Cu immobilized on chitosan-modified iron oxide magnetic nanoparticles: Preparation, characterization and investigation of its anti-lung cancer effects
Bibliographic record
Abstract
Chitosan is a linear polysaccharide and non-toxic bioactive polymer with a wide variety of applications due to its functional properties such as ease of modification, and biodegradability. In this study, a green protocol for supporting of Cu(II) on chitosan-encapsulated magnetic Fe3O4 nanoparticles is described. The morphological and physicochemical features of the material were determined using several advanced techniques like fourier transformed infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), inductively coupled plasma (ICP), vibrating sample magnetometer (VSM) and X-ray photoelectron spectroscopy (XPS). The average diameter of the NPs was approximately 15–25 nm. In addition, the Fe3O/CS/Cu(II) nanocomposite was engaged in biological assays like study of anti-oxidant properties by DPPH mediated free radical scavenging test using BHT as a reference molecule. Thereafter, on having a significant IC50 value in radical scavenging assay, we extended the bio-application of the desired nanocomposite in anticancer study of lung well-differentiated bronchogenic adenocarcinoma, lung moderately differentiated adenocarcinoma, and lung poorly differentiated adenocarcinoma of human lung in-vitro conditions. In the cytotoxicity and anti-human lung studies, the nanocomposite was treated to lung cancer lung well-differentiated bronchogenic adenocarcinoma (HLC-1), lung moderately differentiated adenocarcinoma (LC-2/ad), and lung poorly differentiated adenocarcinoma (PC-14) cell line following MTT assay. The cell viability of malignant lung cell line reduced dose-dependently in the presence of Fe3O/CS/Cu(II) nanocomposite. The recent results suggest that Fe3O/CS/Cu(II) nanocomposite have a suitable anticancer activity against lung cell lines.
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 | 0.000 | 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 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".