Aptamer-Functionalized Hydrogel Microparticles for Fast Visual Detection of Mercury(II) and Adenosine
Why this work is in the frame
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Bibliographic record
Abstract
With a low optical background, high loading capacity, and good biocompatibility, hydrogels are ideal materials for immobilization of biopolymers to develop optical biosensors. We recently immobilized mercury and lead binding DNAs within a monolithic gel and demonstrated ultrasensitive visual detection of these heavy metals. The high sensitivity was attributed to the enrichment of the analytes into the gels. The signaling kinetics was slow, however, taking about 1 h to obtain a stable optical signal because of a long diffusion distance. In this work, we aim to understand the analyte enrichment process and improve the signaling kinetics by preparing hydrogel microparticles. DNA-functionalized gel beads were synthesized using an emulsion polymerization technique and most of the beads were between 10 and 50 μm. Acrydite-modified DNA was incorporated by copolymerization. Visual detection of 10 nM Hg(2+) was still achieved and a stable signal was obtained in just 2 min. The gel beads could be spotted to form a microarray and dried for storage. A new visual sensor for adenosine was designed and immobilized within the gel beads. The adenosine aptamer binds its target about 1000-fold less tightly compared to the mercury binding DNA, allowing a comparison to be made on analyte enrichment by aptamer-functionalized hydrogels.
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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 | 0.000 | 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 it