Trimethoprim derivative Schiff bases are versatile ligands synthesized with carbonyl groups from the condensation of primary amines (amino acids). Because of their broad range of biological activity, these compounds are very important in the medical and pharmaceutical fields. Biological activities such as antibacterial, antifungal and antitumor activity are often seen. Transition metal complexes derived from biological activity Schiff base ligands have been commonly used.

Nowadays, the use of natural bio-products in pharmaceuticals is gaining popularity as safe alternatives to chemicals and synthetic drugs. Algal products are offering a pure, healthy and sustainable choice for pharmaceutical applications. Algae are photosynthetic microorganisms that can survive in different environmental conditions. Algae have many outstanding properties that make them excellent candidate for use in therapeutics. Algae grow in fresh and marine waters and produce in their cells a wide range of biologically active chemical compounds. These bioactive compounds are offering a great source of highly economic bio-products. The prese

Schiff bases (SBs) based on amino acid derivative stand for multipurpose ligands that formed by condensing amino acids with carbonyl groups. They are significant in pharmaceutical and medical areas due to their widespread biological actions such as antiseptic, antifungal, along with antitumor actions. Transition metallic complexes resulting from SB ligands with biological activity were extensively experimented in the literature. In this article, we review, in details, about synthesizing and biological performances of SBs along with its complexes.

A case of angiolymphoid hyperplasia with eosinophilia (ALH) is reported in a 42-year-old woman who developed multiple nodules behind the ear. Angiolymphoid hyperplasia with eosinophilia usually occurs on the head and neck of young adults and is more common in women than in men. Characteristic histologic features of ALH present in this case included proliferation of thick-walled blood vessels lined by prominent endothelial cells, infiltration of the interstitium by chronic inflammatory cells (mainly eosinophils), and presence of lymphoid follicles with germinal centers. The patient referred for surgeon for complete excision. in this context , cases previously described in the literature, and the differential diagnosis of ALH are discussed

Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (K_P, K_I, K_D) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration