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Abstract Nucleotide-binding leucine-rich repeat (NLR) disease resistance genes typically confer resistance against races of a single pathogen. Here, we report that Yr87/Lr85, an NLR gene from Aegilops sharonensis and Aegilops longissima, confers resistance against both P. striiformis tritici (Pst) and Puccinia triticina (Pt) that cause stripe and leaf rust, respectively. Yr87/Lr85 confers resistance against Pst and Pt in wheat introgression as well as transgenic lines. Comparative analysis of Yr87/Lr85 and the cloned Triticeae NLR disease resistance genes shows that Yr87/Lr85 contains two distinct LRR domains and that the gene is only found in Ae. sharonensis and Ae. longissima. Allele mining and phylogenetic analysis indicate multiple events of Yr87/Lr85 gene flow between the two species and presence/absence variation explaining the majority of resistance to wheat leaf rust in both species. The confinement of Yr87/Lr85 to Ae. sharonensis and Ae. longissima and the resistance in wheat against Pst and Pt highlight the potential of these species as valuable sources of disease resistance genes for wheat improvement.

Abstract Amidst the increasing complexity of microgrid optimization, characterized by numerous decision variables and intricate non-linear relationships, there is a pressing need for highly efficient algorithms. This study introduces a tailored Mixed Integer Nonlinear Programming (MINLP) model that optimizes the charging and discharging schedules of electric vehicles (EVs) and energy storage systems (ESS) while incorporating Distributed Flexible AC Transmission System (D-FACTS) devices. To address these challenges, a novel approach based on the Large-Scale Two-Population Algorithm (LSTPA) is proposed. The model's effectiveness was evaluated using a 33-node microgrid, where the proposed method achieved a total purchased energy of 1.2 MWh, a voltage deviation of 0.0357 p.u, and a CPU time of 551 s, outperforming traditional methods like NSGA-II, PSO, and JAYA. Additionally, in a 69-node microgrid, the approach resulted in a total purchased energy of 0.3 MWh and a voltage deviation of 0.0078 p.u. These results demonstrate the superior performance of the proposed method in terms of energy efficiency, voltage stability, and computational time, advancing the efficiency of microgrid management.

Gold nanoclusters (AuNCs), with sizes below 2 nm, have emerged as remarkable nanomaterials exhibiting unique optical, electronic, and chemical properties. Their ultra-small size imparts advantageous characteristics, including high surface area, tunable fluorescence, and excellent biocompatibility, making AuNCs highly promising for diverse applications. This article explores recent advancements in leveraging AuNCs to address critical challenges in clean energy storage and environmental remediation. For energy storage, AuNCs boost the performance of Li-based batteries by facilitating rapid electron transfer kinetics and limiting polysulfide shuttling. The review delves into mechanistic insights governing AuNC–hydrogen interactions, various synthetic approaches for tailoring AuNCs, and their emerging applications as advanced electrodes, efficient catalysts, and conductive additives enabling improved charge storage capabilities. Additionally, using plasmonic effects and hot carrier generation induced by AuNCs shows tremendous potential in photocatalytic water splitting for clean hydrogen fuel production. For environmental applications, AuNCs enable the degradation of persistent organic pollutants, heavy metal ion detection at part-per-trillion levels, and solar-driven water purification, relying on plasmon-enhanced hot carrier processes. However, the long-term ecological impacts of AuNCs remain unclear. This study thus underscores the need for further toxicological assessments and life cycle analyses to promote sustainable AuNC-based technologies through responsible research and innovation. Overall, it highlights the versatile applicability of AuNCs in addressing critical energy and environmental challenges.

Abstract The integration of renewable energy sources into smart distribution grids poses substantial challenges in maintaining grid stability, efficiency, and reliability due to their inherent variability and intermittency. This study addresses these challenges by proposing a novel two-level optimization model aimed at enhancing operational efficiency and robustness in smart distribution grids. The model synergistically integrates renewable energy sources, energy storage systems, electric vehicles, and demand-side management through a dynamic reconfiguration approach. It employs a robust optimization framework combined with a two-stage second-order cone optimization model to manage real-time operations and strategic grid reconfiguration. Key findings from simulations on the IEEE 33 and 69-bus networks underscore the model’s effectiveness. In the 33-bus system, implementing the demand response program led to a significant reduction in power losses, from 0.64 MW to 0.52 MW, and improved voltage stability, with the minimum voltage increasing from 0.970 to 0.980 p.u. Similarly, in the 69-bus system, power losses decreased from 0.85 MW to 0.79 MW, and voltage stability improved, with the minimum voltage rising from 0.962 to 0.972 p.u. The model also demonstrated reduced energy procurement needs, showcasing its impact on enhancing grid efficiency and reliability. These results highlight the model’s potential for advancing smart grid management strategies, offering significant improvements in operational performance and stability under varying demand conditions.

Abstract Background Traumatic brain injury (TBI) is a major medical and social concern in developing countries. TBI-related morbidity and mortality statistics in Egypt are lacking and do not reflect the actual magnitude of the problem. Objectives To overview the incidence of moderate and severe head trauma in a heavily populated developing country and document the outcome of moderate and severe TBI associated with skull base fracture (SBF). Methodology Data of patients admitted to our center with moderate and severe TBI associated with skull base fracture (SBF) were reviewed in the period between January 2019 and March 2023. Results The most common type of trauma was road traffic accidents in 54.2% of the patients; 91.2% had Single SBF (middle cranial fossa fracture was predominant 58.5%). 25.5% had an initial GCS of ≤ 8. Periorbital ecchymosis was the most common presenting sign in 36.3%. The most frequent complication (37.3%) was pneumocephalus. The presence of skull base fracture inversely affected the Glasgow outcome scale extended GOSE (P = 0.001, r = 0.674). Higher initial GCS scores were positively correlated with good GOSE (GOSE) (P = 0.001, r =− 0.222). Conclusions RTA represents a significant cause for moderate and severe TBI in young male population. SBF is associated with poor outcome in moderate and severe TBI. Higher initial GCS score was positively correlated with good GOSE. It is important to have an overview of different types of TBI in Egypt.

Abstract Background Medial sphenoid wing meningiomas are best treated through pterional craniotomy, as pterional craniotomy provides wide and multidirectional exposure of the anterior and middle cranial fossa. Anterior clinoidectomy can increase the exposure potential. To delineate the role of anterior clinoidectomy (AC) in the standard pterional craniotomy approach through the evaluation of operability score measures (manoeuvrability arc, depth of surgical field, and surgical angle of attack). All patients with inner sphenoidal wing meningioma who underwent microsurgical excision between February 2022 and October 2023 were enrolled in the study. Preoperative and postoperative imaging studies (MR contrast studies and 3D thin-slice CT scans of the brain) were performed to determine the tumour size, extent, and pattern of optic canal involvement by comparing pre- and postoperative operability score parameters. Results Twenty-five patients met our inclusion criteria: 2 males (8%) and 23 females (92%). The mean age (SD) was 49.08 ± 6.42 years, with an age range of 39–60 years. The preoperative visual manifestations were as follows: eight patients (32%) had mild visual impairment, five patients (20%) had moderate visual impairment, six patients (24%) had severe visual impairment, and five patients (20%) had blindness. There was a significant positive correlation between the operability score and extent of resection (gross total resection was correlated with a higher operability score) (r = 0.301, n = 25, p = 0.005). Conclusions A well-planned manoeuvrable arc allows neurosurgeons to perform surgery with precision, ultimately impacting surgical outcomes and the potential for complete tumour removal with minimal patient morbidity.

