Electrophoretic Analysis of Biomarkers using Capillary Modification with Gold Nanoparticles Embedded in a Polycation and Boron Doped Diamond Electrode
Bibliographic record
Abstract
Field-amplified sample stacking using a fused silica capillary coated with gold nanoparticles (AuNPs) embedded in poly(diallyl dimethylammonium) chloride (PDDA) has been investigated for the electrophoretic separation of indoxyl sulfate, homovanillic acid (HVA), and vanillylmandelic acid (VMA). AuNPs (27 nm) exhibit ionic and hydrophobic interactions, as well as hydrogen bonding with the PDDA network to form a stable layer on the internal wall of the capillary. This approach reverses electro-osmotic flow allowing for fast migration of the analytes while retarding other endogenous compounds including ascorbic acid, uric acid, catecholamines, and indoleamines. Notably, the two closely related biomarkers of clinical significance, HVA and VMA, displayed differential interaction with PDDA-AuNPs which enabled the separation of this pair. The detection limit of the three analytes obtained by using a boron doped diamond electrode was approximately 75 nM, which was significantly below their normal physiological levels in biological fluids. This combined separation and detection scheme was applied to the direct analysis of these analytes and other interfering chemicals including uric and ascorbic acids in urine samples without off-line sample treatment or preconcentration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".