University of Gujrat

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.

Development of reliable and eco-accommodating methods for the synthesis of nanoparticles is a vital step in the field of nanotechnology. Silver nanoparticles are important because of their exceptional chemical, physical, and biological properties, and hence applications. In the last decade, numerous efforts were made to develop green methods of synthesis to avoid the hazardous byproducts. This review describes the methods of green synthesis for Ag-NPs and their numerous applications. It also describes the comparison of efficient synthesis methods via green routes over physical and chemical methods, which provide strong evidence for the selection of suitable method for the synthesis of Ag-NPs.

Abstract We present the role of heat and electricity storage systems on the rapid rise of renewable energy resources and the steady fall of fossil fuels. The upsurge in renewable resources and slump in fossil fuel consumptions is attributed to sustainable energy systems, energy transition, climate change, and clean energy initiatives. The fast growth of renewables brings new design and operational challenges to transition towards 100% renewable energy goal. Energy storage systems can help ride‐through energy transition from hydrocarbon fuels to renewable sources. Nuclear fusion and artificial photosynthesis are the ultimate Holy Grails for permanent clean energy solutions. Plants harvest light and store it in chemical energy to regulate the food supply chain that may be a guideline for an energy transition from fossil fuels to renewables. Heat and electricity storage devices can account for the periodic nature of solar and wind energy sources. Solar thermal systems for water and space heating are also a viable solution for subzero temperature areas. This study presents the transition of world's energy prospect from fossil fuels to renewables and new advances in energy storage systems.

From the last several years, in serious consideration of the worldwide economic and environmental pollution issues there has been increasing research interest in the value of bio-sourced lignocellulosic biomass. Agro-industrial biomass comprised on lignocellulosic waste is an inexpensive, renewable, abundant and provides a unique natural resource for large-scale and cost-effective bio-energy collection. To expand the range of natural bio-resources the rapidly evolving tools of biotechnology can lower the conversion costs and also enhance target yield of the product of interest. In this background green biotechnology presents a promising approach to convert most of the solid agricultural wastes particularly lignocellulosic materials into liquid bio based energy-fuels. In fact, major advances have already been achieved to competitively position cellulosic ethanol with corn ethanol. The present summarized review work begins with an overview on the physico-chemical features and composition of agro-industrial biomass. The information is also given on the multi-step processing technologies of agro-industrial biomass to fuel ethanol followed by a brief summary of future considerations.

The research progress on the production of 2,5-furandicarboxylic acid by the oxidation of biomass-derived 5-hydroxymethyl furfural has been reviewed, focusing on the chemical-catalytic routes.

Cancer is a frightful disease and represents one of the biggest health-care issues for the human race and demands a proactive strategy for cure. Plants are reservoirs for novel chemical entities and provide a promising line for research on cancer. Hitherto, being effective, chemotherapy is accompanied by certain unbearable side effects. Nevertheless, plants and plant derived products is a revolutionizing field as these are Simple, safer, eco-friendly, low-cost, fast, and less toxic as compared with conventional treatment methods. Phytochemicals are selective in their functions and acts specifically on tumor cells without affecting normal cells. Carcinogenesis is complex phenomena that involves many signaling cascades. Phytochemicals are considered suitable candidates for anticancer drug development due to their pleiotropic actions on target events with multiple manners. The research is in progress for developing potential candidates (those can block or slow down the growth of cancer cells without any side effects) from these phytochemicals. Many phytochemicals and their derived analogs have been identified as potential candidates for anticancer therapy. Effort has been made through this comprehensive review to highlight the recent developments and milestones achieved in cancer therapies using phytomolecules with their mechanism of action on nuclear and cellular factors. Furthermore, drugs for cancer treatment and their limitations have also been discussed.

