Elucidating the inhibitory mechanism of Zika virus NS2B-NS3 protease with dipeptide inhibitors: Insights from molecular docking and molecular dynamics simulations.

Microcephaly, Guillain-Barré syndrome, and potential sexual transmission stand as prominent complications associated with Zika virus (ZIKV) infection. The absence of FDA-approved drugs or vaccines presents a substantial obstacle in combatting the virus. Furthermore, the inclusion of pregnancy in the pharmacological screening process complicates and extends the endeavor to ensure molecular safety and minimal toxicity. Given its pivotal role in viral assembly and maturation, the NS2B-NS3 viral protease emerges as a promising therapeutic target against ZIKV. In this context, a dipeptide inhibitor was specifically chosen as a control against 200 compounds for docking analysis. Subsequent molecular dynamics simulations extending over 200 ns were conducted to ascertain the stability of the docked complex and confirm the binding of the inhibitor at the protein's active site. The simulation outcomes exhibited conformity to acceptable thresholds, encompassing parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), ligand-protein interaction analysis, ligand characterization, and surface area analysis. Notably, analysis of ligand angles bolstered the identification of prospective ligands capable of inhibiting viral protein activity and impeding virus dissemination. In this study, the integration of molecular docking and dynamics simulations has pinpointed the dipeptide inhibitor as a potential candidate ligand against ZIKV protease, thereby offering promise for therapeutic intervention against the virus.

Enhanced Network Intrusion Detection System for Internet of Things Security Using Multimodal Big Data Representation with Transfer Learning and Game Theory.

Internet of Things (IoT) applications and resources are highly vulnerable to flood attacks, including Distributed Denial of Service (DDoS) attacks. These attacks overwhelm the targeted device with numerous network packets, making its resources inaccessible to authorized users. Such attacks may comprise attack references, attack types, sub-categories, host information, malicious scripts, etc. These details assist security professionals in identifying weaknesses, tailoring defense measures, and responding rapidly to possible threats, thereby improving the overall security posture of IoT devices. Developing an intelligent Intrusion Detection System (IDS) is highly complex due to its numerous network features. This study presents an improved IDS for IoT security that employs multimodal big data representation and transfer learning. First, the Packet Capture (PCAP) files are crawled to retrieve the necessary attacks and bytes. Second, Spark-based big data optimization algorithms handle huge volumes of data. Second, a transfer learning approach such as word2vec retrieves semantically-based observed features. Third, an algorithm is developed to convert network bytes into images, and texture features are extracted by configuring an attention-based Residual Network (ResNet). Finally, the trained text and texture features are combined and used as multimodal features to classify various attacks. The proposed method is thoroughly evaluated on three widely used IoT-based datasets: CIC-IoT 2022, CIC-IoT 2023, and Edge-IIoT. The proposed method achieves excellent classification performance, with an accuracy of 98.2%. In addition, we present a game theory-based process to validate the proposed approach formally.

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations.

Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths', country-wise distribution, 'new cases and recovery', and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/.

Correction: The Omega-3 Fatty Acid Eicosapentaenoic Acid Accelerates Disease Progression in a Model of Amyotrophic Lateral Sclerosis.

[This corrects the article DOI: 10.1371/journal.pone.0061626.].

A comprehensive review of wind power integration and energy storage technologies for modern grid frequency regulation.

Integrating wind power with energy storage technologies is crucial for frequency regulation in modern power systems, ensuring the reliable and cost-effective operation of power systems while promoting the widespread adoption of renewable energy sources. Power systems are changing rapidly, with increased renewable energy integration and evolving system architectures. These transformations bring forth challenges like low inertia and unpredictable behavior of generation and load components. As a result, frequency regulation (FR) becomes increasingly important to ensure grid stability. Energy Storage Systems (ESS) with their adaptable capabilities offer valuable solutions to enhance the adaptability and controllability of power systems, especially within wind farms. This research provides an updated analysis of critical frequency stability challenges, examines state-of-the-art control techniques, and investigates the barriers that hinder wind power integration. Moreover, it introduces emerging ESS technologies and explores their potential applications in supporting wind power integration. Furthermore, this paper offers suggestions and future research directions for scientists exploring the utilization of storage technologies in frequency regulation within power systems characterized by significant penetration of wind power.

The HABD: Home of All Biological Databases Empowering Biological Research With Cutting-Edge Database Systems.

