Damietta University

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Importance Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). Conclusions and Relevance The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.

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.

Fe3O4 nanoparticles and non aqueous stable magnetic fluid (MF) containing Fe3O4 nanoparticles with mean diameters of 10 nm, which are in the range of super-paramagnetism, are prepared. Magnetite nanoparticles are synthesized via co-precipitation method from ferrous and ferric solutions. X-ray diffraction (XRD), transmission electron microscopy (TEM) and vibrating sample magnetometer (VSM) are used to study the physical properties of the (MF) and powder. The band gap parameters of the magneto-nanopowders such as the direct, indirect-band gap energies, Fermi energy and Urbach energy are determined.

Proline is an important component of salt-stress responses of plants. In this study the role of proline as part of salt-stress signalling in the desert plant Pancratium maritimum L. was examined. The data showed that salt-stress brought about a reduction of the growth and protein content, particularly at 300 mM NaCl, that was significantly increased by exogenous proline. In the leaves, salt-stress up-regulated ubiquitin, a small protein targeting damaged proteins for degradation via the proteasome, up to 5-fold as detected by western blotting. This change was also affected by proline even in non-stressed leaves. However, salt-stress resulted in a decrease in the amount of ubiquitin-conjugates, particularly in the roots, and this effect was reversed by exogenous proline. Severe salt-stress resulted in an inhibition of the antioxidative enzymes catalase and peroxidase as revealed by spectrophotometric assays and activity gels, but the activity of these enzymes was also maintained significantly higher in the presence of proline. Salt-stress also up-regulated several dehydrin proteins, analysed by western blotting, even in non-stressed plants. It is concluded that proline improves the salt-tolerance of Pancratium maritimum L. by protecting the protein turnover machinery against stress-damage and up-regulating stress protective proteins.

Salt tolerance is a complex trait involving the coordinated action of many gene families that perform a variety of functions such as control of water loss through stomata, ion sequestration, metabolic adjustment, osmotic adjustment and antioxidative defense. In spite of the large number of publications on the role of antioxidative defense under salt stress, the relative importance of this process to overall plant salt tolerance is still a matter of controversy. In this article, the generation and scavenging of reactive oxygen species (ROS) under normal and salt stress conditions in relation to the type of photosynthesis is discussed. The CO(2) concentrating mechanism in C4 and CAM plants is expected to contribute to decreasing ROS generation. However, the available data supports this hypothesis in CAM but not in C4 plants. We discuss the specific roles of enzymatic and non enzymatic antioxidants in relation to the oxidative load in the context of whole plant salt tolerance. The possible preventive antioxidative mechanisms are also discussed.

In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting trapped at the local optima). The main idea of the proposed model, called FPASSA-ANFIS, is to improve the performance of ANFIS by determining the parameters of ANFIS using FPASSA. The FPASSA-ANFIS model is evaluated using the World Health Organization (WHO) official data of the outbreak of the COVID-19 to forecast the confirmed cases of the upcoming ten days. More so, the FPASSA-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination ( R 2 ), and computing time. Furthermore, we tested the proposed model using two different datasets of weekly influenza confirmed cases in two countries, namely the USA and China. The outcomes also showed good performances.

COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. In this paper, a new ML-method proposed to classify the chest x-ray images into two classes, COVID-19 patient or non-COVID-19 person. The features extracted from the chest x-ray images using new Fractional Multichannel Exponent Moments (FrMEMs). A parallel multi-core computational framework utilized to accelerate the computational process. Then, a modified Manta-Ray Foraging Optimization based on differential evolution used to select the most significant features. The proposed method evaluated using two COVID-19 x-ray datasets. The proposed method achieved accuracy rates of 96.09% and 98.09% for the first and second datasets, respectively.

