Riphah International University

Nanotechnology has recently gained increased attention for its capability to effectively diagnose and treat various tumors. Nanocarriers have been used to circumvent the problems associated with conventional antitumor drug delivery systems, including their nonspecificity, severe side effects, burst release and damaging the normal cells. Nanocarriers improve the bioavailability and therapeutic efficiency of antitumor drugs, while providing preferential accumulation at the target site. A number of nanocarriers have been developed; however, only a few of them are clinically approved for the delivery of antitumor drugs for their intended actions at the targeted sites. The present review is divided into three main parts: first part presents introduction of various nanocarriers and their relevance in the delivery of anticancer drugs, second part encompasses targeting mechanisms and surface functionalization on nanocarriers and third part covers the description of selected tumors, including breast, lungs, colorectal and pancreatic tumors, and applications of relative nanocarriers in these tumors. This review increases the understanding of tumor treatment with the promising use of nanotechnology.

An outbreak of novel coronavirus disease (COVID-19) in China has influenced every aspect of life. Healthcare professionals, especially dentists, are exposed to a higher risk of getting infected due to close contact with infected patients. The current study was conducted to assess anxiety and fear of getting infected among dentists while working during the current novel coronavirus diseases (COVID-19) outbreak. In addition, dentists' knowledge about various practice modifications to combat COVID-19 has been evaluated. A cross-sectional study was conducted using an online survey from 10th to 17th March 2020. The well-constructed questionnaire was designed and registered at online website (Kwiksurveys) and validated. A total of 669 participants from 30 different countries across the world responded. After scrutiny, completed questionnaires (n = 650) were included in the study. Statistical analysis was performed using SPSS version 25. Chi-Square and Spearman correlation tests were applied to control confounders and assess the relation of dentists' response with respect to gender and educational level. More than two-thirds of the general dental practitioners (78%) from 30 countries questioned were anxious and scared by the devastating effects of COVID-19. A large number of dentists (90%) were aware of recent changes in the treatment protocols. However, execution of amended treatment protocol was recorded as 61%. The majority of the dentists (76%) were working in the hospital setting out of which 74% were from private, and 20% were from government setups. Individually we received a large number of responses from Pakistan and Saudi Arabia, but collectively more than 50% of the responses were from other parts of the world. Despite having a high standard of knowledge and practice, dental practitioners around the globe are in a state of anxiety and fear while working in their respective fields due to the COVID-19 pandemic impact on humanity. A number of dental practices have either modified their services according to the recommended guidelines to emergency treatment only or closed down practices for an uncertain period.

A wide range of polymers are commonly used for various applications in prosthodontics. Polymethyl methacrylate (PMMA) is commonly used for prosthetic dental applications, including the fabrication of artificial teeth, denture bases, dentures, obturators, orthodontic retainers, temporary or provisional crowns, and for the repair of dental prostheses. Additional dental applications of PMMA include occlusal splints, printed or milled casts, dies for treatment planning, and the embedding of tooth specimens for research purposes. The unique properties of PMMA, such as its low density, aesthetics, cost-effectiveness, ease of manipulation, and tailorable physical and mechanical properties, make it a suitable and popular biomaterial for these dental applications. To further improve the properties (thermal properties, water sorption, solubility, impact strength, flexural strength) of PMMA, several chemical modifications and mechanical reinforcement techniques using various types of fibers, nanoparticles, and nanotubes have been reported recently. The present article comprehensively reviews various aspects and properties of PMMA biomaterials, mainly for prosthodontic applications. In addition, recent updates and modifications to enhance the physical and mechanical properties of PMMA are also discussed.

