Identification of key biomarkers and associated pathways of pancreatic cancer using integrated transcriptomic and gene network analysis.

Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the CDKN1A, IL6, and MYC genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer.

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.

Carbon-based nanomaterial intervention and efficient removal of various contaminants from effluents - A review.

Water treatment is a worldwide issue. This review aims to present current problems and future challenges in water treatments with the existing methodologies. Carbon nanotube production, characterization, and prospective uses have been the subject of considerable and rigorous research around the world. They have a large number of technical uses because of their distinct physical characteristics. Various catalyst materials are used to make carbon nanotubes. This review's primary focus is on integrated and single-treatment technologies for all kinds of drinking water resources, including ground and surface water. Inorganic non-metallic matter, heavy metals, natural organic matter, endocrine-disrupting chemicals, disinfection by-products and microbiological pollutants are among the contaminants that these treatment systems can remediate in polluted drinking water resources. Significant advances in the antibacterial and adsorption capabilities of carbon-based nanomaterials have opened up new options for excluding organic/inorganic and biological contaminants from drinking water in recent years. The advancements in multifunctional nanocomposites synthesis pave the possibility for their use in enhanced wastewater purification system design. The adsorptive and antibacterial characteristics of six main kinds of carbon nanomaterials are single-walled carbon nanotubes, multi-walled carbon nanotubes, graphene, graphene oxide, fullerene and single-walled carbon nanohorns. This review potentially addressed the essential metallic and polymeric nanocomposites, are described and compared. Barriers to use these nanoparticles in long-term water treatment are also discussed.

Efficiency of various biofilm carriers and microbial interactions with substrate in moving bed-biofilm reactor for environmental wastewater treatment.

In a moving bed-biofilm reactor (MBBR), the fluidization efficiency, immobilization of microbial cells, and treatment efficiency are directly influenced by the shape and pores of biofilm carriers. Moreover, the efficacy of bioremediation mainly depends on their interaction interface with microbes and substrate. This review aims to comprehend the role of different carrier properties such as material shapes, pores, and surface area on bioremediation productivity. A porous biofilm carrier with surface ridges containing spherical pores sizes > 1 mm can be ideal for maximum efficacy. It provides diverse environments for cell cultures, develops uneven biofilms, and retains various cell sizes and biomass. Moreover, the thickness of biofilm and controlled scaling shows a significant impact on MBBR performance. Therefore, the effect of these parameters in MBBR is discussed detailed in this review, through which existing literature and technical strategies that focus on the surface area as the primary factor can be critically assessed.

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.

Identification and Structure Prediction of Human Septin-4 as a Biomarker for Diagnosis of Asthenozoospermic Infertile Patients-Critical Finding Toward Personalized Medicine.

Semen parameters are been found as a key factor to evaluate the count and morphology in the given semen sample. The deep knowledge of male infertility will unravel with semen parameters correlated with molecular and biochemical parameters. The current research study is to identify the motility associated protein and its structure through the in-silico approach. Semen samples were collected and initial analysis including semen parameters was analyzed by using the World Health Organization protocol. Semen biochemical parameters, namely, seminal plasma protein concentration, fructose content, and glucosidase content were calculated and evaluated for correlation. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) were carried out for identification of Septin-4 presence in the semen sample. Mascot search was done for protein conformation and in-silico characterization of Septin-4 by structural modeling in Iterative Threading Assembly Refinement (I-TASSER). Twenty-five nanoseconds molecular dynamics (MD) simulations results showed the stable nature of Septin-4 in the dynamic system. Overall, our results showed the presence of motility-associated protein in normospermia and control samples and not in the case of asthenospermia and oligoasthenospermia. Molecular techniques characterized the presence of Septin-4 and as a novel biomarker for infertility diagnosis.

Ecotoxicological assessment and dermal layer interactions of nanoparticle and its routes of penetrations.

