Isatin is a heterocyclic molecule that belongs to one of the most important classes of organic compounds known as indolines. Isatin, isatin analogs, and their Schiff bases have recently attracted a lot of attention in medicinal chemistry. Isatin, itself, shows various biological activities such as antiviral, anticancer, antimicrobial, anti-inflammatory, analgesic, antioxidant, and anticonvulsant. Bis- Schiff bases containing isatin moiety have been known to possess a wide spectrum of pharmacological activities. This review offers up-to-date information on the most active isatin bis-Schiff bases, which would include anticancer, antimicrobial, antiviral, anticonvulsant, anti-inflammatory, and analgesic activities. These observations c

Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

 The power factors and electronic thermal conductivities in bismuth telluride (Bi2Te3), lead-telluride (PbTe), and gallium arsenide (GaAs) at room temperature (300K) quantum wires and quantum wells are theoretically investigated. Our formalism rigorously takes into account modification of these power factors and electronic thermal conductivities in free-surface wires and wells due to spatial confinement. From our numerical results, we predict a significant increase of the power factor in quantum wires with diameter w=20 Ã…. The increase is always stronger in quantum wires than in quantum wells of the corresponding dimensions. An unconfined phonon distribution assumed based on the bulk lattice thermal conductivity is then employed

In this work, a (CdO)_0.94:(In₂O₃)_0.06 film was developed on a glass substrate using Q- switching pulse laser beam (Nd:YAG; wavelength 1064 nm). The quantitative elemental analysis of the (CdO)_0.94:(In₂O₃)_0.06 thin film was achieved using energy dispersive X- ray diffraction (EDX). The topological and morphological properties of the deposited thin film were investigated using atomic force microscope (AFM) and field emission scan electron microscopy (FESEM). The I-V characteristic and Hall effect of (CdO)_0.94 :(In₂O₃)_0.06 thin films were used  to  study the electrical properties. The gas sensor prope

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.