A Lightweight Method for Breast Cancer Detection Using Thermography Images with Optimized CNN Feature and Efficient Classification.

Breast cancer is a prominent cause of death among women worldwide. Infrared thermography, due to its cost-effectiveness and non-ionizing radiation, has emerged as a promising tool for early breast cancer diagnosis. This article presents a hybrid model approach for breast cancer detection using thermography images, designed to process and classify these images into healthy or cancerous categories, thus supporting disease diagnosis.

Development and clinical application of a preimplantation genetic testing for monogenic disease (PGT-M) for beta thalassemia in Vietnam.

Purpose: The purpose of this research is to study the clinical outcomes using a next-generation sequencing-based protocol allowing for simultaneous testing of mutations in the beta thalassemia (HBB) gene, including single nucleotide polymorphism (SNP) markers for PGT-M along with low-pass whole genome analysis of chromosome aneuploidies for PGT-A.

Methods: A combined PGT-M (thalassemia) plus PGT-A system was developed for patients undergoing IVF in Vietnam. Here we developed a system for testing numerous thalassemia mutations plus SNP-based testing for backup mutation analysis and contamination control using next-generation sequencing (NGS).

Design, Synthesis and Biological Evaluation of Novel N-hydroxyheptanamides Incorporating 6-hydroxy-2-methylquinazolin-4(3H)-ones as Histone Deacetylase Inhibitors and Cytotoxic Agents.

Background: Target-based approach to drug discovery currently attracts a great deal of interest from medicinal chemists in anticancer drug discovery and development worldwide, and Histone Deacetylase (HDAC) inhibitors represent an extensive class of targeted anti-cancer agents. Among the most explored structure moieties, hydroxybenzamides and hydroxypropenamides have been demonstrated to have potential HDAC inhibitory effects. Several compounds of these structural classes have been approved for clinical uses to treat different types of cancer, such as vorinostat and belinostat.

Beyond model interpretability using LDA and decision trees for α-amylase and α-glucosidase inhibitor classification studies.

In this report are used two data sets involving the main antidiabetic enzyme targets α-amylase and α-glucosidase. The prediction of α-amylase and α-glucosidase inhibitory activity as antidiabetic is carried out using LDA and classification trees (CT). A large data set of 640 compounds for α-amylase and 1546 compounds in the case of α-glucosidase are selected to develop the tree model.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling.

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability.