Global Journal of Multidisciplinary Sciences and Arts
The Global Journal of Multidisciplinary Sciences and Arts is an internationally recognized Pakistan-based journal that is published by a well-known publisher of Pakistan GLOBAL ALLIANCE FOR SCIENTIFIC STUDIES. Global Journal of Multidisciplinary Sciences and Arts operates under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) It welcomes submissions from various disciplines. It is a peer-reviewed and open-access publication that aims to showcase high-quality original research, reviews, letters, and case reports in natural sciences, social sciences, applied sciences, formal sciences, arts, and related areas. Our goal is to improve the efficient dissemination of new research ideas and findings, enabling researchers to generate new knowledge, studies, and inventions that will serve as a valuable reference for the future. The Journal is affiliated with Global Alliance for Scientific Studies (SMC-Private) Limited Multan, Pakistan. Journal Description Journal Name Global Journal of Multidisciplinary Sciences and Arts ISSN Number 3078-2724 Editor in Chief Abdul Samad | Department of Animal Science Gyeongsang National University 501, Jinju-daero, Jinju-si, Gyeongsangnam-do Frequency a Half Year| June and Decemeber Research Scope Computer Science | Management | Veterinary | Mathematics | Agriculture | Engineering | Health
Next-Generation Healthcare: How AI is shaping the Future of Healthcare Informatics
The field of healthcare informatics is also being transformed by artificial Intelligence (AI), which allows conducting intelligent data analysis, predictive modeling, and automating clinical and administrative processes. This review discusses the underlying technologies in AI, such as machine learning and deep learning and natural language processing and computer vision, and their current applications in electronic health records, diagnostics, clinical decision support, and population health management. The combination of AI and healthcare infrastructure is associated with the opportunities of the personalized care, workflow optimization, and proactive approaches to the population health, as well as with ethical, legal, and operational issues. New developments in generative AI, digital twins, and autonomous systems point to a more efficient future being easier to achieve, patient-focused.
Artificial Intelligence, Healthcare Informatics, Machine Learning, Clinical Decision Support, Predictive Analytics.
Copyright (c) 2024 Bimalendu Pendy (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Advancing Healthcare through Artificial Intelligence: A Comprehensive Review of Machine Learning Applications in Health Informatics
Deep learning and other types of Artificial Intelligence (AI) are quickly changing the healthcare and health informatics landscape to allow deeper data analysis, predictive modeling, and customized care of patients. Convolutional and recurrent neural networks are examples of deep learning architecture that have demonstrated spectacular performance in medical imaging, disease prediction, drug discovery and telemedicine applications. Health informatics will ensure the required data collection, data storage, and integration structures that will ensure efficient and safe operation of AI models. The emerging techniques are mitigating these drawbacks despite the various problems posed by data quality, interpretability, ethical issues, and infrastructure needs. The review presents the existing innovations, uses, challenges, and prospects, focusing on the synergistic opportunities of AI and deep learning to transform the modern healthcare.
AI, Deep Learning, Healthcare, Health Informatics, Medical Imaging, Predictive Analytics, Personalized Medicine, Telemedicine.
Copyright (c) 2024 Mohammad Ali (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Quality and Efficiency in the Age of AI: A Review of Healthcare Informatics, Computer Science Innovations, Nanocarrier Drug Delivery, Cybersecurity, Food Production, and Lean Six Sigma
Computational technologies and artificial intelligence (AI) are revolutionizing the healthcare, food production, and biomedical research spheres through the increase of efficiency, quality, and optimization. This review discusses AI-controlled healthcare systems, health informatics, nanocarrier drug delivery, computational modeling, and cybersecurity and their role in diagnostics, patient care, and optimization of operations. Simultaneously, AI-based solutions in the agricultural sector, food production, and supply chain management enhance resource use and sustainability. The combination of the Lean Six Sigma and AI indicates quantifiable improvements in the efficiency of processes in the domains. Ethical, technical and regulatory issues are presented, focusing on the interdisciplinary cooperation and future research strategies on the way to the sustainable, intelligent, and high-quality systems.
