Hydrogen peroxide increases the activities of regulon enzymes and the levels of oxidized proteins and lipids in
Bibliographic record
Abstract
The effects of hydrogen peroxide treatments on Escherichia coli KS400 and AB1157 cells were assessed by monitoring the accumulation of oxidative damage products, carbonyl proteins and thiobarbituric acid-reactive substances (TBARS), as well as the activities of selected antioxidant enzymes. H(2)O(2) treatment stimulated increases in both TBARS and carbonyl protein levels in dose- and time-dependent manners in KS400 cells. The accumulation of TBARS was much more variable with H(2)O(2) treatment; TBARS content was significantly increased in response to 5 microM H(2)O(2), whereas a significant increase in carbonyl protein content occurred at 100 microM H(2)O(2). Similarly, treatment with 20 microM hydrogen peroxide for different lengths of time resulted in peak TBARS accumulation by 20 min, whereas carbonyl protein levels were significantly elevated only after 60 min. In AB1157 cells, treatment with 20 microM hydrogen peroxide for 20 min led to strong increases in both carbonyl protein and TBARS levels. This treatment also triggered increased activities of enzymes of the oxyR regulon (catalase, peroxidase, and glutathione reductase) in both strains. In the AB1157 strain, H(2)O(2) exposure also increased the activities of two enzymes of the soxRS regulon (superoxide dismutase and glucose-6-phosphate dehydrogenase) by 50-60%. The data show differential variability of lipids versus proteins to oxidative damage induced by H(2)O(2,) as well as strain-specific differences in the accumulation of damage products and the responses by antioxidant enzymes to H(2)O(2) stress.
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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".