Islamic Azad University, Science and Research Branch

Liposomes, sphere-shaped vesicles consisting of one or more phospholipid bilayers, were first described in the mid-60s. Today, they are a very useful reproduction, reagent, and tool in various scientific disciplines, including mathematics and theoretical physics, biophysics, chemistry, colloid science, biochemistry, and biology. Since then, liposomes have made their way to the market. Among several talented new drug delivery systems, liposomes characterize an advanced technology to deliver active molecules to the site of action, and at present, several formulations are in clinical use. Research on liposome technology has progressed from conventional vesicles to 'second-generation liposomes', in which long-circulating liposomes are obtained by modulating the lipid composition, size, and charge of the vesicle. Liposomes with modified surfaces have also been developed using several molecules, such as glycolipids or sialic acid. This paper summarizes exclusively scalable techniques and focuses on strengths, respectively, limitations in respect to industrial applicability and regulatory requirements concerning liposomal drug formulations based on FDA and EMEA documents.

<h3>Importance</h3> 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. <h3>Objective</h3> To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. <h3>Evidence Review</h3> 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. <h3>Findings</h3> 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). <h3>Conclusions and Relevance</h3> 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.

Abstract Background Osteoporosis affects all sections of society, including families with people affected by osteoporosis, government agencies and medical institutes in various fields. For example, it involves the patient and his/her family members, and government agencies in terms of the cost of treatment and medical care. Providing a comprehensive picture of the prevalence of osteoporosis globally is important for health policymakers to make appropriate decisions. Therefore, this study was conducted to investigate the prevalence of osteoporosis worldwide. Methods A systematic review and meta-analysis were conducted in accordance with the PRISMA criteria. The PubMed, Science Direct, Web of Science, Scopus, Magiran, and Google Scholar databases were searched with no lower time limit up till 26 August 2020. The heterogeneity of the studies was measured using the I 2 test, and the publication bias was assessed by the Begg and Mazumdar’s test at the significance level of 0.1. Results After following the systematic review processes, 86 studies were selected for meta-analysis. The sample size of the study was 103,334,579 people in the age range of 15–105 years. Using meta-analysis, the prevalence of osteoporosis in the world was reported to be 18.3 (95% CI 16.2–20.7). Based on 70 studies and sample size of 800,457 women, and heterogenicity I 2 : 99.8, the prevalence of osteoporosis in women of the world was reported to be 23.1 (95% CI 19.8–26.9), while the prevalence of osteoporosis among men of the world was found to be 11.7 (95% CI 9.6–14.1 which was based on 40 studies and sample size of 453,964 men.). The highest prevalence of osteoporosis was reported in Africa with 39.5% (95% CI 22.3–59.7) and a sample size of 2989 people with the age range 18–95 years. Conclusion According to the medical, economic, and social burden of osteoporosis, providing a robust and comprehensive estimate of the prevalence of osteoporosis in the world can facilitate decisions in health system planning and policymaking, including an overview of the current and outlook for the future; provide the necessary facilities for the treatment of people with osteoporosis; reduce the severe risks that lead to death by preventing fractures; and, finally, monitor the overall state of osteoporosis in the world. This study is the first to report a structured review and meta-analysis of the prevalence of osteoporosis worldwide.

In this study, several simple equations are suggested to investigate the effects of size and density on the number, surface area, stiffening efficiency, and specific surface area of nanoparticles in polymer nanocomposites. In addition, the roles of nanoparticle size and interphase thickness in the interfacial/interphase properties and tensile strength of nanocomposites are explained by various equations. The aggregates/agglomerates of nanoparticles are also assumed as large particles in nanocomposites, and their influences on the nanoparticle characteristics, interface/interphase properties, and tensile strength are discussed. The small size advantageously affects the number, surface area, stiffening efficiency, and specific surface area of nanoparticles. Only 2 g of isolated and well-dispersed nanoparticles with radius of 10 nm (R = 10 nm) and density of 2 g/cm3 produce the significant interfacial area of 250 m2 with polymer matrix. Moreover, only a thick interphase cannot produce high interfacial/interphase parameters and significant mechanical properties in nanocomposites because the filler size and aggregates/agglomerates also control these terms. It is found that a thick interphase (t = 25 nm) surrounding the big nanoparticles (R = 50 nm) only improves the B interphase parameter to about 4, while B = 13 is obtained by the smallest nanoparticles and the thickest interphase.