AI, healthcare informatics, nanocarrier drug delivery, cybersecurity, Lean Six Sigma, predictive analytics, process optimization, sustainability.
Copyright (c) 2025 Ali Husnain (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Advancements and Integrative Approaches in Modern Healthcare: AI-Driven Health Informatics, Nanocarrier-Based Drug Delivery, Cybersecurity, and Lean Six Sigma Applications
Healthcare industry has been experiencing revolutionary developments in the fields of artificial intelligence (AI), drug delivery using nanocarriers, cybersecurity, and Lean Six Sigma. The artificial intelligence-based health informatics improves the quality of diagnostics, predictive analytics, and individual therapy, and nanocarriers provide the delivery of drugs to specific tissue sites in a targeted and controlled manner, improving therapy effectiveness and minimizing side effects. At the same time, effective cybersecurity allows protecting sensitive patient data and medical systems, which promotes safe online healthcare activities. Lean Six Sigma streamlines operations, diminishes mistakes, and improves the efficiency of operations. This review identifies the synergistic prospects of these areas, current applications, challenges, and future prospects, and the overall thrust of these areas in delivering precise, efficient, and secure healthcare delivery.
Artificial intelligence, Health informatics, Nanocarrier drug delivery, Cybersecurity, Lean Six Sigma, Precision medicine.
Copyright (c) 2024 Alexandra Harry (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Integrating AI in Healthcare, Health Informatics, and Food Production: Advances in Machine Learning, Nanocarrier Drug Delivery, Computational Methods, Cybersecurity, and Quality Assurance
Artificial Intelligence (AI) is transforming the healthcare system, health informatics, drug delivery, and food production as it allows making predictions, tailored treatment and streamlining processes. This review discusses the combination of AI and machine learning, nanocarrier-based drug delivery, computational solution, cybersecurity, and quality assurance in these fields. In the healthcare sector, AI has improved diagnostics, treatment planning, and patient monitoring, whereas in the food production industry it is applied in precision agriculture, optimization of the supply chain, and safety monitoring. Data privacy, bias in algorithms, and compliance with regulations are the other issues that were discussed in the paper. Future looks indicate interdisciplinary innovations that may offer safer, effective and sustainable solutions in the health and nutrition.
Artificial Intelligence, Machine Learning, Nanocarrier Drug Delivery, Health Informatics, Food Production.
Copyright (c) 2024 George Edison (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Harnessing C–H Activation and Photoredox Catalysis in Organic Synthesis: A Contemporary Review
C–H activation and photoredox catalysis have become complementary and are leading to the synergistic integration into a new potent approach to modern organic synthesis that is highly selective, efficient, and sustainable in its ability to transform molecules. Site-selective functionalization of inert C-H bonds is achieved through C-H activation, and the formation of reactive radical intermediates in mild conditions under visible light is achieved through photoredox catalysis. Their combination enables two-catalytic processes, which provides the possibility to build new bonds and functionalize functional groups late, as well as bring complex molecules, such as natural products, pharmaceuticals, and heterocycles, into easy reach. Recent developments include the emphasis on environmentally friendly procedures, widening the range of substrates, and reaction design that is guided by calculations. This review has outlined key principles, mechanistic understanding, applications, challenges and emerging trends in this field of synthetic chemistry with particular focus on its transformative nature through this dual approach.
C–H activation, photoredox catalysis, dual catalysis, visible-light reactions, late-stage functionalization
Copyright (c) 2024 Javeriya Sayed (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
AI in Lean Six Sigma: A Review of Industrial Implementations, Benefits, and Barriers
The present review addresses the concept of Artificial Intelligence (AI) integration in the methods of Lean Six Sigma (LSS), its industrial applications, advantages, and obstacles. The AI technologies like machine learning, predictive analytics, and computer vision can support LSS by facilitating real-time processing of data, forecasting decision-making, and optimization of processes. The paper presents the examples of successful applications in manufacturing, healthcare, services and logistics showing that the efficiency, quality and innovation are strongly improved. Nevertheless, the problems of data quality, cultural resistance, and lack of skills remain. The review concludes that AI-based LSS promotes smart and flexible and sustainable continuous improvement in line with Industry 4.0 and beyond.
