Inactivation of <i>Cronobacter sakazakii</i> by blue light illumination and the resulting oxidative damage to fatty acids
Bibliographic record
Abstract
Blue light (BL) exerts an antimicrobial effect on pathogenic bacteria. It has been hypothesized that its bactericidal activity depends upon the generation of reactive oxygen species (such as anion superoxides) and the resultant cellular damage. However, some aspects of this hypothesis needed to be tested and investigated. Thus, the work conducted herein examined the molecular impact of BL treatment on Cronobacter sakazakii, an emerging foodborne pathogen. The results showed that BL exhibited an efficient bactericidal effect against C. sakazakii. Under a sublethal BL dose, both intracellular anion superoxides and malondialdehyde (a marker of oxidative stress) contents were increased gradually. Moreover, permeability of the outer membrane was increased by approximately 50%, indicating membrane damage. Further investigation revealed alterations to cellular fatty acid profiles, with a decrease and disappearance of unsaturated fatty acids, including C18:2, C16:1, and C18:1. These data indicate that bacterial lipids, especially unsaturated fatty acids, are important molecular targets of BL photo-oxidation. The transcriptional response of bacteria to BL was also studied, and it was found that three genes were upregulated, including genes encoding antioxidants. The current study contributes towards an improved understanding of the bactericidal mechanisms of BL and highlights the importance of lipid and membrane damage.
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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) | 0.001 | 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".