Iron oxide nanoparticles were synthesized starting from two aqueous extracts based on L. leaf and stems, employing a simplest, eco-friendliness and low toxicity method-green synthesis. The nanoparticles were characterized by powder X-ray diffraction (XRD), Fourier transformed infrared spectroscopy (FT-IR), X-ray fluorescence analysis (XRF), thermal analysis (TG/DSC), and scanning electron microscopy (SEM). Lack of magnetic properties and the reddish-brown color of all the samples confirms the presence of hematite as majority phase. The FTIR bands located at 435 cm and 590 cm, are assigned to Fe-O stretching vibration from hematite, confirming the formation of α-FeO nanoparticles (NPs). The in vitro screening of the samples revealed that the healthy cell line (HaCaT) presents a good viability (above 80%) after exposure to iron oxide NPs and lack of apoptotic features, while the tumorigenic cell lines manifested a higher sensitivity, especially the melanoma cells (A375) when exposed to concentration of 500 µg/mL iron oxide NPs for 72 h. Moreover, A375 cells elicited significant apoptotic markers under these parameters (concentration of 500 µg/mL iron oxide NPs for a contact time of 72 h).
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http://dx.doi.org/10.3390/nano12122012 | DOI Listing |
Curr Cancer Drug Targets
January 2025
Department of Clinical Laboratory, Gongli Hospital of Shanghai Pudong New Area, Shanghai, 200135, China.
Background: Lenvatinib is an oral tyrosine kinase inhibitor that selectively inhib-its receptors involved in tumor angiogenesis and tumor growth. It is an emerging first-line treatment agent for hepatocellular carcinoma (HCC). However, there is no intravenous ad-ministration of Lenvatinib.
View Article and Find Full Text PDFCurr Org Synth
January 2025
Stem Cells Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Introduction: The development of efficient and sustainable catalytic methodolo-gies has garnered considerable attention in contemporary organic synthesis.
Methods: Herein, we present a novel approach employing the Cu@DPP-SPION catalyst for the synthesis of ethyl 4-(aryl)-6-methyl-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate derivatives. This versatile catalytic system incorporates copper nanoparticles supported on 4-(1H-imidazo[4,5-f][1,10]phenanthrolin-2-yl)benzoic acid-functionalized superparamagnetic iron oxide nanoparticles (SPIONs).
J Am Chem Soc
January 2025
Chemical Engineering, School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, Arizona 85287, United States.
Visualizing the structure of the protein-inorganic interface is critically important for a more complete understanding of biomineralization. Unfortunately, there are limited approaches for the direct and detailed study of biomolecules that interact with inorganic materials. Here, we use single-particle cryo-electron microscopy (cryo-EM) to study the protein-nanoparticle (NP) interactions of human light chain ferritin and visualize the high-resolution details of the protein-inorganic interface.
View Article and Find Full Text PDFJ Nanobiotechnology
January 2025
State Key Laboratory of Pharmaceutical Biotechnology, Division of Sports Medicine and Adult Reconstructive Surgery, Department of Orthopedic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, 321 Zhongshan Road, Nanjing, 210008, People's Republic of China.
RNA interference (RNAi) and oxidative stress inhibition therapeutic strategies have been extensively utilized in the treatment of osteoarthritis (OA), the most prevalent degenerative joint disease. However, the synergistic effects of these approaches on attenuating OA progression remain largely unexplored. In this study, matrix metalloproteinase-13 siRNA (siMMP-13) was incorporated onto polyethylenimine (PEI)-polyethylene glycol (PEG) modified FeO nanoparticles, forming a nucleic acid nanocarrier termed si-Fe NPs.
View Article and Find Full Text PDFSci Rep
January 2025
Renewable Energy Research Group, Isfahan, Iran.
The performance of nanofluids is largely determined by their thermophysical properties. Optimizing these properties can significantly enhance nanofluid performance. This study introduces a hybrid strategy based on computational intelligence to determine the optimal conditions for ternary hybrid nanofluids.
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