Artificial Intelligence, Lean Six Sigma, Process Optimization, Predictive Analytics, Industry 4.0, Continuous Improvement.
Copyright (c) 2024 Muhammad Mohsin Kabeer (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Synergizing AI and Lean Six Sigma: A Comprehensive Review of Smart Quality Assurance Systems
This review examines how Artificial Intelligence (AI) can be integrated with Lean Six Sigma (LSS) in making intelligent and data-driven Quality Assurance (QA) systems. The new AI technology can complement the old LSS techniques by adding predictive analytics, automation, and optimization of processes at any moment, allowing to control the quality pro-actively and constantly improve the processes. The article discusses the important uses, advantages, issues and future of AI-driven Lean Six Sigma within the contemporary industries. The results indicate that AI is highly useful in enhancing the accuracy, efficiency, and decision-making in the DMAIC framework; in addition, it corresponds to the Industry 4.0 and 5.0 paradigms. The paper concludes that AI-enhanced LSS can be taken as a radical change to smarter, adaptive, and sustainable quality management systems.
Artificial Intelligence, Lean Six Sigma, Quality Assurance, Predictive Analytics, Automation, Continuous Improvement, Industry 4.0, Smart Manufacturing.
Artificial Intelligence in Product Management: Driving Innovation and Market Success
The use of Artificial Intelligence (AI) in product management is changing very fast, as it allows making decisions based on data, optimizing processes, and introducing novel solutions. This review examines how AI can be used throughout the product lifecycle including market research, product strategy, development and project management. Using AI, predictive analytics, customer insights, allocation of resources, and risk assessment are increased, making AI more efficient, personalized, and time-to-market. Although it has considerable benefits, the issues that may arise when adopting AI include problems with data quality, ethical aspects, and complexities with integrations, as well as adapting the workforce. The review shows industry case studies and trends, with an accent on the possibility of strategic, responsible AI implementation to drive innovation, improve performance of the products and provide market success with the time of growing competition of the business world.
AI, Product Management, Innovation, Predictive Analytics, Customer Insights, Project Management, Decision-Making, Market Success.
Copyright (c) 2024 Muhammad Shahrukh Aslam (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Artificial Intelligence as a Catalyst for the Next Generation of Healthcare Innovation
The application of Artificial Intelligence (AI) in healthcare is changing the industry, making it more precise, efficient, and personalized in the care of patients. This review examines the history, underlying technologies, and various uses of AI in diagnostics, treatment plan, and healthcare management. It emphasizes the significant advantages, which are better diagnostic accuracy, predictive medicine, and the efficiency of its operation, and problems in ethics, law, and social issues, which include data privacy, biases, and responsibility. The paper is also focused on the existing constraints and opportunities with a particular emphasis on the transition to explainable, equitable, and human-centered AI systems. AI is an effective innovation driver that can influence a smarter, more equitable and compassionate future of healthcare.
Machine learning, Healthcare innovation, artificial intelligence, predictive analytics, deep learning, ethical issues, digital health.
Copyright (c) 2024 Muhammad Fahad, Mazhar farooq, Shah Zeb (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
AI in Manufacturing Quality Management: A Review of Techniques, Tools, and Industrial Adoption
It is true that Artificial Intelligence (AI) is fast transforming the quality management of manufacturing services by providing smarter, data-driven solutions to detect defects in manufacturing processes, optimize processes and provide predictive maintenance. Conventional approaches to quality assurance are easily surpassed by complex data and dynamic production contexts, whereas AI-based technologies, including machine learning, deep learning, computer vision, and reinforcement learning, demonstrate increased accuracy, scale and flexibility. This review discusses the principles of AI in quality management, its major technologies, tools, and implementation in Industry 4.0 ecosystems. It also emphasizes industry adoption in the automotive, electronic, pharmaceutical and aerospace sectors and discusses the issues of data quality, implementation cost, employee preparation and readiness and interpretability. The trends of the future focus on explainable AI, sustainable manufacturing and human-AI cooperation. In contemporary manufacturing AI is offering radical possibilities of attaining better quality management that is efficient, reliable, and sustainable.
