Microbial colonization of human ileal conduits
Bibliographic record
Abstract
Study design: A pilot study of 15 spinal cord injured patients. Objective: To determine whether alteration of fluid intake and use of cranberry juice altered the bacterial biofilm load in the bladder. Setting: London, Ontario, Canada. Methods: Urine samples were collected on day 0 (start of study), on day 7 following each patient taking one glass of water three times daily in addition to normal diet, and on day 15 following each patient taking one glass of cranberry juice thrice daily. One urine sample was sent for culture and a second processed to harvest, examine by light microscopy and Gram stain non-squamous uroepithelial cells to generate bacterial adhesion per 50 cells data. Results: The results showed that cranberry juice intake significantly reduced the biofilm load compared to baseline (P=0.013). This was due to a reduction in adhesion of Gram negative (P=0.054) and Gram positive (P=0.022) bacteria to cells. Water intake did not significantly reduce the bacterial adhesion or biofilm presence. Conclusion: The findings provide evidence in support of further, larger clinical trials into the use of functional foods, particularly cranberry juice, to reduce the risk of UTI in a patient population highly susceptible to morbidity and mortality associated with drug resistant uropathogens. Sponsorship: This study was funded by Ocean Spray Cranberries, Lakeville, MA, USA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".