Artificial Intelligence is no more the talk of the fiction read in novels or seen in movies. It has been making inroads slowly and gradually in medical education and clinical management of patients apart from all other walks of life. Recently, chatbots particularly ChatGPT, were developed and trained, using a huge amount of textual data from the internet. This has made a significant impact on our approach in medical science. Though there are benefits of this new technology, a lot of caution is required for its use. doi: https://doi.org/10.12669/pjms.39.2.7653 How to cite this: Khan RA, Jawaid M, Khan AR, Sajjad M. ChatGPT - Reshaping medical education and clinical management. Pak J Med Sci. 2023;39(2):605-607. doi: https://doi.org/10.12669/pjms.39.2.7653 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Nanoparticles typically have dimensions of less than 100 nm. Scientists around the world have recently become interested in nanotechnology because of its potential applications in a wide range of fields, including catalysis, gas sensing, renewable energy, electronics, medicine, diagnostics, medication delivery, cosmetics, the construction industry, and the food industry. The sizes and forms of nanoparticles (NPs) are the primary determinants of their properties. Nanoparticles’ unique characteristics may be explored for use in electronics (transistors, LEDs, reusable catalysts), energy (oil recovery), medicine (imaging, tumor detection, drug administration), and more. For the aforementioned applications, the synthesis of nanoparticles with an appropriate size, structure, monodispersity, and morphology is essential. New procedures have been developed in nanotechnology that are safe for the environment and can be used to reliably create nanoparticles and nanomaterials. This research aims to illustrate top-down and bottom-up strategies for nanomaterial production, and numerous characterization methodologies, nanoparticle features, and sector-specific applications of nanotechnology.

Antibiotic resistance (ABR) is a growing public health concern worldwide, and it is now regarded as a critical One Health issue. One Health's interconnected domains contribute to the emergence, evolution, and spread of antibiotic-resistant microorganisms on a local and global scale, which is a significant risk factor for global health. The persistence and spread of resistant microbial species, and the association of determinants at the human-animal-environment interface can alter microbial genomes, resulting in resistant superbugs in various niches. ABR is motivated by a well-established link between three domains: human, animal, and environmental health. As a result, addressing ABR through the One Health approach makes sense. Several countries have implemented national action plans based on the One Health approach to combat antibiotic-resistant microbes, following the Tripartite's Commitment Food and Agriculture Organization (FAO)-World Organization for Animal Health (OIE)-World Health Organization (WHO) guidelines. The ABR has been identified as a global health concern, and efforts are being made to mitigate this global health threat. To summarize, global interdisciplinary and unified approaches based on One Health principles are required to limit the ABR dissemination cycle, raise awareness and education about antibiotic use, and promote policy, advocacy, and antimicrobial stewardship.

With a diverse sample (N = 231 paired responses) of employees from various organizations in Pakistan, the authors tested for the main effects of perceived organizational politics and psychological capital on turnover intentions, job satisfaction, and supervisor-rated job performance. They also examined the moderating influence of psychological capital in the politics–outcomes relationships. Results provided good support for the proposed hypotheses. While perceived organizational politics was associated with all outcomes, psychological capital had a significant relationship with job satisfaction and supervisor-rated performance only. As hypothesized, the negative relationship of perceived organizational politics with job satisfaction and supervisor-rated performance was weaker when psychological capital was high. However, the result for turnover intentions was counter to expectations where the politics–turnover intention relationship was stronger when psychological capital was high.

Mixed convection is a mechanism of heat transport in a thermodynamic system in which the motion of fluid particles is produced by gravity as well as external forces like fans, pumps, or any other devices. Such type of heat transport has a fruitful application in daily life due to reliable maintenance. In this regard, numerous researchers and analyst have focused on the importance of mixed convective flow to explore its different aspects, and frequent research articles are published in this area. In this work, mixed convective entropy optimized nanomaterial magnetohydrodynamics (MHD) flow of Ree‐Eyring fluid is discussed between two rotating disks. The effects of porosity and velocity slip are considered. Both the disks are rotating with different angular frequency and stretching rates. Modeling is performed for the energy equation subject to heat generation/absorption, dissipation, radiative heat flux, and Joule heating. Four types of irreversibilities are discussed, and total entropy rate is calculated. The obtained results are compared with past studies and found good agreement with them. The physical curiosity like skin friction and Sherwood and Nusselt numbers are numerically calculated. Series solutions are computed via homotopy method. Our obtained outcomes show that the velocity and temperature fields show contrast behavior against larger magnetic parameter. It is also noticed that the entropy rate and Bejan number have opposite behaviors against higher values of Weissenberg number. The entropy rate increases for higher Weissenberg number while Bejan number decays.

