Chitozyme: First Peroxidase-like Activity of Chitosan for Multiplexed Visual Detection of H <sub>2</sub> O <sub>2</sub> , Glucose and Lactate on Paper-based Device
Bibliographic record
Abstract
Abstract Visual read-out diagnostics tools are promising candidates for field applicable medical devices. Current colorimetric biosensors require introduction of natural enzymes or nanozymes, which has some serious drawbacks for practical applications. Chitosan, a natural polymer, provides safe and efficient compound in medical and pharmaceutical technology. Herein, we report on a simple, cost-efficient, field-portable, environmental friendly and ultra-sensitive multiplex detection platform based on peroxidase-like activity of chitosan in the presence of 3,3’,5,5’-Tetramethylbenzidine (TMBZ) and H 2 O 2 . This straight forward signal amplification strategy was successfully applied to detect H 2 O 2 , glucose and lactate with the limit of detection (LOD) of 2.64 pM, 0.104 μM and 2.8 nM respectively, represents the lowest LOD of H 2 O 2 , glucose and lactate with visual read-out. The chitosan-based assay performance was also retained in complex biological media for glucose and lactate detection. Furthermore, the proposed assay was successfully demonstrated as a paper-based colorimetric biosensor. Most importantly, the simplicity, biocompatibility and sensitivity of the proposed assay will open new doors for instrument free naked eye visual detection of H 2 O 2 , glucose and lactate detection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".