Microbial Diversity of Genital Ulcer Disease in Men Enrolled in a Randomized Trial of Male Circumcision in Kisumu, Kenya
Bibliographic record
Abstract
BACKGROUND: Medical male circumcision (MMC) reduces the risk of genital ulcer disease (GUD) in men by 50%. In Ugandan and Kenyan trials, a sexually transmissible agent was not identified in 50-60% of GUD specimens by polymerase chain reaction (PCR) assay. We sought to better define the etiology of GUD in men participating in the Kenyan trial and examine how MMC affects GUD etiology. METHODS: We defined GUD of unknown etiology as negative for HSV (type 1 and type 2), T. pallidum, and H. ducreyi by PCR, and negative for HSV-2 and T. pallidum by serology. We identified bacterial microbiota in a subset of 59 GUD specimens using multitag pyrosequencing of the 16S rRNA gene, and compared results by unknown vs. STI-associated etiology. Statistical analysis employed Bray-Curtis similarity measure of bacterial community by etiology, hierarchical clustering and logistic regression. RESULTS: In 59 GUD specimens from 59 men, 23 (39%) had unknown etiology. Bacterial diversity was greater in GUD of unknown than STI etiology (p = 0.01). Fusobacteria (Fusobacterium spp. and Sneathia spp.) were more commonly detected in men with GUD of unknown etiology [adjusted OR = 5.67; 95% CI: 1.63-19.8] as were Oxobacter spp. and Anaerovorax spp. [adjusted OR = 3.12; 95% CI: 0.83-11.7]. Sequences from these four anaerobic bacterial taxa were more often detected in uncircumcised men than circumcised men (p<0.05). CONCLUSIONS: Anaerobic bacteria are more common in genital ulcers of uncircumcised men. The specific anaerobic bacteria associated with GUD of unknown etiology have cytotoxic properties that can exacerbate epithelial disruptions leading to ulcer-like appearance. MMC may reduce GUD through a reduction in these anaerobic bacteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".