Smart Diagnosis of Adenocarcinoma Using Convolution Neural Networks and Support Vector Machines

Adenocarcinoma is a type of cancer that develops in the glands present on the lining of the organs in the human body. It is found that histopathological images, obtained as a result of biopsy, are the most definitive way of diagnosing cancer. The main objective of this work is to use deep learning techniques for the detection and classification of adenocarcinoma using histopathological images of lung and colon tissues with minimal preprocessing. Two approaches have been utilized. The first method entails creating two CNN architectures: CNN with a Softmax classifier (AdenoCanNet) and CNN with an SVM classifier (AdenoCanSVM). The second approach corresponds to training some of the prominent existing architecture such as VGG16, VGG19, LeNet, and ResNet50. The study aims at understanding the performance of various architectures in diagnosing using histopathological images with cases taken separately and taken together, with a full dataset and a subset of the dataset. The LC25000 dataset used consists of 25,000 histopathological images, having both cancerous and normal images from both the lung and colon regions of the human body. The accuracy metric was taken as the defining parameter for determining and comparing the performance of various architectures undertaken during the study. A comparison between the several models used in the study is presented and discussed

Green Synthesis and Characterization of Cobalt Oxide Nanoparticles Using <i>Psidium guajava</i> Leaves Extracts and Their Photocatalytic and Biological Activities

The advanced technology for synthesizing nanoparticles utilizes natural resources in an environmentally friendly manner. Additionally, green synthesis is preferred to chemical and physical synthesis because it takes less time and effort. The green synthesis of cobalt oxide nanoparticles has recently risen due to its physico-chemical properties. In this study, many functional groups present in Psidium guajava leaf extracts are used to stabilize the synthesis of cobalt oxide nanoparticles. The biosynthesized cobalt oxide nanoparticles were investigated using UV-visible spectroscopic analysis. Additionally, Fourier-transform infrared spectroscopy revealed the presence of carboxylic acids, hydroxyl groups, aromatic amines, alcohols and phenolic groups. The X-ray diffraction analysis showed various peaks ranging from 32.35 to 67.35°, and the highest intensity showed at 36.69°. The particle size ranged from 26 to 40 nm and confirmed the average particle size is 30.9 nm. The green synthesized P. guajava cobalt oxide nanoparticles contain cobalt as the major abundant element, with 42.26 wt% and 18.75 at% confirmed by the EDAX techniques. SEM images of green synthesized P. guajava cobalt oxide nanoparticles showed agglomerated and non-uniform spherical particles. The anti-bacterial activity of green synthesized P. guajava cobalt oxide nanoparticles was evaluated against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli with a 7 to 18 mm inhibitory zone. The photocatalytic activity was evaluated using green synthesized P. guajava cobalt oxide nanoparticles and observed 79% of dye degradation. The MTT assay of P. guajava cobalt oxide nanoparticles showed an excellent cytotoxic effect against MCF 7 and HCT 116 cells compared to normal cells. The percentage of cell viability of P. guajava cobalt oxide nanoparticles was observed as 90, 83, 77, 68, 61, 58 and 52% for MCF-7 cells and 82, 70, 63, 51, 43, 40, and 37% for HCT 116 cells at the concentration of 1.53, 3.06, 6.12, 12.24, 24.48, 50, and 100 μg/mL compared to control cells. These results confirmed that green synthesized P. guajava cobalt oxide nanoparticles have a potential photocatalytic and anti-bacterial activity and also reduced cell viability against MCF-7 breast cancer and HCT 116 colorectal cancer cells

Recent Insights and Multifactorial Applications of Carbon Nanotubes

Nanotechnology has undergone significant development in recent years, particularly in the fabrication of sensors with a wide range of applications. The backbone of nanotechnology is nanostructures, which are determined on a nanoscale. Nanoparticles are abundant throughout the universe and are thought to be essential building components in the process of planet creation. Nanotechnology is generally concerned with structures that are between 1 and 100 nm in at least one dimension and involves the production of materials or electronics that are that small. Carbon nanotubes (CNTs) are carbon-based nanomaterials that have the structure of tubes. Carbon nanotubes are often referred to as the kings of nanomaterials. The diameter of carbon is determined in nanometers. They are formed from graphite sheets and are available in a variety of colors. Carbon nanotubes have a number of characteristics, including high flexibility, good thermal conductivity, low density, and chemical stability. Carbon nanotubes have played an important part in nanotechnology, semiconductors, optical and other branches of materials engineering owing to their remarkable features. Several of the applications addressed in this review have already been developed and used to benefit people worldwide. CNTs have been discussed in several domains, including industry, construction, adsorption, sensors, silicon chips, water purifiers, and biomedical uses, to show many treatments such as injecting CNTs into kidney cancers in rats, drug delivery, and directing a near-infrared laser at the cancers. With the orderly development of research in this field, additional therapeutic modalities will be identified, mainly for dispersion and densification techniques and targeted drug delivery systems for managing and curing posterior cortical atrophy. This review discusses the characteristics of carbon nanotubes as well as therapeutic applications such as medical diagnostics and drug delivery

Atypical response patterns in renal cell carcinoma treated with immune checkpoint inhibitors—navigating the radiologic potpourri

10.3390/cancers13071689Cancers137168