Assessing the properties of internal standards for quantitative matrix‐assisted laser desorption/ionization mass spectrometry of small molecules
Bibliographic record
Abstract
Growing interest in the ability to conduct quantitative assays for small molecules by matrix-assisted laser desorption/ionization (MALDI) has been the driving force for several recent studies. This present work includes the investigation of internal standards for these analyses using a high-repetition rate MALDI triple quadrupole instrument. Certain physicochemical properties are assessed for predicting possible matches for internal standards for different small molecules. The importance of similar molecular weight of an internal standard to its analyte is seen through experiments with a series of acylcarnitines, having a fixed charge site and growing alkyl chain length. Both acetyl- and hexanoyl-carnitine were systematically assessed with several other acylcarnitine compounds as internal standards. The results clearly demonstrate that closely matched molecular weights between analyte and internal standard are essential for acceptable quantitation results. Using alpha-cyano-4-hydroxycinnamic acid as the organic matrix, the similarities between analyte and internal standard remain the most important parameter and not necessarily their even distribution within the solid sample spot. Several 4-quinolone antibiotics as well as a diverse group of pharmaceutical drugs were tested as internal standards for the 4-quinolone, ciprofloxacin. Quantitative results were shown using the solution-phase properties, log D and pKa, of these molecules. Their distribution coefficients, log D, are demonstrated as a fundamental parameter for similar crystallization patterns of analyte and internal standard. In the end, it was also possible to quantify ciprofloxacin using a drug from a different compound class, namely quinidine, having a similar log D value as the analyte.
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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 | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".