Mechanistic insight to ROS and Apoptosis regulated cytotoxicity inferred by Green synthesized CuO nanoparticles from Calotropis gigantea to Embryonic Zebrafish
Bibliographic record
Abstract
With the rapid development of nanotechnology, much has been anticipated with copper oxide nanoparticles (CuO NP) due to their extensive industrial and commercial application. However, it has raised concern over the environmental safety and human health effects. In this study, CuO nanoparticles were synthesized using the green method with floral extract of Calotropis gigantea and characterized by standard physiochemical techniques like DLS, Zeta potential determination, UV- Visible Spectroscopy, XRD, FTIR, FESEM, and TEM. Mechanistic cytotoxicity studies were performed using experimental and computational assays including morphological analysis, hatching, and viability rate analysis along with ROS and apoptosis analysis. Physiochemical characterization of CuO NP determined the size and zeta potential of synthesized nanoparticles to be 30 ± 09 nm to 40 ± 2 nm and -38 mV ± 12 mV respectively. Cytotoxicity evaluation with Zebrafish revealed malfunctioned organ development with differential viability and hatching rate at 48 hpf and 72 hpf with LC50 of 175 ± 10 mg/l. Computational analysis depicted the influential role of CuO nanoparticles on zebrafish embryo's he1a, sod1 and p53 functional expression through hydrophobic and hydrogen bond interaction with amino acid residues. Study demonstrated valuable information of cytotoxic impact which can be influential in further studies of their eco-toxicological effects.
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 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".