Docetaxel-Loaded Disulfide Cross-Linked Nanoparticles Derived from Thiolated Sodium Alginate for Colon Cancer Drug Delivery
Bibliographic record
Abstract
In this study, fluorescein-labelled wheat germ agglutinin (fWGA)-conjugated disulfide cross-linked sodium alginate nanoparticles were developed to specifically target docetaxel (DTX) to colon cancer cells. Different amounts of 3-mercaptopropionic acid (MPA) were covalently attached to sodium alginate to form thiolated sodium alginate (MPA1-5). These polymers were then self-assembled and air-oxidised to form disulfide cross-linked nanoparticles (MP1-5) under sonication. DTX was successfully loaded into the resulting MP1-5 to form DTX-loaded nanoparticles (DMP1-5). DMP2 had the highest loading efficiency (17.8%), thus was chosen for fWGA surface conjugation to form fWGA-conjugated nanoparticles (fDMP2) with a conjugation efficiency of 14.1%. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) analyses showed spherical nanoparticles, and an in vitro drug release study recorded a cumulative drug release of 48.6%. Dynamic light scattering (DLS) analysis revealed a mean diameter (MD) of 289 nm with a polydispersity index (PDI) of 0.3 and a zeta potential of -2.2 mV for fDMP2. HT-29 human colon cancer cells treated with fDMP2 showed lower viability than that of L929 mouse fibroblast cells. These results indicate that fDMP2 was efficiently taken up by HT-29 cells (29.9%). Fluorescence and confocal imaging analyses also showed possible internalisation of nanoparticles by HT-29 cells. In conclusion, fDMP2 shows promise as a DTX carrier for colon cancer drug delivery.
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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".