In vitro activity of an ear rinse containing tromethamine, EDTA, and benzyl alcohol on bacterial pathogens from dogs with otitis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the in vitro activity of an ear rinse (ER) containing tromethamine, EDTA, and benzyl alcohol on bacterial pathogens from dogs with otitis. SAMPLE POPULATION: Organisms were collected from ear swab specimens from the external and middle ear and included Staphylococcus spp (n = 11; Staphylococcus intermedius [7] and Staphylococcus spp [4]), Pseudomonas aeruginosa (5), Proteus spp (5), beta-hemolytic streptococcus (11), and 1 control strain of each organism. PROCEDURES: 3 test solutions were evaluated including EDTA, tromethamine, and benzyl alcohol (ER); EDTA and tromethamine (ER without benzyl alcohol [ER - BA]); and purified water. Ten-milliliter aliquots of each test solution were transferred into 36 tubes and inoculated with one of the organisms. Samples were retrieved from each tube at 0, 15, 30, 45, and 60 minutes, transferred to Petri dishes, mixed with soybean-casein digest agar, and incubated. After incubation, plates were examined for growth, and the number of colonies was expressed as CFU per milliliter. RESULTS: ER significantly decreased bacterial growth in vitro of P aeruginosa and beta-hemolytic streptococcal organisms within 15 minutes, Proteus spp within 30 minutes, and Staphylococcus spp within 60 minutes. Comparatively, the presence of benzyl alcohol in ER significantly decreased bacterial growth of beta-hemolytic streptococcus and Proteus spp. CONCLUSIONS AND CLINICAL RELEVANCE: On the basis of results of this study, future studies should be performed to evaluate the in vivo efficacy of ER alone as a treatment for otic infections caused by beta-hemolytic streptococcus, P aeruginosa, and Proteus spp and of ER combined with an antimicrobial agent for otic infections caused by Staphylococcus spp.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".