Electrochemistry-High Resolution Mass Spectrometry to Study Oxidation Products of Trimethoprim
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study of the fate of emerging organic contaminants (EOCs), especially the identification of transformation products, after water treatment or in the aquatic environment, is a topic of growing interest. In recent years, electrochemistry coupled to mass spectrometry has attracted a lot of attention as an alternative technique to investigate oxidation metabolites of organic compounds. The present study used different electrochemical approaches, such as cyclic voltammetry, electrolysis, electro-assisted Fenton reaction coupled offline to high resolution mass spectrometry and thin-layer flow cell coupled online to high resolution mass spectrometry, to study oxidation products of the anti-infective trimethoprim, a contaminant of emerging concern frequently reported in wastewaters and surface waters. Results showed that mono- and di-hydroxylated derivatives of trimethoprim were generated in electrochemically and possibly tri-hydroxylated derivatives as well. Those compounds have been previously reported as mammalian and bacterial metabolites as well as transformation products of advance oxidation processes applied to waters containing trimethoprim. Therefore, this study confirmed that electrochemical techniques are relevant not only to mimic specific biotransformation reactions of organic contaminants, as it has been suggested previously, but also to study the oxidation reactions of organic contaminants of interest in water treatment. The key role that redox reactions play in the environment make electrochemistry-high resolution mass spectrometry a sensitive and simple technique to improve our understanding of the fate of organic contaminants in the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.003 | 0.002 |
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 it