CdO nanoparticles,c‐MWCNT nanoparticles and CdO nanoparticles/c‐MWCNT nanocomposite fibres: in vitro assessment of anti‐proliferative and apoptotic studies in HeLa cancer cell line

A simple ultrasonic assisted chemical technique was used to synthesise cadmium oxide (CdO) nanoparticles (NPs) and CdO NPs/c‐Multiwalled carbon nanotube (c‐MWCNT) nanocomposite fibres.To confirm the physio‐chemico properties and to analyse surface morphology of the obtained nanomaterials X‐Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM) were performed. To evaluate the anti‐cancer property of CdO NPs, c‐MWCNT NPs and CdO NPs/c‐MWCNT nanocomposite fibres, an anti‐proliferative assay test (Methylthiazolyl diphenyl‐ tetrazolium bromide ‐ MTT assay) were performed on HeLa cells which further estimated IC50 value (Least concentration of sample in which nearly 50% of cells remain alive) under in‐vitro conditions. On comparison, CdONPs/c‐MWCNT based system was found to be superior by achieving 52.3% cell viability with its minimal IC50 value of 31.2 μg/ml. Lastly, the CdO NPs based system was taken up for an apoptotic study using DNA fragmentation assay for estimating its ability to cleave the DNA of the HeLa cells into internucleosomal fragments using the agarose gel electrophoresis method. In conclusion, based on our observations, CdO NPs/c‐MWCNT hybrid based system can be further used for the development of efficient drug delivery and therapeutic systems.Inspec keywords: drug delivery systems, electrophoresis, oxidation, toxicology, DNA, nanoparticles, drugs, field emission electron microscopy, scanning electron microscopy, nanofabrication, surface morphology, cancer, X‐ray diffraction, nanomedicine, cellular biophysics, filled polymers, biomedical materials, molecular biophysics, biochemistry, Fourier transform infrared spectra, multi‐wall carbon nanotubesOther keywords: c‐MWCNT nanoparticles, apoptotic study, HeLa cancer cell line, cadmium oxide nanoparticles, c‐MWCNT NPs, anti‐proliferative assay test [methyl thiazolyl diphenyl‐tetrazolium bromide assay], human epithelioid cervix carcinoma cells, live cells, CdO NP‐based system, IC50 concentration, HeLa cell line, cell deaths, CdO‐C     

Investigation on natural radiation level and its hazardous nature of river sediments using γ-ray spectroscopy

The content of natural radionuclides (²³⁸U, ²³²Th, ⁴⁰K) in sediment samples of Ponnaiyar River, taken from different depths, were determined using a γ-ray spectroscopic system with a NaI(TI) detector with an aim of evaluating the radiation hazard. The results are compared with Indian and world average values. To know the complete radiological characteristics, the radiological indices such as absorbed dose rate, annual effective dose equivalent (indoor and outdoor), radium equivalent activity, hazard index (H _ex and H _in), γ-index, activity utilization index, and excess lifetime cancer risk were calculated. The results obtained were discussed and compared with the recommended values. The outdoor γ-dose rates were measured at each sampling site using an environmental radiation dosimeter. The measured results were compared with literature values and correlated with the calculated absorbed dose rate. Averages of all the radiation hazard indices and concentrations of all the measured radionuclides in all the layers are lower than the recommended level. The origin of the detected radionuclides is assessed by comparing the present results with the corresponding values for the earth crust and other rock formations.     

Solubility of Ruthenium Dioxide in Lead Borosilicate Glasses

The solubility of RuO₂ in a lead borosilicate glass was measured in the range of 700° to 1000°C. The effect of dissolved alumina in the glass was studied in the same range using 2%, 4%, 6%, and 10% dissolved alumina. The solubility showed an exponential dependence on temperature, and the dissolved alumina decreased the solubility at any given temperature; however, the solubility was essentially the same in all of the alumina-containing glasses. The Kelvin equation was used to deduce the concentration of RuO₂ in glass as a function of the curvature of the RuO₂ particles, and the dependence was found to be quite small. The implications of the results in processing thick-film resistors using RuO₂ as the conductive phase and these glasses as insulating phases on an alumina substrate are discussed.     

Observation of magnetic, structural and surface morphological studies of triangle-like nickel nanoplates

Two-dimensional triangle-like nickel nanoplates have been synthesized by solvothermal method in the presence of triethylamine as a structure directing agent. The structure, morphology and magnetic properties of the as-synthesized products were characterized by X-ray diffraction, Atomic force microscopy and Superconducting quantum interference device magnetometer. The as-synthesized products have been confirmed to be phase-pure crystalline nickel with face centered cubic structure on the basis of X-ray diffraction characterization. Atomic force microscopy image demonstrated that the as-prepared nickel product possess two-dimensional triangle-like structure with edge length of about 65-85 nm. Magnetic measurements showed that the coercive forces at 4.2 K and 300 K for nickel nanoplates are 363.3 and 182 Oe, respectively. The nickel nanoplates exhibit a distinct enhanced coercive force due to the presence of shape anisotropy when compared with that of bulk. A possible mechanism for the formation of triangle-like Ni nanoplate structure is proposed.     

Osteoporosis Prediction for Trabecular Bone using Machine Learning: A Review

Trabecular bone holds the utmost importance due to its significance regarding early bone loss. Diseases like osteoporosis greatly affect the structure of the Trabecular bone which results in different outcomes like high risk of fracture. The objective of this paper is to inspect the characteristics of the Trabecular Bone by using the Magnetic Resonance Imaging (MRI) technique. These characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as osteoporosis. The things that were considered before the selection of the articles for the systematic review were language, research field, and electronic sources. Only those articles written in the English language were selected as it is the most prominent language used in scientific, engineering, computer science, and biomedical researches. This literature review was conducted on the articles published between 2006 and 2020. A total of 62 research papers out of 1050 papers were extracted which were according to our topic of review after screening abstract and article content for the title and abstract screening. The findings from those researches were compiled at the end of the result section. This systematic literature review presents a comprehensive report on scientific researches and studies that have been done in the medical area concerning trabecular bone.     

DDoS Detection in SDN using Machine Learning Techniques

Software-defined network (SDN) becomes a new revolutionary paradigm in networks because it provides more control and network operation over a network infrastructure. The SDN controller is considered as the operating system of the SDN based network infrastructure, and it is responsible for executing the different network applications and maintaining the network services and functionalities. Despite all its tremendous capabilities, the SDN face many security issues due to the complexity of the SDN architecture. Distributed denial of services (DDoS) is a common attack on SDN due to its centralized architecture, especially at the control layer of the SDN that has a network-wide impact. Machine learning is now widely used for fast detection of these attacks. In this paper, some important feature selection methods for machine learning on DDoS detection are evaluated. The selection of optimal features reflects the classification accuracy of the machine learning techniques and the performance of the SDN controller. A comparative analysis of feature selection and machine learning classifiers is also derived to detect SDN attacks. The experimental results show that the Random forest (RF) classifier trains the more accurate model with 99.97% accuracy using features subset by the Recursive feature elimination (RFE) method.     

Effect of growth temperature on the morphology control and optical behavior of monolayer MoS2 on SiO2 substrate

Journal of Materials Science: Materials in Electronics - Chemical vapor deposition (CVD) is a promising method for producing high-quality two-dimensional (2D) transition metal dichalcogenides...