Design of Smart Nanodiamonds: Introducing pH Sensitivity to Improve Nucleic Acid Carrier Efficiency of Diamoplexes
Bibliographic record
Abstract
The mechanism of cellular uptake and intracellular fate of nanodiamond/nucleic acid complexes (diamoplexes) are major determinants of its performance as a gene carrier. Our group designed lysine-nanodiamonds (K-NDs) as vectors for nucleic acid delivery. In this work, we modified the surface of K-NDs with histidine to overcome endo-lysosomal entrapment diamoplexes, the major rate limiting step in gene transfer. Histidine is conjugated onto the NDs in two configurations: lysyl-histidine-NDs (HK-NDs) where histidine is loaded on 100% of the lysine moieties and lysine/lysyl-histidine-NDs (H50K50-NDs) where histidine is loaded on 50% of the lysine moieties. Both HK-NDs and H50K50-NDs maintained the optimum size distribution (i.e., <200 nm) and a cationic surface (zeta potential > 20 mV), similar to K-NDs. HK-NDs binds plasmid deoxyribonucleic acid (pDNA) and small interfering ribonucleic acid (siRNA) forming diamoplexes at mass ratios of 10:1 and 60:1, respectively. H50K50-NDs significantly improved nucleic acid binding, forming diamoplexes at a 2:1 mass ratio with pDNA and a 30:1 mass ratio with siRNA, which are at values similar to the K-NDs. The amount of histidine on the surface also impacted the interactions with mammalian cells. The HK-NDs reduced the cell viability by 30% at therapeutic concentrations, while H50K50-NDs maintained more than 90% cell viability, even at the highest concentrations. H50K50-NDs also showed highest cellular uptake within 24 h, followed by K-NDs and HK-NDs. Most functionalized NDs show cellular exit after 5 days, leaving less than 10% of cells with internalized diamonds. The addition of histidine to the ND resulted in higher transfection of anti-green fluorescent protein siRNA (anti-GFP siRNA) with the fraction of GFP knockdown being 0.8 vs. 0.6 for K-NDs at a mass ratio of 50:1. H50K50-NDs further improved transfection by achieving a similar fraction of GFP knockdown (0.8) at a lower mass ratio of 30:1. Overall, this study provides evidence that the addition of histidine, a pH-modulating entity in the functionalization design at an optimized ratio, renders high efficiency to the diamoplexes. Further studies will elucidate the uptake mechanism and intracellular fate to build the relationship between physicochemical characteristics and biological efficacy and create a platform for solid-core nanoparticle-based gene delivery.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".