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Abstract Insider threats pose a significant challenge to IT security, particularly with the rise of generative AI technologies, which can create convincing fake user profiles and mimic legitimate behaviors. Traditional intrusion detection systems struggle to differentiate between real and AI-generated activities, creating vulnerabilities in detecting malicious insiders. To address this challenge, this paper introduces a novel Deep Synthesis Insider Intrusion Detection (DS-IID) model. The model employs deep feature synthesis to automatically generate detailed user profiles from event data and utilizes binary deep learning for accurate threat identification. The DS-IID model addresses three key issues: it (i) detects malicious insiders using supervised learning, (ii) evaluates the effectiveness of generative algorithms in replicating real user profiles, and (iii) distinguishes between real and synthetic abnormal user profiles. To handle imbalanced data, the model uses on-the-fly weighted random sampling. Tested on the CERT insider threat dataset, the DS-IID achieved 97% accuracy and an AUC of 0.99. Moreover, the model demonstrates strong performance in differentiating real from AI-generated (synthetic) threats, achieving over 99% accuracy on optimally generated data. While primarily evaluated on synthetic datasets, the high accuracy of the DS-IID model suggests its potential as a valuable tool for real-world cybersecurity applications.

Abstract Desiccation tolerance is a complex phenomenon observed in the lichen Flavoparmelia ceparata. To understand the reactivation process of desiccated thalli, completely dried samples were rehydrated. The rehydration process of this lichen occurs in two phases. The first phase, characterized by rapid rehydration, involves the conversion of non-functional reaction centers (RCs) into functional PSII RCs, and the accumulation of ROS along with the increment in SOD antioxidant enzyme. These coordinated mechanisms initiate the light reaction of photosynthesis by forming active light-harvesting complexes (LHCs). This adaptation ensures efficient recovery, as evidenced by specific energy fluxes (ABS/RC, TR/RC, ET/RC, and DI/RC), phenomenological fluxes (ABS/CS, TR/CS, ET/CS, and DI/CS), quantum efficiencies (ФP0, ФE0, and ФD0), primary and secondary photochemistry, photochemical and non-photochemical quenching, and performance index, highlighting the essential role of rapid water uptake in restoring turgor pressure for cell structure and function maintenance. The interconnected network of antioxidant defenses, including catalase (CAT) and peroxidase (POD), underscores the plant's ability to cope with oxidative stress during resilience. The acid phosphomonoesterase (PME) enzymatic activity corresponds to its role in releasing phosphate for essential cellular functions and post-rehydration thallus growth. The activity of CAT, GPOD, and PME signifies the gradual reactivation of lichen F. caperata. Moreover, the investigation into chlorophyll a fluorescence emphasizes the efficient reactivation of the photosynthetic process in F. caperata. In conclusion, lichen F. caperata demonstrates significant potential for desiccation tolerance through the rapid transformation of chloroplasts, chlorophylls, and PSII RCs from their inactive to active states upon rehydration. This research not only enhances our understanding of desiccation tolerance in resurrection plants but also highlights the importance of lichens, particularly F. caperata, as valuable models for studying plant resilience in challenging environments.

Background: Short-term blood pressure variability (BPV) has been associated with adverse cardiovascular outcomes, but its impact on left atrium (LA) function and structure remains unclear. This study aims to explore the relationship between short-term BPV and LA function in patients with controlled and uncontrolled hypertension, using speckle-tracking echocardiography (STE). Methods: In this cross-sectional study, 150 hypertensive patients were recruited and categorized into controlled and uncontrolled hypertension groups based on ambulatory blood pressure (BP) monitoring. BPV was calculated from 24-h ambulatory BP recordings, and LA function was assessed using STE to measure LA volume, strain, and strain rate parameters. Univariate and multivariate analyses were performed to investigate associations between BPV and LA functions. Results: Higher short-term BPV was significantly associated with impaired LA function, including reduced LA strain and increased LA volume index, in both hypertensive groups. After adjusting for confounding factors such as age, body mass index, and duration of hypertension, BPV remained an independent predictor of LA dysfunction (P < 0.01). The relationship was more pronounced in the uncontrolled hypertension group. Conclusion: Short-term BPV is independently associated with left atrial dysfunction in hypertensive patients, particularly in those with uncontrolled hypertension. These findings suggest that BPV could serve as a potential marker for early left atrial remodeling in hypertensive populations, providing insights for better risk stratification and management.

Abstract Local haemodynamics control arterial homeostasis and dysfunction by generating wall shear stress (WSS) which regulates endothelial cell (EC) physiology. Here we use a zebrafish model to identify genes that regulate EC proliferation in response to flow. Suppression of blood flow in zebrafish embryos (by targeting cardiac troponin) reduced EC proliferation in the intersegmental vessels (ISVs) compared to controls exposed to flow. The expression of candidate regulators of proliferation was analysed in EC isolated from zebrafish embryos by qRT-PCR. Genes shown to be expressed in EC were analysed for the ability to regulate proliferation in zebrafish vasculature exposed to flow or no-flow conditions using a knockdown approach. wnk1 negatively regulated proliferation in no-flow conditions, whereas fzd5, gsk3β, trpm7 and bmp2a promoted proliferation in EC exposed to flow. Immunofluorescent staining of mammalian arteries revealed that WNK1 is expressed at sites of low WSS in the murine aorta, and in EC overlying human atherosclerotic plaques. We conclude that WNK1 is expressed in EC at sites of low WSS and in diseased arteries and may influence vascular homeostasis by reducing EC proliferation.

Abstract Nowadays, climate change is the primary factor shaping the future of food and nutritional security. To investigate the interactive effects of various climate variables on photosynthetic efficiency, an experiment was conducted using 10 dryland wheat genotypes. These genotypes were exposed to different conditions: temperatures of 25 ± 3 °C and 34 ± 3 °C, carbon dioxide concentrations of 380 ± 50 ppm and 800 ± 50 ppm, and irrigation regimes of 50% field capacity and well-watered. Our results indicated that the wheat genotypes responded differently to both individual and combined climate stress factors. The traditional winter wheat genotype *Sardari*, along with the newly developed dryland wheat genotype *Ivan*, exhibited resilience to anticipated climate conditions. This resilience was reflected in enhancements in photochemical quantum efficiency parameters (Y(II), qP, and qL) under combined stress conditions. Resilient genotypes demonstrated superior regulation of the stomatal conductance (GS) and electron transport rate (ETR) under elevated temperature and CO2 levels. Principal component analysis (PCA) revealed significant correlations between chlorophyll fluorescence parameters and climate factors, such as NPQ with temperature, Y(NO) with CO2, qL in response to drought stress, and both qP and Y(II) with the interactions among temperature, CO2, and drought stress. Elevated CO2 reduced the ETR and GS across all genotypes. Our findings underscore the importance of assessing not only fundamental chlorophyll fluorescence parameters like Fm and Fo but also the efficiency of NPQ and Y(II) to understand climate change impacts on dryland wheat genotypes. We suggest that these parameters could serve as valuable biomarkers for breeding programs aimed at improving plant adaptation to future dryland climate conditions.

