Abnormal Immunological Profile and Vaginal Microbiota in Women Prone to Urinary Tract Infections
Bibliographic record
Abstract
The host determinants of susceptibility to recurrent urinary tract infections (UTI) are poorly understood. We investigated whether the susceptibility is associated with abnormalities in the immunological defense and further explored the linkage to vaginal microbiota. For this purpose, we compared vaginal, urine, and blood samples collected during a disease-free period from 22 women with recurrent UTI and from 17 controls. In UTI-prone women, interleukin-12 (IL-12) production in peripheral monocytes and myeloid dendritic cells (DCs) was significantly (P < 0.05) enhanced whether measured in relative numbers of IL-12-producing cells or in mean IL-12 production per cell. In contrast, no T-cell polarization was observed. Interestingly, it seemed that the cytokine production of DCs and monocytes did not translate into T-cell activation in the UTI-prone group in a manner similar to that seen with the controls. In vaginal mucosa, UTI-prone women had a lower concentration of tissue repair-associated vascular endothelial growth factor (VEGF) (P = 0.006) and less often had detectable amounts of the chief monocyte and DC chemoattractant, monocyte chemotactic protein 1 (P = 0.005), than the controls. The microbiota of UTI-prone women was characterized by a diminished lactobacillus morphotype composition, with an abnormally high (>3) mean Nugent score of 4.6 compared to 1.7 for the controls (P = 0.003). Normal lactobacillus composition was associated with increased IL-17 and VEGF concentrations in vaginal mucosa. In conclusion, immunological defects and a persistently aberrant microbiota, a lack of lactobacilli in particular, may contribute to susceptibility to recurrent UTI. Further studies of antigen-presenting-cell function and T-cell activation in recurrent UTI are called for.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".