Artificial Intelligence, Quality Management, Manufacturing, Machine Learning, Deep Learning, Computer Vision, Industry 4.0, Predictive Maintenance, Digital Twins
From Algorithms to AI: A Comprehensive Review of Core Concepts in Computer Science
The review delves into the very ideas of Computer Science and constantly-developing fields, thoroughly reviewing the theoretical basis and the most modern technologies. The theory is started with basic concepts like algorithms, data structures and models of computation then moves to programming paradigms, architecture of computation, and operating systems. The explanations are carried out to its practical fields such as databases, networking, software engineering and artificial intelligence. Emerging fields like quantum computing, human-computer interaction, cloud and edge computing and ethical considerations are also outlined. Through the combination of fundamental knowledge and its application in the real world, the review highlights the cross-disciplinary purpose of Computer Science and its central role in innovation of the present times. The goal of this synthesis is to help learners, educators, and professionals learn the depth and relevance, as well as the future development direction of the field.
Algorithms, artificial intelligence, computer architecture, operating systems, programming paradigms, quantum computing, and software engineering.
Copyright (c) 2025 Ankur Singh (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Privacy, Policy, and Progress: Reviewing the Regulatory Landscape in Health Informatics
Because of health informatics, digital systems can now gather, analyze and trade health information. Nevertheless, using new technologies such as electronic health records, artificial intelligence and telehealth brings up important issues related to data privacy, proper use and being controlled by rules. It reviews basic health informatics principles and studies international rules, like HIPAA and GDPR, pointing out the difficulties in fulfilling these rules and the need for similar regulations. It also deals with ethical issues about consent, who owns data and the bias found in algorithms, as well as rules that ensure both progress and responsibility. AI, block chain and remote monitoring have huge potential, but to avoid problems, strong guidelines should be adopted. The review underlines how adaptive and inclusive governance guarantees progress in health informatics by focusing on patients’ rights and technology at the same time.
Copyright (c) 2025 Mohammed Javeedullah, Shah Zeb (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Digital Health Revolution: Wearables in Health Informatics
Advancements in wearable technology have enabled health informatics to continuously monitor an individual’s health and behavior.The review looks at various wearables for consumers and medical use and how they support chronic disease management, monitoring patients from a distance, spotting diseases early, and personalized care. Wearable data can be added to health information systems so that healthcare professionals can improve decisions and offer preventive healthcare. Still, issues such as data accuracy, privacy, challenges with sharing information, and following regulations are making it difficult for more people to use Block chain. Innovations in sensors, AI, smart clothes, and handling data are expected to remove these problems and improve the accuracy, confidentiality, and user experience of wearables. Because of their continual advancements, wearables will have a greater impact on health informatics to help patients and support public health. It brings out how wearable technology can have a significant impact on healthcare and points out the main obstacles to using them successfully.
Copyright (c) 2025 Mohammed Javeedullah (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Harnessing AI for Product Design and Processing
This review brings forth the major changes that Artificial Intelligence is bringing to product design and manufacturing. Thanks to generative design, machine learning and computer vision, AI makes creativity, optimization and automation much easier in product development. In designing products, AI speeds up coming up with new ideas, testing ideas and meeting customer needs and in processing products, it raises the quality, helps prevent problems and automates several tasks in smart facilities. The writing covers the key aspects of artificial intelligence, important tools involved and recent advancements. While AI greatly helps, still, some obstacles, for instance, problems with data quality, mixing multiple systems, transparent explanations and ethical questions persist. After that, considerations are given to areas such as sustainable design, working together with AI and explainable AI, revealing how AI could lead to more advanced, efficient and ethical development of products. This overview proves useful for researchers, engineers and industry leaders who want to apply AI to succeed against competition.