Abstract Background This study examines the effects of various complementary light spectra on the growth, development, antioxidant activity, and nutrient absorption in strawberry plants under stress conditions. Light-emitting diodes (LEDs) were used to provide specific wavelengths, including monochromatic blue (460 nm), monochromatic red (660 nm), a dichromatic mix of blue and red (1:3 ratio), full-spectrum white light (400–700 nm), and ambient light as a control (no LED treatment). The stress treatments applied were: control (no stress), salinity (80 mM NaCl), alkalinity (40 mM NaHCO₃), and a combined salinity/alkalinity condition. Results Our results indicated that complementary light spectra, especially red and blue/red, helped mitigate the adverse effects of stress on plant growth and development. These spectra improved plant tolerance by enhancing the activity of polyphenol oxidase and peroxidase enzymes and increasing starch accumulation in the leaves. Furthermore, under stress conditions, red and blue-red light significantly boosted fruit anthocyanin levels. Although stress elevated antioxidant activity, supplementary light reduced this activity by alleviating stress compared to ambient light. While stress led to increased Na and Cl ion concentrations in leaves, treatments with blue, red, and blue-red light minimized these harmful effects and promoted the absorption of beneficial ions such as K, Mg, Fe, and Cu. Conclusions Adjusting light quality significantly influences the morphology and physiology of strawberry plants, underscoring the role of specific light spectra in promoting optimal growth under stress conditions. Clinical trial number Not applicable

Abstract Early detection of COVID-19 improves the chance of recovery and helps identify high-risk patients. Our study aimed to statistically predict the time to improvement with the admission data of COVID-19 patients. Methods: Our prospective cohort study occurred between January and September 2022 at Alexandria University Hospital’s outpatient clinic and isolation department. We enrolled 43 patients after assessing their eligibility and collecting their baseline data. Results: The mean age was 34.8 years (± 12.3). Most of them were females (65.1%). The mean of oxygen saturation was 95.2% (± 2.8). We used linear regression to predict how long it would take to improve [time to improvement (days) = 1.186*P (mmol/L) + 0.010*IL-10 (pg/mL)]. Its diagnostic performance was 0.723 (95% CI: 0.552–0.894), and it was accurate at predicting improvement within a week but not at longer delays; additionally, its positive and negative predictive values were 56.3% and 85.2%, respectively. Conclusion: We recommend monitoring phosphorus and interleukin-10 levels. The time-to-improvement delay negatively correlated with a reduction in baseline oxygen saturation upon admission. Additionally, for every 0.84 meq/L increase in phosphorus or 100 pg/mL increase in interleukin-10, there was a 1-day delay provided that the other was constant, with a coefficient of determination of 85.9%.

Genetic diversity, heritability, and genetic advance are crucial considerations in the field of plant breeding. This research aimed to evaluate these factors for traits related to yield in faba bean (Vicia faba L.), specifically focusing on the F3 and F4 generations resulting from the cross between ‘Sakha 3’ and ‘Nubaria 3’. In the initial season (2021/ 2022), 200 families from each F3 population were cultivated with specific spacing, and selection criteria included seed yield per plant (SYP) and the number of pods per plant (NPP). Top-performing plants were identified for the second cycle of pedigree selection. In the following season (2022/2023), the F4 families were arranged in a randomised complete block design. Traits like the number of branches per plant (NBP), NPP, SYP, and seed index (SI) showed substantial phenotypic and genotypic coefficients of variation, indicating their noteworthy variation. Phenotypic and genotypic correlation analyses showed positive associations between SYP and the NBP and NPP. Additionally, path coefficient analysis indicated that these traits had high positive direct effects on SYP. This research provides valuable insights into the genetic variability, heritability, and selection parameters for yield-related traits in faba bean, offering a foundation for future breeding programs aimed at improving yield and productivity.

Abstract In order to increase the likelihood of obtaining treatment and achieving a complete recovery, early illness identification and diagnosis are crucial. Artificial intelligence is helpful with this process by allowing us to rapidly start the necessary protocol for treatment in the early stages of disease development. Artificial intelligence is a major contributor to the improvement of medical treatment for patients. In order to prevent and foresee this problem on the individual, family, and generational levels, Monitoring the patient's therapy and recovery is crucial. This study's objective is to outline a non-invasive method for using mammograms to detect breast abnormalities, classify breast disorders, and identify cancerous or benign tumor tissue in the breast. We used classification models on a dataset that has been pre-processed so that the number of samples is balanced, unlike previous work on the same dataset. Identifying cancerous or benign breast tissue requires the use of supervised learning techniques and algorithms, such as random forest (RF) and decision tree (DT) classifiers, to examine up to thirty features, such as breast size, mass, diameter, circumference, and the nature of the tumor (solid or cystic). To ascertain if the tissue is malignant or benign, the examination's findings are employed. These features are mostly what determines how effectively anything may be categorized. The DT classifier was able to get a score of 95.32%, while the RF satisfied a far higher 98.83 percent.

Background: The liver is crucial for maintaining normal metabolism in the body. Various substances, such as toxic chemicals, drugs, and alcohol, can damage hepatocyte cells, leading to metabolic imbalances. Aim: The experiment aimed to determine the efficacy of Lagenaria siceraria seed oil (LSS) as a hepatoprotective agent against acute hepatotoxicity triggered by carbon tetrachloride (CCl4). Methods: A total of 20 rats were randomly separated into four groups. The control group: rats received 2 ml of distilled water orally, followed by 1.25 ml of olive oil intraperitoneally (i.p.) after 30 minutes. CCL4 group: rats were given a single intraperitoneal dose of 1.25 ml/kg b.w. of CCl4 in a 1:1 mixture with olive oil. Silymarin group: received 100 mg of silymarin per kg of b.w. diluted in 2 ml of distilled water orally, followed by CCl4 treatment after 30 minutes. LSS oil group: received LSS oil at 3g/kg b.w. orally, followed by CCl4 treatment after 30 minutes. Blood samples were collected to assess liver enzymes (AST, ALT and ALP), proteins and bilirubin fractions, and redox status (catalase, reduced glutathione (GSH), and malondialdehyde (MDA)) were assessed in hepatic tissues. Changes in liver histopathological examination were also evaluated. Results: In CCl4-treated rats, there was a significant increase in serum liver marker enzyme activity (ALP, AST and ALT) along with a significant elevation (p < 0.05) in total bilirubin, indirect bilirubin, and direct bilirubin compared to the control rats. However, all these parameters decreased in the CCl4+ Silymarin and CCl4+LSS groups compared to CCl4-treated rats. There was a significant decline in total protein level and serum albumin in all experimental groups compared to the control, while globulin levels significantly increased in all experimental groups. There was a significant (p < 0.05) reduction in the level of GSH and catalase, with an increase in MDA level in CCl4 rats compared to other rats. Histopathological investigation of the LSS-treated group showed a hepatoprotective effect against CCl4. Conclusion: The study revealed that LSS oil has antioxidant activity against CCl4-induced toxicity. [Open Vet J 2024; 14(8.000): 2016-2028]

Abstract Infectious coryza (IC) is an acute upper respiratory disease of chicken caused by Avibacterium (A.) paragallinarum. This disease results in an increased culling rate in meat chicken and a marked decrease in egg production (10% to more than 40%) in laying and breeding hens. Vaccines were first used against IC and effectively controlled the disease. Nanotechnology provides an excellent way to develop a new generation of vaccines. NPs have been widely used in vaccine design as adjuvants and antigen delivery vehicles and as antibacterial agents; thus, they can be used as inactivators for bacterial culture. In this research, the antibacterial effects of several nanoparticles (NPs), such as silicon dioxide with chitosan (SiO2-CS), oleoyl-chitosan (O.CS), silicon dioxide (SiO2), and iron oxide (Fe3O4), on A. paragallinarum were studied. Additionally, different A. paragallinarum vaccines were made using the same nanomaterials at a concentration of 400 µg/ml to help control infectious coryza disease in chicken. A concentration of 400 µg/ml of all the NPs tested was the best concentration for the inactivation of A. paragallinarum. Additionally, this study showed that the infectious coryza vaccine adjuvanted with SiO2 NPs had the highest immune response, followed by the infectious coryza vaccine adjuvanted with Fe3O4 NPs, the infectious coryza vaccine adjuvanted with SiO2-CS NPs, and the infectious coryza vaccine adjuvanted with O.CS NPs in comparison with the infectious coryza vaccine adjuvanted with liquid paraffin (a commercial vaccine).