Importance: Understanding global variation in firearm mortality rates could guide prevention policies and interventions. Objective: To estimate mortality due to firearm injury deaths from 1990 to 2016 in 195 countries and territories. Design, Setting, and Participants: This study used deidentified aggregated data including 13 812 location-years of vital registration data to generate estimates of levels and rates of death by age-sex-year-location. The proportion of suicides in which a firearm was the lethal means was combined with an estimate of per capita gun ownership in a revised proxy measure used to evaluate the relationship between availability or access to firearms and firearm injury deaths. Exposures: Firearm ownership and access. Main Outcomes and Measures: Cause-specific deaths by age, sex, location, and year. Results: Worldwide, it was estimated that 251 000 (95% uncertainty interval [UI], 195 000-276 000) people died from firearm injuries in 2016, with 6 countries (Brazil, United States, Mexico, Colombia, Venezuela, and Guatemala) accounting for 50.5% (95% UI, 42.2%-54.8%) of those deaths. In 1990, there were an estimated 209 000 (95% UI, 172 000 to 235 000) deaths from firearm injuries. Globally, the majority of firearm injury deaths in 2016 were homicides (64.0% [95% UI, 54.2%-68.0%]; absolute value, 161 000 deaths [95% UI, 107 000-182 000]); additionally, 27% were firearm suicide deaths (67 500 [95% UI, 55 400-84 100]) and 9% were unintentional firearm deaths (23 000 [95% UI, 18 200-24 800]). From 1990 to 2016, there was no significant decrease in the estimated global age-standardized firearm homicide rate (-0.2% [95% UI, -0.8% to 0.2%]). Firearm suicide rates decreased globally at an annualized rate of 1.6% (95% UI, 1.1-2.0), but in 124 of 195 countries and territories included in this study, these levels were either constant or significant increases were estimated. There was an annualized decrease of 0.9% (95% UI, 0.5%-1.3%) in the global rate of age-standardized firearm deaths from 1990 to 2016. Aggregate firearm injury deaths in 2016 were highest among persons aged 20 to 24 years (for men, an estimated 34 700 deaths [95% UI, 24 900-39 700] and for women, an estimated 3580 deaths [95% UI, 2810-4210]). Estimates of the number of firearms by country were associated with higher rates of firearm suicide (P < .001; R2 = 0.21) and homicide (P < .001; R2 = 0.35). Conclusions and Relevance: This study estimated between 195 000 and 276 000 firearm injury deaths globally in 2016, the majority of which were firearm homicides. Despite an overall decrease in rates of firearm injury death since 1990, there was variation among countries and across demographic subgroups.

BACKGROUND: Chronic kidney disease (CKD) is common and ranks among the leading causes of mortality and morbidity. This analysis aimed to present global CKD estimates using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 to inform evidence-based policies for CKD identification and treatment. METHODS: This analysis focused on adults aged 20 years and older over the period 1990 to 2023, from 204 countries and territories. Data sources used were published literature, vital registration systems, kidney failure treatment registries, and household surveys. Estimates of CKD burden, including deaths, incidence, prevalence, and disability-adjusted life-years (DALYs), were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool. A comparative risk assessment approach estimated the proportion of cardiovascular deaths attributable to impaired kidney function and estimated risk factors for CKD. FINDINGS: Globally, in 2023, 788 million (95% uncertainty interval 743-843) people aged 20 years and older were estimated to have CKD, up from 378 million (354-407) in 1990. The global age-standardised prevalence of CKD in adults was 14·2% (13·4-15·2), a relative rise of 3·5% (2·7-4·1) from 1990. The region with the highest age-standardised prevalence was north Africa and the Middle East (18·0%; 16·9-19·4). Most people had stage 1-3 CKD, with a combined prevalence of 13·9% (13·1-15·0). In 2023, CKD was the ninth leading cause of death globally, accounting for 1·48 million (1·30-1·65) deaths, and the 12th leading cause of DALYs, with an age-standardised DALY rate of 769·2 (691·8-857·4) per 100 000. Impaired kidney function as a risk factor accounted for 11·5% (8·4-14·5) of cardiovascular deaths. High fasting plasma glucose, body-mass index, and systolic blood pressure were all leading risk factors for CKD DALYs. INTERPRETATION: CKD is a major global health issue, with rising prevalence and increasing importance as a cause of death and as a risk factor for cardiovascular death. A better understating of aetiology, appropriate screening, and implementation programmes are needed to translate advances in CKD treatment into improved patient outcomes. FUNDING: Gates Foundation, Wellcome, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.

