Biofilm exacerbates antibiotic resistance: Is this a current oversight in antimicrobial stewardship?
Bibliographic record
Abstract
OBJECTIVE: To raise awareness of the role of environmental biofilm in the emergence and spread of antibiotic resistance and its consideration in antimicrobial stewardship. BACKGROUND: Antibiotic resistance is a major threat to public health. Overuse of antibiotics, increased international travel, and genetic promiscuity amongst bacteria have contributed to antibiotic resistance, and global containment efforts have so far met with limited success. Antibiotic resistance is a natural mechanism by which bacteria have adapted to environmental threats over billions of years and is caused either by genetic mutations or by horizontal gene transfer. Another ancient survival strategy involves bacteria existing within a self-produced polymeric matrix, which today is termed biofilm. Biofilm similarly enables bacterial tolerance to environmental threats, and also encourages the transfer of antibiotic resistance genes between bacterial species. This natural and ubiquitous mode of bacterial life has not been considered amongst strategies to tackle antibiotic resistance in healthcare facilities, despite its ability to significantly enhance bacterial survival and persistence, and to encourage antibiotic resistance. CONCLUSION: Biofilm must be considered synonymously with antibiotic resistance because of its proficiency in transferring resistance genes as well as its innate phenotypic tolerance to antibiotics. Although biofilm falls outside of the current definition of antimicrobial stewardship, greater awareness of the existence, ubiquity, and consequences of environmental biofilm amongst healthcare practitioners is crucial to improving hygiene practices and controlling the emergence and spread of antibiotic resistance in healthcare facilities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".