Additional file 1 of Genomic and phenotypic profiling of Staphylococcus aureus isolates from bovine mastitis for antibiotic resistance and intestinal infectivity
Bibliographic record
Abstract
Additional file 1: Figure S1. a) Intracellular responses of Sa9, Sa11, Sa14, Sa3014, Sa3154, Sa3489, and Sa3603 to antibiotic treatment. The aminoglycosides and ampicillin failed to show efficiency against the Caco-2 internalized isolates, whereas chloramphenicol and ceftiofur were comparatively more effective (p < 0.05). Tetracycline was more efficient (p < 0.05) against all the isolates except the tetracycline-resistant Sa9. b-h) Assessment of antibiotic efficiency against b) Sa9, c) Sa11, d) Sa14, e) Sa3014, f) Sa3154, g) Sa3489, and h) Sa3603 infection in C. elegans. The infected worms were exposed to ampicillin (AMP) (10 µg/mL), kanamycin (K) (30 µg/mL), streptomycin (S) (10 µg/mL), chloramphenicol (C) (30 µg/mL), tetracycline (TET) (30 µg/mL), and ceftiofur (CF) (30 µg/mL). The aminoglycosides, ampicillin, and chloramphenicol failed to show infection remediation in the worms, whereas, ceftiofur was comparatively more effective (p < 0.05). Tetracycline was effective (p < 0.05) as well except against Sa9 infected worms. Average values plotted in the graph with different alphabets indicate a significant difference (p < 0.05). ‘IF-control’ stands for infected Caco-2 cells without antibiotic treatment. ‘NIF-Worms’ and ‘IF-Worm UT’ stands for non-infected worms and infected untreated worms, respectively.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.813 | 0.131 |
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".