Abstract Due to urbanization and industrialization, there has been an increase in solid waste generation and has become a global concern and leakage of leachate from landfills contaminate the soil and groundwater and hence can have a severe impact on human health. The present study aimed to determine the composition of toxic metals (Cr, Mn, Cu, As) and heavy metals (Cd, Ba, Hg, Pb) in soil and water by an inductively coupled plasma optical emission spectrometer (ICP-OES). To ensure accuracy during the analysis of Cr, Mn, Cu, As, Cd, Ba, Hg, and Pb in real samples, certified reference material (CRM, SRM 2709a) of San Joaquin soil and water (SRM 1640a) were analyzed and results were presented in terms of % recovery studies. The mean concentration of all the metals in soil and water did not exceed the limit set by the European Community (EU), WHO, and US EPA except Cu where the permissible limit defined by the EU is 50–140 mg/kg in soil. The soil is uncontaminated to moderately contaminated with respect to all metals except the Cu and Pb. Among the average daily dose (ADD) of soil, ADD ing and ADD inh for children had the maximum dose for all metals than adults while ADD derm was higher in adults. Hazard quotient (HQ) trend in both adults and children was found in order HQ ing > HQ derm > HQ inh of soil for all metals except Ba which followed HQ ing > HQ inh > HQ derm . Hazard index (HI) values of soil for Cr and Pb in children were 7 and 7.5 times higher than adults respectively. Lifetime cancer risk (LCR) value for Cr by different exposure pathways of soil was 5.361 × 10 −4 for children which are at the lower borderline of risk for cancer.

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.

Lactic acid is one of the most important organic acid which is being extensively used around the globe in a range of industrial and biotechnological applications. From its very old history to date, many methods have been introduced to improve the optimization of lactic acid to get highest yields of the product of industrial interests. In serious consideration of the worldwide economic and lactic acid consumption issues there has been increasing research interest in the value of materials with natural origin, which are cheap, abundant and easily available all around the year. Recent trends showed that lactic acid production through fermentation is advantageous over chemical due to the environmental concerns of the modern world. The eco-friendly processing and fermentable capability of many of the agricultural and agro-industrial based raw materials or by-products respectively makes them attractive candidates in fermentation biotechnology to produce a value-added product with multiple applications. In fact, major advances have already been achieved in recent years in order to get pure lactic acid with optimal yield. The present review work is summarized on the multi-step processing technologies to produce lactic acid from different substances as a starting material potentially from various agro-industrial based biomasses. The information is also given on a purification through schematic representation of the product of quality interests.

The World Wide Web such as social networks, forums, review sites and blogs generate enormous heaps of data in the form of users views, emotions, opinions and arguments about different social events, products, brands, and politics. Sentiments of users that are expressed on the web has great influence on the readers, product vendors and politicians. The unstructured form of data from the social media is needed to be analyzed and well-structured and for this purpose, sentiment analysis has recognized significant attention. Sentiment analysis is referred as text organization that is used to classify the expressed mind-set or feelings in different manners such as negative, positive, favorable, unfavorable, thumbs up, thumbs down, etc. The challenge for sentiment analysis is lack of sufficient labeled data in the field of Natural Language Processing (NLP). And to solve this issue, the sentiment analysis and deep learning techniques have been merged because deep learning models are effective due to their automatic learning capability. This Review Paper highlights latest studies regarding the implementation of deep learning models such as deep neural networks, convolutional neural networks and many more for solving different problems of sentiment analysis such as sentiment classification, cross lingual problems, textual and visual analysis and product review analysis, etc.

To minimize the detrimental effects of contaminated water, technology-based smart treatment processes are prerequisite for sustainable supply of drinking water. Nano-sized metal oxides are the best choice futuristic adsorbents for the removal of water toxins as such materials are associated with the characteristics of simplicity, versatility, efficacy and high surface reactivity. In this study, we describe a nanostructured ZnO adsorbent, which displays remarkable efficiency toward the removal of widely used azo dyes, methyl orange (MO) and amaranth (AM), from aqueous systems. The ZnO nanoparticles (ZnO-NPs) were prepared by simple co-precipitation method, and the structural morphology of the as-prepared NPs was revealed by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform IR (FTIR) and Brunauer–Emmett–Teller (BET). After complementary characterization, as-prepared ZnO-NPs were further used as adsorbent for the removal of toxic azo dyes (MO and AM) from water. The results revealed that an amount of 0.3 g ZnO-NPs showed maximum removal efficiency of each dye (40 ppm) at pH 6. It was further confirmed that the adsorption of both dyes on ZnO-NPs strongly followed the Langmuir model whereas the kinetics studies revealed that each adsorption process was pseudo second order. Moreover, the findings suggested that R-SO3– groups were active sites and the electrostatic attraction between the dyes (MO–, AM–) and ZnO-NPs+ may be the prime adsorption mechanism of designated removal systems.

