Aggregation and Particle Formation of tRNA by Dendrimers
Bibliographic record
Abstract
Major attention has been focused on dendrimer-DNA complexes because of their applications in gene delivery systems. Dendrimers are also used to transport miRNA and siRNA in vitro. We examine the interaction of tRNA with several dendrimers of different compositions, mPEG-PAMAM (G3), mPEG-PAMAM (G4), and PAMAM (G4) under physiological conditions using constant tRNA concentration and various dendrimer contents. FTIR, UV-visible, and CD spectroscopic methods as well as atomic force microscopy (AFM) were used to analyze the macromolecule binding mode, the binding constant, and the effects of dendrimer complexation on RNA stability, aggregation, particle formation, and conformation. Structural analysis showed that dendrimer-tRNA complexation occurred via RNA bases and the backbone phosphate group with both hydrophilic and hydrophobic contacts. The overall binding constants of K(mPEG-G3) = 7.6 (± 0.9) × 10(3) M(-1), K(mPEG-G4) = 1.5 (± 0.40) × 10(4) M(-1), and K(PAMAM-G4) = 5.3 (± 0.60) × 10(4) M(-1) show stronger polymer-RNA complexation by PAMAM-G4 than pegylated dendrimers. RNA remains in the A-family structure, whereas biopolymer aggregation and particle formation occurred at high polymer concentrations.
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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".