Human bile microbiota: A retrospective study focusing on age and gender
Bibliographic record
Abstract
AIMS: The emerging biliary colonization of microorganisms in patients with biliary diseases may be devastating. Recent evidence suggests that age and gender may influence changes in the microbial composition of gut microbiota. To study the relationship between these parameters on bile microbiota, we retrospectively reviewed positive bile cultures following an endoscopic retrograde cholangiopancreatography (ERCP) in a QA-certified academic surgical unit of a single institution. METHODS: 449 positive bile cultures from 172 Italian patients with diseases of the biliopancreatic system hospitalized from 2006 through 2017 were investigated for aerobic, anaerobic, and fungal organisms. The patients were stratified into four age intervals (22-66, 67-74, 75-81, and 82-93 years) and followed up for five years. RESULTS: = -0.114, p = 0.017), with younger patients prone to harbor GPB and older patients likely to have Gram-negative bacteria (GNB). There was a definite link with the male gender using both univariate and multivariate analysis (p < 0.001). Enterococcus spp. was the most common strain identified in patients with GPB except for patients aged 67-74 years for male (95.2%) and female (80.9%) patients. Escherichia coli and Klebsiella spp. were most frequent than others in every group analyzed. Analogous results were found for bacteria Non-fermenting Gram-negative bacilli (NFGNB), such as Pseudomonas spp. and Stenotrophomonas spp. apart of the 2nd quartile. CONCLUSIONS: Our study strengthens the bond of age and gender with bile microbiota composition and suggests that further investigations may be required in targeting the aging microbiome. Other studies should also focus on Mediterranean epidemiological characteristics and antibiotic resistance surveillance system strategies.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".