This study was conducted at Department of Zoology, University of Gujrat, Pakistan during 2016- 2017 as a term paper for Master of Philosophy. The data regarding water pollution and human health was obtained and compiled through a thorough review of various published research articles of international reputed journal and relevant books. Water covers about 70% Earth’s surface. Safe drinking water is a basic need for all humans. The WHO reports that 80% diseases are waterborne. Industrialization, discharge of domestic waste, radioactive waste, population growth, excessive use of pesticides, fertilizers and leakage from water tanks are major sources of water pollution. These wastes have negative effects on human health. Different chemicals have different affects depending on their locations and kinds. Bacterial, viral and parasitic diseases like typhoid, cholera, encephalitis, poliomyelitis, hepatitis, skin infection and gastrointestinal are spreading through polluted water. It is recommended to examine the water quality on regular basis to avoid its destructive effects on human health. Domestic and agriculture waste should not be disposed of without treating.

Throughout the world, the public is being informed about the physical effects of SARS-CoV-2 infection and steps to take to prevent exposure to the coronavirus and manage symptoms of COVID-19 if they appear. However, the effects of this pandemic on one's mental health have not been studied at length and are still not known. As all efforts are focused on understanding the epidemiology, clinical features, transmission patterns, and management of the COVID-19 outbreak, there has been very little concern expressed over the effects on one's mental health and on strategies to prevent stigmatization. People's behavior may greatly affect the pandemic's dynamic by altering the severity, transmission, disease flow, and repercussions. The present situation requires raising awareness in public, which can be helpful to deal with this calamity. This perspective article provides a detailed overview of the effects of the COVID-19 outbreak on the mental health of people.

Plants are as vulnerable by diseases as animals. Citrus is a major plant grown mainly in the tropical areas of the world due to its richness in vitamin C and other important nutrients. The production of the citrus fruit has been widely affected by citrus diseases which ultimately degrades the fruit quality and causes financial loss to the growers. During the past decade, image processing and computer vision methods have been broadly adopted for the detection and classification of plant diseases. Early detection of diseases in citrus plants helps in preventing them to spread in the orchards which minimize the financial loss to the farmers. In this article, an image dataset citrus fruits, leaves, and stem is presented. The dataset holds citrus fruits and leaves images of healthy and infected plants with diseases such as Black spot, Canker, Scab, Greening, and Melanose. Most of the images were captured in December from the Orchards in Sargodha region of Pakistan when the fruit was about to ripen and maximum diseases were found on citrus plants. The dataset is hosted by the Department of Computer Science, University of Gujrat and acquired under the mutual cooperation of the University of Gujrat and the Citrus Research Center, Government of Punjab, Pakistan. The dataset would potentially be helpful to researchers who use machine learning and computer vision algorithms to develop computer applications to help farmers in early detection of plant diseases. The dataset is freely available at https://data.mendeley.com/datasets/3f83gxmv57/2.

Titanium dioxide (TiO2) is one of the most widely used photocatalysts due to its physical and chemical properties. In this study, hydrogen energy production using TiO2- and titanate-based photocatalysts is discussed along with the pros and cons. The mechanism of the photocatalysis has been elaborated to pinpoint the photocatalyst for better performance. The chief characteristics and limitations of the TiO2 photocatalysts have been assessed. Further, TiO2-based photocatalysts modified with a transition metal, transition metal oxide, noble metal, graphitic carbon nitride, graphene, etc. have been reviewed. This study will provide a basic understanding to beginners and detailed knowledge to experts in the field to optimize the TiO2-based photocatalysts for hydrogen production.