The emergence of computer technologies and computing power has led to the development of several database systems that provide standardized access to vast quantities of data, making it possible to collect, search, index, evaluate, and extract useful knowledge across various fields. The Home of All Biological Databases (HABD) has been established as a continually expanding platform that aims to store, organize, and distribute biological data in a searchable manner, removing all dead and non-accessible data. The platform meticulously categorizes data into various categories, such as COVID-19 Pandemic Database (CO-19PDB), Database relevant to Human Research (DBHR), Cancer Research Database (CRDB), Latest Database of Protein Research (LDBPR), Fungi Databases Collection (FDBC), and many other databases that are categorized based on biological phenomena. It currently provides a total of 22 databases, including 6 published, 5 submitted, and the remaining in various stages of development. These databases encompass a range of areas, including phytochemical-specific and plastic biodegradation databases. HABD is equipped with search engine optimization (SEO) analyzer and Neil Patel tools, which ensure excellent SEO and high-speed value. With timely updates, HABD aims to facilitate the processing and visualization of data for scientists, providing a one-stop-shop for all biological databases. Computer platforms, such as PhP, html, CSS, Java script and Biopython, are used to build all the databases. © 2024 Wiley Periodicals LLC.

Intelligent decision making for energy efficient fog nodes selection and smart switching in the IOT: a machine learning approach.

With the emergence of Internet of Things (IoT) technology, a huge amount of data is generated, which is costly to transfer to the cloud data centers in terms of security, bandwidth, and latency. Fog computing is an efficient paradigm for locally processing and manipulating IoT-generated data. It is difficult to configure the fog nodes to provide all of the services required by the end devices because of the static configuration, poor processing, and storage capacities. To enhance fog nodes' capabilities, it is essential to reconfigure them to accommodate a broader range and variety of hosted services. In this study, we focus on the placement of fog services and their dynamic reconfiguration in response to the end-device requests. Due to its growing successes and popularity in the IoT era, the Decision Tree (DT) machine learning model is implemented to predict the occurrence of requests and events in advance. The DT model enables the fog nodes to predict requests for a specific service in advance and reconfigure the fog node accordingly. The performance of the proposed model is evaluated in terms of high throughput, minimized energy consumption, and dynamic fog node smart switching. The simulation results demonstrate a notable increase in the fog node hit ratios, scaling up to 99% for the majority of services concurrently with a substantial reduction in miss ratios. Furthermore, the energy consumption is greatly reduced by over 50% as compared to a static node.

Diagnosis and Treatment of Liver Disease: Current Trends and Future Directions.

This narrative review delves into the intricate landscape of liver diseases, providing a comprehensive background of the diverse conditions that afflict this vital organ. Liver diseases, ranging from viral hepatitis and non-alcoholic fatty liver disease (NAFLD) to cirrhosis and hepatocellular carcinoma (HCC), pose significant global health challenges. Understanding these diseases' multifaceted origins and progression is pivotal for developing effective diagnostic and therapeutic strategies. The epidemiology and etiology of liver diseases emphasize the global impact of viral hepatitis, with hepatitis B and C as significant contributors. Concurrently, the rising prevalence of NAFLD, linked to lifestyle factors and metabolic syndrome, underscores the intricate relationship between modern living and liver health. Chronic liver diseases often evolve insidiously, progressing from inflammation to fibrosis and, ultimately, to cirrhosis - a stage characterized by irreversible scarring and compromised function. The heightened risk of HCC in advanced liver disease stages further underscores the urgency of effective diagnostic and therapeutic interventions. The evolving landscape of non-invasive diagnostic tools is explored for their role in enabling early detection and accurate staging of liver diseases. In the realm of treatment, there is a continuous transition toward personalized medicine, customized to suit the unique profiles of individual patients. This shift encompasses a broad spectrum, ranging from personalized pharmacological interventions to lifestyle modifications and surgical options. Delving into innovative therapies, such as gene editing and immunomodulation, offers a glimpse into the promising future directions that have the potential to redefine the landscape of liver disease diagnosis and treatment.

Cardio-Oncology: Managing Cardiovascular Complications of Cancer Therapies.

This narrative review explores the complex relationship between cancer medicines and cardiovascular health in the junction of oncology and cardiology, known as cardio-oncology. The study examines the historical development of cancer treatments and highlights the growing importance of cardiovascular problems in patient care. This text delves into the topic of cardiotoxicity, examining both conventional chemotherapeutic drugs like anthracyclines and more recent tyrosine kinase and immune checkpoint inhibitors. The complex molecular and cellular mechanisms that control cardiovascular problems are explained, including an understanding of how genetic predisposition influences an individual's sensitivity. The narrative expands into the crucial realm of risk stratification and evaluation, revealing advanced instruments for identifying cardiovascular risk in cancer patients. The importance of non-invasive imaging methods and biomarkers in early detection and continuous monitoring is emphasized. The prioritization of preventive tactics emphasizes the need to take proactive measures incorporating therapies to protect the heart throughout cancer treatment. It also highlights the significance of making lifestyle improvements to reduce risk factors. The narrative emphasizes the changing collaborative treatment environment, advocating for merging oncologists and cardiologists in a coordinated endeavor to maximize patient outcomes. In addition to clinical factors, the review explores the critical domain of patient education and support, acknowledging its crucial role in promoting informed decision-making and improving overall patient well-being. The latter portions of the text anticipate and consider upcoming treatments and existing research efforts that offer the potential for the future of cardio-oncology. This review seeks to provide a detailed viewpoint on the intricate connection between cancer treatments and cardiovascular well-being. Its objective is to encourage a more profound comprehension of the subject and prompt careful contemplation regarding the comprehensive care of cancer patients who confront the intricate difficulties presented by their treatment plans.

