Stimuli Responsive Molecular Exchange of Structure Directing Agents on Gold Nanobipyramids: Cancer Cell Detection and Synergistic Therapeutics
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Bibliographic record
Abstract
Surface-engineered gold nanoparticles have been considered as versatile systems for theranostics applications. Moreover, surface covering or stabilizing agents on gold nanoparticles especially gold nanobipyramids (AuNBPs) provides an extra space for cargo molecules entrapment. However, it is not well studied yet and also the preparation of AuNBPs still remains dependent largely on cetyltrimethylammonium bromide (CTAB), a cytotoxic surfactant. Therefore, the direct use of CTAB stabilized nanoparticles is not recommended for cancer theranostics applications. Herein, we address an approach of dodecyl ethyl dimethylammonium bromide (DMAB) as biocompatible structure directing agent for AuNBPs, which also accommodate anticancer drug doxorubicin (45%), an additional chemotherapeutics agent. Upon near-infrared light (NIR, 808 nm) exposure, engineered AuNBPs exhibit (i) better phototransduction (51 °C) due to NIR absorption ability (650-900 nm), (ii) photo triggered drug release (more than 80%), and (iii) synergistic chemophototherapy for breast cancer cells. Drug release response has been evaluated in tumor microenvironment conditions (84% in acidic pH and 80% at high GSH) due to protonation and high affinity of thiol binding with AuNBPs followed by DMAB replacement. Intracellular glutathione (GSH, 5-7.5 mM) replaces DMAB from AuNBPs, which cause easy aggregation of nanoparticles as corroborated by colorimetric shifts, suggesting their utilization as a molecular sensing probe of early stage cancer biomarkers. Our optimized recipe yield is monodisperse DMAB-AuNBPs with ∼90% purity even at large scales (500 mL volume per batch). DMAB-AuNBPs show better cell viability (more than 90%) across all concentrations (5-500 ug/mL) when directly compared to CTAB-AuNBPs (less than 10%). Our findings show the potential of DMAB-AuNBPs for early stage cancer detection and theranostics applications.
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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