A novel microfluidic wound model for testing antimicrobial agents against Staphylococcus pseudintermedius biofilms
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Bibliographic record
Abstract
BACKGROUND: Current methods for testing treatments for veterinary surgical site infections can successfully emulate elements of a chronic wound, but these are time consuming and costly, requiring specialized laboratory equipment and considerable space to house study animals. Microfluidic devices however, can be coated with collagen and maintained at basal body temperature, providing a more cost-effective and space-saving model of a chronic wound. Our study assesses the applicability of a new microfluidic model by testing the activity of DispersinB against biofilms of methicillin-resistant Staphylococcus pseudintermedius (MRSP); DispersinB has been shown to prevent biofilm growth of Staphylococcus epidermidis, another prominent wound colonizer. RESULTS: We successfully developed a microfluidic model to examine the effects of antimicrobial therapy on biofilms formed by organisms associated with wound infections in companion animals (e.g. MRSP). Although, we were unable to recapitulate previous findings that DispersinB-Gentamycin is highly effective against Staphylococcal biofilms using this model, we were able to confirm its effect in a microtitre plate. Differences in the experimental conditions likely account for this result (e.g. strains tested, flow conditions, treatment time, etc.). In the microtitre plate assay, DispersinB inhibited biofilm growth after a 24 hour period; there was an inverse relationship between the concentration of DispersinB-Gentamycin and the amount of biofilm remaining following treatment. Collagen-coated microtitre plates showed a similar result, but this did not correlate as well; collagen, the most abundant protein in the body may help to retain the biomass of treated biofilms. CONCLUSIONS: Our model may be useful in examining the effect of treatment on wound infections, although we acknowledge that in this model the test organisms may be more recalcitrant to antimicrobials than in other published systems. We contend that this may in fact better represent the conditions in vivo, where organisms associated with chronic wound infections are highly resistant to antimicrobials.
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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 | 0.001 | 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