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.

Crystal structure of ()'-[1-(4-amino-phen-yl)ethyl-idene]-2-hy-droxy-5-iodo-benzohydrazide methanol monosolvate.

In the title compound, CHINO·CHOH, two aromatic rings are linked by an -substituted hydrazide function. The dihedral angle between the aromatic rings is 10.53 (8)°.

Phylogenomics and barcoding of Panax: toward the identification of ginseng species.

Background: The economic value of ginseng in the global medicinal plant trade is estimated to be in excess of US$2.1 billion. At the same time, the evolutionary placement of ginseng (Panax ginseng) and the complex evolutionary history of the genus is poorly understood despite several molecular phylogenetic studies.

A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents.

Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease.

Learning from Multiple Classifier Systems: Perspectives for Improving Decision Making of QSAR Models in Medicinal Chemistry.

Quantitative Structure - Activity Relationship (QSAR) modeling has been widely used in medicinal chemistry and computational toxicology for many years. Today, as the amount of chemicals is increasing dramatically, QSAR methods have become pivotal for the purpose of handling the data, identifying a decision, and gathering useful information from data processing. The advances in this field have paved a way for numerous alternative approaches that require deep mathematics in order to enhance the learning capability of QSAR models.

The profile of leucocytes, CD3+, CD4+, and CD8+ T cells, and cytokine concentrations in peripheral blood of children with acute asthma exacerbation.

Objective To determine the leucocyte profile and cytokine concentrations in the peripheral blood of children with an acute asthma exacerbation (AAE). Methods This descriptive, cross-sectional study enrolled paediatric patients admitted to hospital for AAE. The severity of AAE was assessed using the paediatric asthma score (PAS).

Quantitative structure-activity relationship analysis and virtual screening studies for identifying HDAC2 inhibitors from known HDAC bioactive chemical libraries.

Histone deacetylases (HDAC) are emerging as promising targets in cancer, neuronal diseases and immune disorders. Computational modelling approaches have been widely applied for the virtual screening and rational design of novel HDAC inhibitors. In this study, different machine learning (ML) techniques were applied for the development of models that accurately discriminate HDAC2 inhibitors form non-inhibitors.

A Simple Method to Predict Blood-Brain Barrier Permeability of Drug- Like Compounds Using Classification Trees.

Background: To know the ability of a compound to penetrate the blood-brain barrier (BBB) is a challenging task; despite the numerous efforts realized to predict/measure BBB passage, they still have several drawbacks.

Method: The prediction of the permeability through the BBB is carried out using classification trees. A large data set of 497 compounds (recently published) is selected to develop the tree model.

Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative.

In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22- 24), an unique event, named connected subgraphs, (based on the Kier-Hall's subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach's subgraphs), fingerprints (MACCs, E-state and substructure fingerprints) and atomic contributions (Ghose and Crippen atom-types for hydrophobicity and refractivity) for F generation.

Prediction of acute toxicity of phenol derivatives using multiple linear regression approach for Tetrahymena pyriformis contaminant identification in a median-size database.

In this article, the modeling of inhibitory grown activity against Tetrahymena pyriformis is described. The 0-2D Dragon descriptors based on structural aspects to gain some knowledge of factors influencing aquatic toxicity are mainly used. Besides, it is done by some enlarged data of phenol derivatives described for the first time and composed of 358 chemicals.

Physico-Chemical and Structural Interpretation of Discrete Derivative Indices on N-Tuples Atoms.

This report examines the interpretation of the Graph Derivative Indices (GDIs) from three different perspectives (i.e., in structural, steric and electronic terms).

Nucleoside analogs: ready to enter the era of precision medicine?

Introduction: The term 'precision medicine' has garnered significant attention in the oncological setting in relation to attempts to optimize anticancer treatment. Precision medicine is mostly associated with oral targeted therapies and biotherapies, however, to date classic cytotoxics still remain the backbone of most regimens for treating solid tumors or in hematology, both in children and in adults. Among the existing cytotoxic therapies, nucleosides are widely used for treating a variety of cancerous diseases, alone or as part of combination therapies.

Multi-output Model with Box-Jenkins Operators of Quadratic Indices for Prediction of Malaria and Cancer Inhibitors Targeting Ubiquitin- Proteasome Pathway (UPP) Proteins.

The ubiquitin-proteasome pathway (UPP) is the primary degradation system of short-lived regulatory proteins. Cellular processes such as the cell cycle, signal transduction, gene expression, DNA repair and apoptosis are regulated by this UPP and dysfunctions in this system have important implications in the development of cancer, neurodegenerative, cardiac and other human pathologies. UPP seems also to be very important in the function of eukaryote cells of the human parasites like Plasmodium falciparum, the causal agent of the neglected disease Malaria.

Organ and tissue-dependent effect of resveratrol and exercise on antioxidant defenses of old mice.

Background: Oxidative stress has been considered one of the causes of aging. For this reason, treatments based on antioxidants or those capable of increasing endogenous antioxidant activity have been taken into consideration to delay aging or age-related disease progression.

Aim: In this paper, we determine if resveratrol and exercise have similar effect on the antioxidant capacity of different organs in old mice.

Towards Better BBB Passage Prediction Using an Extensive and Curated Data Set.

In the present report, the challenging task of drug delivery across the blood-brain barrier (BBB) is addressed via a computational approach. The BBB passage was modeled using classification and regression schemes on a novel extensive and curated data set (the largest to the best of our knowledge) in terms of log BB. Prior to the model development, steps of data analysis that comprise chemical data curation, structural, cutoff and cluster analysis (CA) were conducted.

Multi-output model with Box-Jenkins operators of linear indices to predict multi-target inhibitors of ubiquitin-proteasome pathway.

The ubiquitin-proteasome pathway (UPP) plays an important role in the degradation of cellular proteins and regulation of different cellular processes that include cell cycle control, proliferation, differentiation, and apoptosis. In this sense, the disruption of proteasome activity leads to different pathological states linked to clinical disorders such as inflammation, neurodegeneration, and cancer. The use of UPP inhibitors is one of the proposed approaches to manage these alterations.

A rational workflow for sequential virtual screening of chemical libraries on searching for new tyrosinase inhibitors.

The tyrosinase is a bifunctional, copper-containing enzyme widely distributed in the phylogenetic tree. This enzyme is involved in the production of melanin and some other pigments in humans, animals and plants, including skin pigmentations in mammals, and browning process in plants and vegetables. Therefore, enzyme inhibitors has been under the attention of the scientist community, due to its broad applications in food, cosmetic, agricultural and medicinal fields, to avoid the undesirable effects of abnormal melanin overproduction.

Tyrosinase enzyme: 1. An overview on a pharmacological target.

The tyrosinase enzyme (EC 1.14.18.