One-Step Analysis of DNA/Chitosan Complexes by Field-Flow Fractionation Reveals Particle Size and Free Chitosan Content
Bibliographic record
Abstract
The composition of samples obtained upon complexation of DNA with chitosan was analyzed by asymmetrical flow field flow fractionation (AF4) with online UV-visible, multiangle light scattering (MALS), and dynamic light scattering (DLS) detectors. A chitosan labeled with rhodamine B to facilitate UV-vis detection of the polycation was complexed with DNA under conditions commonly used for transfection (chitosan glucosamine to DNA phosphate molar ratio of 5). AF4 analysis revealed that 73% of the chitosan-rhodamine remained free in the dispersion and that the DNA/chitosan complexes had a broad size distribution ranging from 20 to 160 nm in hydrodynamic radius. The accuracy of the data was assessed by comparison with data from batch-mode DLS and scanning electron microscopy. The AF4 combined with DLS allowed the characterization of small particles that were not detected by conventional batch-mode DLS. The AF4 analysis will prove to be an important tool in the field of gene therapy because it readily provides, in a single measurement, three important physicochemical parameters of the complexes: the amount of unbound polycation, the hydrodynamic size of the complexes, and their size distribution.
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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 | 0.001 | 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".