Background: Doxorubicin (DOX) is a chemotherapeutic drug applied clinically for the remedy of cancer, but its possibly life-threatening cardiotoxicity effects remain a concern. Aim: After that, this study evaluates the cardioprotective impacts of Lagenaria siceraria (LSS) oil on doxorubicin-induced cardiomyopathy in rats. Methods: Wistar male rats (n= 28, weighting 190-210 g) were arbitrarily allocated into four equal groups. Group 1 (CTR) received normal saline orally (1 ml/kg); group 2 (DOX) received DOX (10 mg/kg); group 3 (DOLS) received DOX + 3g of Lagenaria siceraria seeds oil/kg and group 4 (LSSO) received Lagenaria siceraria seeds oil (3 g/kg) daily for 18 days. The serum samples were collected to determine the creatine kinase-MB (CK-MB) isoenzyme, lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and Troponin I activity. At the same time, the catalase, malondialdehyde (MDA), and reduced glutathione (GSH) were assessed in heart tissues. Additionally, histopathological investigations for the heart tissue were performed. Results: Results revealed no significant change in CK-MB levels between the DOLS group compared to the CTR group (p>0.05). DOX group confirmed a substantial increase in AST, LDH, and Troponin1 serum levels compared to DOLS and LLSO groups (p [Open Vet J 2024; 14(7.000): 1668-1676]

Railway infrastructure plays a critical role in transportation networks, and ensuring its integrity and resilience is of utmost importance. Culverts are vital components of railway tracks, providing drainage and water management to prevent structural damage and disruptions. Identifying suitable locations for culverts requires careful evaluation and consideration of various factors. A study using GIS techniques was conducted on an existing commercial railway track in the Eastern Desert of Upper Egypt to assess the effectiveness of existing culverts in preventing flash floods. The culvert suitability index map revealed that areas with high slopes and large drainage areas were more susceptible to water accumulation, indicating the need for culverts. The study also highlighted areas where culverts could be installed without significantly impacting existing infrastructure. It was recommended to install culverts in 27 locations along the track where they intersect with watercourses. Existing culverts covered just 93 watercourses, while 5 specialized culverts needed to be relocated. The findings have significant implications for railway engineering, as using GIS techniques streamlines the process of culvert location evaluation, saving time and resources. The systematic approach ensures culverts are installed in the most appropriate locations, minimizing flooding risks and ensuring the safety and efficiency of railway operations. HIGHLIGHT The research aims to develop a GIS-based methodology for assessing culvert locations on Egyptian railways, specifically the Qena–Safaga Track. The methodology aims to improve decision-making and infrastructure development by enhancing efficiency and accuracy. It addresses traditional methods and uses GIS techniques for railway engineering.;

Abstract Background This study explores the impact of various light spectra on the photosynthetic performance of strawberry plants subjected to salinity, alkalinity, and combined salinity/alkalinity stress. We employed supplemental lighting through Light-emitting Diodes (LEDs) with specific wavelengths: monochromatic blue (460 nm), monochromatic red (660 nm), dichromatic blue/red (1:3 ratio), and white/yellow (400–700 nm), all at an intensity of 200 µmol m-2 S-1. Additionally, a control group (ambient light) without LED treatment was included in the study. The tested experimental variants were: optimal growth conditions (control), alkalinity (40 mM NaHCO3), salinity (80 mM NaCl), and a combination of salinity/alkalinity. Results The results revealed a notable decrease in photosynthetic efficiency under both salinity and alkalinity stresses, especially when these stresses were combined, in comparison to the no-stress condition. However, the application of supplemental lighting, particularly with the red and blue/red spectra, mitigated the adverse effects of stress. The imposed stress conditions had a detrimental impact on both gas exchange parameters and photosynthetic efficiency of the plants. In contrast, treatments involving blue, red, and blue/red light exhibited a beneficial effect on photosynthetic efficiency compared to other lighting conditions. Further analysis of JIP-test parameters confirmed that these specific light treatments significantly ameliorated the stress impacts. Conclusions In summary, the utilization of blue, red, and blue/red light spectra has the potential to enhance plant resilience in the face of salinity and alkalinity stresses. This discovery presents a promising strategy for cultivating plants in anticipation of future challenging environmental conditions.

This paper presents a neutrosophic inference model for bioinformatics. The model is used to develop a system for accurate comparisons of human nucleic acids, where the new nucleic acid is compared to a database of old nucleic acids. The comparisons are analyzed in terms of accuracy, certainty, uncertainty, neutrality, andbias. The proposed system achieves good results and provides a reliable standard for future comparisons. It highlights the potential of neutrosophic inference models in bioinformatics applications. Data mining and bioinformatics play a crucial role in computational biology, with applications in scientific research and industrial development. Biological analysts rely on specialized tools and algorithms to collect, store, categorize, and analyze large volumes of unstructured data. Data mining techniques are used to extract valuable information from this data, aiding in the development of new therapies and understanding genetic relationships between organisms. Recent advancements in bioinformatics include gene expression tools, Bio sequencing, and Bio databases, which facilitate the extraction and analysis of vital biological information. These technologies contribute to the analysis of big data, identification of key bioinformatics insights, and generation of new biological knowledge. Data collection, analysis, and interpretation in this field involvesthe use of modern technologies such as cloud computing, machine learning, and artificial intelligence, enabling more efficient and accurate results. Ultimately, data mining and bioinformatics enhance our understanding of genetic relationships, aid in developing new therapies, and improve healthcare outcomes.

Let $ N = \left\{{n}_{1}, {n}_{2}, \;\dots , {n}_{k}\right\} $ be a finite set of positive numbers. The problem of finding the minimal number of additions required to compute all elements of N starting from 1 (called the addition sequence problem) is NP-complete. It is equivalent to finding the minimum number of multiplications needed to compute a group exponentiation $ {g}^{{n}_{1}}, {g}^{{n}_{2}}, \;\dots , {g}^{{n}_{k}} $, where g is an element in a group. This paper aims to propose a new metaheuristic algorithm using a simulated annealing strategy to generate a short addition sequence. The performance of the proposed algorithm is measured by considering two parameters: The size of N and the domain of $ {n}_{\mathrm{i}}, 1\le i\le k $. The proposed algorithm is a new trade-off between the length of the generated addition sequence and the average running time of generating addition sequences. It sometimes produces longer addition sequences than exact algorithms that are slower, and it is slower than suboptimal algorithms that produce longer addition sequences.

Ribonucleic acid (RNA) structure alignment is an important problem in computational biology to identify structural similarity of RNAs. Obtaining an efficient method for this problem is challenging due to the high computational time for the optimal solution and the low accuracy of a heuristic solution. In this paper, an efficient algorithm is proposed based on a mathematical model called longest arc-preserving common subsequence. The proposed algorithm uses a heuristic technique and high-performance computing to optimize the solution of RNA structure alignment, both in terms of the running time and the accuracy of the output. Extensive experimental studies on a multicore system are conducted to show the effectiveness of the proposed algorithm on two types of data. The first is simulated data that consists of 450 comparisons of RNA structures, while the second is real biological data that consists of 357 comparisons of RNA structures. The results show that the proposed algorithm outperforms the best-known heuristic algorithm in terms of execution time, with a percentage improvement of 71% and increasing the length of the output, i.e., accuracy, by approximately 45% in all studied cases. Finally, future approaches are discussed.