The good quality of life, growth, nutrition and development of all living beings directly or indirectly depends upon natural surroundings. Urbanization, agriculture, industrial work and greenhouse effects are the leading causes of the climatic changes all over the world. These climatic changes are responsible to increase Carbon dioxide (CO2) and temperature on surface of the earth every year. All components of environment i.e. air, water and soil are altering mainly due to anthropogenic activities especially with changing life styles. The objective of this mini review is to elaborate the different climate changes, their causes and effects. Generally, climate change refers to any disturbance in climate which can cause negative impacts on living organisms which include humans, plants, and animals, which will be adverse for environment. With increase in population on the earth and industrialization the environment of the world is being disturbed every day. Human is destroying natural resources continuously for his own pleasure and convenience. Due to Carbon dioxide and other dangerous gases expelling from automobiles and industries are continuously poisoning air. Factories are releasing their wastes directly in water bodies without proper treatment and making them unfit for aquatic life. Plants act as filters which trap all pollutants to make environment cool, clean and green. Increase in population multiplication without increasing the plantation would completely damage the quality of life and our society in future. Plants are natural purifier of environment. Due to increasing concentration of carbon dioxide and global warming, temperature of earth is increasing day by day which cause various disorders in environment. The purpose of this review is to highlight climate change which is mostly occurring when there is rise in temperature and CO2 concentration and its impacts on environment. This change in climate is not beneficial rather it causes the damage of an ecosystem. So, human activities are changing the environment adversely. Increasing climate changes have affected life in different aspects. It is concluded that if we don’t plan the strategies to overcome these changes, in coming few years life on the earth will not be an easy task, and situation will be out of hand.

BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.

COVID-19 has been considered the most significant threat since World War II and the greatest global health disaster of the century. Wuhan City, Hubei Province, China, reported a new infection affecting residents in December 2019. The Coronavirus Disease 2019 (COVID-19) has been named by the World Health Organization (WHO). Across the globe, it is spreading rapidly, posing significant health, economic, and social challenges for everyone. The content of this paper is solely intended to provide a visual overview of COVID-19 global economic impact. The Coronavirus outbreak is causing a global economic collapse. Most countries have implemented full or partial lockdown measures to slow the spread of disease. The lockdown has slowed global economic activity substantially, many companies have reduced operations or closed down, and people are losing their jobs at an increasing rate. Service providers are also affected, in addition to manufacturers, agriculture, the food industry, a decline in education, the sports industry, and of entertainment sector also observed. The world trade situation is expected to deteriorate substantially this year.

The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast proliferation in many areas such as wearable devices, smart sensors and home appliances. IoT devices are characterized by their connectivity, pervasiveness and limited processing capability. The number of IoT devices in the world is increasing rapidly and it is expected that there will be 50 billion devices connected to the Internet by the end of the year 2020. This explosion of IoT devices, which can be easily increased compared to desktop computers, has led to a spike in IoT-based cyber-attack incidents. To alleviate this challenge, there is a requirement to develop new techniques for detecting attacks initiated from compromised IoT devices. Machine and deep learning techniques are in this context the most appropriate detective control approach against attacks generated from IoT devices. This study aims to present a comprehensive review of IoT systems-related technologies, protocols, architecture and threats emerging from compromised IoT devices along with providing an overview of intrusion detection models. This work also covers the analysis of various machine learning and deep learning-based techniques suitable to detect IoT systems related to cyber-attacks.

