Differential Survival of Hyper-Aerotolerant Campylobacter jejuni under Different Gas Conditions
Bibliographic record
Abstract
Campylobacter jejuni accounts for a significant number of foodborne illnesses around the world. C. jejuni is microaerophilic and typically does not survive efficiently in oxygen-rich conditions. We recently reported that hyper-aerotolerant (HAT) C. jejuni are highly prevalent in retail poultry meat. To assess the capabilities of HAT C. jejuni in foodborne transmission and infection, in this study, we investigated the prevalence of virulence genes in HAT C. jejuni and the survival in poultry meat in atmosphere at a refrigeration temperature. When we examined the prevalence of eight virulence genes in 70 C. jejuni strains from raw poultry meat, interestingly, the frequencies of detecting virulence genes were significantly higher in HAT C. jejuni strains than aerosenstive C. jejuni strains. This suggests that HAT C. jejuni would potentially be more pathogenic than aerosensitive C. jejuni. Under aerobic conditions, aerosensitive C. jejuni survived at 4°C in raw poultry meat for three days, whereas HAT C. jejuni survived in poultry meat for a substantially extended time; there was a five-log CFU reduction over two weeks. In addition, we measured the effect of other gas conditions, including N2 and CO2, on the viability of HAT C. jejuni in comparison with aerosensitive and aerotolerant strains. N2 marginally affected the viability of C. jejuni. However, CO2 significantly reduced the viability of C. jejuni both in culture media and poultry meat. Based on the results, modified atmosphere packaging using CO2 may help us to control poultry contamination with HAT C. jejuni.
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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 | 0.000 |
| 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) | 0.001 | 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".