Abstract Introduction The accurate prediction of COVID-19 mortality risk, considering influencing factors, is crucial in guiding effective public policies to alleviate the strain on the healthcare system. As such, this study aimed to assess the efficacy of decision tree algorithms (CART, C5.0, and CHAID) in predicting COVID-19 mortality risk and compare their performance with that of the logistic model. Methods This retrospective cohort study examined 5080 cases of COVID-19 in Babol, a city in northern Iran, who tested positive for the virus via PCR from March 2020 to March 2022. In order to check the validity of the findings, the data was randomly divided into an 80% training set and a 20% testing set. The prediction models, such as Logistic regression models and decision tree algorithms, were trained on the 80% training data and tested on the 20% testing data. The accuracy of these methods for the test samples was assessed using measures like ROC curve, sensitivity, specificity, and AUC. Results The findings revealed that the mortality rate for COVID-19 patients who were admitted to hospitals was 7.7%. Through cross validation, it was determined that the CHAID algorithm outperformed other decision tree and logistic regression algorithms in specificity, and precision but not sensitivity in predicting the risk of COVID-19 mortality. The CHAID algorithm demonstrated a specificity, precision, accuracy, and F-score of 0.98, 0.70, 0.95, and 0.52 respectively. All models indicated that factors such as ICU hospitalization, intubation, age, kidney disease, BUN, CRP, WBC, NLR, O2 sat, and hemoglobin were among the factors that influenced the mortality rate of COVID-19 patients. Conclusions The CART and C5.0 models had outperformed in sensitivity but CHAID demonstrates a better performance compared to other decision tree algorithms in specificity, precision, accuracy and shows a slight improvement over the logistic regression method in predicting the risk of COVID-19 mortality in the population under study.

This study synthesized a ferric oxide–nanographite (NG) nanocomposite (Fe2O3@NG) from waste toner powder through carbonization. Subsequently, a TiO2/Fe2O3@NG nanohybrid was fabricated using the sol–gel technique to improve the photocatalytic degradation of dyes. TiO2/Fe2O3@NG nanocomposites were prepared at TiO2:Fe2O3@NG ratios of 2:1 (Ti:T-21), 1:1 (Ti:T-11), and 1:2 (Ti:T-12). The porosity, morphology, surface chemistry, and chemical interactions between TiO2, Fe2O3, and graphite in the prepared TiO2/Fe2O3@NG nanocomposites were characterized using the Brunauer–Emmett–Teller (BET) method and microscopic and spectroscopic analyses. The TiO2/Fe2O3@NG nanohybrid exhibited a reduced bandgap (2.4–2.9 eV) and enhanced charge carrier separation through charge transfer at the junction of the hetero-structured TiO2/Fe2O3@NG nanohybrid. Preliminary experiments revealed that Ti:T-21 was the most effective photocatalyst for degrading acid blue-25 (AB-25) compared to Ti:T-11, Ti:T-12, sole TiO2, and Fe2O3@NG. This study also investigated the impacts of catalyst dose and initial dye concentration on the AB-25 photocatalytic degradation. Notably, 97% of 5-mg/L AB-25 was removed using 1.25-g/L Ti:T-21 at an unmodified pH of 6.4 within 120 min. Furthermore, Ti:T-21 exhibited remarkable recyclability in its immobilized form, achieving degradation ratios of 74.7%–71.8% over five consecutive runs, compared to removal efficiencies of 85.0%–62.3% in the suspended mode. Trapping experiments identified hydroxyl radicals, holes, and superoxide as the principal reactive radicals. The TiO2/Fe2O3@NG/light system was effective in disintegrating and mineralizing other synthetic dyes such as Congo red, methylene blue, and methyl red, indicating its potential for industrial-scale degradation of authentic dye wastewater. The utilization of waste toner for water treatment is highlighted as a strategy to promote environmental sustainability, foster a circular economy, and contribute to pollution remediation.

Data on acute coronary syndrome (ACS) is lacking in Africa where cases of premature ACS seem to be on the rise. Africa would benefit from an epidemiological assessment of premature ACS to determine its risk factors and management in this demographic to inform guidelines and practice. The European Atherosclerosis Society recognised this urgency and formed a growing network across 11 African countries to create the Lipid Registry of Africa (EAS-LIPRA). This article is based on the EAS-LIPRA protocol and presents the aims, concept and methodological considerations, and the operations and collaborative governance structure of this project. EAS-LIPRA aims to report risk factors and outcomes of premature ACS in Africa to further understand its prevalence and management via collating and pooling multinational prospective data on premature ACS across multiple sites in Africa into a standardised registry. Data will be stratified into subgroups based on country-level income as defined by the World Bank, and within country residence of urban versus rural areas. Valid statistical procedures will be employed to compare and observe trends in the pooled data based on demographics, clinical and laboratory variables, and disparities in its management. Being the first multinational lipid registry in Africa, it is envisaged that the network will expand to other African countries and sites yet to participate, facilitate other epidemiological studies in preventive cardiology, and set a precedent for other developing countries and regions.

Background: Coronary artery disease (CAD) is a leading cause of mortality worldwide, with varying patterns and risk factors across different age groups. While CAD is common in older adults, data on young adults are limited, with traditional risk factors and familial history playing a significant role in early disease development. The purpose of this study was to compare the coronary angiographic patterns in young adults (

Water security is a major challenge for agricultural sustainability in Egypt. To tackle water scarcity, the reuse of wastewater such as raw agricultural drainage water (RADW) and treated sewage drainage water (TSDW) can be a potential solution. An investigation was conducted over two seasons (2022 and 2023) for 5 months (January–May) on roughly 8-month-old jojoba plants to study their tolerance for irrigation with different concentrations of wastewater (RADW, TSDW) at 25%, 50%, 75% and 100% compared to the control (tap water). The study examined the effect of wastewater irrigation on growth parameters such as plant height, stem diameter, shoot numbers, leaf physical measurements, visual quality (VQ) and leaf chemical components including heavy metals (HMs), antioxidant capacity (2,2-diphenyl-1-picrylhydrazyl [DPPH]), ion leakage (IL%), superoxide anion (O2•−), hydrogen peroxide (H2O2), malondialdehyde (MDA), leaf minerals, pigments, soluble carbohydrate content (SCC), total phenolic content (TPC) and proline performance in jojoba plants. The findings indicated that jojoba plants can tolerate irrigation with RADW up to a concentration of 100% and TSDW up to a concentration of 75%.

