Identification and structural elucidation of ozonation transformation products of estrone
Bibliographic record
Abstract
BACKGROUND: Quantitative methods for the analysis of contaminants of emerging concern (CECs) are abundant in the scientific literature. However, there are few reports on systematic methods of identification and structural identification of transformation products. For this reason, a new method based on high-resolution mass spectrometry and differential analysis was developed in order to facilitate and accelerate the process of identification and structural elucidation of transformation products CECs. This method was applied to the study of ozonation transformation products (OTPs) of the natural hormone estrone (E1). RESULTS: A control compare trend experiment consisting in the comparison of a control sample to several samples having been exposed to decreasing concentrations of O3(aq) indicated that 593 peaks could be associated with OTPs. After applying various filters to remove background noise, sample contaminants and signal spikes, this data set was reduced to 16 candidate peaks. By inspection of the shape of these peaks, only two compounds OTP-276 (m/z 275.12930) and OTP-318 (m/z 317.14008) were considered as good candidates for further study. Multi-stage tandem mass spectrometry (MSn) experiments of SPE extracts of the ozonated samples of E1 and of a deuterium-labeled analogue (E1-d4) showed that OTP-276 and OTP-318 had carboxylic acid and hydroxyl functional groups, as previously reported for OTPs of other hormones. Structures for these two compounds were proposed based on their MSn spectra. CONCLUSION: These results indicate that the method proposed is a systematic and rapid approach to study transformation products of CECs.
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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 | 0.001 | 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".