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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.

Objective: Preliminary aim of this research work focuses on testing the efficacy of silver nanoparticles synthesised using water soluble polysaccharides extracted from seaweeds against pathogenic fish bacteria. The emergence of various virulence pathogens during the culturing period leads to mass mortality and influence the loss of aquaculture production. Methods: The intervention of nanotechnology in the field of aquaculture improves the growth and immunity of aquatic animals when the part of nanomaterials mixed with fish feed. Sometimes the green synthesis of silver nanoparticles prepared from the seaweed polysaccharide play a vital role in the disease controlling strategies in aquaculture farming. The nanoparticle formation and confirmation was charecterized by Ultra Visible Spectroscopy (UV–Vis), Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscope (SEM), Dynamic Light Scattering (DLS). Results and Conclusion: Biologically synthesized silver nanoparticles have been used as an alternative method for commercial antibiotics to control such pathogenic infection with 70–80% of survival rate. Polysaccharides of Caulerpa racemosa was used as a reducing agent in this present study. Particularly the phytochemicals are involved in the silver salt reduction process. Total polyphenol, total flavonoids, total antioxidant, hydroxyl radical scavenging assay and DPPH was found to be 12.32 mg/g, 18.44 mg/g, 38.12 mg/g equivalence, 82.2% and 49.05% respectively. Biologically synthesised AgNps capable of preventing the Pseudomonas aeruginosa infection in tilapia, it was proved by in vitro and in vivo antibacterial activities. Present study provided the ample achievement and these findings found to be effective in controlling the Pseudomonas infection in tilapia fishes.

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.

Galectins are a family of structurally related carbohydrate-binding proteins and some galectins play a major role in initiation, progression and dissemination of different types of tumors. Multiple sequence alignment was performed for 15 types of galectins and phylogenetic tree was constructed for studying evolutionary relationship. Among galectins, galectin-1 contributes to various events associated with cancer biology including tumor transformation, cell cycle regulation and apoptosis. Hence a rational computational approach was followed for the design of new class of glycol-mimetic inhibitors with high affinity and stability. Ten N-39-triazole analogs have been used for molecular docking with galectin-1. Based on docking studies, hexaconazole is identified as a potential inhibitor of galectin-1 for the inhibition of the tumor activity. The binding mechanism of hexaconazole to galectin-1 in the dynamics system was studied by 10 ns Molecular Dynamics simulation. Thus, our study favors more insight on hexaconazole as a promising inhibitor for galectin-1.

Human ?-aminobutyric acid aminotransferase (GABA-AT), a pyridoxal phosphate dependent enzyme is responsible for the degradation of the inhibitory neurotransmitter GABA. Currently, GABA-AT is a potential drug target for epilepsy due to the selective inhibition in brain. In this computational study, we mainly focus on screening of novel lead candidates against GABA-AT using hexonic derivatives. Structure based virtual screening is performed in Vina that screened top hits based on least binding affinity. Further re-docking on hits is performed in AutoDock results in identification of leads with favorable binding energy and hydrogen bond interactions confirmed the effective inhibition. In conclusion, leads 3-aminohex-5-enoic acid and AG-E-60842 can acts as specific leads for GABA-AT and assist in discovery of novel anti-epileptic drugs.