Reactive DESI-MS Imaging of Biological Tissues with Dicationic Ion-Pairing Compounds
Bibliographic record
Abstract
This work illustrates reactive desorption electrospray ionization mass spectrometry (DESI-MS) with a stable dication on biological tissues. Rat brain and zebra fish tissues were investigated with reactive DESI-MS in which the dictation forms a stable bond with biological tissue fatty acids and lipids. Tandem mass spectrometry (MS/MS) was used to characterize the dication (DC9) and to identify linked lipid-dication compounds formed. The fragment m/z 85 common to both DC9 fragmentation and DC9-lipid fragmentation was used to confirm that DC9 is indeed bonded with the lipids. Lipid signals in the range of m/z 250-350 and phosphoethanolamines (PE) m/z 700-800 observed in negative ion mode were also detected in positive ion mode with reactive DESI-MS with enhanced signal intensity. Reactive DESI-MS imaging in positive ion mode of rat brain and zebra fish tissues allowed enhanced detection of compounds commonly observed in the negative ion mode.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".