Evaluation of biofilm production by<i><scp>P</scp>seudomonas aeruginosa</i>from canine ears and the impact of biofilm on antimicrobial susceptibility<i>in vitro</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Pseudomonas aeruginosa is a common cause of canine otitis; P. aeruginosa biofilm formation has been documented in human medicine, but the role of biofilms in canine disease is not well documented. Bacteria within biofilms can be more resistant to antibiotics compared with their planktonic form; therefore, understanding the biofilm-forming capacity of isolates and their susceptibility to antimicrobials is important when developing treatment regimens. HYPOTHESIS/OBJECTIVES: To evaluate the biofilm-forming capacity of canine otic isolates of P. aeruginosa and to compare the minimal inhibitory concentration (MIC) of the planktonic versus biofilm-embedded bacteria. METHODS: Biofilm-forming ability was assessed using a microtitre plate assay. Broth microdilution was used to assess the MICs of neomycin, polymyxin B, enrofloxacin and gentamicin for the planktonic and biofilm-embedded bacteria. RESULTS: Eighty-three isolates from dogs with otitis were tested; 33 (40%) were classified as biofilm producers. Biofilm MICs for polymyxin B, neomycin, gentamicin and enrofloxacin were significantly higher than for the planktonic form (P < 0.05). CONCLUSIONS AND CLINICAL IMPORTANCE: Biofilm production by otitis isolates of P. aeruginosa is common and may play a role in the pathogenesis of disease. The MICs for biofilm-embedded bacteria differ from their planktonic counterparts, potentially leading to a lack of response to treatment. If polymyxin B, gentamicin, neomycin or enrofloxacin is to be used for topical treatment of a Pseudomonas otitis, the concentration of the medication should be increased, in particular if addressing chronic otitis, because biofilms may have developed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it