Biocompatible Solid-Phase Microextraction Coatings Based on Polyacrylonitrile and Solid-Phase Extraction Phases
Bibliographic record
Abstract
The applications of solid-phase microextraction (SPME) are continuously expanding, and one of the most interesting current aspects consists of applying SPME for fast analysis of biological fluids. The goal of this study is to develop biocompatible SPME coatings that can be utilized for in vivo and in vitro extractions, in direct contact with a biological matrix such as blood or tissue. The biocompatibility of the proposed new coatings is confirmed by X-ray photoelectron spectroscopy, and their performance is tested by developing an SPME/HPLC method for analysis of verapamil, loperamide, diazepam, nordiazepam, and warfarin in buffer solutions and in human plasma. The coatings prove to be biocompatible by not adsorbing proteins and are successfully applied for fast drug analysis and assay of drug plasma protein binding.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".