Our review focused on nanomaterials-based toxicity evaluation and its exposure to the human and aquatic animals when it was leached and contaminated in the environment. Ecotoxicological assessment and its mechanism mainly affect the skin covering layers and its preventive barriers that protect the foreign particles' skin. Nanoscale materials are essential in the medical field, especially in biomedical and commercial applications such as nanomedicine and drug delivery, mainly in therapeutic treatments. However, various commercial formulations of pharmaceutical drugs are manufactured through a series of clinical trials. The role of such drugs and their metabolites has not met the requirement of an individual's need at the early stage of the treatments except few drugs and medicines with minimal or no side effects. Therefore, biology and medicines are taken up the advantages of nano scaled drugs and formulations for the treatment of various diseases. The present study identifies and analyses the different nanoparticles and their chemical components on the skin and their effects due to penetration. There are advantageous factors available to facilitate positive and negative contact between dermal layers. It creates a new agenda for an established application that is mainly based on skin diseases.

Seminal exosomes - An important biological marker for various disorders and syndrome in human reproduction.

BACKGROUND: Exosomes are nano-sized membrane vesicles, secreted by different types of cells into the body's biological fluids. They are found in abundance in semen as compared to other fluids. Exosomes contain a cargo of lipid molecules, proteins, phospholipids, cholesterol, mRNAs, and miRNAs. Each molecule of seminal exosomes (SE) has a potential role in male reproduction for childbirth. Many potential candidates are available within the seminal exosomes that can be used as diagnostic markers for various diseases or syndromes associated with male reproduction. Also these seminal exospmes play a major role in female reproductive tract for effective fertilization. AIM: The aim of this review is to focus on the advancement of human seminal exosomal research and its various properties. METHODS: We used many databases like Scopus, Google scholar, NCBI-NLM and other sources to filter the articles of interest published in exosomes. We used phrases like "Exosomes in human semen", "Composition of exosomes in human semen" and other relevant words to filter the best articles. RESULTS: Seminal exosomes play a major role in sperm functions like cell-to-cell communication, motility of the sperm cells, maintaining survival capacity for the sperm in the female reproductive tract and spermatogenesis. Also, seminal exosomes are used as a carrier for many regulatory elements using small RNA molecules. miRNAs of the seminal exosomes can be used as a diagnostic marker for prostate cancer instead of prostate specific antigen (PSA). Epididymosomes can be used as a biomarker for reproductive diseases and male infertility. CONCLUSION: Seminal exosomes could be used as biological markers for various reproductive disorders, male infertility diagnosis, and it can be used in anti-retroviral research for the identification of novel therapeutics for HIV-1 infection and transmission.

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.

Insights from the docking and molecular dynamics simulation of the Phosphopantetheinyl transferase (PptT) structural model from Mycobacterium tuberculosis.

A great challenge is posed to the treatment of tuberculosis due to the evolution of multidrug-resistant (MDR) and extensively drugresistant (XDR) strains of Mycobacterium tuberculosis in recent times. The complex cell envelope of the bacterium contains unusual structures of lipids which protects the bacterium from host enzymes and escape immune response. To overcome the drug resistance, targeting "drug targets" which have a critical role in growth and virulence factor is a novel approach for better tuberculosis treatment. The enzyme Phosphopantetheinyl transferase (PptT) is an attractive drug target as it is primarily involved in post translational modification of various types-I polyketide synthases and assembly of mycobactin, which is required for lipid virulence factors. Our in silico studies reported that the structural model of M.tuberculosis PptT characterizes the structure-function activity. The refinement of the model was carried out with molecular dynamics simulations and was analyzed with root mean square deviation (RMSD), and radius of gyration (Rg). This confirmed the structural behavior of PptT in dynamic system. Molecular docking with substrate coenzyme A (CoA) identified the binding pocket and key residues His93, Asp114 and Arg169 involved in PptT-CoA binding. In conclusion, our results show that the M.tuberculosis PptT model and critical CoA binding pocket initiate the inhibitor design of PptT towards tuberculosis treatment.