Background: Tumor necrosis factor alpha (TNF-α) produces an inflammatory process and plays a critical role against infection and in the control of viral infection. The present study was conducted to determine the status of serum TNF-α in hospitalized patients with coronavirus disease-2019 (COVID-19). Methods: In this cross-sectional study the serum TNF-α level, sex, and age, were determined in patients with COVID-19. The association between variables was determined using the student t-test, analysis of variance (ANOVA) test, multiple logistic regression analysis, and the statistical package for the Social Sciences (SPSS)-18 (p < 0.05). Results: A total of 91 (women 41.75%, and men 58.24%) patients with a mean serum TNF-α level of 9.9 picograms per milliliter (pg/mL) were considered. In all (100%) patients, the TNF-α serum level was more than the normal limit (P=0.95). 95.60% of patients suffered severe COVID-19, with a TNF-a serum level of 10.20 pg/mL (P=0.87). Mean TNF-α serum levels in women and men were 11.37 pg/mL and 8.8 pg/mL, respectively (P= 0.17). In the age group of > 70 years (11.30 pg/mL), serum TNF-α concentration was higher than the other age groups (p>0.05). Conclusion: A significant proportion of women and men patients with COVID-19 in the middle and old age had a high concentration of serum TNF-α which may indicate the severity of the disease. Serum TNF-α level is different in women and men of different ages, so it can contribute to treatment strategies.

Abstract Background Autologous stem cell transplantation (ASCT) is a pivotal treatment for lymphoma patients. The BeEAM regimen (Bendamustine, Etoposide, Cytarabine, Melphalan) traditionally relies on cryopreservation, whereas the CEM regimen (Carboplatin, Etoposide, Melphalan) has been optimized for short-duration administration without the need for cryopreservation. This study rigorously compares the clinical and safety profiles of the BeEAM and CEM regimens. Methods A controlled, randomized clinical trial was conducted with 58 lymphoma patients undergoing ASCT at the International Medical Center (IMC) in Cairo, Egypt. Patients were randomly assigned to either the BeEAM (n = 29) or CEM (n = 29) regimen, with an 18-month follow-up period. Clinical and safety outcomes were meticulously compared, focusing on time to engraftment for neutrophils and platelets, side effects, length of hospitalization, transplant-related mortality (TRM), and survival rates. Results The findings demonstrate a significant advantage for the CEM regimen. Neutrophil recovery was markedly faster in the CEM group, averaging 8.5 days compared to 14.5 days in the BeEAM group (p

Abstract This study presents a novel method for planning the expansion of transmission lines and energy storage systems while considering the interconnectedness of electricity and gas networks. We developed a two-level stochastic planning model that addresses both the expansion of transmission and battery systems in the electrical grid and the behavior of the gas network. This research explores the challenges and effects of integrating high levels of renewable energy sources while ensuring security within both networks. Our model uses a stochastic mixed-integer non-linear programming approach. To solve this complex model, we applied the Human Evolutionary Model (HEM). We tested our approach on two case studies: a simple 6-node network and the more complex IEEE RTS 24-bus network for the electricity grid, combined with 5-node and 10-node gas networks, respectively. The results demonstrate the effectiveness of our model, particularly in scenarios where connections in the power and gas networks are disrupted, preventing load shedding even when integrated network connections are cut.

Compost is commonly utilized to improve properties of infertile sandy soils, despite its high biodegradability which may increase greenhouse gases emissions. It is possible to combine compost with biochar, which degrades at a slower rate, forming a “co-composted biochar” product. This mixture could enhance plant growth parameters beyond those attained for using each component, individually. To investigate this assumption, zucchini was selected as a test plant to be grown, under greenhouse conditions, on a sandy soil that received biochar, compost or co-composted biochar (from rice straw or sugarcane bagasse (SB)) for a duration of 15 days. This timeframe was deemed sufficient to achieve a relatively stable degradation rate for compost. Application of organic materials increased both fresh and dry weights of zucchini plants, particularly when co-composted biochar of SB was used. Specifically, plant fresh weights increased by 1.24–1.71 folds when using this additive versus the control group. Additionally, availability of nitrogen, phosphorus, and potassium in soil and their uptake by plants significantly increased owing to application of all additives, with superiority for the co-composted biochar of SB. Enhancements in plant fresh weights were strongly correlated with increasing availability and uptake of phosphorus by plants. In conclusion, organic amendments have a substantial positive impact on enhancing the nutritional status and growth of zucchini, even during the early vegetative growth stage (within the first 15 days after planting). The greatest improvements were observed when co-composted biochar of SB was used and this confirm the main hypothesis of the study.

Abstract Tremendous research efforts have been directed toward developing polymer-based piezoelectric nanogenerators (PENG) in a promising step to investigate self-charging powered systems (SCPSs) and consequently, support the need for flexible, intelligent, and ultra-compact wearable electronic devices. In our work, electrospun polyvinylidene fluoride (PVDF) nanofiber mats were investigated while graphene oxide (GO) was added with different concentrations (from 0 to 3 wt.%). Sonication treatment was introduced for 5 min to GO nanosheets before combined PVDF solution. A comprehensive study was conducted to examine the GO incremental effect. Microstructural and mechanical properties were examined using a scanning electron microscope (SEM) and a texture analyzer. Moreover, piezoelectric properties were assessed via various tests including impulse response, frequency effect, d33 coefficient, charging and discharging analysis, and sawyer tower circuit. Experimental results indicate that incorporation of GO nanosheets enhances piezoelectric properties for all concentrations, which was linked to the increase in β phase inside the nanofibers, which has a significant potential of enhancing nanogenerator performance. PVDF-GO 1.5 wt.% shows a notably higher enhancing effect where the electroactive β-phase and γ-phase are recorded to be boosted to ~ 68.13%, as well as piezoelectric coefficient (d33 ~ 55.57 pC/N). Furthermore, increasing impact force encouraged the output voltage. Also noted that the delivered open circuit voltage is ~ 3671 V/g and the power density is ~ 150 µw/cm2. It was observed that GO of concentration 1.5 wt.% recorded a conversion efficiency of ~ 74.73%. All results are in line, showing better performance for PVDF-GO 1.5 wt.% for almost all concentrations.

Abstract The fragility and weakness of historical, archaeological, and heritage leather artifacts in museums, and libraries due to unsuitable environmental conditions are significant challenges. This study aims to assess the effectiveness of Hydroxypropyl Beta Cyclodextrin, a novel material, in consolidating leather artifacts by examining their physical, chemical, and mechanical properties. Vegetable-tanned leather samples were treated with different concentrations of Hydroxypropyl Beta Cyclodextrin and subjected to artificial heat aging. Evaluation methods included digital and scanning electron microscopy, contact angle measurements, mechanical testing, color analysis, pH measurement, and Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy. Results showed that Hydroxypropyl Beta Cyclodextrin at 1% and 2% concentrations improved chemical stability, surface morphology, color retention, and mechanical properties of the leather samples. The third concentration yielded less favorable outcomes. This study recommends using Hydroxypropyl Beta Cyclodextrin at 1% and 2% concentrations for consolidating historical leathers.

