Majmaah University

Assessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. Fornell and Larcker criterion is the most widely used method for this purpose. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. Therefore, this article presents the results of discriminant validity assessment using these methods. Data from previous study was used that involved 429 respondents for empirical validation of value-based excellence model in higher education institutions (HEI) in Malaysia. From the analysis, the convergent, divergent and discriminant validity were established and admissible using Fornell and Larcker criterion. However, the discriminant validity is an issue when employing the HTMT criterion. This shows that the latent variables under study faced the issue of multicollinearity and should be looked into for further details. This also implied that the HTMT criterion is a stringent measure that could detect the possible indiscriminant among the latent variables. In conclusion, the instrument which consisted of six latent variables was still lacking in terms of discriminant validity and should be explored further.

Good sleep is necessary for good physical and mental health and a good quality of life. Insufficient sleep is a pervasive and prominent problem in the modern 24-h society. A considerable body of evidence suggests that insufficient sleep causes hosts of adverse medical and mental dysfunctions. An extensive literature search was done in all the major databases for "insufficient sleep" and "public health implications" in this review. Globally, insufficient sleep is prevalent across various age groups, considered to be a public health epidemic that is often unrecognized, under-reported, and that has rather high economic costs. This paper addresses a brief overview on insufficient sleep, causes, and consequences, and how it adds to the existing burden of diseases. Insufficient sleep leads to the derailment of body systems, leading to increased incidences of cardiovascular morbidity, increased chances of diabetes mellitus, obesity, derailment of cognitive functions, vehicular accidents, and increased accidents at workplaces. The increased usage of smart phones and electronic devices is worsening the epidemic. Adolescents with insufficient sleep are likely to be overweight and may suffer from depressive symptoms. The paper concludes by emphasizing sleep quality assessments as an important early risk indicator, thereby reducing the incidence of a wide spectrum of morbidities.

Dietary polyphenols including phenolic acids, flavonoids, catechins, tannins, lignans, stilbenes, and anthocyanidins are widely found in grains, cereals, pulses, vegetables, spices, fruits, chocolates, and beverages like fruit juices, tea, coffee and wine. In recent years, dietary polyphenols have gained significant interest among researchers due to their potential chemopreventive/protective functions in the maintenance of human health and diseases. It is believed that dietary polyphenols/flavonoids exert powerful antioxidant action for protection against reactive oxygen species (ROS)/cellular oxidative stress (OS) towards the prevention of OS-related pathological conditions or diseases. Pre-clinical and clinical evidence strongly suggest that long term consumption of diets rich in polyphenols offer protection against the development of various chronic diseases such as neurodegenerative diseases, cardiovascular diseases (CVDs), cancer, diabetes, inflammatory disorders and infectious illness. Increased intake of foods containing polyphenols (for example, quercetin, epigallocatechin-3-gallate, resveratrol, cyanidin etc.) has been claimed to reduce the extent of a majority of chronic oxidative cellular damage, DNA damage, tissue inflammations, viral/bacterial infections, and neurodegenerative diseases. It has been suggested that the antioxidant activity of dietary polyphenols plays a pivotal role in the prevention of OS-induced human diseases. In this narrative review, the biological/pharmacological significance of dietary polyphenols in the prevention of and/or protection against OS-induced major human diseases such as cancers, neurodegenerative diseases, CVDs, diabetes mellitus, cancer, inflammatory disorders and infectious diseases have been delineated. This review specifically focuses a current understanding on the dietary sources of polyphenols and their protective effects including mechanisms of action against various major human diseases.

