Lysine-functionalized nanodiamonds: synthesis, physiochemical characterization, and nucleic acid binding studies
Bibliographic record
Abstract
PURPOSE: Detonation nanodiamonds (NDs) are carbon-based nanomaterials that, because of their size (4-5 nm), stable inert core, alterable surface chemistry, fluorescence, and biocompatibility, are emerging as bioimaging agents and promising tools for the delivery of biochemical molecules into cellular systems. However, diamond particles possess a strong propensity to aggregate in liquid formulation media, restricting their applicability in biomedical sciences. Here, the authors describe the covalent functionalization of NDs with lysine in an attempt to develop nanoparticles able to act as suitable nonviral vectors for transferring genetic materials across cellular membranes. METHODS: NDs were oxidized and functionalized by binding lysine moieties attached to a three-carbon-length linker (1,3-diaminopropane) to their surfaces through amide bonds. Raman and Fourier transform infrared spectroscopy, zeta potential measurement, dynamic light scattering, atomic force microscopic imaging, and thermogravimetric analysis were used to characterize the lysine-functionalized NDs. Finally, the ability of the functionalized diamonds to bind plasmid DNA and small interfering RNA was investigated by gel electrophoresis assay and through size and zeta potential measurements. RESULTS: NDs were successfully functionalized with the lysine linker, producing surface loading of 1.7 mmol g(-1) of ND. These modified NDs formed highly stable aqueous dispersions with a zeta potential of 49 mV and particle size of approximately 20 nm. The functionalized NDs were found to be able to bind plasmid DNA and small interfering RNA by forming nanosized "diamoplexes". CONCLUSION: The lysine-substituted ND particles generated in this study exhibit stable aqueous formulations and show potential for use as carriers for genetic materials.
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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".