Abstract Background This study aimed to develop a vaccine for controlling salmonellosis, a zoonotic disease affecting both humans and chicken, by employing Fe2O3 ferrous iron oxide (FNPs), silicon dioxide (SiNPs), carboxymethyl chitosan (C.CS NPs), and FNPs-chitosan (FCNPs) nanocomposite as immunological adjuvants. The immune response of vaccinated chicken was assessed through ELISA and challenge tests. Results The hydrodynamic diameters of Fe2O3, Fe2O3-CS, C.CS, and SiO2 NPs were found to be 81.95 ± 14.95, 137.1 ± 20.5, 32.86 ± 14.05, and 15.64 ± 3.6 nm, respectively. The incorporation of nanoparticles into the vaccine formulation significantly enhanced its efficacy by eliciting a robust immune response. According to the study, FNPs, SiNPs, C.CS NPs, and FCNPs can be used as immunological adjuvants to strengthen chicken’s immune systems and help prevent salmonellosis. By gradually raising antibody titers, all five vaccine formulations successfully stimulated an immunological response against Salmonella in vaccinated chicken. The size of the immunological response, however, differed amongst the various vaccination formulations. The SiNPs group had the highest antibody titer, followed by the locally administered vaccine. Conclusions These findings suggest that the use of silicon dioxide SiNPs as a vaccine delivery system could enhance the immune response to Salmonella in chicken. Overall, the study demonstrates that the use of adjuvanted vaccines with nanomaterials, particularly SiNPs, has significantly increased the protection rate from 67 to 93.3% when compared to the locally used vaccine, which had a protection rate of 83%.

Abstract This study proposed a novel technique for early diabetes prediction with high accuracy. Recently, Deep Learning (DL) has been proven to be expeditious in the diagnosis of diabetes. The supported model is constructed by implementing ten hidden layers and a multitude of epochs using the Deep Neural Network (DNN)-based multi-layer perceptron (MLP) algorithm. We proceeded to meticulously fine-tune the hyperparameters within the fully automated DL architecture to optimize data preprocessing, prediction, and classification using a novel dataset of Mansoura University Children's Hospital Diabetes (MUCHD), which allowed for a comprehensive evaluation of the system’s performance. The system was validated and tested using a sample of 548 patients, each with 18 significant features. Various validation metrics were employed to ensure the reliability of the results using cross-validation approaches with various statistical measures of accuracy, F-score, precision, sensitivity, specificity, and Dice similarity coefficient. The high performance of the proposed system can help clinicians accurately diagnose diabetes, with a remarkable accuracy rate of 99.8%. According to our analysis, implementing this method results in a noteworthy increase of 0.39% in the overall system performance compared to the current state-of-the-art methods. Therefore, we recommend using this method to predict diabetes.

Abstract Background Left atrial global longitudinal strain (LA GLS) has been used as a new assessment tool for left atrial function. This article aims to investigate the effect of balloon mitral valvuloplasty (BMV) in patients with severe rheumatic mitral stenosis on LA GLS and its relation to the mitral valve area achieved after the procedure. The study included 95 patients with severe mitral stenosis who fulfilled the criteria for BMV (case group) and 80 normal healthy subjects (control group). All included participants underwent complete echocardiographic examinations. For the case group, LA GLS was assessed by 2D speckle-tracking Echocardiography before valvuloplasty, immediately after, within 24 h, at 6 months, and at 12 months, and the results were compared. Results The impaired left-atrium strain in patients with severe mitral stenosis was improved immediately after BMV, and the improvement continued at 6 and 12 months post-BMV (23.1% ± 4.2 vs. 36.0% ± 4.9, 36.2% ± 4.5, and 40.1% ± 9.5, respectively p

Abstract The paper is a study of risk assessment posed by trees in selected urban woodlands (urban forests) of Warsaw. Two groups of trees were analysed and compared: exhibiting signs of maturity and ageing (hollow-bearing trees with open or hidden cavities and/or caries) and with no signs of decay. 373 individual trees growing near routes frequently or continuously used for recreational purposes were examined using Roloff's vitality classification, and tree risk assessment method, complemented by instrumental studies: a resistance resistograph, pulling tests, and sonic tomography (SoT). The collected data was analysed using the Chi-square test. The results indicate that it is not possible to conclude unequivocally that the presence of hollows in aged trees significantly increases the risk of falling. According to the safety factor results from the SoT and pulling tests, no correlation was demonstrated between the presence of hollow trees and an increase in risk class. The highest proportion of hollow trees (89.42%) was in the low risk group for trunk fracture and uprooting. The results also indicate the coherence of the diagnostic methods to be necessary for providing sufficient information to assess the statics and, ultimately, as our study showed, the protection of hollow trees.

The efficiency of most cancer therapies and antibiotics is restricted due to several issues, including medication resistance and non-specific negative effects. Hydrogels based on graphene derivative and silver nano-particles (Ag-NPs) have been employed to overcome these limitations. In this manuscript, we synthesized gelatin methacryloyl (Gel-MA) to combine with functional nano-materials. Reduced graphene oxide (rGO) was synthesized by utilising ascorbic acid as a green reductant to form a composite with Gel-MA without affecting its unique characteristics. The prepared rGO and nano-composite hydrogels were characterized by the usual characteristic spectroscopic techniques. We found that the nano-composite swelled up to 2444% due to the high porosity of the hydrogel. The results demonstrated that the nanocomposite hydrogel showed higher antimicrobial activities than virgin (Gel-MA). The cytotoxicity of Gel-MA/rGO and Gel-MA/rGO/Ag composites against human lung cancer (A549) cells was evaluated using MTT assay. The Gel-MA/rGO/Ag composite showed remarkable cytotoxicity with an IC50 of 27µg/ml towards A549 cells compared with 109µg/ml of Gel-MA/rGO.

While most children with epilepsy find their seizures manageable through medication, some continue to experience seizures despite trying multiple drugs. Failure of medical treatment often becomes apparent early on, and for these cases, it is advisable to seek further treatment options at a specialized epilepsy center. Such centers offer additional treatments like epilepsy surgery, vagus nerve stimulation, and ketogenic diets. There is no universal definition for what constitutes “medically intractable” epilepsy. A proposal by a task force from the International League Against Epilepsy suggests that drug-resistant epilepsy could be defined as the inability to control seizures even after two adequate treatment attempts with well-chosen and tolerated medications, either alone or in combination. In this review, the authors discussed the management of intractable epilepsy in children.

The depletion of natural resources such as freshwater and cropland makes it necessary to find a new solution for sustainable food production. Aquaponic systems seem to be a great alternative to traditional agriculture, however, there are still many unknowns that need to be explored. It is already known how fish stocking affects water quality in aquaponic systems, but not how it affects the plants’ growth, and especially on chlorophyll fluorescence. In this study, we examined how the density of 0, 2, 4, 8, and 16 stocking fish in five aquaria affects lettuce growth. The first tank was only a hydroponic system with plants but without fish (control). In the remaining four aquaria – 2, 4, 8 and 12 specimens of common carp fry with an average weight of 20 grams (average 8.5–33.2 g) were placed in the aquaponic growing system. Physicochemical analysis of water was conducted to determine the levels of pH, electrical conductivity ( EC), N-NO 3, N-NO 2, N-NH 4, P-PO 4, O 2 and physiological parameters of plants (nitrogen balance index – NBI, chlorophyll content index – CCI, quantum yield – QY, flavonoid content – Flv) were analysed. The results showed that fish stocking density has different effects on plant physiological parameters, but in most cases, was insignificant. It seems that the greater number of fishes and higher density indirectly causes growth inhibition (lower photosynthetic efficiency) due to the increase of N-NO 3 and a decrease of O 2 in the water.