Machine learning (ML) is becoming an ever more important tool in hydrologic modeling. Previous studies have shown the higher prediction accuracy of those ML models over traditional process-based ones. However, there is another advantage of ML which is its lower computational demand. This is important for the applications such as hydraulic soil erosion estimation over a large area and at a finer spatial scale. Using traditional models like Rangeland Hydrology and Erosion Model (RHEM) requires too much computation time and resources. In this study, we designed an Artificial Neural Network that is able to recreate the RHEM outputs (annual average runoff, soil loss, and sediment yield and not the daily storm event-based values) with high accuracy (Nash-Sutcliffe Efficiency ≈ 1.0) and a very low computational time (13 billion times faster on average using a GPU). We ran the RHEM for more than a million synthetic scenarios and train the Emulator with them. We also, fine-tuned the trained Emulator with the RHEM runs of the real-world scenarios (more than 32,000) so the Emulator remains comprehensive while it works specifically accurately for the real-world cases. We also showed that the sensitivity of the Emulator to the input variables is similar to the RHEM and it can effectively capture the changes in the RHEM outputs when an input variable varies. Finally, the dynamic prediction behavior of the Emulator is statistically similar to the RHEM.

This study explores the enhancement of electric grid flexibility and the realization of smart grid objectives through the integration of renewable energy (RE) resources and energy storage systems (ESS). While prior research has mainly concentrated on optimizing ESS operations either within the transmission network as a versatile power source or within the distribution network using small-scale batteries, our approach offers a more holistic perspective. We introduce a bi-level stochastic model for integrated energy management that encompasses renewable energy, demand side management (DSM), transmission, and distribution networks as interconnected entities. To tackle the binary variables inherent in the model, we employ a precise method based on reformulation and decomposition techniques to ensure globally optimal solutions. We evaluate the efficacy of our proposed model and the influence of ESS on the networks using various integrated transmission and distribution network systems. Our findings demonstrate the model's efficiency and underscore the cost-saving benefits of integrating energy storage systems. Specifically, incorporating ESS into the distribution grid results in a 13 % reduction in distribution network costs, while deploying large batteries in the transmission grid leads to an impressive 83 % cost reduction.

Mental illness is a common disease that at its extremes leads to personal and societal suffering. A complicated multi-factorial disease, mental illness is influenced by a number of socioeconomic and clinical factors, including individual risk factors. Traditionally, approaches relying on personal interviews and filling out questionnaires have been employed to diagnose mental illness; however, these manual procedures have been found to be frequently prone to errors and unable to reliably identify individuals with mental illness. Fortunately, people with mental illnesses frequently express their ailments on social media, making it possible to more precisely identify mental disease by harvesting their social media posts. This study offers a thorough analysis of how to identify mental illnesses (more specifically, depression) from users’ social media data. Along with the explanation of data acquisition, preprocessing, feature extraction, and classification techniques, the most recent published literature is presented to give the readers a thorough understanding of the subject. Since, in the recent past, the majority of the relevant scientific community has focused on using machine learning (ML) and deep learning (DL) models to identify mental illness, so the review also focuses on these techniques and along with their detail, their critical analysis is presented. More than 100 DL, ML, and natural language processing (NLP) based models developed for mental illness in the recent past have been reviewed, and their technical contributions and strengths are discussed. There exist multiple review studies, however, discussing extensive recent literature along with the complete road map on how to design a mental illness detection system using social media data and ML and DL classification methods is limited. The review also includes detail on how a dataset may be acquired from social media platforms, how it is preprocessed, and features are extracted from it to employ for mental illness detection. Hence, we anticipate that this review will help readers learn more and give them a comprehensive road map for identifying mental illnesses using users’ social media data.

Cultivated and wild species of the genus rye (Secale) are important but underexploited gene sources for increasing the genetic diversity of bread wheat. Gene transfer is possible via bridge genetic materials derived from intergeneric hybrids. During this process, it is essential to precisely identify the rye chromatin in the wheat genetic background. In the present study, backcross generation BC2F8 from a cross between Triticum aestivum (Mv9kr1) and S. cereanum (‘Kriszta,’ a cultivar from the artificial hybrid of S. cereale and S. strictum) was screened using in-situ hybridization (GISH and FISH) and analyzed by DArTseq genotyping in order to select potentially agronomically useful genotypes for prebreeding purposes. Of the 329,267 high-quality short sequence reads generated, 27,822 SilicoDArT and 8,842 SNP markers specific to S. cereanum 1R–7R chromosomes were identified. Heatmaps of the marker densities along the ‘Lo7’ rye reference pseudomolecules revealed subtle differences between the FISH- and DArTseq-based results. This study demonstrates that the “exotic” rye chromatin of S. cereanum introgressed into wheat can be reliably identified by high-throughput DArTseq genotyping. The Mv9kr1-’Kriszta’ addition and translocation lines presented here may serve as valuable prebreeding genetic materials for the development of stress-tolerant or disease-resistant wheat varieties.

Monkeypox, now named mpox, has emerged as a significant public threat, as evidenced by the 2022 outbreak affecting over seventy countries globally. This infectious disease presents debilitating symptoms, including painful skin rashes, mucosal lesions, enlarged lymph nodes, and fever. The situation intensifies with concerns about a novel transmission route, specifically through sexual contact, and the evolution of more transmissible strains. Complicating matters further is the documented spillback of mpox from humans to animals, raising the potential for new animal reservoirs. This study utilized a systematic approach to gather, analyse, and interpret data regarding global mpox outbreaks, phylogenomics, human APOBEC3 enzyme activity, antiviral resistance issues, and the application of the One Health intervention. Emphasizing a One Health approach covers various aspects, including zoonotic origins, pathogenesis, changing epidemiological landscapes, phylogenomic diversity, and clade dynamics. The review underscores the crucial role of global collaboration in understanding and combatting mpox and making it a valuable resource for shaping effective prevention and control measures on a global scale.

Background: Public health threats can significantly impact mass gatherings and enhancing surveillance systems would thus be crucial. Epidemic Intelligence from Open Sources (EIOS) was introduced to Qatar to complement the existing surveillance measures in preparation to the FIFA World Cup Qatar 2022 (FWC22). This study estimated the empirical probability of EIOS detecting signals of public health relevance. It also looked at the factors responsible for discerning a moderate-high risk signal during a mass gathering event. Methods: This cross-sectional descriptive study used data collected between November 8th and December 25th, 2022, through an EIOS dashboard that filtered open-source articles using specific keywords. Triage criteria and scoring scheme were developed to capture signals and these were maintained in MS Excel. EIOS’ contribution to epidemic intelligence was assessed by the empirical probability estimation of relevant public health signals. Chi-squared tests of independence were performed to check for associations between various hazard categories and other independent variables. A multivariate logistic regression evaluated the predictors of moderate-high risk signals that required prompt action. Results: The probability of EIOS capturing a signal relevant to public health was estimated at 0.85 % (95 % confidence interval (CI) [0.82 %−0.88 %]) with three signals requiring a national response. The hazard category of the signal had significant association to the region of occurrence (χ2 (5, N = 2543) = 1021.6, p

ex-ante judicial supervision over prosecution and investigation is one of the new developments in criminal procedure. This supervision is the use of supervision by court judges or independent expert judges outside of the Prosecutor's Office over the actions and decisions of the Prosecutor's Office, including the investigator, especially actions that impact individual rights and freedoms in the pre-trial stage of criminal proceedings. Ex-ante supervision is recognized in the criminal justice system of Italy, and Germany; however, in Iran's law, ex-ante judicial supervision has been considered only case-by-case in some articles of Iran's Criminal Procedure Code, without being correctly extended to all decisions that are related to the rights and freedoms of individuals in the pre-trial stage. This article aims to explain the ex-ante judicial supervision comparatively taken in Germany and Italy and examine their differences with the existing supervision in Iran using analytical and descriptive methods, and at the same time, it is comparative with library collection tools; done. The findings of the research indicate the need for Iranian legislators and legal doctrine to pay attention to the issue of ex-ante judicial supervision over prosecution and investigation, such as in Germany and Italy, in an explicit and precise manner, and to prevent the centralization of powers of prosecution, investigation and supervision in the hands of the prosecutor's office to improve the quality of criminal justice and Prevention of judicial errors and violation of people's rights with these broad powers that were given to the judiciary.