Background The COVID-19 pandemic is found to affect the mental health of the population. Undergraduate medical students are especially prone to mental health disorders and hence could be more vulnerable to the impact of the pandemic. Methods A prospective longitudinal study was conducted on 217 undergraduate medical students in a medical college at Chennai, India. Depression, anxiety, and stress levels were recorded using Depression Anxiety Stress Scale 21 Items (DASS21) before and during the COVID-19 outbreak in India in December 2019 and June 2020, respectively. In the follow-up survey, in addition to DASS21, the Pittsburgh Sleep Quality Index to assess sleep quality and a self-administered questionnaire to assess the impact of COVID-19 related stressors were used. The self-administered questionnaire assessed the status of COVID-19 testing, interactions with COVID-19 patients, self-perceived levels of concerns and worries related to academics (COVID-19-AA (academic apprehensions)) and those pertaining to the self and family/friends (COVID-19-GA (general apprehensions)). Cross-sectional and longitudinal comparison of overall scores of depression, anxiety, and stress and scores stratified by gender, year of study, place of residence and monthly family income were performed. Predictors for depression, anxiety, and stress during COVID-19 were investigated using adjusted binary logistic regression analysis and results were expressed as adjusted odds ratio with 95% confidence interval (CI). A P value < 0.05 was considered statistically significant. Results The average scores of depression, anxiety, and stress during the baseline survey were 7.55 ± 7.86, 4.6 ± 6.19 and 7.31 ± 7.34 with the prevalence (95% Cl) of 33.2% [27–39.9%], 21.2% [16–27.2%] and 20.7% [15.5–26.7%]; in follow-up survey, the mean scores were 8.16 ± 8.9, 6.11 ± 7.13 and 9.31 ± 8.18 with the prevalence being 35.5% [29.1–42.2%], 33.2% [27–39.9%] and 24.9% [19.3–31.2%] for depression, anxiety, and stress respectively. There was a significant increase in both the prevalence and levels of anxiety and stress ( P < 0.001), with depression remaining unchanged during COVID-19, irrespective of gender, year of study, place of residence and family’s monthly income. Poor sleep quality, higher levels of baseline depression, anxiety, and stress, higher COVID-19-GA, COVID-19 patients in family/friends and direct interactions with COVID-19 patients were found to be significant predictors of negative mental health in undergraduate medical students. COVID-19-AA was not significantly associated with depression, anxiety, and stress. Conclusion The COVID-19 pandemic appears to negatively affect the mental health of the undergraduate medical students with the prevalence and levels of anxiety and stress being increased, and depression symptoms remaining unaltered. Addressing and mitigating the negative effect of COVID-19 on the mental health of this population is crucial.

Essential oils (EOs) are more complex and comprise a number of volatile and natural bioactive compounds, which often used in food industries as the best alternatives. This review focuses on the impact of EOs and the roles of their major components in food manufacturing as natural preservatives with the related mechanisms of action. In addition, the major bioactive molecules of different types of EOs and their pharmacological activities such as antioxidant, antifungal and antimicrobial effects on crop protection were also discussed. The major compounds of EOs represent potential antioxidant, antimicrobial and antifungal activities through various mechanisms. Different types of EOs such as tea tree oil, lemon oil, clove oil, cinnamon oil and thyme oil from various traditional plants, have significantly showed better antimicrobial and antioxidant activities, and also effectively increased the shelf lives of the cereal products and increased the quality of food safety. The major groups of EOs such as terpenes and aromatic volatile compounds, play a key role in food safety without affecting the quality. Due to their various activities including antioxidant and antimicrobial activities, EOs could be used as alternative preservatives to increase the shelf lives of cereals and crops.

The prevalence of fungal infections is growing at an alarming pace and the pathogenesis is still not clearly understood. Recurrence of these fungal diseases is often due to their evolutionary avoidance of antifungal resistance. The development of suitable novel antimicrobial agents for fungal diseases continues to be a major problem in the current clinical field. Hence, it is urgently necessary to develop surrogate agents that are more effective than conventional available drugs. Among the remarkable innovations from earlier investigations on natural-drugs, flavonoids are a group of plant-derived substances capable of promoting many valuable effects on humans. The identification of flavonoids with possible antifungal effects at small concentrations or in synergistic combinations could help to overcome this problem. A combination of flavonoids with available drugs is an excellent approach to reduce the side effects and toxicity. This review focuses on various naturally occurring flavonoids and their antifungal activities, modes of action, and synergetic use in combination with conventional drugs.