Abstract Peppermint has gained a promising status due to the presence of a high proportion of bioactive compounds, especially menthol. Due to its pharmacological efficacy, the demand for its plant-based bioactive compounds necessitates its cultivation worldwide. Brassinosteroids are polyhydroxylated sterol derivatives that regulate diverse processes and control many agronomic traits during plant growth and development. A factorial randomised pot experiment was performed in the net house to investigate the effect of 24-Epibrassinolide (EBL) on the growth, physiology, essential oil content, stomatal behaviour and trichome development of the three cultivars of peppermint. Four levels of foliage-applied EBL, viz. 0, 10–5, 10–6 and 10–7 M were applied to the three cultivars of peppermint (Kukrail, Pranjal and Tushar). Among the different treatments of EBL, the application of 10–6 M increased shoot length by 38.84, 37.59 and 36.91%, root length by 36.73, 29.44 and 33.47%, chlorophyll content by 24.20, 22.48 and 23.32%, P N by 32.88, 32.61 and 33.61%, EO content by 32.72, 30.00 and 28.84%, EO yield per plant by 66.66, 77.77 and 73.33% and menthol yield per plant by 127.27, 110 and 118.18% in Kukrail, Tushar and Pranjal respectively, compared with their respective control plants. Further, the 10–6 M EBL exhibited improved trichome size and density, cellular viability and menthol content of the oil analysed from scanning electron microscopy, confocal laser scanning microscopy and GC–MS respectively as compared to the control. In conclusion, out of different levels of EBL, two sprays of 10–6 M EBL proved effective in enhancing the morphophysiological features and productivity of mint plants, particularly for cultivar Kukrail.

Introduction: Chest imaging plays a prominent role in the assessment of patients with blunt trauma. Selection of the right approach at the right time is fundamental in the management of patients with blunt chest trauma.[1] A reliable, economic, bedside, and rapidly accomplished screening test can be pivotal. [2] Objective: The aim of this study was to compare the accuracy of extended- focused assessment with sonography for trauma (E-FAST) to that of the National Emergency X-Radiography Utilisation Study (NEXUS) chest algorithm in detecting blunt chest injuries. Methods: This descriptive cross-sectional study included 50 polytrauma patients with blunt chest trauma from the emergency centre of Suez Canal University Hospital. E-FAST and computed tomography (CT) were conducted, followed by reporting of NEXUS criteria for all patients. Blinding of the E-FAST performer and CT reporter were confirmed. The results of both the NEXUS algorithm and E-FAST were compared with CT chest results. Results: The NEXUS algorithm had 100% sensitivity and 15.3% specificity, and E-FAST had 70% sensitivity and 96.7% specificity, in the detection of pneumothorax.In the detection of hemothorax, the sensitivity and specificity of the NEXUS algorithm were 90% and 7.5%, respectively, whereas E-FAST had a lower sensitivity of 80% and a higher specificity of 97.5%. Conclusion: E-FAST is highly specific for the detection of hemothorax, pneumothorax, and chest injuries compared with the NEXUS chest algorithm, which demonstrated the lowest specificity. However, the NEXUS chest algorithm showed a higher sensitivity than E-FAST and hence can be used effectively to rule out thoracic injury.

Abstract This study aimed to provide a national estimate of the prevalence of the high risk of autism spectrum disorder (ASD) and their determinants. A national screening survey was conducted for 41,640 Egyptian children aged 1 to 12 years in two phases. Tools used were Vineland's Adaptive Behavior Scales, Modified Checklist for Autism in Toddlers, Gilliam Autism Rating scale, and Denver II Developmental screening test. The overall prevalence of children at high risk of ASD was 3.3% (95% CI:3.1%–3.5%). Children living without mothers in homes, suffered from convulsions (AOR = 3.67; 95%CI:2.8–4.8), a history of cyanosis after birth (AOR = 1.87; 95% CI:1.35–2.59) or history of LBW babies (AOR = 1.53; 95% CI:1.23–1.89) carried higher odds of being at high risk of ASD.

Abstract Considering the potential use of nanomaterials, particularly carbon-based nanostructures, in agriculture, we conducted a study to investigate the effect of graphene oxide (GO) on strawberry plants under salinity and alkalinity stress conditions. We used GO concentrations of 0, 2.5, 5, 10, and 50 mg/L, and applied stress treatments at three levels: without stress, salinity (80 mM NaCl), and alkalinity (40 mM NaHCO3). Our results indicate that both salinity and alkalinity stress negatively impacted the gas exchange parameters of the strawberry plants. However, the application of GO significantly improved these parameters. Specifically, GO increased PI, Fv, Fm, and RE0/RC parameters, as well as chlorophyll and carotenoid contents in the plants. Moreover, the use of GO significantly increased the early yield and dry weight of leaves and roots. Therefore, it can be concluded that the application of GO can enhance the photosynthetic performance of strawberry plants, and improve their resistance to stress conditions.

Abstract Perennial ryegrass is a grass species used to establish lawns in urban areas where pollution is a major environmental problems. Cadmium (Cd) and nickel (Ni) contribute significantly to these pollutants and may cause photosynthetic limitation. The main objective of this work was to perform a comprehensive analysis of photosynthetic efficiency of perennial ryegrass seedlings under Cd and Ni stress. Some of the main indices of photosynthetic efficiency (prompt and delayed chlorophyll-a fluorescence signals and modulated reflectance at 820 nm) were compared with growth parameters. Two cultivars were tested: 'Niga' and 'Nira'. A decrease in photosystem (PS) II and PSI activity was observed. This was due to an increase in nonradiative dissipation of the PSII antenna, a decrease in PSII antenna size, or a decrease in the number of photosynthetic complexes with fully closed PSII RCs. Efficiency of electron transport was decreased. The effect on the modulated reflectance signal could indicate a restriction in electron flow from PSII to PSI. The correlation between photosynthetic efficiency parameters, such as Area, Fo, Fm, and Fv, and growth parameters, confirmed that some photosynthetic efficiency parameters can be used as indicators for early detection of heavy metal effects.

Abstract Background Chronic neck and back pain are among the most commonly encountered health problems in neurosurgical practice. Many cases fail prolonged pharmacological and physical therapy and are not proper candidates for surgical interventions, or had refused proposed surgical treatment. Objective To provide an informative critical summary of the literature about the topic of interventional management of axial neck and low back pain and highlighting the new trends and pieces of evidence. Methods The English literature published over the last two decades was reviewed by the author for recent and relevant data about the principles of interventional management of chronic neck and low back pain. A PubMed search was performed through phrase searching and combined searching using Boolean operators. The articles thought to be most relevant to the study aim and the neurosurgeons’ practice were extracted. Results Neck and low back pain continue to be among the most common musculoskeletal health problems and the most common cause of disability worldwide. A detailed understanding of relevant spine anatomy is crucial for interventionists who should deal with the concept of “functional spine unit” with multiple potential pain generators. Chronic spinal pain is best managed through a dedicated multidisciplinary team in well-equipped healthcare facilities. An algorithmic approach for the diagnosis and management of spinal pain is the mainstay of providing the best patient care and should be based on the commonality and treatability of pain generators, values of patients and available resources. Conclusion Management of chronic neck and back pain can represent a clinical dilemma due to the multiplicity of pain generators that may coexist in the same individual resulting in a complex type and pattern of pain. Approach to these patients requires contributions from the members of a multidisciplinary team, implementing a standardized approach in a well-equipped healthcare facility.

