Chiral separation of benzoporphyrin derivative mono- and diacids by laser induced fluorescence-capillary electrophoresis
Bibliographic record
Abstract
A method for the separation of benzoporphyrin derivative mono- and diacid (BPDMA, BPDDA) enantiomers by laser induced fluorescence-capillary electrophoresis (LIF-CE) has been developed. By using 300 mM borate buffer, pH 9.2, 25 mM sodium cholate and 10% acetronitrile as electrolyte, +10 kV electrokinetic sampling injection of 2 s and an applied +20 kV voltage across the ends of a 37 cm capillary (30 cm to the detector, 50 microm ID), all six BPD stereoisomers were baseline-separated within 20 min. Formation constants, free electrophoretic and complexation mobilities with borate and cholate were determined based on dynamic complexation capillary electrophoresis theory. The BPD enantiomers can be quantitatively determined in the range of 10(-2)-10(-5) mg mL(-1). The correlation coefficients (r2) of the least-squares linear regression analysis of the BPD enantiomers are in the range of 0.9914-0.9997. Their limits of detection are 2.18-3.5 x 10(-3) mg mL(-1). The relative standard deviations for the separation were 2.90-4.64% (n = 10). In comparison with high-performance liquid chromatography (HPLC), CE has better resolution and efficiency. This separation method was successfully applied to the BPD enantiomers obtained from a matrix of bovine serum and from liposomally formulated material as well as from studies with rat, dog and human microsomes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".