Studies on the oxidative degradation of paracetamol by a μ-oxo-diiron(III) complex
Bibliographic record
Abstract
In higher organisms, metalloenzymes like cytochrome P450, containing a Fe(III) metal center, play an active role in metabolism of paracetamol (APAP). Here, we have chosen a mimicking μ-oxo-diiron complex, [Fe(III) 2 (μ-O)(phen) 4 (H 2 O) 2 ] 4+ (1, phen = 1,10-phenanthroline), to study spectrophotometrically the kinetics of the redox interactions with APAP. In acidic buffer media (pH = 3.4–5.1), APAP quantitatively reduces 1 following first-order reaction kinetics. Each molecule of 1 accepts two electrons from APAP and is reduced to ferroin [Fe(phen) 3 ] 2+ . On oxidation, APAP produces N-acetyl-p-benzoquinone imine (NAPQI), which on hydrolysis results in a mixture of benzoquinone, quinone oxime, acetamide, and acetic acid. In reaction media due to successive deprotonations, 1 exists in equilibrium with the species [Fe(III) 2 (μ-O)(phen) 4 (H 2 O)(OH)] 3+ (1a) and [Fe(III) 2 (μ-O)(phen) 4 (OH) 2 ] 2+ (1b) (pK a = 3.71 and 5.28, respectively). The kinetic analyses suggest for an unusual reactivity order as 1 < 1a ≫ 1b. The mechanistic possibilities suggest that although 1 is reduced by concerted electron transfer (ET) – proton transfer (PT) mechanism, 1a and 1b may be reduced by a concerted PT–ET mechanism where a slow proton-abstraction step is followed by a rapid ET process. It seems that the initial activation of the bridging μ-oxo group by a proton-abstraction results in the higher reactivity of 1a.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".