Matrix free laser desorption ionization coupled to trapped ion mobility mass spectrometry: an innovative approach for isomer differentiation and molecular network visualization
Bibliographic record
Abstract
The chemical profiling of complex mixtures of natural products (NPs) is a major challenge in analytical chemistry and generally addressed by liquid chromatography coupled to mass spectrometry (LC-MS). In recent years also matrix free laser desorption ionization-mass spectrometry (LDI-MS) has become a versatile and time efficient complement to LC-MS. However, the absence of chromatographic separation in LDI-MS does not permit the differentiation of isomers. Providing a potential solution to this problem, the current work presents a combined LDI-Ion mobility spectrometry-tandem mass spectrometry (LDI-IMS-MS 2 ) approach, which facilitated the successful differentiation of four constitutional xanthone isomers namely butyraxanthone D, cratoxylone, garcinone D and parvixanthone G. In addition, the experimental collision cross section (CCS) distribution values of nine unreported xanthones are described. Based on these results, a proof of concept for the so far unexplored concept of a LDI-IMS-MS 2 based molecular network is being presented. • Differentiation of xanthone isomers by matrix free laser desorption ionization coupled to ion mobility spectroscopy and tandem mass spectrometry (LDI-IMS-MS2). • Experimental ion mobility data for nine xanthones. • Comparison of experimental and predicted CCS values. • Proof of concept for a molecular network (MN) based on LDI-IMS-MS .
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How this classification was reachedexpand
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 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".