Turning Toxic Nanomaterials into a Safe and Bioactive Nanocarrier for Co-delivery of DOX/pCRISPR
Bibliographic record
Abstract
Hybrid bioactive inorganic–organic carbon-based nanocomposites of reduced graphene oxide (rGO) nanosheets enlarged with multi-walled carbon nanotubes (MWCNTs) were decorated to provide a suitable space for in situ growth of CoNi 2 S 4 and green-synthesized ZnO nanoparticles. The ensuing nanocarrier supplied π–π interactions between the DOX drug and a stabilizing agent derived from leaf extracts on the surface of ZnO nanoparticles and hydrogen bonds; gene delivery of (p)CRISPR was also facilitated by chitosan and alginate renewable macromolecules. Also, these polymers can inhibit the potential interactions between the inorganic parts and cellular membranes to reduce the potential cytotoxicity. Nanocomposite/nanocarrier analyses and sustained DOX delivery (cytotoxicity analyses on HEK-293, PC12, HepG2, and HeLa cell lines after 24, 48, and 72 h) were indicative of an acceptable cell viability of up to 91.4 and 78.8% after 48 at low and high concentrations of 0.1 and 10 μg/mL, respectively. The MTT results indicate that by addition of DOX to the nanostructures, the relative cell viability increased after 72 h of treatment; since the inorganic compartments, specifically CoNi 2 S 4, are toxic, this is a promising route to increase the bioavailability of the nanocarrier before reaching the targeted cells. Nanosystems were tagged with (p)CRISPR for co-transfer of the drug/genes, where confocal laser scanning microscopy (CLSM) pictures of the 4′,6-diamidino-2-phenylindole (DAPI) were indicative of appropriate localization of DOX into the nanostructure with effective cell and drug delivery at varied pH. Also, the intrinsic toxicity of CoNi 2 S 4 does not affect the morphology of the cells, which is a breakthrough. Furthermore, the CLSM images of the HEK-293 and HeLa cell displayed effective transport of (p)CRISPR into the cells with an enhanced green fluorescent protein (EGFP) of up to 8.3% for the HEK-293 cell line and 21.4% for the HeLa cell line, a record. Additionally, the specific morphology of the nanosystems before and after the drug/gene transport events, via images by TEM and FESEM, revealed an intact morphology for these biopolymers and their complete degradation after long-time usage.
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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".