Copyright (c) 2025 Muhammad Mohsin Kabeer (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Transforming Supply Chains: Innovations, Sustainability, and Resilience in the Modern Era
Supply chain management continues to transform at present because of technological innovations together with environmental sustainability goals and market demands for operational stability in an unstable worldwide system. Supply chain operations experience revolutionary changes through key trends which include automation with artificial intelligence (AI) and machine learning and the Internet of Things (IoT) that improve efficiency and help make better decisions and provide enhanced visibility. Both Block chain technology improves system transparency and security while digital twins achieve real-time monitoring operations which optimize supply chain process functions. Sustainability stands as the new core priority alongside which companies now devote their resources to establishing sustainable sourcing methods and reducing waste and increasing energy operational efficiency. Business operations focus on resilience together with risk management because companies implement adaptable supply chains that can withstand multiple types of disruptions including geopolitical tensions and natural disasters and unexpected threats. Supply chains of the future will evolve under current scientific innovations while maintaining their emphasis on agile structures and circular economy practices. Firms adopting these trends will better satisfy shifting customer needs and operate with improved efficiency through a global market that requires competitiveness. The abstract details crucial supply chain-transforming trends and disruptive innovations alongside their effects on businesses that plan to succeed in developing complicated market conditions.
Copyright (c) 2024 Abdul Ahad, Muhammad Rehan Ashraf, Khizar Ilyas, Benish Sarfraz (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
Modern Trends in Urdu Literature: A Brief Overview
The contemporary Urdu literary world unites classic heritage with novel emotional content through innovative structural forms. This research project checks vital shifts within contemporary Urdu literature while assessing how progressive writers embraced social justice discussion through protests against repressive practices. Following independence Urdu writers conducted significant investigations into partition trauma through the study of dislocation effects and culture separation together with identity matters. New counting patterns and literary building approaches emerged as fundamental elements in contemporary Urdu literature because authors utilize these elements to express the realities of current times. Publisher and artist women use feminist works to confront patriarchal social structures and express themselves forcefully across poetry and prose forms. Through their literary contributions Ismat Chughtai joined by Qurratulain Hyder and Faiz Ahmed Faiz shaped novel trends in Urdu literature that delved into political events and gender analyses with human experiential study. The combination of worldwide integration and digital platforms has widened Urdu literature's reading audience base while maintaining original language roots to allow writers global literary exposure. Leaving behind social critique and political examination Urdu literature maintains both its academic relevance and cultural depth.
experimentation, feminist literature, social realism, Urdu poetry
Copyright (c) 2024 Global Journal of Multidisciplinary Sciences and Arts
Design and Control of a Ball and Beam Balancing Mechanism Using MATLAB/Simulink
This report begins with an introduction to a ball and beam balancing mechanism. Basic electronic components and transmission mechanisms are also discussed which is then linked to mathematical calculations. An in-depth dynamic model of ball is presented which includes basic dynamic equations derived from newton’s laws of motions and lagrangian approach. However, lagrangian approach is used throughout to model system on a computer. Matlab/simulink was used to generate system output by employing a pid controller and a lead compensator. Root locus method was used to design a lead compensator. Lead compensator designed was also used with simulink model of the system to achieve desired system output. Output generated from each control strategy successfully satisfied the design criteria i.e. Percentage overshoot to be less than 5% and settling time to be less than 3 seconds.
