Susceptibility to Nisin, Bactofencin, Pediocin and Reuterin of Multidrug Resistant Staphylococcus aureus, Streptococcus dysgalactiae and Streptococcus uberis Causing Bovine Mastitis
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
Antibiotics are the most effective strategy to prevent and treat intramammary infections. However, their misuse has led to the dissemination of multidrug resistant bacteria (MDR) for both animals and humans. Efforts to develop new alternative strategies to control bacterial infections related to MDR are continuously on the rise. The objective of this study was to evaluate the antimicrobial activity of different bacteriocins and reuterin against MDR Staphylococcus and Streptococcus clinical isolates involved in bovine mastitis. A bacterial collection including S. aureus (n = 19), S. dysgalactiae (n = 17) and S. uberis (n = 19) was assembled for this study. Antibiotic resistance profiles were determined by the disk diffusion method. In addition, sensitivity to bacteriocins and reuterin was evaluated by determining minimum inhibitory concentrations (MIC). A total of 21 strains (37.5%) were MDR. MICs ranged from ≤1.0 μg/mL to ≥100 μg/mL for nisin and 2.0 to ≥250 μg/mL for bactofencin. Reuterin was active against all tested bacteria, and MICs vary between 70 and 560 μg/mL. Interestingly, 20 MDR strains were inhibited by bactofencin at a concentration of ≤250 μg/mL, while 14 were inhibited by nisin at an MIC of ≤100 μg/mL. Pediocin did not show an inhibitory effect.
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) | 0.000 | 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) | 0.000 | 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 it