Smart cities have been developed over the past decade, and reducing traffic congestion has been the top concern in smart city development. Short delays in communication between vehicles and Roadside Units (RSUs), smooth traffic flow, and road safety are the key challenges of Intelligent Transportation Systems (ITSs). The rapid upsurge in the number of road vehicles has increased traffic congestion and the number of road accidents. To fix this issue, Vehicular Networks (VNs) have developed many new ideas, including vehicular communications, navigation, and traffic control. Machine Learning (ML) is an efficient approach to finding hidden insights into ITS without being programmed explicitly by learning from data. This research proposed a fusion-based intelligent traffic congestion control system for VNs (FITCCS-VN) using ML techniques that collect traffic data and route traffic on available routes to alleviate traffic congestion in smart cities. The proposed system provides innovative services to the drivers that enable a view of traffic flow and the volume of vehicles available on the road remotely, intending to avoid traffic jams. The proposed model improves traffic flow and decreases congestion. The proposed system provides an accuracy of 95% and a miss rate of 5%, which is better than previous approaches.

Multimedia content analysis is applied in different real‐world computer vision applications, and digital images constitute a major part of multimedia data. In last few years, the complexity of multimedia contents, especially the images, has grown exponentially, and on daily basis, more than millions of images are uploaded at different archives such as Twitter, Facebook, and Instagram. To search for a relevant image from an archive is a challenging research problem for computer vision research community. Most of the search engines retrieve images on the basis of traditional text‐based approaches that rely on captions and metadata. In the last two decades, extensive research is reported for content‐based image retrieval (CBIR), image classification, and analysis. In CBIR and image classification‐based models, high‐level image visuals are represented in the form of feature vectors that consists of numerical values. The research shows that there is a significant gap between image feature representation and human visual understanding. Due to this reason, the research presented in this area is focused to reduce the semantic gap between the image feature representation and human visual understanding. In this paper, we aim to present a comprehensive review of the recent development in the area of CBIR and image representation. We analyzed the main aspects of various image retrieval and image representation models from low‐level feature extraction to recent semantic deep‐learning approaches. The important concepts and major research studies based on CBIR and image representation are discussed in detail, and future research directions are concluded to inspire further research in this area.

Major depressive disorder (MDD) is a life-threatening illness characterized by mood changes and high rates of suicide. Although the role of neuroinflammation in MMD has been studied, the mechanistic interplay between antidepressants, neuroinflammation, and autophagy is yet to be investigated. The present study investigated the effect of melatonin on LPS-induced neuroinflammation, depression, and autophagy impairment. Our results showed that in mice, lipopolysaccharide (LPS) treatment induced depressive-like behaviors and caused autophagy impairment by dysregulating ATG genes. Moreover, LPS treatment significantly increased the levels of cytokines (TNFα, IL-1β, IL-6), enhanced NF-ᴋB phosphorylation, caused glial (astrocytes and microglia) cell activation, dysregulated FOXO3a expression, increased the levels of redox signaling molecules such as ROS/TBARs, and altered expression of Nrf2, SOD2, and HO-1. Melatonin treatment significantly abolished the effects of LPS, as demonstrated by improved depressive-like behaviors, normalized autophagy-related gene expression, and reduced levels of cytokines. Further, we investigated the role of autophagy in LPS-induced depressive-like behavior and neuroinflammation using autophagy inhibitors 3-MA and Ly294002. Interestingly, inhibitor treatment significantly abolished and reversed the anti-depressive, pro-autophagy, and anti-inflammatory effects of melatonin. The present study concludes that the anti-depressive effects of melatonin in LPS-induced depression might be mediated via autophagy modulation through FOXO3a signaling.

