Cardiovascular diseases prediction by machine learning incorporation with deep learning.

It is yet unknown what causes cardiovascular disease (CVD), but we do know that it is associated with a high risk of death, as well as severe morbidity and disability. There is an urgent need for AI-based technologies that are able to promptly and reliably predict the future outcomes of individuals who have cardiovascular disease. The Internet of Things (IoT) is serving as a driving force behind the development of CVD prediction. In order to analyse and make predictions based on the data that IoT devices receive, machine learning (ML) is used. Traditional machine learning algorithms are unable to take differences in the data into account and have a low level of accuracy in their model predictions. This research presents a collection of machine learning models that can be used to address this problem. These models take into account the data observation mechanisms and training procedures of a number of different algorithms. In order to verify the efficacy of our strategy, we combined the Heart Dataset with other classification models. The proposed method provides nearly 96 percent of accuracy result than other existing methods and the complete analysis over several metrics has been analysed and provided. Research in the field of deep learning will benefit from additional data from a large number of medical institutions, which may be used for the development of artificial neural network structures.

Semenogelin, a coagulum macromolecule monitoring factor involved in the first step of fertilization: A prospective review.

Human male infertility affects approximately 1/10 couples worldwide, and its prevalence is found more in developed countries. Along with sperm cells, the secretions of the prostate, seminal vesicle and epididymis plays a major role in proper fertilization. Many studies have proven the functions of seminal vesicle secretions, especially semenogelin protein, as an optimiser for fertilization. Semenogelin provides the structural components for coagulum formation after ejaculation. It binds with eppin and is found to have major functions like motility of sperm, transporting the sperm safely in the immune rich female reproductive tract until the sperm cells reach the egg intact. The capacitation process is essential for proper fertilization and semenogelin involved in mediating capacitation in time. Also, it has control of events towards the first step in the fertilization process. It is a Zn ions binding protein, and Zn ions act as a cofactor that helps in the proper motility of sperm cells. Therefore, any imbalance in protein that automatically affect sperm physiology and fertility status. This review sheds a comprehensive and critical view on the significant functions of semenogelin in fertilization. This review can open up advanced proteomics research on semenogelin towards unravelling molecular mechanisms in fertilization.

Role of Zinc (Zn) in Human Reproduction: A Journey from Initial Spermatogenesis to Childbirth.

Zinc (Zn), the second-most necessary trace element, is abundant in the human body. The human body lacks the capacity to store Zn; hence, the dietary intake of Zn is essential for various functions and metabolism. The uptake of Zn during its transport through the body is important for proper development of the three major accessory sex glands: the testis, epididymis, and prostate. It plays key roles in the initial stages of germ cell development and spermatogenesis, sperm cell development and maturation, ejaculation, liquefaction, the binding of spermatozoa and prostasomes, capacitation, and fertilization. The prostate releases more Zn into the seminal plasma during ejaculation, and it plays a significant role in sperm release and motility. During the maternal, labor, perinatal, and neonatal periods, the part of Zn is vital. The average dietary intake of Zn is in the range of 8-12 mg/day in developing countries during the maternal period. Globally, the dietary intake of Zn varies for pregnant and lactating mothers, but the average Zn intake is in the range of 9.6-11.2 mg/day. The absence of Zn and the consequences of this have been discussed using critical evidence. The events and functions of Zn related to successful fertilization have been summarized in detail. Briefly, our current review emphasizes the role of Zn at each stage of human reproduction, from the spermatogenesis process to childbirth. The role of Zn and its supplementation in in vitro fertilization (IVF) opens opportunities for future studies on reproductive biology.

Down-regulation of hepatic G-6-Pase expression in hyperglycemic rats: Intervention with biogenic gold nanoconjugate.

Chronic diabetes extensively complicates the glucose metabolism to onset and progress the complication. Concurrently, several contemporary medicines, especially organo-metallic formulations, are emerging to treat hyperglycemia. The current study aims to emphasize the gold nanoparticles (GNPs) potential for glucose metabolism regulation in Streptozotocin (STZ) induced diabetes. Quantitative real-time polymerase chain reaction (RT-PCR) was carried out to detect the mRNA expression of Glucose transporters 2 (GLUT2), Glucokinase (GK) and Glucose 6 Phosphatase (G-6-Pase). The study shows remarkable results such as the prognostic effect of GNPs in reinforcing the repression of enzyme complex G-6-Pase about 13.3-fold when compared to diabetes control. Also, molecular docking studies showed significant inhibition of G-6-Pase by the terpenoid ligands with alpha and beta amyrin from leaf extract of Couroupita guianensis. Thus the study explored the novel mechanism of G-6-Pase downregulated by GNPs intervention that majorly contributes to the regulation of circulatory glucose homeostasis during diabetes.

Molecular modeling and docking studies of glutamate racemase in Vibrio vulnificus CMCP6.

Identification of novel drug targets in silico in Vibrio vulnificus is important as it is one of the emerging pathogenic microorganisms. Glutamate racemase, an important constituent of bacterial cell wall is chosen for structure prediction using homology modeling. With the aid of tools and software like MODELLER and Swiss-PdbViewer, the 3D structure is predicted and the final model is refined by energy minimization. The quality of the refined model is assessed using PROCHECK. The interaction between the predicted structure of glutamate racemase and its potential inhibitors namely L-serine O-sulfate, (2R,4R)-2-amino-4-(2-benzo[b]thienyl)methyl pentanedioic acid, aziridino glutamate, exiguaquinol, gamma-2 naphthylmethyl-D-glutamate and D-glutamine is analysed in silico by Autodock. The results indicate that certain residues like Aspl3, Tyr45, Gly46, Asn78, Thr79, Cys185, His187 are highly conserved across the active site stretches of different bacterial species and may possibly assume precedence over the other residues for inhibitory action. This study provides an insight into the structure of glutamate racemase in V. vulnificus and also gives an idea about potential sites responsible for inhibitory action that could further be substantiated by experimental investigations.