Electrochemical-Surface Enhanced Raman Spectroscopic (EC-SERS) Study of 6-Thiouric Acid: A Metabolite of the Chemotherapy Drug Azathioprine
Bibliographic record
Abstract
Abstract 6-Thiouric acid (6-TUA) has the potential to be an important biomarker for the action of 6-mercaptopurine (6-MP), an immunosuppressive drug used in patients suffering from acute lymphoblastic leukemia (ALL). 6-TUA, a nonactive metabolite of 6-MP, is excreted in the urine, and routine monitoring of this metabolite can be useful in assessing the efficacy of 6-MP for immune system suppression in patients who have undergone stem cell replacement. In this work, electrochemical surface-enhanced Raman spectroscopy (EC-SERS) is used for the first time to study the adsorption and electrochemical behavior of 6-TUA at a nanostructured silver electrode surface, in both 0.1 M NaF and synthetic urine as supporting electrolytes. In addition, ab initio calculations were completed in an effort to understand the adsorption behavior. It was found that EC-SERS provided excellent signal for 6-TUA down to μM concentrations in synthetic urine and highlights the future potential of EC-SERS for rapid detection of important urine biomarkers at the patient point-of-care.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".