Microdialysis SPR: diffusion-gated sensing in blood
Bibliographic record
Abstract
Chemical measurements are rarely performed in crude blood due to the poor performance of sensors and devices exposed to biofluids. In particular, biosensors have been severely limited for detection in whole blood due to surface fouling from proteins, the interaction of cells with the sensor surface and potential optical interference when considering optical methods of analysis. To solve this problem, a dialysis chamber was introduced to a surface plasmon resonance (SPR) biosensor to create a diffusion gate for large molecules. This dialysis chamber relies on the faster migration of small molecules through a microporous membrane towards a sensor, located at a specified distance from the membrane. Size filtering and diffusion through a microporous membrane restricted the access of blood cells and larger biomolecules to a sensing chamber, while smaller, faster diffusing biomolecules migrated preferentially to the sensor with limited interference from blood and serum. The affinity of a small peptide (DBG178) with anti-atherosclerotic activity and targeting type B scavenger receptor CD36 was successfully monitored at micromolar concentrations in human serum and blood without any pre-treatment of the sample. This concept could be generally applied to a variety of targets for biomolecular interaction monitoring and quantification directly in whole blood, and could find potential applications in biochemical assays, pharmacokinetic drug studies, disease treatment monitoring, implantable plasmonic sensors, and point-of-care diagnostics.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".