Sex-Linked Differences in Pulmonary Functions of COVID-19 Patients After a Six-Minute Walk Test.

Coronavirus disease 2019 (COVID-19) predominantly impacts the respiratory system. Historically, numerous lung diseases have shown sex-related differences throughout their progression. This study aimed to identify sex-linked disparities in pulmonary function tests (PFTs) among individuals who have recovered from COVID-19 when subjected to a six-minute walk test (6MWT). In this observational cross-sectional study, we analyzed 61 participants, consisting of 39 (64%) males and 22 (36%) females, all of whom previously contracted COVID-19 three months or more prior. We measured vitals such as blood pressure, pulse, oxygen saturation, and PFT values before and after the 6MWT. The post-6MWT evaluation revealed notable mean differences between males and females in parameters systolic blood pressure (SBP) (p = 0.003), diastolic blood pressure (DBP) (p = 0.026), forced expiratory volume in the first second (FEV1) (p = 0.038), forced vital capacity (FVC) (p = 0.041), and maximum voluntary ventilation (MVV) index (p = 0.011). PFT outcomes indicated sex-based variations among post-COVID-19 subjects. Specifically, post-stress values for FEV1, FVC, MVV index, SBP, and DBP were more elevated in males than in females. However, females presented with higher oxygen saturation levels post-COVID-19 compared to males. Using multiple linear regression modeling, sex was not found to be a strong predictor of PFT results. However, individual regression analyses for FEV1, FVC, and MVV index consistently showcased higher values in males. In conclusion, significant PFT differences exist between males and females after recovery from COVID-19 when exposed to stress induction via the 6MWT.

Neurological Manifestations of Infectious Diseases: Insights From Recent Cases.

This narrative review examines the complex connection between infectious diseases and their neurological effects. It provides a detailed analysis of recent instances and insights derived from various pathogens. As we explore the realm of infectious agents, including viruses, bacteria, parasites, and fungi, a thorough and diverse analysis reveals the intricacies of neurological problems. The review begins by examining viral infections, specifically focusing on how viruses invade the neurological system and its subsequent effects. Significant instances from recent widespread disease outbreaks function as instructive benchmarks, highlighting the progressing comprehension of these ever-changing interconnections. The article examines the complex pathophysiology of neurological problems caused by bacterial infections. It presents current cases that illustrate the various ways these complications might manifest and the difficulties faced in their therapeutic management. Parasitic and fungal infections, which are typically overlooked, are being carefully examined to emphasize their distinct role in causing neurological complications. The mentioned cases highlight the importance of being thoroughly aware of these less-explored areas ranging from protozoan parasites to opportunistic fungal infections. In addition to the immediate effects caused by infectious agents, the review investigates autoimmune responses activated by infections. It provides a detailed examination of specific instances that shed light on the complex relationship between viral triggers and future neurological problems. This text elaborates on the intricacy of autoimmune-related neurological issues, highlighting the necessity for a comprehensive approach to diagnosing and treating them. The narrative next redirects its attention to the diagnostic difficulties that arise when interpreting the neurological symptoms of viral disorders. This article provides a thorough examination of existing diagnostic tools, along with an investigation into new technologies that have the potential to improve our capacity to identify and comprehend complex presentations. This debate connects to the following examination of treatment methods, where current cases that showcase successful interventions are carefully examined to extract valuable insights into good clinical management. The discussion focuses on the public health implications of preventive efforts against infectious infections, including their neurological consequences. The story emphasizes the link between infectious diseases and overall societal health, advocating for a proactive strategy to reduce the impact of neurological complications. The abstract concludes by providing a prospective viewpoint, highlighting areas of research that still need to be addressed, and suggesting potential future avenues. This narrative review seeks to provide a comprehensive resource for physicians, researchers, and public health professionals dealing with the complex field of neurological manifestations in infectious diseases. It combines recent examples, synthesizes current information, and offers a holistic perspective.