An Investigation into the Impact of Culture Method on Biofilm Recalcitrance from the Perspective of Chronic Ischemic Wounds
Bibliographic record
Abstract
Antimicrobial resistance is a global crisis that requires urgent attention. Although there is significant investment into drug development few of these drugs actually make it to market. There are shortcomings with some of the currently available testing methods, as these do not often take into account the in vivo environment in which the infections form. This requires a better understanding of the parameters that affect resistance and susceptibility, such as hypoxia or the recalcitrance of biofilms. Biofilms (communities of surface associated microorganisms) present a significant challenge for researchers and clinicians alike, as they are reported to be up to 1000 times more resistant to antimicrobials (Van Acker et al, 2014). These complex communities have a wealth of factors that induce increased recalcitrance to antimicrobials, and are reported to be present in up to 80% of chronic infections (Uruén et al., 2021). Yet, antimicrobial testing of biofilms is not yet widely adopted, and the use of biofilm testing in drug development is often not reported. This work aims to investigate these parameters to gain insight on how antimicrobial discovery and testing can be refined. \nThe first aim of this project was to determine the influence of culture method and hypoxia on S aureus susceptibility in several in vitro antimicrobial susceptibility testing methods. This compared broth microdilution methods (BMM), the Calgary Biofilm device (CBD), and the biofilm microtiter assay (MTA). Hypoxia was revealed to impact S aureus susceptibility in the BMM and CBD methods, and there was a large difference in the density of biofilms formed in the CBD and MTA. \nThe second aim of this project was to set up an ex vivo ovine wounded skin model infected with Staphylococcus aureus, which is simple, cost-effective, high throughput, and reproducible. The establishment of wound infection was confirmed by an increase in viable bacterial counts compared to the inoculum. This enabled the final aim to assess if the ex vivo model formed biofilms and if hypoxia would have an impact on the susceptibility of the biofilms within the ex vivo model. The presence of biofilms was confirmed through scanning electron microscopy, histology, and antimicrobial challenge of the biofilms. Hypoxia elicited an impact on the susceptibility of the ex vivo associated biofilms in an antimicrobial specific manner. \nThis work provides insight into the complex environment that is an ischemic infected wound, and has given insight into the parameters that can affect \nantimicrobial drug development in the preclinical stages.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".