Nanoparticles are of great importance in development and research because of their application in industries and biomedicine. The development of nanoparticles requires proper knowledge of their fabrication, interaction, release, distribution, target, compatibility, and functions. This review presents a comprehensive update on nanoparticles' toxic effects, the factors underlying their toxicity, and the mechanisms by which toxicity is induced. Recent studies have found that nanoparticles may cause serious health effects when exposed to the body through ingestion, inhalation, and skin contact without caution. The extent to which toxicity is induced depends on some properties, including the nature and size of the nanoparticle, the surface area, shape, aspect ratio, surface coating, crystallinity, dissolution, and agglomeration. In all, the general mechanisms by which it causes toxicity lie on its capability to initiate the formation of reactive species, cytotoxicity, genotoxicity, and neurotoxicity, among others.

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.

One of the most promising techniques used in various sciences is deep neural networks (DNNs). A special type of DNN called a convolutional neural network (CNN) consists of several convolutional layers, each preceded by an activation function and a pooling layer. The feature map of the previous layer is sampled by the pooling layer (that seems to be an important layer) to create a new feature map with condensed resolution. This layer significantly reduces the spatial dimension of the input. It always accomplished two main goals. As a first step, it reduces the number of parameters or weights to minimize computational costs. The second step is to prevent the overfitting of the network. In addition, pooling techniques can significantly reduce model training time and computational costs. This paper provides a critical understanding of traditional and modern pooling techniques and highlights the strengths and weaknesses for readers. Moreover, the performance of pooling techniques on different datasets is qualitatively evaluated and reviewed. This study is expected to contribute to a comprehensive understanding of the importance of CNNs and pooling techniques in computer vision challenges.

Hydrogels are three-dimensional, cross-linked, and supramolecular networks that can absorb significant volumes of water. Hydrogels are one of the most promising biomaterials in the biological and biomedical fields, thanks to their hydrophilic properties, biocompatibility, and wide therapeutic potential. Owing to their nontoxic nature and safe use, they are widely accepted for various biomedical applications such as wound dressing, controlled drug delivery, bone regeneration, tissue engineering, biosensors, and artificial contact lenses. Herein, this review comprises different synthetic strategies for hydrogels and their chemical/physical characteristics, and various analytical, optical, and spectroscopic tools for their characterization are discussed. A range of synthetic approaches is also covered for the synthesis and design of hydrogels. It will also cover biomedical applications such as bone regeneration, tissue engineering, and drug delivery. This review addressed the fundamental, general, and applied features of hydrogels in order to facilitate undergraduates, graduates, biomedical students, and researchers in a variety of domains.

Potato disease management plays a valuable role in the agriculture field as it might cause a significant loss in crops production. Therefore, timely recognition and classification of potato leaves diseases are necessary to minimize the loss, however, it is time taking task and requires human efforts. Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., ‘The Plant Village Dataset’ and perform classification into only two classes in potato leaves. Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticillium_wilt (PVw) and Potato Healthy (PH) class. The propose model is trained on the existing dataset i.e., “The Plant Village” that comprises of images having two ailments such as Early Blight (EB) and Late Blight (LB), and a Healthy class for potato leaves. Additionally, we have gathered the data for classes i.e., Potato Leaf Roll (PLR), Potato Verticillium_wilt (PVw) and Potato Healthy (PH) manually. A pre-trained Efficient DenseNet model has been employed utilizing an extra transition layer in DenseNet-201 to classify the potato leave diseases efficiently. Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. The dense connections with regularization power help to minimize the overfitting during the training of small training sets of potato leaves samples. The proposed algorithm is a novel and first technique to address and report the successful implementation for the detection and classification of four diseases in potato leaves. The algorithm’s performance was evaluated on the testing set and gave an accuracy of 97.2%. Various experiments have been performed to confirm that our proposed algorithm is more consistent and proficient to detect and classify potato leaves diseases than existing models.

