Dried blood spot on‐card derivatization: an alternative form of sample handling to overcome the instability of thiorphan in biological matrix
Bibliographic record
Abstract
Thiorphan, the active metabolite of racecadotril, can undergo oxidation in biological matrices such as blood and plasma. In bioanalysis, a general approach for the stabilization of such a molecule is to derivatize the thiol group to a more stable thioether, often requiring complex handling procedures at the clinical site. In this research, the concept of dried blood spot (DBS) on-card derivatization was evaluated to stabilize thiorphan. DBS cards were in-house pre-treated with 2-bromo-3'-methoxyacetophenone and left to dry prior to blood spotting. Thiorphan was shown to be effectively derivatized to thiorphan-methoxyacetophenone once applied on the in-house pre-treated cards. Thiorphan-methoxyacetophenone was extracted by soaking a 6 mm DBS punch in methanol containing the internal standard (thiorphan-methoxyacetophenone-D₅). Chromatographic separation was achieved on a Waters XBridge C₁₈ column with a gradient elution of 5 mM NH₄HCO₃ and methanol in 2.5 min and detection by ESI(+)/MS/MS. A linear (weighted 1/x²) relationship was obtained over a concentration range of 5.00-600.00 ng/mL. The assay met regulatory guidelines acceptance criteria for sensitivity, selectivity, precision and accuracy, matrix effect, recovery, dilution integrity and multiple stability evaluations. The DBS on-card derivatization has shown to be an easy and reliable alternative form of sample collection for the quantification of thiorphan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".