Genomic features and heat resistance profiles of<i>Escherichia coli</i>isolated from Brazilian beef
Bibliographic record
Abstract
AIMS: Characterize Escherichia coli and E. coli -producing (STEC) isolates from Brazilian beef to determine heat resistance and the presence of the transmissible locus of stress tolerance (tLST). METHODS AND RESULTS: Twenty-two STEC previously isolated from beef and characterized as STEC by PCR were subjected to different heat survival challenges (60°C and 71°C). Furthermore, the three tLST-positive isolates and one tLST-negative isolate by PCR were selected for WGS analysis. Phenotypic results indicated that 3/22 (13.64%) were heat resistant, 12/22 (54.54%) were moderately resistant, and 7/22 (31.82%) were sensitive to heat treatments. WGS analyses showed that three isolates with heat resistance showed tLST with up to 80% and 42% of similarity by BLAST analysis, with the major tLST genes being responsible for the homeostasis module. However, WGS showed the absence of stx genes associated with tLST-positive isolates, albeit with virulence and resistance genes found in extraintestinal pathogenic E. coli (ExPEC). CONCLUSION: Our findings demonstrate the presence of heat-resistant E. coli as well as confirm some tLST genes in E. coli isolated from Brazilian beef.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".