Flavonoids comprise a large group of structurally diverse polyphenolic compounds of plant origin and are abundantly found in human diet such as fruits, vegetables, grains, tea, dairy products, red wine, etc. Major classes of flavonoids include flavonols, flavones, flavanones, flavanols, anthocyanidins, isoflavones, and chalcones. Owing to their potential health benefits and medicinal significance, flavonoids are now considered as an indispensable component in a variety of medicinal, pharmaceutical, nutraceutical, and cosmetic preparations. Moreover, flavonoids play a significant role in preventing cardiovascular diseases (CVDs), which could be mainly due to their antioxidant, antiatherogenic, and antithrombotic effects. Epidemiological and in vitro/in vivo evidence of antioxidant effects supports the cardioprotective function of dietary flavonoids. Further, the inhibition of LDL oxidation and platelet aggregation following regular consumption of food containing flavonoids and moderate consumption of red wine might protect against atherosclerosis and thrombosis. One study suggests that daily intake of 100 mg of flavonoids through the diet may reduce the risk of developing morbidity and mortality due to coronary heart disease (CHD) by approximately 10%. This review summarizes dietary flavonoids with their sources and potential health implications in CVDs including various redox-active cardioprotective (molecular) mechanisms with antioxidant effects. Pharmacokinetic (oral bioavailability, drug metabolism), toxicological, and therapeutic aspects of dietary flavonoids are also addressed herein with future directions for the discovery and development of useful drug candidates/therapeutic molecules.

Bionanotechnology has pivotal role in the development of a novel therapy, applications of gold nanoparticles (AuNPs) in the treatment of cancer. In this study, we found that therapeutics, pharmaceutics and diagnostic effectiveness of photosynthesized Catharanthus roseus (CR) AuNPs induces mitochondrial-mediated apoptotic signalling pathways via reactive oxygen species (ROS) induced cytotoxicity in cervical cancer cell line (HeLa) by in vitro model. The present examinations were for the most part centred around the gold chloride and photosynthesis AuNPs from the fluid leaf concentrate of CR and their harmful impacts on HeLa cell lines. The synthesized AuNPs were characterized using numerous biophysical analyses such as UV-vis, DLS, EDX, HR-TEM, SAED, FTIR and AFM. The synthesized AuNPs in the particle size range of 25-35 nm was confirmed by HR-TEM. The element gold and the crystalline nature of AuNPs were finalized using EDX, respectively. Anticancer potential of CR-AuNPs was studied using HeLa cells and the cytotoxic mechanism has been evaluated using MTT, mitochondrial-mediated apoptotic pathway through AO/EtBr staining assay, pro-apoptotic (Bax), anti-apoptotic (Bcl-2 and Bid) protein expression western blotting analysis and caspases activity using ELISA analysis. In in vitro study, the IC50 of HeLa cells was found to be 5 µg/ml confirmed using MTT assay. The present data revealed that drug delivery vehicles developed on CR-AuNPs nanocomplexes might include extensive purpose in human cancer diagnosis and treatment.

Staphylococcus aureus (S. aureus) is a Gram-positive bacterium that may cause life-threatening diseases and some minor infections in living organisms. However, it shows notorious effects when it becomes resistant to antibiotics. Strain variants of bacteria, viruses, fungi, and parasites that have become resistant to existing multiple antimicrobials are termed as superbugs. Methicillin is a semisynthetic antibiotic drug that was used to inhibit staphylococci pathogens. The S. aureus resistant to methicillin is known as methicillin-resistant Staphylococcus aureus (MRSA), which became a superbug due to its defiant activity against the antibiotics and medications most commonly used to treat major and minor infections. Successful MRSA infection management involves rapid identification of the infected site, culture and susceptibility tests, evidence-based treatment, and appropriate preventive protocols. This review describes the clinical management of MRSA pathogenesis, recent developments in rapid diagnosis, and antimicrobial treatment choices for MRSA.

This article studies the unsteady MHD free flow of a Casson fluid past an oscillating vertical plate with constant wall temperature. The fluid is electrically conducting and passing through a porous medium. This phenomenon is modelled in the form of partial differential equations with initial and boundary conditions. Some suitable non-dimensional variables are introduced. The corresponding non-dimensional equations with conditions are solved using the Laplace transform technique. Exact solutions for velocity and energy are obtained. They are expressed in simple forms in terms of exponential and complementary error functions of Gauss. It is found that they satisfy governing equations and corresponding conditions, and are reduced to similar solutions for Newtonian fluids as a special case. Expressions for skin-friction and Nusselt number are also evaluated. Computations are carried out and the results are analysed for emerging flow parameters.

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.