Nanomaterials have been extensively studied for heavy metal ions and dye removals from wastewater. This article reviews the role of nanomaterials as effective adsorbents for wastewater purification. In recent years, numerous novel nanomaterial adsorbents have been developed for enhancing the efficiency and adsorption capacities of removing contaminants from wastewater. The innovation, forthcoming development, and challenges of cost-effective and environmentally acceptable nanomaterials for water purification are discussed and reviewed in this article. This review concludes that nanomaterials have many unique morphological and structural properties that qualify them to be used as effective adsorbents to solve several environmental problems.

BACKGROUND: Patient participation means involvement of the patient in decision making or expressing opinions about different treatment methods, which includes sharing information, feelings and signs and accepting health team instructions. OBJECTIVES: Given the importance of patient participation in healthcare decision making which empowers patients and improves services and health outcomes, this study was performed to review previous studies on patient participation in healthcare decision making. MATERIALS AND METHODS: To prepare this narrative review article, researchers used general and specific search engines, as well as textbooks addressing this subject for an in-depth study of patient involvement in healthcare decision-making. As a result, 35 (out of 100 relevant) articles and also two books were selected for writing this review article. RESULTS: BASED ON THE REVIEW OF ARTICLES AND BOOKS, TOPICS WERE DIVIDED INTO SIX GENERAL CATEGORIES: definition of participation, importance of patient participation, factors influencing participation of patients in healthcare decisions, method of patient participation, tools for evaluating participation, and benefits and consequences of patient participation in health care decision-making. CONCLUSIONS: IN MOST STUDIES, FACTORS INFLUENCING PATIENT PARTICIPATION CONSISTED OF: factors associated with health care professionals such as doctor-patient relationship, recognition of patient's knowledge, allocation of sufficient time for participation, and also factors related to patients such as having knowledge, physical and cognitive ability, and emotional connections, beliefs, values and their experiences in relation to health services.

Cancer is one of the leading causes of death worldwide, and the factors responsible for its progression need to be elucidated. Exosomes are structures with an average size of 100 nm that can transport proteins, lipids, and nucleic acids. This review focuses on the role of exosomes in cancer progression and therapy. We discuss how exosomes are able to modulate components of the tumor microenvironment and influence proliferation and migration rates of cancer cells. We also highlight that, depending on their cargo, exosomes can suppress or promote tumor cell progression and can enhance or reduce cancer cell response to radio- and chemo-therapies. In addition, we describe how exosomes can trigger chronic inflammation and lead to immune evasion and tumor progression by focusing on their ability to transfer non-coding RNAs between cells and modulate other molecular signaling pathways such as PTEN and PI3K/Akt in cancer. Subsequently, we discuss the use of exosomes as carriers of anti-tumor agents and genetic tools to control cancer progression. We then discuss the role of tumor-derived exosomes in carcinogenesis. Finally, we devote a section to the study of exosomes as diagnostic and prognostic tools in clinical courses that is important for the treatment of cancer patients. This review provides a comprehensive understanding of the role of exosomes in cancer therapy, focusing on their therapeutic value in cancer progression and remodeling of the tumor microenvironment.

A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its branches is deep learning (DL). Before the rise of DL, conventional machine learning algorithms involving feature extraction were performed. This limited their performance to the ability of those handcrafting the features. However, in DL, the extraction of features and classification are entirely automated. The advent of these techniques in many areas of medicine, such as in the diagnosis of epileptic seizures, has made significant advances. In this study, a comprehensive overview of works focused on automated epileptic seizure detection using DL techniques and neuroimaging modalities is presented. Various methods proposed to diagnose epileptic seizures automatically using EEG and MRI modalities are described. In addition, rehabilitation systems developed for epileptic seizures using DL have been analyzed, and a summary is provided. The rehabilitation tools include cloud computing techniques and hardware required for implementation of DL algorithms. The important challenges in accurate detection of automated epileptic seizures using DL with EEG and MRI modalities are discussed. The advantages and limitations in employing DL-based techniques for epileptic seizures diagnosis are presented. Finally, the most promising DL models proposed and possible future works on automated epileptic seizure detection are delineated.

