Exploiting Activated Alkyne Chemistry for the Synthesis of Tailored Amphiphilic Janus Dendrimers with Aggregation‐Induced Emission and Their Assemblies for Cell Imaging
Bibliographic record
Abstract
Amphiphilic Janus dendrimers (AJDs) are a promising class of macromolecules capable of self-assembling into well-defined nanostructures. In this study, AJDs were synthesized employing, for the first time, the activated alkyne-hydroxyl "click" chemistry approach, enabling the construction of dendritic architectures under mild conditions. The AJDs were functionalized with a π-extended tetraphenylethylene (TPE) derivative, imparting aggregation-induced emission (AIE) property. These AJDs self-assembled into fluorescent nanostructures, including micelles and dendrimersomes, with tunable dimensions. The AIE-active assemblies demonstrated strong photoluminescence upon formation and were characterized by narrow size distributions. Cytotoxicity and cellular uptake studies using Chinese Hamster Ovary K1 (CHO-K1) cells revealed excellent biocompatibility and efficient cellular internalization, confirming their potential for live-cell imaging. Importantly, the extended π-conjugation of the TPE derivative facilitated excitation at longer wavelengths, compatible with conventional confocal microscopy. This work showcases the versatility of activated alkyne-hydroxyl "click" chemistry in dendrimer synthesis and highlights the potential of these AJD-based nanostructures in nanomedicine, particularly for imaging and diagnostic applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".