Ball and Beam Balancing Mechanism, Dynamic Modeling, Lagrangian Approach, Newton’s Laws of Motion, PID Controller, Lead Compensator, Root Locus Method, MATLAB/Simulink, Control Strategies, System Output, Percentage Overshoot, Settling Time
Ethical Implications and Practical Applications of AI in Modern Healthcare
AI is capable of solving many problems in the contemporary healthcare systems, and its application is likely to enhance the diagnostic process, choose individual treatment plans, enhance the level of patient satisfaction and enhance the organization of the delivery of healthcare. Techniques of machine learning and natural language processing based on AI have revealed their efficiency for diagnosing the illness, getting the positive results and client’s oriented recommendations concerning treatment of diseases. Nonetheless, the advancement and use of AI technologies in healthcare brings to the table several innuendos: privacy; security; data control and dissemination; responsibility and prejudice. Luckily however, addressing these challenges needs not only good and advisable policies and guidelines but also cooperation among policy makers, ethicists, technology and health care providers /researchers etc. The purpose of this review is to identify the most common ethical concern regarding the application of AI in health care and the results of practical efforts. It escalates how AI could vary from altering diagnosis approaches, enhancing therapies, controlling documents to raising stress on consumer’s details and securing that those leveraging artificial intelligence act morally and brightly. But the process of getting there into the era of benefit realization from this new technology will open more ideas and details into risks such as bias inference in AI models, patient’s consent and agency, and accessibility of AI technologies in developing countries and remote areas. In conclusion it will be necessary to be purposely reasonable, to be conscious and very communicative in order to introduce AI into better and convenient and humane healthcare.
AI in Healthcare: diagnostic improvements, treatment customization, data issues as storage, security, and analysis, ethical concerns, employing AI for predictions, healthcare factors, staff training, precision healthcare, accountability in AI, healthcare disparities, robotic function, AI transparency, legal implications
Cybercrime and Cybersecurity in the Age of AI: Exploring the Challenges and Opportunities Presented by ChatGPT
One of the most hopeful trends in cybersecurity specialization is the utilization of artificial intelligence (AI) in the anti-cybersecurity movement, which provides specialists with rather elaborate tools to identify, thwart, and respond to newer, and more diverse, digital threats. While AI programs compliment traditional approaches of the identification of cyber threat and other measures, the former stands advantages in the way it can pin-point future threats and act on them. Nevertheless, as the usage of AI grows so does new threats emerge; first of all, AI is hackable which means that it can be used by offenders, thus the threats are consistently evolving exist. In this work the author also described more important role of AI in cyber space for both defense and offense. The FCA has indeed eyed the regulations and governance aspect as being at the heart of the ethical AI, privacy issue and reporting. In order to avoid the situation when security is dominated by technology, and within cyberspace threats are solved cooperatively at the international level, there is an appeal to open, non-discriminatory, and constantly developing architecture. It is anticipated that new trends, such as self-managing systems, computational prognostication, self-healing models, will emerge in the sphere of cybersecurity using AI, however, it is necessary to mention that this field has to be applied at the right level due to potential unfavorable outcomes. Finally, the achievement of a synergy in artificial intelligence alongside human decision-making will create robust digital environments that this author shall use towards the safe development of the new technology alongside the fight against emergent cybercrime challenges.
AI, cybersecurity, cyber threats, Big Data, rule, policy, ethic AI, data privacy, responsibility, probabilistic approaches, autonomous system, threat, cooperation international, self-correcting system, protection, AI military, AI warfare, ethic, openness, regulation, digital.
