Reusable Solid-Phase Microextraction Coating for Direct Immersion Whole-Blood Analysis and Extracted Blood Spot Sampling Coupled with Liquid Chromatography–Tandem Mass Spectrometry and Direct Analysis in Real Time–Tandem Mass Spectrometry
Bibliographic record
Abstract
Three different biocompatible polymers were tested and evaluated in order to improve the whole-blood biocompatibility of previously developed C18-polyacrylonitrile (C18-PAN) thin-film solid-phase microextraction (SPME) coating. Among all methods of modification, UV-dried thin PAN-over C18-PAN provided the best results. This coating presented reusable properties and reproducible extraction efficiency for at least 30 direct extractions of diazepam from whole blood [relative standard deviation (RSD) = 12% using external calibration and 4% using isotope dilution calibration]. The amount of absolute recovery for direct immersion analysis and based on the free concentration of diazepam in blood matrix was about 4.8% (desorption efficiency = 98%). The limit of quantitation (LOQ) for the developed solid-phase microextraction liquid chromatography-tandem mass spectrometry (SPME-LC-MS/MS) method for direct whole-blood analysis was 0.5 ng/mL. The optimized modification of the coating was then used for an extracted blood spot (EBS) sampling approach, a new sampling method which is introduced to address the limitations of dried blood spot sampling. EBS was evaluated using LC-MS/MS and direct analysis in real time (DART)-MS/MS, where, for a 5 μL blood spot, LOQs of 0.2 and 1 μg/mL, respectively, were achieved for extraction of diazepam.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".