Planktonic and biofilm states of <i>Staphylococcus aureus</i> isolated from bone and joint infections and the <i>in vitro</i> effect of orally available antibiotics
Bibliographic record
Abstract
AIMS: To demonstrate the in vitro activity of orally available antibiotics against Staphylococcus aureus isolated from bone or orthopedic implant materials. The biofilm eradication of the combination of three antibiotics was also assessed. METHODS AND RESULTS: Clinical isolates from orthopedic infection samples were collected, and S. aureus isolates were classified according to their biofilm production and composition. Almost all S. aureus isolates (n = 36, 97.3%) produced biofilm and the major biofilm components were polysaccharides. Antimicrobial susceptibility was determined in planktonic (minimal inhibitory concentration; MIC) and biofilm cells (minimal biofilm eradication concentration; MBEC) using the MBEC Calgary Device. Overall, the MBEC ranged higher than the MIC. When combined at borderline-susceptible concentrations, moxifloxacin-rifampin and doxycycline-rifampin were both able to eradicate biofilms in a third of the strains whereas the doxycycline-moxifloxacin combination proved ineffective at eradicating biofilm, inhibiting it only in three strains. CONCLUSIONS: We propose rifampin in combination with moxifloxacin or doxycycline for the design of clinical trials of bone and/or orthopedic device infection without proper debridement or material retention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".