Cardiovascular Diseases: Understanding the Leading Cause of Death Worldwide
This comprehensive review paper thoroughly explains the complex domain of cardiovascular diseases (CVDs), offering a detailed overview of their various aspects. This review effectively explores the role of atherosclerosis as the central factor in the development of cardiovascular diseases (CVD). It highlights the chronic and asymptomatic nature of these diseases, emphasizing their significant impact on worldwide mortality and morbidity. An in-depth examination of risk factors reveals the significant influence of type 2 diabetes, hypertension, and dyslipidemia. The conversation smoothly moves on to coronary artery disease, providing insight into the complex mechanisms of plaque formation and its potentially devastating outcomes, including stroke and myocardial infarction. The review provides significant insights into cerebrovascular illnesses, clarifying the diverse etiologies and highlighting the essential connection between risk factors and atherosclerosis. The pathogenesis of cardiovascular diseases (CVDs) is analyzed meticulously, focusing on endothelial dysfunction and emphasizing the interaction between oxidative stress, inflammation, and apoptosis in the degradation of the heart muscle. The frequency of cardiovascular diseases (CVDs) is examined by considering age and gender, and by doing a detailed investigation into hormone replacement therapy and its effects on the aging heart. This article comprehensively analyzes atherosclerosis as a significant risk to the small blood vessels, with particular emphasis on dyslipidemia and its association with diabetes. This review explores the influence of diabetes on the autonomic nervous system and local metabolism, establishing links to macro vascular disorders. Inflammation has an important role in causing cardiovascular diseases specifically in obese people. The article focuses on the clinical symptoms of cardiovascular diseases caused by diabetes, highlighting the significance of promptly identifying and evaluating autonomic neuropathy. The report finishes by endorsing a comprehensive approach to cardiovascular health, emphasizing the importance of lifestyle variables and patient education in the context of secondary prevention. The article emphasizes the relevance of pharmacotherapies in managing cardiovascular disease (CVD).
Cardiovascular Diseases, Hypertension, Dyslipidemia, Obesity
The Silent Threat: Understanding Microbial Toxins and Their Global Impacts
This abstract looks on to microbial toxins that play important role in shaping the ecosystem and affecting various aspects of human life. These toxic substances are produced by variety of microorganisms such as bacteria, viruses and algae. Understanding their nature and effects is essential for studying global impacts. Bacterial toxins contains strains of different bacterial species such as Escherichia coli, and Clostridium botulinum, have significant implications for human health. They can causes severe diseases from gastrointestinal infections to life threatening conditions. The food borne illness is often related to bacterial toxins. Fungal toxins such as mycotoxins, pose serious threat to crops and food security. The global trade of food makes it easy for mycotoxins to spread and affect human health (such as liver and kidney damage) and crops. Algae toxins, produced by certain species of microalgae, can lead to harmful algae blooms (HABs). These toxins cause mass mortality of marine life and disrupting the aquatic ecosystem. HABs can contaminate sea food and cause diseases to humans through contaminated fish and shell fish. Climate change further complicates the scenario by promoting the prevalence of toxins producing substances. Rising temperature and precipitation patterns create favorable conditions for toxin producing species. Efforts to address this, lies with the collaboration of microbiologists, ecologists and public health experts. Surveillance systems for early detection, regulations on food safety and research strategies. In conclusion, microbial toxins exerts many effects on global health, and ecosystem. Understanding their nature and implementing effective measures is necessary for the sustainability of the planet.
Toxins, microbial toxins, aflatoxins, mycotoxins, domoic acid, cyano toxins, global impact.
Diabetes Mellitus Disclosure: A Comprehensive Review on a Global Issue
Diabetes mellitus is a long-term metabolic disease associated with increased blood sugar levels that result from imperfections in insulin secretion. It is a genetic disorder that affects millions of people annually and inflicts substantial health threats. Various genetic and environmental factors play a significant role in the pathogenesis of diabetes. Type 1 diabetes is induced by an autoimmune reaction in the body that causes the deterioration of insulin-secreting cells in the pancreas. Whereas, Type 2 diabetes is a more severe form that is illustrated by the resistance and hindrance of insulin production. The contributing risk factors for diabetes comprise the genetic history of diabetes mellitus, overweight, poor way of living, and increasing age. The complexities linked with diabetes influence different organs by inducing heart disorders, nephrosis, retinal vascular disease, and peripheral neuropathy. Since diabetes mellitus is a chronic disease, it can develop the risk of other infections that affect the person’s fitness. Management techniques for diabetes are important for keeping blood glucose levels in check. Insulin therapy, a healthy lifestyle, and proper exercise are crucial parameters to prevent diabetes mellitus. Some oral medications and injectable treatments aim to enhance the susceptibility, efficacy, and secretion of insulin to inhibit glucose assimilation. By comprehending the etiology and potential determinants, we can execute extensive management procedures to eliminate the soaring occurrence and problems analogous to diabetes mellitus. This review essentially highlights the essential factors linked with diabetes mellitus and useful management to improve the grade of life for people impacted by this chronic disease.
