Rapid on‐plate and one‐pot derivatization of carbonyl compounds for enhanced detection by reactive matrix LDI‐TOF MS using the tailor‐made reactive matrix, 4‐dimethylamino‐6‐(4‐methoxy‐1‐naphthyl)‐1,3,5‐triazine‐2‐hydrazine (DMNTH)
Bibliographic record
Abstract
In this study, a very sensitive and economical high-throughput methodology has been developed for the analysis of small carbonyl compounds using rapid derivatization with 4-dimethylamino-6-(4-methoxy-1-naphthyl)-1,3,5-triazine-2-hydrazine (DMNTH), a derivatizing agent developed by the Karst group at the University of Münster. DMNTH is highly ionizable by the UV laser and reacts selectively and rapidly with carbonyl moieties. The resulting hydrazone is easily detectable by laser desorption ionization time of flight mass spectrometry (LDI-TOF MS), eliminating the need for the matrix assisted variant (MALDI) and the associated issue of matrix optimization, which greatly simplifies the analysis. It has been demonstrated that a range of carbonyl compounds can be conveniently analyzed by this reactive matrix LDI-TOF MS (RM-LDI-TOF MS) procedure and that furfural DMNThydrazone (prior labeled and labeled in situ) can be used as an internal standard for semiquantitative analysis. Amounts as low as 0.5 ng ml(-1) of 4-methoxybenzaldehyde have been detected using a one-pot derivatization methodology. Rapid on-plate derivatization was also found to be a simple approach for fast and reliable screening of various analytes, although with slightly higher detection limits. To test its applicability in complex matrices, analysis of furfural spiked in beer has been demonstrated. This RM-LDI-TOF MS method shows considerable promise for the analysis of carbonyl compounds in water, particularly for disinfection by-products that result from reaction of natural organic matter with oxidative disinfectants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".