Silver ion binding to the organophosphorus pesticide diazinon and hydrolytic pathways revealed by mass spectrometric and NMR studies
Bibliographic record
Abstract
This paper describes the first study of the interactions of Ag+ with the organophosphorus (OP) insecticide diazinon, 1. Electrospray ionization mass spectrometry (ESI-MS) with corroborative collision-induced dissociation-mass spectrometry (CID-MS) demonstrates that 1 forms a bidentate chelate with Ag+. The hydrolysis products of 1, the pyrimidinol (PY) and O,O-diethylphosphorothioic acid (PA), are also found to bind to Ag+ via N (PY) and S (PA) Lewis base sites, respectively. 31P and 1H nuclear magnetic resonance (NMR) spectra in solution, followed over time with varying ratios of Ag+ to 1, confirm the MS evidence and show Ag+ catalysis of hydrolysis (e.g., complete hydrolysis of 1 in ∼5 min (first-order half-life = 3 × 10−4 d; kobs = 2 × 103 d−1)) with equimolar Ag+; this represents an approximate 150 000-fold enhancement in hydrolysis with Ag+ as compared to its absence. A mechanism for the enhanced hydrolysis is proposed in which bidentate binding of Ag+ to S of the P=S electrophilic site in tandem with binding to N of the leaving group stabilizes the SN2(P) transition state relative to the ground state; this effect is described by qualitative energy profiles.
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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".