Abstract The organic enrichment effects on the meiofauna and nematofauna were assessed for field sediment and other experimental ones enriched with organic matters conducted in the laboratory for 4 weeks. Also, dissolved oxygen (DO) and pH were monitored for each one. The abundance and diversity of meiofaunal groups and nematofauna varied. Strong significant correlations were found between DO and the studied items. Nematoda was the most abundant group in the field sediment and other experimental ones; their counts increased with the increase in organic enrichments and were dominated by deposit feeders. Amphipoda, Ostracoda and predator/omnivore nematodes disappeared in highly organic-enriched sediments. Changes in DO and organic enrichments might be the more attributable reasons for the alteration of the meiobenthic assemblages. The generic compositions of Nematoda provide a good indicator for environmental alterations.

Summary The sustained instability in Afghanistan, along with ongoing disease outbreaks and the impact of the COVID-19 pandemic, has significantly affected the country. During the COVID-19 pandemic, the country’s detection and response capacities faced challenges. Case identification was done in all health facilities from primary to tertiary levels but neglected cases at the community level, resulting in undetected and uncontrolled transmission from communities. This emphasizes a missed opportunity for early detection that Event-Based Surveillance (EBS) could have facilitated. Therefore, Afghanistan planned to strengthen the EBS component of the national public health surveillance system to enhance the capacity for the rapid detection and response to infectious disease outbreaks, including COVID-19 and other emerging diseases. This effort was undertaken to promptly mitigate the impact of such outbreaks. We conducted a landscape assessment of Afghanistan’s public health surveillance system to identify the best way to enhance EBS, and then we crafted an implementation work plan. The work plan included the following steps: establishing an EBS multisectoral coordination and working group, identifying EBS information sources, prioritizing public health events of importance, defining signals, establishing reporting mechanisms, and developing standard operating procedures and training guides. EBS is currently being piloted in seven provinces in Afghanistan. The lessons learned from the pilot phase will support its overall expansion throughout the country.

Abstract Background Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma (NHL), constituting 31% of all NHL. Malignancy and inflammation are closely linked. Inflammatory processes have been identified to play an important role in the pathogenesis of lymphoma. Obesity is a well-known risk factor not only for the development of cardiovascular disease and diabetes but also for the development of several types of cancer, including lymphomas. Objective To find out the association of pan-immune-inflammation value (PIV) and body mass index (BMI) with survival in adults with diffuse large B-cell lymphoma. Patients and methods We conducted an observational retrospective study on 110 patients to unravel the association of PIV and BMI with survival outcome in a cohort of adults diagnosed as de novo DLBCL (NOS) and treated at the hematology units of International Medical Center, Helwan and Menoufia University Hospitals, in the period from 2014 to 2018. Results The mean age of the studied patients was 54.27 years, the mean BMI was 28.91, and the median and IQR for PIV were 195.84 (96.20–498.52). The cutoff value for detecting mortality in BMI was 29.74 kg/m2 with poor sensitivity (44.4%) and poor specificity (67.2%). The cutoff value for detecting mortality in PIV was 250.49 with poor sensitivity (50.0%) and poor specificity (67.2%). The mean duration of overall survival was 21.596 months. There was nonsignificant difference regarding 2-year overall survival according to BMI grouping (p-value = 0.195) and PIV grouping (p-value = 0.275). Conclusion Neither PIV nor BMI were associated with 2-year overall survival in patients with DLBCL.

Abstract Objective To detect demographic, clinical, and radiological predictors of patient outcomes and prognosis in spontaneous cerebellar hematoma patients that may guide accurate decision making. Methods This retrospective study was conducted on 45 patients with spontaneous cerebellar hematoma who underwent surgical treatment. The patient data including demographics (age, gender), preoperative consciousness at the time of admission, medical comorbidities (HTN, DM), radiological findings (location, volume, and diameter of the cerebellar hematoma, hydrocephalus, compression of the fourth ventricle, effacement of the quadrigeminal cistern, intraventricular hematoma, tight posterior fossa, and brain stem compression), and treatment methods were collected and correlated with prognosis. Outcome assessment was done using the Glasgow Outcome Scale (GOS), classified into good outcome (favorable result; GOS > 4) and poor outcome (unfavorable result; GOS

They are directly integrated into smart distribution networks and can supply stored energy during peak demand periods, while absorbing and storing energy during periods of low demand. This capability helps maintain a balance between supply and demand in power grids, preventing voltage fluctuations and the inability to meet peak loads during high-demand hours. Thanks to technological advancements, it is now possible to upgrade large-scale energy storage facilities. The modern architecture and technology of these facilities facilitate the efficient utilization of renewable energy sources, significantly reducing energy costs and increasing energy efficiency. Additionally, through the use of artificial intelligence algorithms and optimization techniques, the performance and operations of large-scale energy storage facilities can be enhanced. This article focuses on the management of large-scale energy storage facilities, introducing innovative measures that include constraints on the number of charge and discharge processes. Furthermore, the use of the advanced Fakete search algorithm is employed as a powerful and efficient method for solving the proposed model. This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. Simulation results demonstrate that adopting this approach in managing large-scale energy storage facilities leads to significant economic impacts. These impacts include reduced energy costs, increased efficiency, greater independence from fossil fuel resources, the preservation of grid stability, and improved performance of the power transmission system.

Abstract Background members of the genus Sarcocystis are intracellular obligate protozoan parasites classified within the phylum Apicomplexa and have an obligate heteroxenous life cycle involving two hosts. A more comprehensive understanding of the prevalence and geographic range of different Sarcocystis species in marine ecosystems is needed globally and nationally. Hence, the objective of this study was to document the incidence of Sarcocystis infection in sharks within the aquarium ecosystem of Egypt and to identify the species through the characterization of the SSU rDNA gene. Methods All organs of the mako shark specimen underwent macroscopic screening to detect the existence of a Sarcocystis cyst. Ten cysts were collected from the intestine and processed separately to extract the genomic DNA. The polymerase chain reaction (PCR) was accomplished by amplifying a specific 18S ribosomal RNA (rRNA) gene fragment. Subsequently, the resulting amplicons were subjected to purification and sequencing processes. Results Macroscopic examination of the mako shark intestinal wall sample revealed the presence of Sarcocystis cysts of various sizes and shapes, and sequencing of the amplicons from Sarcocystis DNA revealed a 100% nucleotide identity with the sequence of Sarcocystis tenella recorded from sheep in Iran; The mako shark sequence has been deposited in the GeneBank with the accession number OQ721979. This study presents the first scientific evidence demonstrating the presence of the Sarcocystis parasite in sharks, thereby documenting this specific marine species as a novel intermediate host in the Sarcocystis life cycle. Conclusions This is the first identification of Sarcocystis infection in sharks, and we anticipate it will be an essential study for future screenings and establishing effective management measures for this disease in aquatic ecosystems.