The cost of some primitive operations such as multiplication and division significantly affects the running time of some applications in science and engineering especially when the size of data is big. In this study, we propose a formula to minimize the cost of the multiplication operation on integer numbers when the size of each integer and the number of integers to be multiplied are large. Based on a window strategy, we derived, theoretically, the best size of window for minimizing the cost of multiplying a sequence of big integers. To the best of our knowledge, no previous studies have proposed this formula. Then we designed three efficient algorithms, one sequential and two parallel. Experimental studies were conducted using three parameters: (1) the size of integer, (2) the size of a sequence, and (3) the number of threads. The results of a comparison with the best known previous algorithms showed that (1) the designed sequential algorithm is faster than the previous algorithms with an improvement greater than 64%, (2) the designed parallel algorithms are faster than the best known parallel algorithm with an improvement greater than 50% on the average, and (3) the designed parallel algorithms have super linear speed up.

Abstract Car congestion is a pressing issue for everyone on the planet. Car congestion can be caused by accidents, traffic lights, rapid accelerations, deceleration, and hesitation of drivers, as well as a small low-carrying capacity road without bridges. Increasing road width and constructing roundabouts and bridges are solutions to car congestion, but the cost is significant. TLR (traffic light recognition) reduces accidents and traffic congestion caused by traffic lights (TLs). Image processing with convolutional neural network (CNN) lakes dealing with harsh weather. A semi-automatic annotation for traffic light detection employs a global navigation satellite system, raising the cost of automobiles. Data was not collected in harsh conditions, and tracking was not supported. Integrated channel feature tracking (ICFT) combines detection and tracking, but it does not support sharing information with neighbors. This study used vehicular ad-hoc networks (VANETs) for VANET traffic light recognition (VTLR). Information exchange as well as monitoring of the TL status, time remaining before a change, and recommended speeds are supported. Based on testing, it has been determined that VTLR performs better than semi-automatic annotation, image processing with CNN, and ICFT in terms of delay, success ratio, and the number of detections per second.

Abstract Seed production for polyploid watermelons is costly, complex, and labor-intensive. Tetraploid and triploid plants produce fewer seeds/fruit, and triploid embryos have a harder seed coat and are generally weaker than diploid seeds. In this study, we propagated tetraploid and triploid watermelons by grafting cuttings onto gourd rootstock (C. maxima × C. mochata). We used three different scions: the apical meristem (AM), one-node (1N), and two-node (2N) branches of diploid, triploid, and tetraploid watermelon plants. We then evaluated the effects of grafting on plant survival, some biochemical traits, oxidants, antioxidants, and hormone levels at different time points. We found significant differences between the polyploid watermelons when the 1N was used as a scion. Tetraploid watermelons had the highest survival rates and the highest levels of hormones, carbohydrates, and antioxidant activity compared to diploid watermelons, which may explain the high compatibility of tetraploid watermelons and the deterioration of the graft zone in diploid watermelons. Our results show that hormone production and enzyme activity with high carbohydrate content, particularly in the 2–3 days after transplantation, contribute to a high survival rate. Sugar application resulted in increased carbohydrate accumulation in the grafted combination. This study also presents an alternative and cost-effective approach to producing more tetraploid and triploid watermelon plants for breeding and seed production by using branches as sprouts.

Abstract Deep learning algorithms provide visual tracking robustness at an unprecedented level, but realizing an acceptable performance is still challenging because of the natural continuous changes in the features of foreground and background objects over videos. One of the factors that most affects the robustness of tracking algorithms is the choice of network architecture parameters, especially the depth. A robust visual tracking model using a very deep generator (RTDG) was proposed in this study. We constructed our model on an ordinary convolutional neural network (CNN), which consists of feature extraction and binary classifier networks. We integrated a generative adversarial network (GAN) into the CNN to enhance the tracking results through an adversarial learning process performed during the training phase. We used the discriminator as a classifier and the generator as a store that produces unlabeled feature-level data with different appearances by applying masks to the extracted features. In this study, we investigated the role of increasing the number of fully connected (FC) layers in adversarial generative networks and their impact on robustness. We used a very deep FC network with 22 layers as a high-performance generator for the first time. This generator is used via adversarial learning to augment the positive samples to reduce the gap between the hungry deep learning algorithm and the available training data to achieve robust visual tracking. The experiments showed that the proposed framework performed well against state-of-the-art trackers on OTB-100, VOT2019, LaSOT and UAVDT benchmark datasets.

The internet of vehicular things (IOVT) is an important modern technology that offers many advantages and facilities; however, if vehicular malfunctions are not detected in a timely manner, it may cause many dangers and serious accidents. To achieve safe self-driving vehicles, safety and security measures must be taken. In this work, a safety and security model are proposed to evaluate the level of vehicular malfunctions and determine the corresponding danger in terms of road safety. The proposed model presents the optimal actions and alternatives for self-driving vehicles to avoid crises. The objective of this study to develop a hybrid model for multicriteria decision-making problems using neutrosophic theory to handle vehicular malfunctions that occur in the IOVT environment under uncertain conditions and conflicting information. In addition, the technique for order of preference by similarity to the ideal solution is used to prioritize the corresponding alternatives in the case of vehicular malfunction. A case study considering four likely vehicular defects is presented to ensure the applicability and availability of the proposed model.

Wireless sensor networks (WSNs) are periodically collecting data through randomly dispersed sensors (motes), which typically consume high energy in radio communication that mainly leans on data transmission within the network. Furthermore, dissemination mode in WSN usually produces noisy values, incorrect measurements or missing information that affect the behaviour of WSN. In this article, a Distributed Data Predictive Model (DDPM) was proposed to extend the network lifetime by decreasing the consumption in the energy of sensor nodes. It was built upon a distributive clustering model for predicting dissemination-faults in WSN. The proposed model was developed using Recursive least squares (RLS) adaptive filter integrated with a Finite Impulse Response (FIR) filter, for removing unwanted reflections and noise accompanying of the transferred signals among the sensors, aiming to minimize the size of transferred data for providing energy efficient. The experimental results demonstrated that DDPM reduced the rate of data transmission to ∼20%. Also, it decreased the energy consumption to 95% throughout the dataset sample and upgraded the performance of the sensory network by about 19.5%. Thus, it prolonged the lifetime of the network.

Background/aim Circulating forms of micro(mi)RNAs are nowadays increasingly recognized as noninvasive promising biomarkers for early diagnosis and management of breast cancer (BC). Among the numerous miRNAs studied in BC, tissue expressed miR-497-5p and miR-182-5p proved to serve as promising diagnostic, prognostic, and therapeutic target tools in BC; yet little is known about their circulating forms in the peripheral blood of such patients. The study aimed to evaluate serum expression levels of miR-497-5p and miR-182-5p in Egyptian female patients with newly diagnosed BC and their possible association with different clinicopathological features. Patients and methods The study was conducted on 50 primary BC patients at the Medical Research Institute, Alexandria, Egypt, in addition to 50 healthy female volunteers as a control group. Preoperative serum samples were taken from all patients and from healthy volunteers. Relative quantifications of serum miR-182-5p and miR-497-5p expression levels were done using a reverse transcription-quantitative real time PCR. Results The study showed that the median value for fold change in serum miR-497-5p expression was significantly down regulated in BC patients group compared to the healthy control group. A receiver operating characteristics curve generated a cutoff value of 0.54. In serum miR-497-5p expression level was used to discriminate BC patients from controls with a diagnostic specificity of 88%, a sensitivity of 56%, and an overall test accuracy of 68.8%. However, no statistically significant difference was noted in serum miR-182-5p expression level between BC patients and control group. Nevertheless, its serum expression level was significantly higher in BC patients with lymph node involvement compared with BC patients without nodal involvement. Conclusion The downregulated serum miR-497-5p expression in BC patients compared with the healthy control group points to loss of its protective role in such BC patients. Further studies of this miRNA on a larger sample of patients with different molecular subtypes are recommended.

