Concave Magnetic-Responsive Hydrogel Discs for Enhanced Bioassays
Bibliographic record
Abstract
Receptor-based biosensors often suffer from slow analyte diffusion, leading to extended assay times. Moreover, existing methods to enhance diffusion can be complex and costly. In response to this challenge, we presented a rapid and cost-effective technique for fabricating concave magnetic-responsive hydrogel discs (CMDs) by straightforward pipetting directly onto microscope glass slides. This approach enables immediate preparation and customization of hydrogel properties such as porosity, magnetic responsiveness, and embedded particles and is adaptable for use with microarray printers. The concave design increased the surface area by 43% compared to conventional hemispherical hydrogels, enhancing diffusion rates and accelerating reactions. By incorporating superparamagnetic particles, the hydrogels become magnetically responsive, allowing for stirring within reagent droplets using magnets to improve mixing. Our experimental results showed that CMDs dissolved approximately 2.5 times faster than hemispherical ones. Numerical simulations demonstrated up to a 46% improvement in diffusion speed within the hydrogel. Particles with lower diffusion coefficients, like human antibodies, benefited most from the concave design, resulting in faster biosensor responses. The increased surface area and ease of fabrication make our CMDs efficient and adaptable for various biological and biomedical applications, particularly in point-of-care diagnostics where rapid and accurate biomarker detection is critical.
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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 | 0.000 |
| 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".