Soft nanoparticles incorporating a benzo[<i>c</i>]xanthene fluorophore: facile synthesis and ratiometric pH sensing
Bibliographic record
Abstract
or physical encapsulation of the fluorophore. The characteristic high Stokes shift and ratiometric emission behaviour of SNAFL-C were retained in its polymer conjugate as well as in the self-assembled structures. Assemblies of the miktoarm fluorophore conjugate exhibited moderately reduced brightness as a result of aggregation induced quenching, an effect not observed for the physically encapsulated species. Fluorescence quenching experiments probing the partitioning of SNAFL-C in the core shell structures revealed localization of the primary fluorescent species in equilibrium based on their physiochemical properties, providing rationalization of differing aggregation behaviour observed for physically encapsulated and covalently linked formulations. Live cell fluorescence imaging in human glioblastoma cells integrating both SNAFL-C and its nanoformulations demonstrated the utility of the fluorophore in biological imaging applications and highlighted the necessity of detailed and stepwise spectral and photophysical evaluations. Collectively, these systems offer new avenues to explore fluorescence imaging using polymeric nanocarriers, leading to insights of broad importance to drug delivery and theragnostics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".