Winter oilseed rape (Brassica napus L.), Europe’s foremost oilseed crop, is significantly impacted by hailstorms, leading to substantial yield reductions that are difficult to predict and measure using conventional methods. This research aimed to assess the effectiveness of photosynthetic efficiency analysis for predicting yield loss in winter rapeseed subjected to hail exposure. The aim was to pinpoint the chlorophyll fluorescence parameters most affected by hail stress and identify those that could act as non-invasive biomarkers of yield loss. The study was conducted in partially controlled conditions (greenhouse). Stress was induced in the plants by firing plastic balls with a 6 mm diameter at them using a pneumatic device, which launched the projectiles at speeds of several tens of meters per second. Measurements of both continuous-excitation and pulse-modulated-amplitude chlorophyll fluorescence were engaged to highlight the sensitivity of the induction curve and related parameters to hail stress. Our research uncovered that some parameters such as Fs, Fm’, ΦPSII, ETR, Fo, Fv/Fm, and Fv/Fo measured eight days after the application of stress had a strong correlation with final yield, thus laying the groundwork for the creation of new practical protocols in agriculture and the insurance industry to accurately forecast damage to rapeseed crops due to hail stress.

Abstract This article is a study of risk assessment of trees with hollows, cavities and fruiting bodies for the improvement of the management and protection of urban trees growing along pedestrian routes. 317 trees were examined using TRAQ risk classes, VTA and ISA BMP methodology, Roloff's vitality classification, and sonic tomography (SoT) during the spring and summer of 2021. The collected data was analysed using the Kruskal–Wallis H-test, the Dunn multiple comparison test, the pairwise comparison of proportions with Holm correction, the U-Manna-Whitney test, and the Fisher exact test. The analysed trees grow alongside public footpaths and footways in central Zakopane, Poland. The study results indicate that tree trunk hollows are judged to have no adverse effects on a tree’s vitality when assessed using visual methods and are deemed to have a limited effect on vitality estimated with SoT. Though most high and moderate-risk trees, according to SoT (88% and 80%, respectively), had hollows, such trees were a small fraction of all 171 trees with hollows, cavities and/or fruiting bodies, 2.3% and 8.8%, respectively. Therefore, the decision to remove a tree should be based on advice from a professional arborist, supported by sonic tomography (SoT) or similar objective methods.

Offline Arabic handwritten word recognition is still a challenging task. Many deep learning approaches perform admirably on this task if the lexicon size is not too large and the number of training samples is sufficient for the training process. The transfer learning technique is commonly used to compensate for the lack of training samples, but there is a wide controversy about the effectiveness of applying it to cross-domain tasks. In this paper, we examine the performance of three deep convolution neural networks that have been randomly initialized for recognizing Arabic handwritten words. Then, we evaluate the performance of the ResNet18 model that has been pre-trained on the ImageNet dataset for the same task. Finally, we propose an approach based on sequentially transferring the mid-level word image representations through two consecutive phases using the ResNet18 model. We carried out four different sets of experiments using two popular offline Arabic handwritten word datasets: the AlexU-W and the IFN/ENIT (v2.0p1e) to figure out the most effective way of applying transfer learning. Our results demonstrate that using the ImageNet as a source dataset improves the recognition accuracy of the ten frequently misclassified words in the IFN/ENIT dataset by 14%, while our proposed approach gives a rise of 35.45%. In the whole dataset, we achieved recognition accuracy up to 96.11%, which is nearly a 2.5% enhancement compared with other state-of-the-art methods.

Abstract Background Bipolar electrocautery tonsillectomy has been the preferred technique for many otolaryngologists, yet coblation tonsillectomy is gaining popularity in the current practice. This study aims at comparing both techniques in terms of pain, bleeding, and healing. Results A total of 120 patients were randomly divided into two equal groups. Overall mean pain score associated with coblation tonsillectomy was statistically less than that caused by bipolar electrocautery throughout the follow-up period (p < 0.001). The difference in pain duration was statistically longer for the bipolar group. The incidence of postoperative hemorrhage—both reactionary and secondary—was statistically higher in the bipolar group. Coblation tonsillectomy showed statistically shorter duration of healing (p < 0.001). Conclusions Coblation tonsillectomy is associated with less pain severity and shorter pain duration, fewer bleeding incidents, and more prompt healing.

Ocular surface disease (OSD), a disorder affecting the lacrimal and meibomian glands and the corneal and conjunctival epithelium, is a well-known complication of topical glaucoma therapy. OSD can present as a new or pre-existing condition that virtually any anti-glaucoma formulation can exacerbate. As such, both glaucoma and OSD frequently coexist. Typical OSD symptoms include ocular discomfort, redness, burning, and dryness, whereas signs include periorbital and eyelid skin pigmentation, conjunctival scarring, and superficial punctate keratitis. Pressure-lowering eyedrops can cause toxic, allergic, and inflammatory reactions on the ocular surface. The latter can result from either preservatives or direct toxicity from the active molecule. Although usually mild, OSD can cause significant symptoms that lead to poor quality of life, decreased compliance to therapy, glaucoma progression, and worse visual outcomes. Given the chronic nature of glaucoma, lack of curative therapy, and subsequent lifelong treatment, addressing OSD is necessary. This manuscript aims to provide an up-to-date overview of OSD’s signs, symptoms, and pathogenic mechanisms from glaucoma therapy toxicity.

Introduction: Computer-aided design has become an important tool to develop novel pesticides based on natural lead compounds. Tenuazonic acid (TeA), a typical representative of the natural tetramic acid family, was patented as a potential bioherbicide. However, its herbicidal efficacy is still not up to the ideal standard of commercial products. Objectives: We aim to find new TeA’s derivatives with improved potency. Methods: Molecular docking was used to build ligand-acceptor interaction models, design and screen new derivatives. Phytotoxicity, oxygen evolution rate, chlorophyll fluorescence and herbicidal efficacy were determined to estimate biological activity of compounds. Results: With the aid of a constructed molecular model of natural lead molecule TeA binding to the QB site in Arabidopsis D1 protein, a series of derivatives differing in the alkyl side chain were designed and ranked according to free energies. All compounds are stabilized by hydrogen bonding interactions between their carbonyl oxygen O2 and D1-Gly256 residue; moreover, hydrogen bond distance is the most important factor for maintaining high binding affinity. Among 54 newly designed derivatives, D6, D13 and D27 with better affinities than TeA were screened out and synthesized to evaluate their photosynthetic inhibitory activity and herbicidal efficacy. Analysis of structure-activity relationship indicated that D6 and D13 with sec-pentyl and sec-hexyl side chains, respectively, were about twice more inhibitory of PSII activity and effective as herbicide than TeA with a sec-butyl side chain. Conclusion: D6 and D13 are promising compounds to develop TeA-derived novel PSII herbicides with superior performance.

