Enhanced detection of porphyrins by capillary electrophoresis-laser induced fluorescence
Bibliographic record
Abstract
A highly sensitive technique for the analysis of urinary porphyrins using capillary electrophoresis (CE) coupled with laser-induced fluorescence (LIF) detection is reported. Separation of mesoporphyrin IX, coproporphyrin, uroporphyrin and the penta-, hexa- and heptacarboxylic acid porphyrins was achieved in 11 min using a 10 mM 2-(N-cyclohexylamino)ethanesulfonic acid (CHES, pH 10) -75 mM sodium dodecyl sulfate (SDS) buffer. Migration time and peak area repeatability were less than 1 and 5% relative standard deviation (RSD), respectively. Limits of detection of 20 pM (2 x 10(-11) M) were achieved employing the recently introduced Nichia violet diode laser for excitation at 400 nm. This represents an enhancement in sensitivity of over two orders of magnitude compared to previous reports. This high sensitivity for urinary porphyrins was demonstrated through the quantification of coproporphyrin and uroporphyrin in urine samples after up to a 100-fold dilution.
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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 | 0.001 |
| 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) | 0.002 | 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".