Synergistic effects of Non Contact Induction Heating & Antibiotics on Staphylococcus aureus Biofilm
Bibliographic record
Abstract
Staphylococcus aureus is a major cause of prosthetic joint infection (PJI) in which it forms adherent biofilms, thick aggregates of extracellular polymeric substances (EPS) produced by the bacteria. Biofilm associated infections are difficult to treat as they have increased resistance to various antimicrobial agents, which means infected implants often require multiple procedures and prolonged antibiotic therapy. However, a new and emerging method of treatment of PJI is non-contact induction heating (NCIH) of metal implants. We sought to investigate the feasibility and effectiveness of NCIH along with synergistic effects of antibiotics (Vancomycin) in reducing bacterial load within surface associated biofilms in vitro on stainless steel and titanium washers.\nOur preliminary results support the hypothesis that NCIH of metal implants is effective in reducing bacterial load of S. aureus within a biofilm in vitro. In our study, the synergistical use of the dual treatment strategy (heat and antibiotics) resulted in a ~1000-fold total decrease in CFUs/ml (~3 log reduction). This suggests the potential synergistic effect between the heat and antibiotic treatment against biofilms. These results can be further explored as a new treatment modality for PJI and infections of orthopedic implants. Future work in this study will investigate if NCIH can be used synergistically with antibiotics to more effectively eliminate biofilm associated infections
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".