Malodorous biogenic amines in Escherichia coli-caused urinary tract infections in women—a metabolomics approach
Bibliographic record
Abstract
Many women suffer from urinary tract infections (UTIs). In addition to pain and increased urgency to urinate, malodour is a significant issue for these patients. The specific factors causing this malodour are unclear, and there are no targeted treatment options to counteract it effectively. We used a metabolomics approach to compare the chemical composition of metabolites in the urine of women with E. coli UTIs (n = 15) and those who are healthy (n = 10). The biogenic amines trimethylamine and putrescine, which cause malodour in other urogenital conditions, were significantly increased in UTI patients. Conversely, the precursor of trimethylamine, trimethylamine N-oxide, was lower. To further confirm the source of the malodorous compounds, in vitro experiments were conducted by incubating strains of uropathogenic E. coli in sterilized urine from healthy women. All tested strains accumulated trimethylamine and putrescine. Notably, cadaverine was also produced by E. coli strains in vitro; however, it was not significantly different between both groups. We confirmed that the malodorous amines TMA and putrescine are found in higher concentrations in the urine of patients with an E.coli-caused UTI.
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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 | 0.001 | 0.001 |
| 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".