Migraine is a neurological ailment that is characterized by severe throbbing unilateral headache and associated with nausea, photophobia, phonophobia and vomiting. A full and clear mechanism of the pathogenesis of migraine, though studied extensively, has not been established yet. The current available information indicates an intracranial network activation that culminates in the sensitization of the trigemino-vascular system, release of inflammatory markers, and initiation of meningeal-like inflammatory reaction that is sensed as headache. Genetic factors might play a significant role in deciding an individual's susceptibility to migraine. Twin studies have revealed that a single gene polymorphism can lead to migraine in individuals with a monogenic migraine disorder. In this review, we describe recent advancements in the genetics, pathophysiology, diagnosis, treatment, management, and prevention of migraine. We also discuss the potential roles of genetic and abnormal factors, including some of the metabolic triggering factors that result in migraine attacks. This review will help to accumulate current knowledge about migraine and understanding of its pathophysiology, and provides up-to-date prevention strategies.

OBJECTIVES: Autism spectrum disorder (ASD) is a developmental disorder characterized by pervasive deficits in social interaction, impairment in verbal and non-verbal communication, and stereotyped patterns of interests and activities. Vitamin-D deficiency was previously reported in autistic children. However, the data on the relationship between vitamin D deficiency and the severity of autism are limited. METHODS: We performed a case-controlled cross-sectional analysis conducted on 122 ASD children, to assess their vitamin D status compared to controls and the relationship between vitamin D deficiency and the severity of autism. We also conducted an open trial of vitamin D supplementation in ASD children. RESULTS: Fifty-seven percent of the patients in the present study had vitamin D deficiency, and 30% had vitamin D insufficiency. The mean 25-OHD levels in patients with severe autism were significantly lower than those in patients with mild/moderate autism. Serum 25-OHD levels had significant negative correlations with Childhood Autism Rating Scale (CARS) scores. Of the ASD group, 106 patients with low-serum 25-OHD levels (<30 ng/ml) participated in the open label trial. They received vitamin D3 (300 IU/kg/day not to exceed 5000 IU/day) for 3 months. Eighty-three subjects completed 3 months of daily vitamin D treatment. Collectively, 80.72% (67/83) of subjects who received vitamin D3 treatment had significantly improved outcome, which was mainly in the sections of the CARS and aberrant behavior checklist subscales that measure behavior, stereotypy, eye contact, and attention span. CONCLUSION: Vitamin D is inexpensive, readily available and safe. It may have beneficial effects in ASD subjects, especially when the final serum level is more than 40 ng/ml. TRIAL REGISTRATION NUMBER: UMIN-CTR Study Design: trial Number: R000016846.

In this work, we report the synthesis of porous activated carbon (AC). AC was derived from rotten carrot, at different values of activating temperature under inert atmosphere, employing chemical activation method and ZnCl2 as activation agent. On the basis of results observed by surface area and pore size analysis, effect of activation temperature on synthesized AC was determined. Other material properties such as morphology, thermal stability, vibrational response, and crystal structure of prepared AC were studied using standard techniques of material characterization. Further, the electrochemical performance of synthesized AC was studied as an electrode, in aqueous, organic and ionic liquid based electrolyte. It was found that the synthesized AC based electrode exhibits highest specific capacitance (135.5 F g−1 at 10 mHz) in aqueous electrolyte and highest specific energy (29.1 Wh kg−1 at 2.2 A g−1) and specific power (142.5 kW kg−1 at 2.2 A g−1) in ionic liquid based electrolyte. This shows the suitability of synthesized material for use in energy storage applications. Keywords: Waste, Biomass, Rotten carrot, Porous carbon, Electrolytes, Supercapacitor

Atangana and Baleanu (AB) in their recent work introduced a new version of fractional derivatives which uses the generalized Mittag-Leffler function as the non-singular and non-local kernel and accepts all properties of fractional derivatives. This articles aims to apply the AB fractional derivative to free convection flow of generalized Casson fluid due to the combined gradients of temperature and concentration with heat generation and first order chemical reaction. For the sake of comparison, this problem is also solved via Caputo-Fabrizio (CF) derivative technique. Exact solutions in both cases of AB and CF derivatives are obtained via Laplace transform and compared graphically as well as in tabular form. In the case of AB approach, the influence of pertinent parameters on velocity field is displayed in plots and discussed. It is found that for a unit time, the velocities obtained via AB and CF derivatives are identical. Velocities for the time less than 1 show little variation and for time bigger than 1, this variation increases.