Differentiating Toxic and Nontoxic Tricresyl Phosphate Isomers Using Ion–Molecule Reactions with Oxygen
Bibliographic record
Abstract
Ortho-substituted isomers of tricresyl phosphates (TCPs) and their toxic metabolites (e.g., CBDP: cresyl saligenin phosphate) can cause neurotoxic effects in humans. When TCP is introduced to an atmospheric pressure chemical ionization source using gas chromatography, radical cations M •+ are formed by charge exchange. The mass spectrum of an ortho-substituted isomer displays two intense peaks that are absent in the spectra of non-ortho-substituted isomers, leading us to propose structure-diagnostic ion–molecule reactions between ions M •+ and oxygen species present in the source. However, the mechanisms of these reactions have not yet been established. In this study, we propose a mechanism and provide support through computational and experimental analyses using density functional theory and cyclic ion mobility-mass spectrometry. The mechanism consists of a multistep reaction starting with the rearrangement of the molecular ion into a distonic isomer followed by an oxidation step and then decomposition into [CBDP-H] + . This proposal is consistent with the results obtained from a series of isotopically labeled analogues. Cyclic ion mobility experiments with a tri- o -cresyl phosphate standard reveal the presence of at least two hydrogen shift isomers of the product ion [CBDP-H] + that are connected by a low-lying barrier. The selectivity of the ion–molecule reactions toward ortho-substituted cresyl TCP isomers provides us with an identification tool that can select potentially neurotoxic triaryl phosphate esters present in complex mixtures that are produced in large volume by industry.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".