Co-immobilization of multiple enzymes by metal coordinated nucleotide hydrogel nanofibers: improved stability and an enzyme cascade for glucose detection
Why this work is in the frame
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Bibliographic record
Abstract
Preserving enzyme activity and promoting synergistic activity via co-localization of multiple enzymes are key topics in bionanotechnology, materials science, and analytical chemistry. This study reports a facile method for co-immobilizing multiple enzymes in metal coordinated hydrogel nanofibers. Specifically, four types of protein enzymes, including glucose oxidase, Candida rugosa lipase, α-amylase, and horseradish peroxidase, were respectively encapsulated in a gel nanofiber made of Zn(2+) and adenosine monophosphate (AMP) with a simple mixing step. Most enzymes achieved quantitative loading and retained full activity. At the same time, the entrapped enzymes were more stable against temperature variation (by 7.5 °C), protease attack, extreme pH (by 2-fold), and organic solvents. After storing for 15 days, the entrapped enzyme still retained 70% activity while the free enzyme nearly completely lost its activity. Compared to nanoparticles formed with AMP and lanthanide ions, the nanofiber gels allowed much higher enzyme activity. Finally, a highly sensitive and selective biosensor for glucose was prepared using the gel nanofiber to co-immobilize glucose oxidase and horseradish peroxidase for an enzyme cascade system. A detection limit of 0.3 μM glucose with excellent selectivity was achieved. This work indicates that metal coordinated materials using nucleotides are highly useful for interfacing with biomolecules.
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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