A pH-responsive amphiphilic chitosan–pyranine core–shell nanoparticle for controlled drug delivery, imaging and intracellular pH measurement
Bibliographic record
Abstract
A pH-responsive multifunctional core-shell nanoparticle, named CHC-PY nanoparticle, was successfully synthesized through electrostatic interaction of a thin shell of fluorescent pyranine dye (PY) with amphiphilic carboxymethylhexanoyl chitosan (CHC) nanoparticles. Upon encapsulating an anticancer drug, camptothecin (CPT), the CHC-PY nanoparticles exhibited an excellent drug loading efficiency (>95%). The resulting CPT-loaded CHC-PY nanoparticles also exhibited efficient cell internalization and good pH-responsive behavior. After being internalized (via efficient endocytosis pathway), the presence of fluorescent PY shell showed a pH-dependent emission characteristic which allowed the internalized CHC-PY nanoparticles acting as an indicator to distinguish the acidic microenvironment of cancerous cells, compared with normal cells. The pH-sensitive PY shell also acted as a modulator to control the CPT release wherein a higher release rate was detected at lower pH value, which is essentially a potential therapeutic niche for anticancer purposes. This new type of CHC-PY core-shell nanoparticle provides multiple functionality, where a synergistic performance of nanotherapeutics, imaging and even diagnosis at a cellular resolution can be achieved simultaneously.
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 | 0.001 | 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".