DNA/chitosan nanoparticles: internalization and cytokines production by human elutriated monocytes and Thp-1 macrophages
Bibliographic record
Abstract
Summary form only given. We have synthesized a non-viral gene delivery system based on chitosan, a cationic biocompatible and biodegradable polymer, comprising amino groups and a plasmid DNA. Chitosan interact with and neutralize the negatively-charged DNA. This results in a more compact DNA structure leading to the formation of nanoparticles with a mean size of 75 nm. Previous studies have shown efficient cell transfection and b galactosidasc expression. The present work is focusing on THP-1 macrophages and human elutriated monocytes interaction with the nanoparticles. This is of primordial importance either in the design of more effective therapeutic strategies for macrophage associated pathogenesis or in establishing new approaches for pharmacological action avoiding macrophages. Internalization and cytokine (IL-6, IL-10, TNF-a) and MMP-2, MMP-9 metalloproteinase production were assessed to investigate the inflammatory reaction. Flow cytometry and fluorescence microscopy were used, after FITC nanoparticle labeling. The results show that most of the nanoparticles are internalized within the first hour by macrophages and that human monocytes are more sensitive than macrophages in terms of cytokine production. This system could be used to modulate macrophage function using gene therapy. This could result in new approaches to treat diseases where macrophage activity plays a major role, such as rheumatoid arthritis and infectious diseases.
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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".