Polysaccharide-based packaging and its ever-increasing applications in response to the need for sustainable and safe packaging have prompted researchers to investigate the development of antimicrobial biopolymer-based packaging for shelf-life enhancement of food samples. A film made by blending chitosan and pectin had good mechanical properties, that is, a tensile strength of 7.43 MPa and an elongation at break of 23.033%. To produce active packaging, thyme essential oil (TEO) was added to the blend at concentrations of 10%, 15%, and 20%. The developed film was characterized for its techno-functional and antimicrobial properties. Further the developed films were employed in an active food packaging system for milk cake. Films with added TEO showed significant enhancements in elongation at break (28.22%) and water vapor barrier properties (30.08 g/h.m2). Additionally, the microstructure of the film was also improved, as demonstrated by scanning electron microscopy (SEM) and atomic force microscopy (AFM) measurements. Fourier transform infrared spectroscopy (FTIR) indicated the interaction of blended matrix (chitosan and pectin) and TEO as observed from the formation of hydrogen bonds with the addition of TEO owing to the OH functional groups. The use of TEO in pectin and chitosan-based film and its application for milk cake packaging showed delayed microbiological contamination and hardness of milk cake samples. The shelf life of milk cake packaged in pectin and chitosan blend film with 20% TEO was enhanced by > 10 days.

IntroductionCryopreservation is a critical process of cell products for achieving a commercial viability through wide scale adoption. By preserving cells in a lower temperature, cryopreservation enables a product to be off-the-shelf and ready for infusion. An optimized cryopreservation strategy can maintain the viability, phenotype, and potency of thawed mesenchymal stromal/stem cells (MSCs) while being regulatory compliant. We compared three clinical-ready formulations with one research cryopreservation solutions and evaluated key quality parameters of post thawed MSCs.Method and resultMSCs were cryopreserved at 3, 6, and 9 million cells/mL (M/mL) in four different cryopreservation solutions: NutriFreez (10% dimethyl sulfoxide [DMSO]), Plasmalyte A (PLA)/5% human albumin (HA)/10% DMSO (PHD10), CryoStor CS5 (5% DMSO), and CryoStor CS10 (10% DMSO). To establish post thaw viability, cells were evaluated with no dilution of DMSO (from 3 M/mL), 1:1 dilution (from 6 M/mL), or 1:2 dilution (from 9 M/mL) with PLA/5% HA, to achieve uniform concentration at 3 M/mL. Cell viability was measured at 0-, 2-, 4-, and 6-h post thaw with Trypan blue exclusion and Annexin V/PI staining. Dilution (1:2) of final cell products from 9M/mL resulted in an improvement of cell viability over 6 h but showed a trend of decreased recovery. MSCs cryopreserved in solutions with 10% DMSO displayed comparable viabilities and recoveries up to 6 h after thawing, whereas a decreasing trend was noted in cell viability and recovery with CS5. Cells from all groups exhibited surface marker characteristics of MSCs. We further evaluated cell proliferation after 6-day recovery in culture. While cells cryopreserved in NutriFreez and PHD10 presented similar cell growth post thaw, MSCs cryopreserved in CS5 and CS10 at 3 M/mL and 6M/mL showed 10-fold less proliferative capacity. No significant differences were observed between MSCs cryopreserved in NutriFreez and PHD10 in their potency to inhibit T cell proliferation and improve monocytic phagocytosis.ConclusionMSCs can be cryopreserved up to 9 M/mL without losing notable viability and recovery, while exhibiting comparable post thaw potency with NutriFreez and PHD10. These results highlight the importance of key parameter testing for selecting the optimal cryopreservation solution for MSC-based therapy.

Managing microgrid energy presents a complex challenge due to unpredictable renewable sources, fluctuating demand, and diverse equipment like batteries, distributed generators, and electric vehicles. This paper introduces a novel two-step optimization model, the Robust Day-Ahead Scheduling for Enhanced Resilience, tailored for microgrid operations. The model addresses the integration of electronic generation, uncertain demand patterns, and small-scale renewable resources. Detailed formulations optimize microgrid energy use, including strategic battery usage, efficient electric vehicle charging, balancing device utilization, and distributed generation dispatch. This multi-faceted approach aims to minimize costs over 24 h, including energy loss, power purchases, reduced power usage, generator operation, and battery/EV expenses. Employing a column-and-constraint generation (C&CG) algorithm ensures efficient problem solving. The proposed model achieved a significant reduction in operational costs, outperforming existing methods by at least 8%. Notably, it minimized energy purchases, energy losses, and load shedding while improving voltage stability, showcasing its effectiveness in enhancing microgrid performance and resilience.

The gut microbiota (GM), as a forgotten organ, refers to the microbial community that resides in the gastrointestinal tract and plays a critical role in a variety of physiological activities in different body organs. The GM affects its targets through neurological, metabolic, immune, and endocrine pathways. The GM is a dynamic system for which exogenous and endogenous factors have negative or positive effects on its density and composition. Since the mid-twentieth century, laboratory animals are known as the major tools for preclinical research; however, each model has its own limitations. So far, two main models have been used to explore the effects of the GM under normal and abnormal conditions: the isolated germ-free and antibiotic-treated models. Both methods have strengths and weaknesses. In many fields of host-microbe interactions, research on these animal models are known as appropriate experimental subjects that enable investigators to directly assess the role of the microbiota on all features of physiology. These animal models present biological model systems to either study outcomes of the absence of microbes, or to verify the effects of colonization with specific and known microbial species. This paper reviews these current approaches and gives advantages and disadvantages of both models.

The most important information required to successfully issue a flood warning is the quantitative precipitation forecasts (QPFs). This is important to run subsequent rainfall–runoff simulations. A rainfall–runoff simulation derives its accuracy mainly from the accuracy of the input QPFs. The dynamically based global numerical weather prediction models (NWPMs) are strong candidate sources of QPFs. A main problem is the real-time selection of which NWPM should be used to provide the QPFs for flood warning simulations. This paper develops an automated technique to solve this problem. The technique performs real-time comparisons with measured rainfall fields using a novel ‘tolerant’ hydrologic approach. The ‘tolerant’ approach performs the comparison on the basin scale and allows for timing shifts in the forecasts. This is because QPFs can be good but only a few hours early or late. Two events are used for illustration, and the proposed real-time application in flood warning is presented. The developed technique, employing the tolerant approach, could eliminate the effects of the timing shifts and, accordingly, succeeded to select the QPFs to be used. A Python package was developed for automation. The developed technique is expected to also be useful for offline assessments of historical performances of NWPMs. HIGHLIGHTS An automated technique was developed for the assessment of numerical weather prediction model (NWPM) forecasts.; This technique employs a novel tolerant hydrologic approach imitating the human eye/brain judgment for evaluating the forecasting skills.; Real-time selection of the best NWPM, including real-time bias and uncertainty estimation, for flood warning applications is described.; A Python package for automation was developed.;