Pristine films of polyvinyl alcohol (PVA)/polyvinyl pyrrolidone (PVP) polymer blend filled with gradient contents of (MWCNTs) multi-walled carbon nanotubes have been prepared using ordinary casting technique. Fourier transform infrared (FT-IR) revealed the existence of main characteristic peaks corresponding to vibrational groups that characterized the synthesized samples. The interaction between nano-composite components was indicated by variation of main vibrational bands in the spectral range 1500–1750 cm −1 . X-ray diffraction (XRD) confirms the structural modification in PVA/PVP matrix due to MWCNTs filling. Transmission electron microscopy (TEM (shows the presence of MWCNTs with a diameter between 80 and 30 nm and length of about several micrometers. Scanning electron microscopy (SEM) used to approve the homogenous nature of prepared samples. The absorption coefficient spectra show the appearance of two absorption peaks at 290 and 620 nm attributed to n → π* and π → π* electronic transitions. The optical energy gap ( E g ) have been obtained from the indirect allowed transition. It was found that, E g decrease with increasing MWCNTs content. Analysis of refractive index n showed a normal dispersion in the wavelength range 866–2500 nm, as well as an anomalous dispersion in the wavelength range 190–866 nm. The oscillator parameters (oscillator energy and dispersion energy) were calculated. The decrease in optical energy gap and the increase in refractive index due to filling with MWCNTs suppose the possibility of their use in optical devices.

White Blood Cell (WBC) Leukaemia is caused by excessive production of leukocytes in the bone marrow, and image-based detection of malignant WBCs is important for its detection. Convolutional Neural Networks (CNNs) present the current state-of-the-art for this type of image classification, but their computational cost for training and deployment can be high. We here present an improved hybrid approach for efficient classification of WBC Leukemia. We first extract features from WBC images using VGGNet, a powerful CNN architecture, pre-trained on ImageNet. The extracted features are then filtered using a statistically enhanced Salp Swarm Algorithm (SESSA). This bio-inspired optimization algorithm selects the most relevant features and removes highly correlated and noisy features. We applied the proposed approach to two public WBC Leukemia reference datasets and achieve both high accuracy and reduced computational complexity. The SESSA optimization selected only 1 K out of 25 K features extracted with VGGNet, while improving accuracy at the same time. The results are among the best achieved on these datasets and outperform several convolutional network models. We expect that the combination of CNN feature extraction and SESSA feature optimization could be useful for many other image classification tasks.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.

Currently, we witness the severe spread of the pandemic of the new Corona virus, COVID-19, which causes dangerous symptoms to humans and animals, its complications may lead to death. Although convolutional neural networks (CNNs) is considered the current state-of-the-art image classification technique, it needs massive computational cost for deployment and training. In this paper, we propose an improved hybrid classification approach for COVID-19 images by combining the strengths of CNNs (using a powerful architecture called Inception) to extract features and a swarm-based feature selection algorithm (Marine Predators Algorithm) to select the most relevant features. A combination of fractional-order and marine predators algorithm (FO-MPA) is considered an integration among a robust tool in mathematics named fractional-order calculus (FO). The proposed approach was evaluated on two public COVID-19 X-ray datasets which achieves both high performance and reduction of computational complexity. The two datasets consist of X-ray COVID-19 images by international Cardiothoracic radiologist, researchers and others published on Kaggle. The proposed approach selected successfully 130 and 86 out of 51 K features extracted by inception from dataset 1 and dataset 2, while improving classification accuracy at the same time. The results are the best achieved on these datasets when compared to a set of recent feature selection algorithms. By achieving 98.7%, 98.2% and 99.6%, 99% of classification accuracy and F-Score for dataset 1 and dataset 2, respectively, the proposed approach outperforms several CNNs and all recent works on COVID-19 images.