Diabetes mellitus (DM) is considered as a main challenge in both developing and developed countries, as lifestyle has changed and its management seems to be vital. Type I and type II diabetes are the main kinds and they result in hyperglycemia in patients and related complications. The gene expression alteration can lead to development of DM and related complications. The AMP-activated protein kinase (AMPK) is an energy sensor with aberrant expression in various diseases including cancer, cardiovascular diseases and DM. The present review focuses on understanding AMPK role in DM. Inducing AMPK signaling promotes glucose in DM that is of importance for ameliorating hyperglycemia. Further investigation reveals the role of AMPK signaling in enhancing insulin sensitivity for treatment of diabetic patients. Furthermore, AMPK upregulation inhibits stress and cell death in β cells that is of importance for preventing type I diabetes development. The clinical studies on diabetic patients have shown the role of AMPK signaling in improving diabetic complications such as brain disorders. Furthermore, AMPK can improve neuropathy, nephropathy, liver diseases and reproductive alterations occurring during DM. For exerting such protective impacts, AMPK signaling interacts with other molecular pathways such as PGC-1α, PI3K/Akt, NOX4 and NF-κB among others. Therefore, providing therapeutics based on AMPK targeting can be beneficial for amelioration of DM.

The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM) constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42) and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF) against the Iran Meteorological Organization (IMO) daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (&gt;15 mm/day), IMERG is superior to the other products in all study areas and could be used in future for meteorological and hydrological models, etc.

Abstract Data mining techniques have been concentrated for malware detection in the recent decade. The battle between security analyzers and malware scholars is everlasting as innovation grows. The proposed methodologies are not adequate while evolutionary and complex nature of malware is changing quickly and therefore turn out to be harder to recognize. This paper presents a systematic and detailed survey of the malware detection mechanisms using data mining techniques. In addition, it classifies the malware detection approaches in two main categories including signature-based methods and behavior-based detection. The main contributions of this paper are: (1) providing a summary of the current challenges related to the malware detection approaches in data mining, (2) presenting a systematic and categorized overview of the current approaches to machine learning mechanisms, (3) exploring the structure of the significant methods in the malware detection approach and (4) discussing the important factors of classification malware approaches in the data mining. The detection approaches have been compared with each other according to their importance factors. The advantages and disadvantages of them were discussed in terms of data mining models, their evaluation method and their proficiency. This survey helps researchers to have a general comprehension of the malware detection field and for specialists to do consequent examinations.

Removal of noxious materials such as heavy metal ions (which are hazardous above certain ppm concentration) from wastewater is one of the biggest environmental challenges that suffers the economy nowadays. On the basis of their versatility, environmental friendliness, the adsorption was proved to be a most economical and efficient technology, which is used extensively for their removal from the aqueous media. Among the various developed adsorbents used so far, carbon nanotubes (CNTs) show a unique impact on the fast adsorption and rapid removal of noxious impurities from the aqueous source. CNTs festooned on the sources like activated carbon, nanoparticles, and nanocomposities enhanced the efficiency and potential of the adsorbent. Due to their unique structural, electronic, optoelectronic, semiconductor, as well as mechanical, chemical, and physical properties, they have been extensively used to remove heavy metals in wastewater treatment. The adsorption mechanisms are majorly contributed by the chemical interactions between the metal ions and the functional groups present on the surface of the CNTs. Greater the surface area more will be the number of reducing groups hence more attributable to better CNT sorption performances.

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.

Increased variety of products and the instability of the global economy in twenty first century caused increasingcomplexity of financial decisions and also caused consumers faced with the challenge in economic and financialactivities. For this reason, in the last decade, the importance of financial management skills in personal and worklife has increased and researches in this area has been done. In this regard, this study tries to evaluate the relationbetween financial literacy, financial wellbeing and financial concerns. For this purpose, a questionnaire wasdesigned and distributed using random sampling among people. Data was analyzed using correlation test,Independent two-sample test based on the T distribution and regression. The results showed that age andeducation are positively correlated with financial literacy and financial wellbeing. Married people and men aremore financially literate. Higher financial literacy leads to greater financial well-being and less financialconcerns. Finally, financial wellbeing leads to less financial concern.

