Folic acid-conjugated amphiphilic alternating copolymer as a new active tumor targeting drug delivery platform
Bibliographic record
Abstract
Targeted drug delivery using polymeric nanostructures is an emerging cancer research area, engineered for safer, more efficient, and effective use of chemotherapeutic drugs. A pH-responsive, active targeting delivery system was designed using folic acid functionalized amphiphilic alternating copolymer poly(styrene-alt-maleic anhydride) (FA-DABA-SMA) via a biodegradable linker 2,4-diaminobutyric acid (DABA). The polymeric template is pH responsive, forming amphiphilic nanostructures at pH 7, allowing the encapsulation of hydrophobic drugs on its interior. Moreover, the structure is stable only at neutral pH and collapses in the acidic tumor microenvironment, releasing drugs on-site from its core. The delivery vehicle is investigated using human pancreatic PANC-1 cancer cells and RAW-Blue™ mouse macrophage reporter cell line, both of which have overly expression of folic acid receptors. To trace the cellular uptake by both cell lines, curcumin was selected as a dye and drug mimic owing to its fluorescence nature and hydrophobic properties. Fluorescent microscopy of FA-DABA-SMA loaded with curcumin revealed a significant internalization of the dye by human pancreatic PANC-1 cancer cells compared to those with unfunctionalized polymers (SMA). Moreover, the FA-DABA-SMA polymers exhibit rodlike association specific to the cells. Both empty SMA and FA-DABA-SMA show little toxicity to PANC-1 cells as characterized by WST-1 cell proliferation assay. These results clearly indicate that FA-DABA-SMA polymers show potential as an active tumor targeting drug delivery system with the ability to internalize hydrophobic chemotherapeutics after they specifically attach to cancer cells.
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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".