Objectives: to assess chronic diseases patients’ knowledge toward stroke risk factors and warning signs, besides
determining the relationship between chronic diseases patients’ knowledge and their sociodemographical
characteristics.
Methodology: A descriptive study was carried out at public medical clinics which has started from December
2
nd, 2008 to August 8th, 2009. A purposive "non-probability" sample of (300) chronic diseases individuals who
were clients of Public Medical Clinics who have one or more of the following chronic diseases (hypertension,
diabetes mellitus, heart diseases, and previous stroke), in Baghdad city. The data were collected through the use
of a constructed questionnaire which consists

Therapeutically and prophylactically using Microspheres containing doxycycline isolated from shell of shrimp. Low molecule weight poly lactic acid was prepared. In this study, Poly lactic acid (PLA)/ poly vinyl alcohol (PVA)/poly ethyleneglycol(PEG) loading doxycycline blend solutions was prepared. Also Poly lactic acid (PLA)-Tannin blend via solvent evaporation method was prepared. Microspheres of chitosan/gelatin microsphere loading doxycycline was prepared by emulsion crosslinking technique. Both microsphere and blends were characterized by Fourier transform infrared (FTIR) spectrophotometer. The FTIR spectra were shown distinguish bands. The in vitro release of doxcycline from its matrix at pH 7 was studied. The prophylactic

Personalized Medicine represents a recent revolution in healthcare practice, focusing on tailoring different therapies to be precise for a specific individual; this is aided by exploring the number of genetic predispositions and lifestyle choices that fit each individual. In this article, the authors utilize and gather recent literature and opinions to discuss the impact of personalized medicine on chronic disease management and patient quality of life. Additional attention is paid to limits and possible ethical issues. Chronic diseases such as Hypertension, Diabetes, and chronic kidney diseases adversely affect multiple health indicators, including Quality of Life (QoL) and well-being. This will have additional impacts on physical

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

GH and IGF-2 were examined histologically in the present study on adult hens to learn more about the organs’ responses to GH and IGF-2. Cardiac protein synthesis is stimulated by GH and IGF-2, according to microscopic examination. The recent research found a considerable amount of adipose tissue in the cardiac muscle bundles, which is linked to the metabolic process. In addition, GH and IGF-2 were shown to promote protein synthesis and mitosis in liver and gizzard tissues, according to the research. In addition, the apoptosis, regeneration, and secretory activity of gizzard glands are increased by the aforementioned hormones.

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

S Khalifa E, AH Khalil I, N Adil A, AB Razan A…, 2009

Parasitic diseases can affect infection with COVID-19 obviously, as protective agents, or by reducing severity of this viral infection. This current review mentions the common symptoms between human parasites and symptoms of COVID-19, and explains the mechanism actions of parasites, which may prevent or reduce severity of this viral infection. Pre-existing parasitic infections provide prohibition against pathogenicity of COVID-19, by altering the balance of gut microbiota that can vary the immune response to this virus infection.