A comparative study of antioxidant capacity of amino acids using the Fe(II)/1-nitroso-2-naphthol-3,6-disulfonic complex and the Folin–Ciocalteu reagent: application in blood serum
Bibliographic record
Abstract
The oxidation of 20 amino acids (AA; alanine, arginine, asparagine, aspartic acid, cysteine (Cys), glutamic acid, glutamine, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine) by Fe(III) in a buffered aqueous solution (pH 8.0, Tris) containing 1-nitroso-2-naphthol-3,6-disulfonic acid (H 2 NRS) was spectrophotometrically evaluated. Under the employed conditions, Fe(III) was reduced to Fe(II) to afford greenish Fe(NRS) 3 4− , the absorbance of which at λ max = 730 nm was correlated to AA reducing capacity and expressed as ascorbic acid equivalents (AS E ). Comparison of the thus obtained AS E values with those determined using the Folin–Ciocalteu reagent (FCR) revealed that all analyzed AA preferentially reacted with Fe(III)–H 2 NRS rather than with the FCR. The obtained insights were utilized to develop a spectrophotometric procedure for the quantitation of the total antioxidant capacity (TAC) of blood serum samples in solution containing Fe(III) and H 2 NRS (pH 8.0, Tris). The TAC values (in mg Cys mL −1 serum) of 22 serum samples determined by the Fe(III)–NRS method were well correlated with those determined using the FCR method ( r = 0.788), which suggested that the proposed procedure can be used to quantify the TAC of other protein-rich biological samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".