Single-step analysis of low abundance phosphoamino acids via on-line sample preconcentration with chemical derivatization by capillary electrophoresis
Bibliographic record
Abstract
New strategies for rapid, sensitive and high-throughput analysis of low abundance metabolites in biological samples are required for future metabolomic research. In this report, a direct method for sub-micromolar analyses of phosphoamino acids was developed using on-line sample preconcentration with 9-fluorenylmethyloxycarbonyl chloride (FMOC) derivatization by capillary electrophoresis (CE) and UV detection. Analyte focusing by dynamic pH junction and FMOC labeling efficiency were influenced by several experimental factors including buffer pH, ionic strength, sample injection length and FMOC concentration. About a 200-fold enhancement in concentration sensitivity was achieved under optimal conditions relative to conventional off-line derivatization, as reflected by a detection limit (S/N approximately 3) of 0.1 microM. In-capillary sample preconcentration with chemical labeling by CE offers a unique single-step analytical platform for high-throughput screening of low abundance metabolites without intrinsic chromophores.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".