Ultrasound-Induced Escherichia coli O157:H7 Cell Death Exhibits Physical Disruption and Biochemical Apoptosis
Bibliographic record
Abstract
Ultrasound has attracted great interest of both industry and scientific communities for its potential use as a physical processing and preservation tool. In this study, Escherichia coli O157:H7 was selected as the model microbe to investigate the ultrasound-induced cell death. Slight variations in membrane potential and ion exchanges across membrane induced by low-intensity ultrasound increased the membrane permeability of E. coli O157:H7, and this reversible sublethal effect can preserve the viability of E. coli O157:H7 and meanwhile be beneficial for bioprocessing application. In comparison, high-intensity ultrasound resulted in irreversible lethal effect on E. coli O157:H7, which can be applied in the field of microbial inactivation. In addition, both low- and high-intensity ultrasound induced either physical destruction or trigger genetically encoded apoptosis of E. coli O157:H7. Accumulation of reactive oxygen species and decrease of adenosine tri-phosphate might be related to the physiological and biochemical hallmarks of apoptosis, including exposed phosphatidylserine and activated caspases in E. coli O157:H7. The result provides novel insight into the mechanisms of non-thermal physical treatment on the inactivation of bacteria, and lays foundation for the further research on the cell signaling and metabolic pathway in apoptotic bacteria.
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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".