Biofilm evidence and the microbial diversity of horse wounds
Bibliographic record
Abstract
Evidence of biofilms in human chronic wounds are thought to be responsible for preventing healing in a timely manner. However, biofilm evidence in horse wounds has not yet been documented. Consequently, this study aimed to determine whether biofilms could be detected in wounds, and to investigate the microbiology of chronic wounds in horses. Prior to analysis, wound surfaces were irrigated with 5 mL of sterile saline to remove debris. All wounds were swabbed twice (1 cm2 area) using sterile cotton-tipped swabs. In addition to this, 2 tissue biopsies were taken to investigate evidence of biofilm and the microbiology richness of the wounds. All swabs and 1 biopsy sample were transported to the laboratory in Robertson's cooked meat broth. Traditional culturable techniques and denaturing gradient gel electrophoresis with PCR were utilized to identify common bacteria isolated in all wounds. Following analysis of a number of the biopsy samples, biofilms could be clearly seen. The most common bacteria isolated from each wound analysed included Pseudomonas aeruginosa, Staphylococcus epidermidis, Serratia marcescens, Enterococcus faecalis, and Providencia rettgeri. Sequencing of the 16S ribosmonal DNAs, selected on the basis of DGGE profiling, enabled identification of bacterial species not identified using culturable technology. This study is the first to identify biofilms in the chronic wounds of horses. In addition, this study also demonstrated the importance of combining DGGE-PCR with culture techniques to provide better microbiology analysis of chronic wounds.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".