Use of an in Vitro Assay for Determination of Biofilm-Forming Capacity of Bacteria in Chronic Rhinosinusitis
Bibliographic record
Abstract
BACKGROUND: Bacterial biofilms are increasingly implicated in the pathogenesis of chronic disease and have been established in several chronic ear, nose, and throat conditions, including chronic sinusitis (CRS). However, this relies on specialized imaging methods not widely available. We wished to assess the capacity of an easily performed, inexpensive in vitro test to assess biofilm production by bacteria recovered from individuals with CRS with or without nasal polyposis. METHODS: Bacterial isolates were recovered from patients consulting an academic tertiary rhinology practice. Biofilm formation was determined with an in vitro staining method using crystal violet. Ten isolates of Pseudomonas aeruginosa, Staphylococcus aureus, and 11 of coagulase-negative staphylococcus from patients with CRS having previously undergone endoscopic sinus surgery for >1 year were assessed. Samples were cultured 24 hours at 37 degrees C on 96-well plates in tryptic soy broth 0.5% glucose medium. After staining with crystal violet, optical density at 570 nm was measured to quantify biofilm production. Biofilm-forming capacity was compared with positive and negative controls for each species obtained from commercial sources. RESULTS: Positive controls all grew biofilms, with a tendency of lesser biofilm formation at higher dilutions. Twenty-two of 31 clinical samples produced a biofilm greater or equal to the positive control. Biofilm was recovered consistently for all three species studied. CONCLUSION: This in vitro assessment method is capable of detecting biofilm-forming capacity in bacteria recovered from individuals with CRS. This simple assay may be a useful complement to existing techniques for clinical research.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".