Abstract Background Carbapenems represent the first line treatment of serious infections caused by drug-resistant Klebsiella pneumoniae. Carbapenem-resistant K. pneumoniae (CRKP) is one of the urgent threats to human health worldwide. The current study aims to evaluate the carbapenemase inhibitory potential of coumarin and to test its ability to restore meropenem activity against CRKP. Disk diffusion method was used to test the antimicrobial susceptibility of K. pneumoniae clinical isolates to various antibiotics. Carbapenemase genes (NDM-1, VIM-2, and OXA-9) were detected using PCR. The effect of sub-MIC of coumarin on CRKP isolates was performed using combined disk assay, enzyme inhibition assay, and checkerboard assay. In addition, qRT-PCR was used to estimate the coumarin effect on expression of carbapenemase genes. Molecular docking was used to confirm the interaction between coumarin and binding sites within three carbapenemases. Results K. pneumoniae clinical isolates were found to be multi-drug resistant and showed high resistance to meropenem. All bacterial isolates harbor at least one carbapenemase-encoding gene. Coumarin significantly inhibited carbapenemases in the crude periplasmic extract of CRKP. The checkerboard assay indicated that coumarin-meropenem combination was synergistic exhibiting a fractional inhibitory concentration index ≤ 0.5. In addition, qRT-PCR results revealed that coumarin significantly decreased carbapenemase-genes expression. Molecular docking revealed that the binding energies of coumarin to NDM1, VIM-2, OXA-48 and OXA-9 showed a free binding energy of -7.8757, -7.1532, -6.2064 and − 7.4331 Kcal/mol, respectively. Conclusion Coumarin rendered CRKP sensitive to meropenem as evidenced by its inhibitory action on hydrolytic activity and expression of carbapenemases. The current findings suggest that coumarin could be a possible solution to overcome carbapenems resistance in CRKP.

Abstract The impacts of climate change on heritage collections in Mediterranean museums are serious and lead to accelerated material degradation, loss of value, increasing conservation costs and climatisation. Climate change scenarios and simulation models have been developed to predict the extreme and average future environmental conditions and to assess the future long-term risks caused by global warming for museum buildings and their collections in Mediterranean countries, with Egypt being particularly at risk. This paper presents the results of the risk analysis of the indoor and outdoor environments in Alexandria Museum of Fine Arts (AMFA) in Egypt to provide an overview of the current situation of conservation and museum management and to provide evidence-based data to support decision-making regarding preventive conservation given the museum's limited funding, capacity and resources. Unfortunately, the air quality in the museum cannot be considered satisfactory and specific measures need to be taken to improve the level of air quality and museum and building management. The results enabled an assessment of indoor air quality and provided information on potential risks to the museum building and collections, including variations in temperature (T) and relative humidity (RH), concentrations of NO2, SO2, O3, CO2, acetic and formic acid and lighting conditions, as well as the location and management of the museum. The results necessitate the development of a preventive conservation plan to address the challenges associated with high T/RH fluctuations and pollution pressure. This requires more regular use of the HVAC system within certain T/RH set points as well as minimising light exposure and the use of UV-filtering glazing. Care should be taken to ensure that housekeeping and emergency preparedness reduce the damping and salt florescence in the museum building. However, dealing with the impact of climate change on indoor and outdoor environments and museum collections in Mediterranean museums requires a holistic and adaptive approach that includes joint collaboration, research, training and strategic planning to ensure the long-term preservation of valuable cultural heritage collections in different climates with customised adaptations based on local environmental conditions, resources and needs. Resilience planning should be region-specific and take into account the potential impacts of extreme weather events, sea level rise and other climate-related challenges.

Subclinical mastitis (SCM) is a serious production and financial health issue facing small ruminant farms. Shami dairy does, and Rahmani ewes were chosen for this study. The udder dimensions of the test animals were evaluated, while the taken milk samples were analysed for chemical composition and the somatic cell count (SCC). The presence milk lactate dehydrogenase (LDH) enzyme in milk samples, haemogram and leukogram were determined, too. The incidence of SCM in goats and sheep was 53.33 % and 41.67 %, respectively. In both ovine and caprine milk, there was an increase in LDH concerning the increase in SCC. There was a significant difference (p

Abstract Background The aim of the present study was to compare the epidemiological patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infections, hospitalizations, deaths, and duration of hospitalization during the fourth, fifth and sixth epidemic waves of coronavirus disease 2019 (COVID-19) in Iran. Methods A multicenter retrospective observational study was conducted on hospitalized patients in four hospitals in the Babol district of northern Iran. The study periods were during the fourth, fifth, and sixth waves of the epidemic in Iran, (March 2021 to March 2022). A total of 13,312 patients with suspected COVID-19 were included. Patient demographics, medical history, length of hospital stay, and clinical outcomes were obtained from the hospital information system. Data on the cycle threshold (Ct) and SARS-CoV2 variant were collected for SARS-CoV2-positive cases. Results The highest number of hospitalized patients was reported during the fifth (Delta) wave (5231; 39.3%), while the lowest number of hospitalized patients was reported during the sixth (Omicron) wave (2143; 16.1%). In total, 6459 (48.5%) out of 13,312 hospitalized patients with suspected COVID-19 had a positive rRT-PCR result. The fifth (Delta) wave had the highest number of SARS-CoV2 rRT-PCR-positive hospitalized patients (3573, 55.3%), while the sixth (Omicron) wave had the lowest number (835, 12.9%). Moreover, 238 (3.7%) patients with laboratory-confirmed COVID-19 died. The hospital mortality rate was 6.8% in the fourth (Alpha) wave, which reduced to 2.7 and 3.5% in the fifth (Delta) and sixth (Omicron) waves, respectively (p

Objective. The intend of the present study was to assess the diagnostic performance of strain elastography in investigating the thyroid nodule malignancy taking the surgical biopsy as a gold standard reference test.

Background and purpose: Extracellular electron transferring (EET) or redox bacteria employ a shuttle of flavins to transfer electrons to the oxygen in the intestinal mucosa. Although clinical studies suggest that the gut microbiome modulates the efficiency of immune checkpoint therapy in patients with cancer, the modulation mechanisms have not been well-characterized yet. Experimental approach: In the present study, the oral gavage administration of Shewanella oneidensis MR-1 as a prototypic EET bacteria was assayed in a mouse model of lung cancer to determine the effect of EET bacterium on the efficacy of the programmed cell death protein 1 (PD1)-immune checkpoint therapy. Findings/Results: It was indicated that in vitro EET from S. oneidensis was mediated by riboflavins that were supplied through extrinsic sources. Co-administration of S. oneidensis and anti-PD 1 antibodies represent better tumor remission compared to the single-administration of each one; however, no statistically significant change was observed in the tumor volume. Conclusion and implications: More detailed studies are needed to definitively confirm the therapeutic effects of electrogenic bacteria in patients with cancer. Given the findings of the present study, increasing flavin compounds or EET bacteria in the intestine may provide novel strategies for modulating cancer immunotherapy.

