Three-layer matrix/sample preparation method for MALDI MS analysis of low nanomolar protein samples
Bibliographic record
Abstract
A robust and sensitive sample preparation method is presented for matrix-assisted laser desorption ionization (MALDI) mass spectrometric analysis of low nanomolar concentrations of proteins containing high amounts of common salts and buffers. This method involves the production of densely packed sub-micrometer matrix crystals by depositing a matrix solution on top of a matrix seed-layer prepared on a MALDI target. A sub-microliter aliquot of analyte solution is then directly added to the top of the matrix crystals to form a thin-layer. alpha-Cyano-4-hydroxycinnamic acid (4-HCCA) is used as matrix and demonstrated to give better performance than other commonly used matrices, such as 2,5-dihydroxybenzoic acid (DHB), 2-(4-hydroxy-phenylazo) benzoic acid (HABA), or sinapinic acid. This three-layer method is shown to be superior to the other MALDI sample preparation methods, particularly for handling low nanomolar protein solutions containing salts and buffers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".