We present an investigation for the generation of a dust-acoustic rogue wave in a dusty plasma composed of negatively charged dust grains, as well as nonextensive electrons and ions. For this purpose, the reductive perturbation technique is used to obtain a nonlinear Schrödinger equation. The critical wave-number threshold k(c), which indicates where the modulational instability sets in, has been determined precisely for various regimes. Two different behaviors of k(c) against the nonextensive parameter q are found. For small k(c), it is found that increasing q would lead to an increase of k(c) until q approaches a certain value q(c), then further increase of q beyond q(c) decreases the value of k(c). For large k(c), the critical wave-number threshold k(c) is always increasing with q. Within the modulational instability region, a random perturbation of the amplitude grows and thus creates dust-acoustic rogue waves. In order to show that the characteristics of the rogue waves are influenced by the plasma parameters, the relevant numerical analysis of the appropriate nonlinear solution is presented. The nonlinear structure, as reported here, could be useful for controlling and maximizing highly energetic pulses in dusty plasmas.

The purpose of the research is to identify the determinants of students’ acceptance of online learning and to investigate how these determinants can shape students’ intention to use online learning. A conceptual framework based on the Technology Acceptance Model (TAM) was modified. A questionnaire was developed and used to solicit information from the 153 undergraduate students who used online learning in DBMU. The results reveal that students’ perception of ease of use, usefulness, attitudes towards online learning, and the social influence of students’ referent group were identified as significant determinants of students’ intention to practice online learning. The possibility of using the social influence of students’ referent group, students’ perceived ease of use, students’ perceived usefulness and their attitudes towards online learning to predict their behavioral intention to use online learning was also confirmed.

A new Schiff base ligand named (E)‐2‐(((3‐aminophenyl)imino)methyl)phenol (HL) was prepared through condensation reaction of m‐phenylenediamine and 2‐hydroxybenzaldehyde in 1:1 molar ratio. The new ligand was characterized by elemental analysis and spectral techniques. The coordination behavior of a series of transition metal ions named Cr (III), Mn (II), Fe (III), Co (II), Ni (II), Cu (II), Zn (II) and Cd (II) with the newly prepared Schiff base ligand (HL) is reported. The nature of bonding and the stereochemistry of the complexes have been deduced from elemental analyses, IR, UV–Vis, 1H NMR, mass, electronic spectra, magnetic susceptibility and conductivity measurements and further their thermal stability was confirmed by thermogravimetric analysis (TG). From IR spectra, it was observed that the ligand is a neutral tridentate ligand coordinates to the metal ions through protonated phenolic oxygen, azomethine nitrogen and nitrogen atom of NH2 group. The existence, the number and the position of the water molecules was studied by thermal analysis. The molecular structures of the Schiff base ligand (HL) and its metal complexes were optimized theoretically and the quantum chemical parameters were calculated. The synthesized ligand and its complexes were screened for antimicrobial activities against bacterial species (Staphylococcus aureus and Bacillis subtilis, (gram positive bacteria)), (Salmonella SP., Escherichia coli and Pseudomonas aeruginosa, (gram negative bacteria)) and fungi (Aspergillus fumigatus and Candida albicans). The complexes were found to possess high biological activities against different organisms. Molecular docking was used to predict the efficiency of binding between Schiff base ligand (HL) and both receptors of Escherichia coli (3 T88) and Staphylococcus aureus (3Q8U). The receptor of Escherichia coli (3 T88) showed best interaction with Schiff base ligand (HL) compared to receptor of Staphylococcus aureu (3Q8U).

Photorefractive screening-photovoltaic solitons are observed in lithium niobate. Two-dimensional bright circular solitons are formed thanks to a strong static bias field, externally applied, opposite to the photovoltaic internal field. The dynamics of the soliton formation is monitored and compared to a time-dependent numerical model allowing determination of the photovoltaic field. Efficient single mode waveguides are shown to be memorized by the soliton beam for a long time.

