Stable J‐Aggregation of an aza‐BODIPY‐Lipid in a Liposome for Optical Cancer Imaging
Bibliographic record
Abstract
Abstract Organic building blocks are the centerpieces of “one‐for‐all” nanoparticle development. Herein, we report the synthesis of a novel aza‐BODIPY‐lipid building block and its self‐assembly into a liposomal nanoparticle (BODIPYsome). We observed optically stable NIR J‐aggregation within the BODIPYsome that is likely attributed to J‐dimerization. BODIPYsomes with cholesterol showed enhanced colloidal stability while maintaining a high extinction coefficient (128 mm−1 cm−1) and high fluorescence quenching (99.70±0.09 %), which enables photoacoustic (PA) properties from its intact structure and recovered NIR fluorescence properties when it is disrupted in cancer cells. Finally, its capabilities for optical imaging (PA/fluorescence) were observed in an orthotopic prostate tumor mouse model 24 h after intravenous administration. Overall, the BODIPYsome opens the door for engineering new building blocks in the design of optically stable biophotonic imaging agents.
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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) | 0.000 | 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 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".