Historical background of Diabetes, Types of Diabetes, Risk factors, Signs and symptoms, Prevention, Pathophysiology, Management, Treatment
Transformative Applications of ChatGPT: A Comprehensive Review of Its Impact across Industries
ChatGPT, developed by OpenAI, represents a significant advancement in conversational artificial intelligence. As a model based on the GPT (Generative Pre-trained Transformer) architecture, it excels in generating human-like text and engaging in natural language interactions. Its ability to understand and produce contextually relevant responses has made it a transformative tool across various sectors. The proliferation of ChatGPT's applications highlights its potential to enhance efficiency, personalize interactions, and automate complex tasks. However, its integration into different fields also brings challenges related to ethics, bias, and technical limitations. This review aims to provide a comprehensive examination of ChatGPT's applications and impact across diverse domains, including healthcare, education, business, legal services, creative industries, and social media. It seeks to elucidate how ChatGPT enhances operations and interactions in these fields by offering personalized support, automating processes, and driving innovation. Additionally, the review aims to identify the challenges and limitations associated with ChatGPT’s deployment, including ethical concerns, technical constraints, and the balance between human and AI collaboration. By analyzing these aspects, the review intends to offer insights into the current and future role of ChatGPT in shaping industry practices and improving user experiences. ChatGPT is reshaping various industries by providing advanced conversational capabilities that enhance efficiency, personalization, and automation. In healthcare, it supports patient care and research; in education, it aids personalized learning and teaching; in business, it revolutionizes customer service and operational workflows; in legal services, it assists with research and compliance; and in creative fields, it fosters content creation and artistic expression. Despite its transformative potential, ChatGPT faces challenges such as bias, ethical concerns, and technical limitations. Addressing these issues is crucial for maximizing its benefits while ensuring responsible and equitable use. The future of ChatGPT holds promise with advancements in multimodal AI and hyper-personalization, positioning it as a key player in the ongoing evolution of artificial intelligence.
ChatGPT, Conversational AI, Personalized support. Automation, Ethics, Future of AI
Use of Probiotics and Prebiotics in the Management and Intervention of Cardiovascular Diseases
Cardiovascular disease is one of the leading causes of illness and death worldwide. The following are risk factors for cardiovascular disease: smoking, dyslipidemia, diabetes, obesity, inflammation, and hypertension. From the immediate effects of the gut microbiota on energy metabolism and obesity to the adjacent interaction between periodontal illness, heart attack, and stroke, microorganisms have a major effect on cardiovascular health. The probability of affecting or determining microorganisms is associated with probiotic and prebiotic applications. Probiotics are referred to as "live microorganisms that, when used in sufficient amounts, provide major advantageous effects for the host." The effectiveness of probiotics can be determined by the relationship between probiotic bacteria and the host's microbiome. Many of these fermented strains of probiotic bacteria are obtained from foods. Prebiotics are not microbes; they're just chemical substances that help microorganisms grow. Prebiotics can be observed in various foods, such as unprocessed grains, soybeans, and human milk; however, one of the most common forms is organic oligosaccharide. Probiotics and prebiotics are involved in the treatment of a variety of immune system diseases, such as type 2 diabetes, obesity, and cancer, according to an increasing number of recent studies. Yet, little is known about the potential use of these supplements as essential dietary components in the prevention or treatment of cardiovascular disease. The goal of this review is to discuss the function of probiotics, prebiotics, and gut microbiota in the treatment and prevention of cardiovascular diseases.
Cardiovascular disease, probiotic, prebiotic, microorganisms, gut microbiota.