BACKGROUND: To better understand the potential ecotoxicological impacts of silver nanoparticles released into freshwater environments, the Daphnia magna 48-hour immobilization test was used. METHODS: The toxicities of silver nitrate, two types of colloidal silver nanoparticles, and a suspension of silver nanoparticles were assessed and compared using standard OECD guidelines. Also, the swimming behavior and visible uptake of the nanoparticles by Daphnia were investigated and compared. The particle suspension and colloids used in the toxicity tests were well-characterized. RESULTS: The results obtained from the exposure studies showed that the toxicity of all the silver species tested was dose and composition dependent. Plus, the silver nanoparticle powders subsequently suspended in the exposure water were much less toxic than the previously prepared silver nanoparticle colloids, whereas the colloidal silver nanoparticles and AgNO(3) were almost similar in terms of mortality. The silver nanoparticles were ingested by the Daphnia and accumulated under the carapace, on the external body surface, and connected to the appendages. All the silver species in this study caused abnormal swimming by the D. magna. CONCLUSION: According to the present results, silver nanoparticles should be classified according to GHS (Globally Harmonized System of classification and labeling of chemicals) as "category acute 1" to Daphnia neonates, suggesting that the release of nanosilver into the environment should be carefully considered.

Synthesis of chitosan–ZnO nanoparticles (CS–ZnONPs) composite beads was performed by a polymer-based method. The resulting bionanocomposite was characterized by scanning electron microscopy (SEM), X-ray powder diffraction (XRD) spectroscopy and infrared spectroscopy (FT-IR). Adsorption applications for removal of pesticide pollutants were conducted. The optimum conditions, including adsorbent dose, agitating time, initial concentration of pesticide and pH on the adsorption of pesticide by chitosan loaded with zinc oxide nanoparticles beads were investigated. Results showed that 0.5 g of the bionanocomposite, in room temperature and pH 7, could remove 99% of the pesticide from permethrin solution (25 ml, 0.1 mg L−1), using UV spectrophotometer at 272 nm. Then, the application of the adsorbent for pesticide removal was studied in the on-line column. The column was regenerated with NaOH solution (0.1 M) completely, and then reused for adsorption application. The CS–ZnONPs composite beads appear to be the new promising material in water treatment application with 56% regeneration after 3 cycles.

In the light of promising potency of selenium nanoparticles in biomedical applications, this is the first study to report the synergistic antibacterial activity of these nanoparticles and lysozyme. The nanohybrid system was prepared with various concentrations of each component. Resistance of Escherichia coli and Staphylococcus aureus was compared in the presence of individual Nano and Bio counterparts as well as the nanohybrid system. Upon interaction of SeNPs with Lysozyme, the nanohybrid system efficiently enhanced the antibacterial activity compared to the protein. Therefore, SeNPs play an important role in inhibition of bacterial growth at very low concentrations of protein; whereas very high amount of the protein is required to inhibit bacterial growth individually. On the other hand, lysozyme has also played a vital role in antibacterial property of SeNPs, inducing 100% inhibition at very low concentration of each component. Hence, presence of both nano and bio counterparts induced vital interplay in the Nanohybrid system. The aged samples also presented good stability of SeNPs both as the intact and complex form. Results of this effort highlight design of nanohybrid systems with synergistic antibacterial properties to overcome the emerging antibiotic resistance as well as to define fruitful applications in biomedicine and food safety.

