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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it