Abstract Metal organic framework (MOF) hybrid materials could be one of the answers in this investigation. We describe a simple and effective encapsulation of doxorubicin (DOX), an anticancer drug, inside Zr‐MOF, which have been little studied as drug delivery organizations. We investigated the measured release of the drug from Zr‐MOF in response to external incentives such as pH changes and interaction with biomimetic schemes. Zr‐MOF with encapsulated doxorubicin (DOX@Zr‐MOF) can be manufactured in one pot by addition the anticancer medication DOX to the reaction combination. They demonstrated pH‐responsive medication release and cancer cell killing capability. MOFs can be designed as multifunctional distribution vehicles for a diversity of loads, including medicinal and imaging agents, using our simple one‐pot approach. Fourier transform infrared (FTIR), X‐ray diffraction, scanning electron microscopy, and N2 sorption isotherm were used to analyze MOF and the developed drug delivery (DOX@Zr‐MOF) scheme. It investigated the effects of MOF and a bespoke drug delivery system on the feasibility of patient breast as well as liver tumor cell lines. At pH 5, the trapped drug can be released more quickly than at pH 7.4. Zr‐MOF nanoparticles had modest cytotoxicity; however, DOX@Zr‐MOF has higher cytotoxicity in MCF‐7 and HepG‐2 cells than DOX at concentrations greater than 31.25 μg ml−1. These results were discovered that DOX@Zr‐MOF could be a promising technique for delivering medicines to cancer cells. Furthermore, using the agar well dispersion technique, Zr‐MOF, DOX, and captured DOX@Zr‐MOF samples were assessed for their potential antibacterial activity against pathogenic bacteria in comparison to traditional antibiotics. In compared to the reference medication Gentamycin, the DOX@Zr‐MOF exhibits a large inhibitory zone against Gram negative organisms (Escherichia coli). The docking active place interactions were assessed to see if DOX might bind to the breast cancer 3hb5‐oxidoreductase receptor, prostate cancer protein 2q7k, and SARS‐CoV‐2 protease 6YB7 for anticancer and anticovid‐19 activities.

Metal–organic framework (MOF) nano particles are a class of promising porous nano materials for biomedical applications. Owing to its high loading potential and pH‐sensitive degradation, most promising of the MOFs is the zeolitic imidazolate crystal framework (ZIF‐8), a progressive useful material for small molecule distribution. Doxorubicin (DOX), designated as a classical drug, was jobwise entrapped in ZIF‐8 nano particles. ZIF‐8 nano particles, as a novel carrier, were used to monitor the release of the anticancer drug DOX and prevent it from dissipating before reaching its goal. ZIF‐8 nano particles with encapsulated DOX (DOX@ZIF‐8) can be synthesized in a single pot by incorporation of DOX into the reaction mixture. MOFs and the designed drug delivery (DOX@ZIF‐8) system were characterized by Fourier transfer infrared, scanning electron microscopy, N2sorption isotherm and X‐ray diffraction. The impact of MOFs and the engineered drug delivery system on the viability of human breast and liver cancer cell lines was evaluated. The loaded drug was released at pH 5 faster than at pH 7.4. The nano particles of ZIF‐8 showed low cytotoxicity, while DOX@ZIF‐8 showed high cytotoxicity to HepG‐2 and MCF‐7 cells compared with free DOX at the equivalent concentration of DOX of >12.5 μg/ml. These findings indicate that DOX@ZIF‐8 nano particles are a promising method for the delivery of cancer cells to drugs. Furthermore, ZIF‐8, DOX and encapsulated DOX@ZIF‐8 compounds were screened for their potential antibacterial activities against pathogenic bacteria compared with standard antibiotics by the agar well diffusion technique. The results demonstrate that the DOX@ZIF‐8 exhibits a strong inhibition zone against Gram‐negative strains (Escherichia coli) in comparison with the reference drug gentamycin. The docking active site interactions were evaluated to predict the binding between DOX with the receptor of breast cancer 3hb5‐oxidoreductase and liver cancer 2h80‐lipid binding protein for anticancer activity.