Biofilm Formation by Escherichia coli Isolated from Urinary Tract Infections from Aguascalientes, Mexico
Bibliographic record
Abstract
Uropathogenic Escherichia coli (UPEC) strains are among the leading causes of urinary tract infections (UTIs) worldwide. They can colonize the urinary tract and form biofilms that allow bacteria to survive and persist, causing relapses of infections and life-threatening sequelae. Here, we analyzed biofilm production, antimicrobial susceptibility, virulence factors, and phylogenetic groups in 74 E. coli isolated from diagnosed patients with UTIs to describe their microbiological features and ascertain their relationship with biofilm capabilities. High levels of ceftazidime resistance are present in hospital-acquired UTIs. Isolates of multidrug resistance strains (p = 0.0017) and the yfcV gene (p = 0.0193) were higher in male patients. All the strains tested were able to form biofilms. Significant differences were found among higher optical densities (ODs) and antibiotic resistance to cefazolin (p = 0.0395), ceftazidime (p = 0.0302), and cefepime (p = 0.0420). Overall, the presence of fimH and papC coincided with strong biofilm formation by UPEC. Type 1 fimbriae (p = 0.0349), curli (p = 0.0477), and cellulose (p = 0.0253) production was significantly higher among strong biofilm formation. Our results indicated that high antibiotic resistance may be related to male infections as well as strong and moderate biofilm production. The ability of E. coli strains to produce biofilm is important for controlling urinary tract infections.
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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 | 0.000 |
| 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 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".