A Novel Procedure for Generating both Nitric Oxide and Superoxide in Situ from Chemical Sources at Any Chosen Mole Ratio. First Application: Tyrosine Oxidation and a Comparison with Preformed Peroxynitrite
Bibliographic record
Abstract
The first method for generating (*)NO and O(2)(*)(-) at any known, constant ratio has been developed. Spermine NONOate and di(4-carboxybenzyl)hyponitrite decay with first-order kinetics and exactly equal rate constants (half-lives of 80 min) at 37 degrees C and pH 7.5 to give 200 and 40 mol % (*)NO and O(2)(*)(-), respectively. Tyrosine oxidation to dityrosine and 3-nitrotyrosine (the major and minor products under the conditions used in these experiments) has been studied (mainly in the presence of CO(2)) using various different ratios of the rates of formation of (*)NO and O(2)(*)(-). The (*)NO/O(2)(*)(-) = 1.0 product profiles are very similar to those of the products derived from equal amounts of (*)NO and O(2)(*)(-) generated at a (*)NO/O(2)(*)(-) ratio of 1.0 from SIN-1 but are very different from those derived from preformed peroxynitrite. All the experimental results can be explained in terms of free radical chemistry. The product profiles at all the (*)NO/O(2)(*)(-) ratios could be satisfactorily simulated provided an important group of reactions which lead to the consumption of dityrosine was included.
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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 | 0.001 |
| 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".