Electrospinning has been used for decades to generate nano-fibres via an electrically charged jet of polymer solution. This process is established on a spinning technique, using electrostatic forces to produce fine fibres from polymer solutions. Amongst, the electrospinning of available biopolymers (silk, cellulose, collagen, gelatine and hyaluronic acid), chitosan (CH) has shown a favourable outcome for tissue regeneration applications. The aim of the current review is to assess the current literature about electrospinning chitosan and its composite formulations for creating fibres in combination with other natural polymers to be employed in tissue engineering. In addition, various polymers blended with chitosan for electrospinning have been discussed in terms of their potential biomedical applications. The review shows that evidence exists in support of the favourable properties and biocompatibility of chitosan electrospun composite biomaterials for a range of applications. However, further research and in vivo studies are required to translate these materials from the laboratory to clinical applications.

At present, researchers in the field of biomaterials are focusing on the oral hard and soft tissue engineering with bioactive ingredients by activating body immune cells or different proteins of the body. By doing this natural ground substance, tissue component and long-lasting tissues grow. One of the current biomaterials is known as bioactive glass (BAG). The bioactive properties make BAG applicable to several clinical applications involving the regeneration of hard tissues in medicine and dentistry. In dentistry, its uses include dental restorative materials, mineralizing agents, as a coating material for dental implants, pulp capping, root canal treatment, and air-abrasion, and in medicine it has its applications from orthopedics to soft-tissue restoration. This review aims to provide an overview of promising and current uses of bioactive glasses in dentistry.

This study examines the impact of artificial intelligence (AI) on loss in decision-making, laziness, and privacy concerns among university students in Pakistan and China. Like other sectors, education also adopts AI technologies to address modern-day challenges. AI investment will grow to USD 253.82 million from 2021 to 2025. However, worryingly, researchers and institutions across the globe are praising the positive role of AI but ignoring its concerns. This study is based on qualitative methodology using PLS-Smart for the data analysis. Primary data was collected from 285 students from different universities in Pakistan and China. The purposive Sampling technique was used to draw the sample from the population. The data analysis findings show that AI significantly impacts the loss of human decision-making and makes humans lazy. It also impacts security and privacy. The findings show that 68.9% of laziness in humans, 68.6% in personal privacy and security issues, and 27.7% in the loss of decision-making are due to the impact of artificial intelligence in Pakistani and Chinese society. From this, it was observed that human laziness is the most affected area due to AI. However, this study argues that significant preventive measures are necessary before implementing AI technology in education. Accepting AI without addressing the major human concerns would be like summoning the devils. Concentrating on justified designing and deploying and using AI for education is recommended to address the issue.

In the recent era, the increasing persistence of hazardous contaminants is badly affecting the globe in many ways. Due to high environmental contamination, almost every second species on earth facing the worst issue in their survival. Advances in newer remediation approaches may help enhance bioremediation's quality, while conventional procedures have failed to remove hazardous compounds from the environment. Chemical and physical waste cleanup approaches have been used in current circumstances; however, these methods are costly and harmful to the environment. Thus, there has been a rise in the use of bioremediation due to an increase in environmental contamination, which led to the development of genetically engineered microbes (GEMs). It is safer and more cost-effective to use engineered microorganisms rather than alternative methods. GEMs are created by introducing a stronger protein into bacteria through biotechnology or genetic engineering to enhance the desired trait. Biodegradation of oil spills, halobenzoates naphthalenes, toluenes, trichloroethylene, octanes, xylenes etc. has been accomplished using GEMs such bacteria, fungus, and algae. Biotechnologically induced microorganisms are more powerful than naturally occurring ones and may degrade contaminants faster because they can quickly adapt to new pollutants they encounter or co-metabolize. Genetic engineering is a worthy process that will benefit the environment and ultimately the health of our people.

The objective of this study is to explore the role of artificial intelligence applications (AIA) in education. AI applications provide the solution in many ways to the exponential rise of modern-day challenges, which create difficulties in access to education and learning. They play a significant role in forming social robots (SR), smart learning (SL), and intelligent tutoring systems (ITS) to name a few. The review indicates that the education sector should also embrace the modern methods of teaching and the necessary technology. Looking into the flow, the education sector organizations need to adopt AI technologies as a necessity of the day and education. The study needs to be tested statistically for better understanding and to make the findings more generalized in the future.