Biofilm formation of the pathogens of fatal bacterial granuloma after trauma: Potential mechanism underlying the failure of traditional antibiotic treatments
Bibliographic record
Abstract
The pathogen of a new type of disease - fatal bacterial granuloma after trauma (FBGT) - was found to be Propionibacterium acnes (P. acnes). Although in vitro studies showed that the pathogenic P. acnes are sensitive to conventional antibiotics, treatments of FBGT patients with these antibiotics were ineffective. The underlying mechanisms were not clear. Since P. acnes are able to form biofilm on orthopaedic biomaterials in vitro, and pathogenic P. acnes of acnes vulgaris was known to form biofilm in vivo, we hypothesize that the pathogens of FBGT are also able to form biofilm during the pathogenesis, which may be 1 of the reasons for antibiotics tolerance of FBGT. Biofilm forming capacity of the pathogens of FBGT were examined with XTT reduction method, as well as with scanning electron microscope. The effect of long-term subminimal inhibitory concentration (MIC) lincomycin on the biofilm forming ability of the pathogens was also tested. Our results show that both the type strain (NCTC737) and the pathogenic P. acnes of FBGT can form biofilm in vitro. These data demonstrated the biofilm formation of the FBGT pathogens in vitro, and its acceleration by lincomycin, which may be 1 of the major mechanisms for the failure of antibiotic treatment.
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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 | 0.000 | 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 | 0.001 | 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".