Bibliographic record
Abstract
Many applications using gold nanoparticles (AuNPs) require (i) their functionalization with a biopolymer to increase their stability and (ii) their transformation into an easy-to-handle material, which provide them with specific properties. In this research, a portable tablet platform is presented based on dextran-encapsulated gold nanoparticles (AuNPs-dTab) by a ligand exchange reaction between citrate-capped gold nanoparticles (AuNPs-Cit) and dextran. These newly fabricated tablets were characterized utilizing ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR), transmission electron microscopy (TEM), dynamic light scattering (DLS), X-ray diffraction spectroscopy (XRD), differential scanning calorimetry (DSC), and atomic force microscopy (AFM) techniques. The results showed that dextran-capped gold nanoparticles in a tablet platform (AuNPs-dTab) were well-dispersed and highly stable for at least a year at room temperature. In addition to particle and surface characterization of AuNPs-dTab, the tablet morphology in terms of thickness, diameter, density, and opacity was also measured using 6 and 10% dextran with 2, 4 and 8 nM AuNPs-Cit. We further investigated the pH-responsive behavior of AuNPs-dTab in the presence and absence of sodium chloride. Results showed that neutral and alkaline environments were suitable to render AuNPs dispersed in a tablet, while an acidic condition controls the aggregation rate of AuNPs as confirmed by concentration-dependent aggregation phenomena. Besides the easy fabrication, these tablets were portable and low-cost (approx. 1.22 CAD per 100 tablets of a 100 μL solution of dextran-capped gold nanoparticles (AuNPs-dSol)). The biocompatible nature of dextran along with the acidic medium trigger nature of AuNPs makes our proposed tablet a potential candidate for cancer therapy due to the acidic surrounding of tumor tissues as compared to normal cells. Also, our proposed tablet approach paves the way for the fabrication of portable and easy-to-use optical sensors based on the AuNPs embedded in a natural polymeric architecture that would serve as a colorimetric recognition indicator for detecting analytes of interest.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; both teacher heads agree on what is shown here.
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".