Influence of charge on FITC-BSA-loaded chondroitin sulfate-chitosan nanoparticles upon cell uptake in human Caco-2 cell monolayers
Bibliographic record
Abstract
BACKGROUND AND METHODS: Chondroitin sulfate-chitosan (ChS-CS) nanoparticles and positively and negatively charged fluorescein isothiocyanate-conjugated bovine serum albumin (FITC-BSA)-loaded ChS-CS nanoparticles were prepared and characterized. The properties of ChS-CS nanoparticles, including cellular uptake, cytotoxicity, and transepithelial transport, as well as findings on field emission-scanning electron microscopy, transmission electron microscopy, and confocal laser scanning microscopy were evaluated in human epithelial colorectal adenocarcinoma (Caco-2) fibroblasts. ChS-CS nanoparticles with a mean particle size of 250 nm and zeta potentials ranging from -30 to +18 mV were prepared using an ionic gelation method. RESULTS: Standard cell viability assays demonstrated that cells incubated with ChS-CS and FITC-BSA-loaded ChS-CS nanoparticles remained more than 95% viable at particle concentrations up to 0.1 mg/mL. Endocytosis of nanoparticles was confirmed by confocal laser scanning microscopy and measured by flow cytometry. Ex vivo transepithelial transport studies using Caco-2 cells indicated that the nanoparticles were effectively transported into Caco-2 cells via endocytosis. The uptake of positively charged FITC-BSA-loaded ChS-CS nanoparticles across the epithelial membrane was more efficient than that of the negatively charged nanoparticles. CONCLUSION: The ChS-CS nanoparticles fabricated in this study were effectively endocytosed by Caco-2 fibroblasts without significant cytotoxicity at high nanoparticle concentrations. ChS-CS nanoparticles represent a potential novel delivery system for the transport of hydrophilic macromolecules.
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".