Abstract Powdery mildew poses a significant threat to wheat crops worldwide, emphasizing the need for durable disease control strategies. The wheat-Dasypyrum villosum T5AL·5 V#4 S and T5DL·5 V#4 S translocation lines carrying powdery mildew resistant gene Pm55 shows developmental-stage and tissue-specific resistance, whereas T5DL·5 V#5 S line carrying Pm5V confers resistance at all stages. Here, we clone Pm55 and Pm5V, and reveal that they are allelic and renamed as Pm55a and Pm55b, respectively. The two Pm55 alleles encode coiled-coil, nucleotide-binding site-leucine-rich repeat (CNL) proteins, conferring broad-spectrum resistance to powdery mildew. However, they interact differently with a linked inhibitor gene, SuPm55 to cause different resistance to wheat powdery mildew. Notably, Pm55 and SuPm55 encode unrelated CNL proteins, and the inactivation of SuPm55 significantly reduces plant fitness. Combining SuPm55/Pm55a and Pm55b in wheat does not result in allele suppression or yield penalty. Our results provide not only insights into the suppression of resistance in wheat, but also a strategy for breeding durable resistance.

Abstract Background Flexible denture base polymers have gained popularity in modern dentistry however, their biofilm formation tendency, adversely affecting the oral tissue heath, remains a concern. Consequently, this study aimed to evaluate surface roughness and biofilm formation tendency of two types of denture base resins manufactured with two techniques before and after surface coating with chlorohexidine (CHX) NPs. Materials and methods Acetal (AC) and Polymethyl-methacrylate (PMMA) resins manufactured by conventional and CAD/CAM methods were shaped into disk (10 X 10 X 1 mm). They were dipped for 8 h and 24 h in colloidal suspension prepared by mixing aqueous solution of CHX digluconate and hexa-metaphosphate (0.01 M). Surface roughness, optical density (OD) of microbial growth media and biofilm formation tendency were evaluated directly after coating. Elutes concentrations of released CHX were evaluated for 19 days using spectrophotometer. Three-way ANOVA and Tukey’s post-hoc statistical analysis were used to assess the outcomes. Results AC CAD/CAM groups showed statistically significant higher roughness before and after coating (54.703 ± 4.32 and 77.58 ± 6.07 nm, respectively). All groups showed significant reduction in OD and biofilm formation tendency after surface coating even after 19 days of CHX NPs release. Conclusions Biofilm formation tendency was highly relevant to surface roughness of tested resins before coating. After CHX NPs coating all tested groups showed significant impact on microbial growth and reduction in biofilm formation tendency with no relation to surface roughness. Significant antimicrobial effect remained even after 19 days of NPs release and specimens storage.

ABSTRACTBackground Supraglottic Airway Devices (SGAs) are designed to counteract the drawbacks of endotracheal intubation. They have proven to be easy to use, robust, versatile, and usable in many difficult situations. This work aims to investigate the use of the Baska Mask (BM) airway and ProSeal™ Laryngeal Mask Airway (PLMA) as SGAs for ventilation.Methods This randomized controlled trial was carried out on 74 cases aged 21–65 years old for elective surgery of a planned duration of up to 2 h during general anaesthesia with intermittent positive pressure ventilation. Cases were divided into two equal groups. Ventilation was done either by BM® Airway (group BM) or PLMA (group PLMA).Results BM had a shorter insertion time and lower leak fraction versus PLMA, while seal pressure elevated significantly with BM versus PLMA (P

This paper presents a model for the optimization of a multi-area distribution grid considering the high penetration levels of photovoltaic (PV) resources and electric vehicle charging station (EVCSs) based on distributed flexible AC transmission system (D-FACTS) devices including on-load tap changer (OLTC) transformers and step voltage regulator (SVR) tap control and shunt capacitor (SC) and shunt reactor (ShR) to reduce losses and voltage deviation. The overarching research aim was to avoid the overvoltage caused by power injection by PV sources and the voltage drop caused by charging EVs in distribution grids. The proposed model was designed based on distribution network load flow and was optimized using a modified particle swarm optimization (M-PSO) algorithm. Two different test networks were tested under different scenarios to analyze the proposed model, revealing the efficiency of the proposed model.

ABSTRACTBackground Melatonin is a pineal gland neuro-hormone influencing the biological regulations of the circadian rhythm. Numerous investigations have revealed variable effects of melatonin in vivo, including anti-inflammatory, antioxidant, sedative, and anxiolytic effects. The effects of using exogenous melatonin as an adjuvant to propofol on the degree of sedation in patients were investigated.Aim We aimed to test the feasibility of melatonin as a sedative agent in traumatic brain injury patients.Methods This research was a double-blinded clinical trial conducted on 38 participants suffering from traumatic brain injuries necessitating sedation and mechanical ventilation. Participants were assigned randomly into two groups. Both groups were sedated by propofol infusion and monitored by bispectral index (BIS). Nineteen patients received 10 mg of melatonin, and 19 patients received a placebo (control). Propofol infusion rate and BIS values were recorded each 30 minutes for 12 hours.Results Exogenous melatonin administration led to a significant decrease in the amount of infused propofol necessary to attain the desired level of sedation. The propofol infusion rates were 4.87 ± 2.91 ml/h in the melatonin group and 6.37 ± 2.87 ml/h in the control group (P- values = 0.001).Conclusion Exogenous melatonin acts as an adjuvant to propofol in sedation, reducing the amount of propofol infusion needed.

AbstractBuilding an oil spill segmentation model is very challenging because of the limited available information on oil spill accidents. Therefore, this paper proposes a custom data generator based on Segmentation Network (Seg-Net) model implemented in Conditional Generative Adversarial Network (CGAN). The proposed model is trained for oil spill segmentation using 50 Sentinal-1 Synthetic Aperture Radar (SAR) images. The proposed model employs a modified Seg-Net as a generator to produce high-quality oil spills’ images and a Patch-GAN as discriminator. This architecture results in a significant improvement of the final oil segmentation results, in comparison with Seg-Net model, while using relatively small training dataset. For performance assessment, the paper presents the oil spills segmentation results of four suggested models using Sentinel-1 SAR images. The presented models are U-Net, Seg-Net, CGAN, and a Seg-Net-based CGAN the performance assessment reveals that the proposed model produces oil spill segmentation images with an average accuracy of 99.04%, Intersection over Union (IoU) index of 96.59%, and a precision of 85.24%. In addition, the training time required for the proposed model is 3 h 20 min per 50 epochs, while it is nearly 10 h and 55 min for training a CGAN model.

Masked face recognition (MFR) has emerged as a critical domain in biometric identification, especially with the global COVID-19 pandemic, which introduced widespread face masks. This survey paper presents a comprehensive analysis of the challenges and advancements in recognizing and detecting individuals with masked faces, which has seen innovative shifts due to the necessity of adapting to new societal norms. Advanced through deep learning techniques, MFR, along with face mask recognition (FMR) and face unmasking (FU), represents significant areas of focus. These methods address unique challenges posed by obscured facial features, from fully to partially covered faces. Our comprehensive review explores the various deep learning-based methodologies developed for MFR, FMR, and FU, highlighting their distinctive challenges and the solutions proposed to overcome them. Additionally, we explore benchmark datasets and evaluation metrics specifically tailored for assessing performance in MFR research. The survey also discusses the substantial obstacles still facing researchers in this field and proposes future directions for the ongoing development of more robust and effective masked face recognition systems. This paper serves as an invaluable resource for researchers and practitioners, offering insights into the evolving landscape of face recognition technologies in the face of global health crises and beyond.