Biofilm exacerbates antibiotic resistance: Is this a current oversight in antimicrobial stewardship?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it