Global climate change affects weather patterns, affecting soil salinity and drought tolerance. Crop resilience and agriculture sustainability can be enhanced by exploring soil salinity, plant drought tolerance, microbial diversity, and remediation techniques. This review examines the morpho-physiological, molecular, and genetic mechanisms underlying plant adaptation to soil salinity and drought stress. It highlights their impact on plant growth, productivity, and microbial diversity. Diverse methods are investigated to tackle soil salinity and drought stress, encompassing chemical, physical, and biological approaches. Additionally, water-efficient agricultural practices and drought-resistant crop varieties are presented as ways to increase plant tolerance to these stresses. These implications for sustainable agriculture emphasize the potential of these findings to optimize resource utilization, increase crop yield, and promote environmental sustainability. These implications for sustainable agriculture emphasize the potential of these findings to optimize resource utilization, increase crop yield, and promote environmental sustainability. The review concludes by discussing future research directions, particularly the need for more study into the molecular basis of plant-microbe interactions and stress tolerance mechanisms. By advancing our knowledge in this field, we can develop innovative solutions to mitigate soil salinity and drought stress, ensuring food security and sustainable agriculture in changing climates.

BACKGROUND: Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. METHODS: GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. FINDINGS: The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. INTERPRETATION: We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. FUNDING: Gates Foundation.

Cadmium (Cd) level is continuously increasing in agricultural soils mainly through anthropogenic activities. Cadmium is one of the most phytotoxic metals in soils. The present study investigates the possible role of exogenously applied glycinebetaine (GB) in alleviating Cd toxicity in cotton (Gossypium hirsutum L.) plants in a hydroponic system. Three concentrations of Cd (0, 1.0, and 5.0 μM) were tested with and without foliar application of GB (1.0 mM). Cadmium toxicity caused a significant decrease in plant height, root length, number of leaves per plant, fresh and dry weights of leaf, stem and root and intensively increased Cd concentration in different plant parts. Cadmium toxicity also decreased photosynthetic pigments and gas exchange characteristics in leaves. Superoxide dismutase (SOD), guaiacol peroxidase (POD), catalases (CAT) and ascorbate (APX) activities increased under lower Cd stress (1.0 μM) while decreased under higher Cd stress (5.0 μM). Cadmium toxicity increased the concentration of reactive oxygen species (ROS) as indicated by the increased production of malondialdehyde (MDA), hydgrogen peroxide (H2O2) and electrolyte leakage in both leaves and roots. Application of GB decreased Cd concentration in different plant parts, alleviated Cd-induced inhibition in plant growth and biomass and led to a significant increase in photosynthetic pigments, protein contents and antioxidant enzymes. Glycinebetaine application alleviated the oxidative damage as evidenced by the decreased production of electrolyte leakage, H2O2 and MDA contents. These results revealed that GB might alleviate Cd toxicity in cotton plants through lowering Cd concentrations and regulating Cd induced oxidative stress in different plant parts possibly by increasing the performance of the antioxidant enzymatic system.

With the removal of the barriers of time and distance, E-learning platforms have attracted millions of learners, but these platforms are experiencing a significant drop-out ratio. One of the primary reasons for this problem is the lack of motivation among the learners because of the similar learning experience provided to them despite their varying learning styles. Different researchers have introduced gamification as a solution for students’ engagement. The technique has improved engagement levels a bit, but it is not as useful as it was expected to be. One of the primary problems with gamification elements is their inability to induce intrinsic motivation among learners. To target this issue, we have proposed a framework that identifies the learning style of students based on their interactions with the system and provides an adaptive gamification experience according to their identified learning dimensions. The results of the experiments show that the motivation of learners increases by 25%, and the drop-out ratio is reduced by 26%.

This study analyzes the dynamic linkages between financial inclusion, energy consumption, and carbon emissions taking corruption, infrastructure, and economic growth as control variables. The data of 23 OECD countries covering the period from 2004 to 2017 have been used. The study develops two indexes with the help of Principal Component Analysis; one for financial inclusion and the other for infrastructure. The study also adopts second generation tests for unit root and cross-sectional dependence. To check long-run linkages, this study uses (Dynamic) Common Correlated Effects Estimator technique, also called CS-ARDL, which provides more reliable results. The results indicate positive connections between financial inclusion, energy consumption and carbon emissions. Corruption, infrastructure and economic growth are highly sensitive to carbon emissions. The study provides important points for pollution control and attaining the targets of sustainable development. Efforts are needed on government level to align the financial inclusion targets with energy usage behavior and environmental policies.