Bioorthogonal click chemistry-mediated conjugation of an anti-DR4 antibody to gold nanorods enhances its pro-apoptotic activity under near infra-red-light stimulation
Bibliographic record
Abstract
Pro-apoptotic receptor activators (PARAs), including second-generation agonist antibodies and ligands targeting the TNF receptor superfamily such as TRAIL (TNF-Related Apoptosis-Inducing Ligand), represent a promising class of cancer therapeutics. Enhancing their apoptotic efficacy through multivalency or controlled thermal stimulation has been previously demonstrated. In this study, we report the design and optimization of gold nanorod (GNR)-based nanoconjugates for targeted PARA delivery under near-infrared (NIR)-induced mild hyperthermia. Three conjugation strategies—EDC/NHS coupling, Schiff base formation, and strain-promoted azide–alkyne cycloaddition (SPAAC)—were systematically evaluated. Surface functionalization of GNRs with –COOH, –NH 2 , and −DBCO groups was confirmed via UV–vis spectroscopy, surface-enhanced Raman spectroscopy (SERS), X-ray photoelectron spectroscopy (XPS), zeta potential analysis, and transmission electron microscopy (TEM). Bioactivity assays indicated that SPAAC-mediated click chemistry enabled superior retention of PARA functionality compared to conventional methods. Notably, GNRs conjugated with an anti-DR4 antibody selectively triggered apoptosis in cancer cells upon NIR exposure. These results demonstrate that SPAAC-mediated functionalization enables precise, bioactive nanocarriers for enhanced cancer cell apoptosis under photothermal control
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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 | 0.000 | 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 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".