the uterus of mice to establish an infection that leads to PID. Profoundly different disease outcomes were apparent at different stages of the reproductive cycle. Mice that were infected during the diestrus stage of the reproductive cycle displayed extensive gonococcal penetration into the submucosa, severe inflammation, and clinical signs reflecting discomfort. Meanwhile, infection during the intervening estrus stage showed only modest effects. Furthermore, a gonococcal-specific humoral response was only elicited following the penetrative upper genital tract (UGT) infection during diestrus but not estrus. Strikingly, the potential for antibodies to contribute to protection during re-infection also depends upon the reproductive stage, as antigonococcal antibodies within the genital tract were markedly higher when mice were in diestrus. Combined, this work establishes a robust new model reflecting gonococcal PID in humans and reveals how the reproductive cycle determines the pathogenic outcome of gonococcal infections of the UGT.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".