This article proposes a hybrid intelligent-classic control approach for reconstruction and compensation of cyber attacks launched on inputs of nonlinear cyber-physical systems (CPS) and industrial Internet of Things systems, which work through shared communication networks. In this article, a class of n-order nonlinear systems is considered as a model of CPS while it is in presence of cyber attacks only in the forward channel. An intelligent-classic control system is developed to compensate cyber-attacks. Neural network (NN) is designed as an intelligent estimator for attack estimation and a classic nonlinear control system based on the variable structure control method is designed to compensate the effect of attacks and control the system performance in tracking applications. In the proposed strategy, nonlinear control theory is applied to guarantee the stability of the system when attacks happen. In this strategy, a Gaussian radial basis function NN is used for online estimation and reconstruction of cyber-attacks launched on the networked system. An adaptation law of the intelligent estimator is derived from a Lyapunov function. Simulation results demonstrate the validity and feasibility of the proposed strategy in car cruise control application as the testbed.

In this review paper, a comprehensive study on the concept, theory, and applications of composite right/left-handed transmission lines (CRLH-TLs) by considering their use in antenna system designs have been provided. It is shown that CRLH-TLs with negative permittivity (ε <; 0) and negative permeability (μ <; 0) have unique properties that do not occur naturally. Therefore, they are referred to as artificial structures called “metamaterials”. These artificial structures include series left-handed (LH) capacitances (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub> ), shunt LH inductances (L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub> ), series right-handed (RH) inductances (LR), and shunt RH capacitances (CR) that are realized by slots or interdigital capacitors, stubs or via-holes, unwanted current flowing on the surface, and gap distance between the surface and ground-plane, respectively. In the most cases, it is also shown that structures based on CRLH metamaterial-TLs are superior than their conventional alternatives, since they have smaller dimensions, lower-profile, wider bandwidth, better radiation patterns, higher gain and efficiency, which make them easier and more cost-effective to manufacture and mass produce. Hence, a broad range of metamaterial-based design possibilities are introduced to highlight the improvement of the performance parameters that are rare and not often discussed in available literature. Therefore, this survey provides a wide overview of key early-stage concepts of metematerial-based designs as a thorough reference for specialist antennas and microwave circuits designers. To analyze the critical features of metamaterial theory and concept, several examples are used. Comparisons on the basis of physical size, bandwidth, materials, gain, efficiency, and radiation patterns are made for all the examples that are based on CRLH metamaterialTLs. As revealed in all the metematerial design examples, foot-print area decrement is an important issue of study that have a strong impact for the enlargement of the next generation wireless communication systems.

BACKGROUND: "Candidatus Phytoplasma aurantifolia", is the causative agent of witches' broom disease in Mexican lime trees (Citrus aurantifolia L.), and is responsible for major losses of Mexican lime trees in Southern Iran and Oman. The pathogen is strictly biotrophic, and thus is completely dependent on living host cells for its survival. The molecular basis of compatibility and disease development in this system is poorly understood. Therefore, we have applied a cDNA- amplified fragment length polymorphism (AFLP) approach to analyze gene expression in Mexican lime trees infected by "Ca. Phytoplasma aurantifolia". RESULTS: We carried out cDNA-AFLP analysis on grafted infected Mexican lime trees of the susceptible cultivar at the representative symptoms stage. Selective amplifications with 43 primer combinations allowed the visualisation of 55 transcript-derived fragments that were expressed differentially between infected and non-infected leaves. We sequenced 51 fragments, 36 of which were identified as lime tree transcripts after homology searching. Of the 36 genes, 70.5% were down-regulated during infection and could be classified into various functional groups. We showed that Mexican lime tree genes that were homologous to known resistance genes tended to be repressed in response to infection. These included the genes for modifier of snc1 and autophagy protein 5. Furthermore, down-regulation of genes involved in metabolism, transcription, transport and cytoskeleton was observed, which included the genes for formin, importin β 3, transducin, L-asparaginase, glycerophosphoryl diester phosphodiesterase, and RNA polymerase β. In contrast, genes that encoded a proline-rich protein, ubiquitin-protein ligase, phosphatidyl glycerol specific phospholipase C-like, and serine/threonine-protein kinase were up-regulated during the infection. CONCLUSION: The present study identifies a number of candidate genes that might be involved in the interaction of Mexican lime trees with "Candidatus Phytoplasma aurantifolia". These results should help to elucidate the molecular basis of the infection process and to identify genes that could be targeted to increase plant resistance and inhibit the growth and reproduction of the pathogen.