Abstract The effect of triad application of the phytohormone 24-epibrassinolide (EBL), the polyamine spermine (Spm), and the element silicon (Si) has not yet been considered on plant growth and behavior in water-stressed conditions. We aimed to evaluate the impact of single/dual/triad application of 24-epibrassinolide (EBL), spermine (Spm), and silicon (Si) on the growth, photosynthetic metabolites, and antioxidant enzymes in the maize plant exposed to water stress. This study was conducted as a potential drought resistance system and plants' maintenance against oxidative damage. In this regard, one maize hybrid (Paya) was grown under well-watered and water-deficit conditions (interrupted irrigation at the flowering and the filling seed stages) with and without foliar spraying of EBL, Spm, and/or Si. Drought conditions remarkably reduced growth, productivity, water-related content (RWC), and chlorophyll content. However, the dual and triad applications of EBL (0.1 mg L−1), Spm (25 mg L−1), and Si (7 mg L−1) significantly improved the above parameters. Water stress considerably augmented the levels of H2O2 and MDA. Their content in stress-subjected plants was significantly reduced by triad application. In water-stressed circumstances and after foliar treatments, the activities of superoxide dismutase, catalase, and peroxidase as well as the amounts of total soluble proteins, phenolic compounds, proline, and glycine betaine all improved. Overall, triad application increased the plant's drought resistance and diminished ROS accumulation by raising the scavenging via the enhanced activity of the antioxidant enzymes.

Abstract Considering the destructive effect of stresses on the photosynthetic apparatus of plants and the important role of light in photosynthesis, we investigated the effect of complementary light on the photosynthetic apparatus under salinity and alkalinity stress conditions. Light-emitting diodes (LEDs) in monochromatic blue (460 nm), monochromatic red (660 nm), dichromatic blue/red (1:3), white/yellow (400–700 nm) at 200 μmol m−2 S−1, and without LED treatment were used. The stress treatments were in three stages: Control (no stress), Alkalinity (40 mM NaHCO3), and Salinity (80 mM NaCl). Our results showed that salinity and alkaline stress reduced CO2 assimilation by 62.64% and 40.81%, respectively, compared to the control treatment. The blue light spectrum had the highest increase in water use efficiency (54%) compared to the treatment without supplementary light. Under salinity and alkalinity stress, L, K, and H bands increased and G bands decreased compared to the control treatment, with blue/red light causing the highest increase in L and K bands under both stress conditions. In salinity and alkalinity stress, white/yellow and blue/red spectra caused the highest increase in H bands. Complementary light spectra increased the G band compared to the treatment without complementary light. There was a significant decrease in power indices and quantum power parameters due to salt and alkalinity stress. The use of light spectra, especially blue, red, and blue/red light, increased these parameters compared with treatment without complementary light. Different light spectra have different effects on the photosynthetic apparatus of plants. It can be concluded that using red, blue spectra and their combination can increase the resistance of plants to stress conditions and be adopted as a strategy in planting plants under stress conditions.

Abstract Phytohormones mediate physiological, morphological, and enzymatic responses and are important regulators of plant growth and development at different stages. Even though temperature is one of the most important abiotic stressors for plant development and production, a spike in the temperature may have disastrous repercussions for crop performance. Physiology and growth of two tomato genotypes ('Ahmar' and 'Roma') were studied in two growth chambers (25 and 45 °C) when gibberellic acid (GA3) was applied exogenously. After the 45 days of planting, tomato plants were sprayed with GA3 at concentrations of 25, 50, 75, and 100 mg L−1, whereas untreated plants were kept as control. Under both temperature conditions, shoot and root biomass was greatest in 'Roma' plants receiving 75 mg L−1 GA3, followed by 50 mg L−1 GA3. Maximum CO2 index, photosynthetic rate, transpiration rate, and greenness index were recorded in 'Roma' plants cultivated at 25 °C, demonstrating good effects of GA3 on tomato physiology. Likewise, GA3 enhanced the proline, nitrogen, phosphorus, and potassium levels in the leaves of both genotypes at both temperatures. Foliar-sprayed GA3 up to 100 mg L−1 alleviated the oxidative stress, as inferred from the lower concentrations of MDA and H2O2, and boosted the activities of superoxide dismutase, peroxidase, catalase. The difference between control and GA3-treated heat-stressed plants suggests that GA3 may have a function in mitigating heat stress. Overall, our findings indicate that 75 mg L−1 of GA3 is the optimal dosage to reduce heat stress in tomatoes and improve their morphological, physiological, and biochemical characteristics.

Abstract Identifying environmental factors that improve plant growth and development under nitrogen (N) constraint is essential for sustainable greenhouse production. In the present study, the role of light intensity and N concentrations on the biomass partitioning and physiology of chrysanthemum was investigated. Four light intensities [75, 150, 300, and 600 µmol m−2 s−1 photosynthetic photon flux density (PPFD)] and three N concentrations (5, 10, and 15 mM N L−1) were used. Vegetative and generative growth traits were improved by increase in PPFD and N concentration. High N supply reduced stomatal size and gs in plants under lowest PPFD. Under low PPFD, the share of biomass allocated to leaves and stem was higher than that of flower and roots while in plants grown under high PPFD, the share of biomass allocated to flower and root outweighed that of allocated to leaves and stem. As well, positive effects of high PPFD on chlorophyll content, photosynthesis, water use efficiency (WUE), Nitrogen use efficiency (NUE) were observed in N-deficient plants. Furthermore, photosynthetic functionality improved by raise in PPFD. In conclusion, high PPFD reduced the adverse effects of N deficiency by improving photosynthesis and stomatal functionality, NUE, WUE, and directing biomass partitioning toward the floral organs.

Abstract The use of complementary light spectra is a potential new approach to studying the increase in plant resilience under stress conditions. The purpose of this experiment was to investigate the effect of different spectra of complementary light on the growth and development of strawberry plants under salinity and alkalinity stress conditions. Plants were grown in the greenhouse under ambient light and irradiated with blue (460 nm), red (660 nm), blue/red (1:3), and white/yellow (400–700 nm) light during the developmental stages. The stress treatments were as follows: control (non-stress), alkalinity (40 mM NaHCO3), and salinity (80 mM NaCl). Our results showed that salinity and alkalinity stress decreased fresh and dry weights and the number of green leaves, and increased chlorotic, tip burn, and dry leaves. The blue and red spectra had a greater effect on reducing the effects of stress compared to other spectra. Stress conditions decreased SPAD and RWC, although blue light increased SPAD, and blue/red light increased RWC under stress conditions. Blue/red and white/yellow light had the greatest effect on reproductive traits. Stress conditions affected fruit color indicators, and red and blue light had the most significant effect on these traits. Under stress conditions, sodium uptake increased, while K, Ca, Mg, and Fe uptake decreased, markedly. Blue and red light and their combination alleviated this reducing effect of stress. It can be concluded that the effects of salinity and alkalinity stresses can be reduced by manipulating the supplemental light spectrum. The use of artificial light can be extended to stresses.

Abstract In agriculture, the search for higher net profit is the main challenge in the economy of the producers and nano biochar attracts increasing interest in recent years due to its unique environmental behavior and increasing the productivity of plants by inducing resistance against phytopathogens. The effect of rice straw biochar and fly ash nanoparticles (RSBNPs and FNPs, respectively) in combination with compost soil on bacterial leaf spot of pepper caused by Xanthomonas campestris pv. vesicatoria was investigated both in vitro and in vivo. The application of nanoparticles as soil amendment significantly improved the chili pepper plant growth. However, RSBNPs were more effective in enhancing the above and belowground plant biomass production. Moreover, both RSBNPs and FNPs, significantly reduced (30.5 and 22.5%, respectively), while RSBNPs had shown in vitro growth inhibition of X. campestris pv. vesicatoria by more than 50%. The X-ray diffractometry of RSBNPs and FNPs highlighted the unique composition of nano forms which possibly contributed in enhancing the plant defence against invading X. campestris pv. vesicatoria. Based on our findings, it is suggested that biochar and fly ash nanoparticles can be used for reclaiming the problem soil and enhance crop productivity depending upon the nature of the soil and the pathosystem under investigation.