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Abstract The gallbladder (GB) is a small pouch and a deep tissue placed under the liver. GB Cancer (GBC) is a deadly illness that is complex to discover in an initial phase. Initial diagnosis can significantly enhance the existence rate. Non-ionizing energy, low cost, and convenience make the US a general non-invasive analytical modality for patients with GB diseases. Automatic recognition of GBC from US imagery is a significant issue that has gained much attention from researchers. Recently, machine learning (ML) techniques dependent on convolutional neural network (CNN) architectures have prepared transformational growth in radiology and medical analysis for illnesses like lung, pancreatic, breast, and melanoma. Deep learning (DL) is a region of artificial intelligence (AI), a functional medical tomography model that can help in the initial analysis of GBC. This manuscript presents an Automated Gall Bladder Cancer Detection using an Artificial Gorilla Troops Optimizer with Transfer Learning (GBCD-AGTOTL) technique on Ultrasound Images. The GBCD-AGTOTL technique examines the US images for the presence of gall bladder cancer using the DL model. In the initial stage, the GBCD-AGTOTL technique preprocesses the US images using a median filtering (MF) approach. The GBCD-AGTOTL technique applies the Inception module for feature extraction, which learns the complex and intrinsic patterns in the pre-processed image. Besides, the AGTO algorithm-based hyperparameter tuning procedure takes place, which optimally picks the hyperparameter values of the Inception technique. Lastly, the bidirectional gated recurrent unit (BiGRU) model helps classify gall bladder cancer. A series of simulation analyses were performed to ensure the performance of the GBCD-AGTOTL technique on the GBC dataset. The experimental outcomes inferred the enhanced abilities of the GBCD-AGTOTL in detecting gall bladder cancer.

Abstract Nanoparticle-mediated drug delivery offers a promising approach to targeted cancer therapy, leveraging the ability of nanoparticles to deliver therapeutic agents directly to cancerous tissues with minimal impact on surrounding healthy cells. The presence of these nanoparticles is governed by a concentration equation, which accounts for the diffusion, convection, and reaction of the nanoparticles with the blood components. It is well-known that whenever a disease or infection occurs in a human, in 80% of cases a rise in the concentration of hydrogen peroxide in the blood occurs. This is the reason why blood is assumed to contain hydrogen peroxide (in the present study), which is a biomarker of oxidative stress and inflammation. This study explores the integration of machine learning (ML) techniques into the optimization of drug delivery processes within the human cardiovascular system, focusing on the enhancement of these processes through the application of magnetic fields. By employing ML algorithms, we analyze and predict the behavior of nanoparticles as they navigate the complex fluid dynamics of the cardiovascular system, particularly under the influence of an external magnetic field. The predictive power of ML models enables the precise control of nanoparticle trajectories, optimizing their accumulation in cancerous tissues and improving the efficacy of the drug delivery system. The findings of this study demonstrate that ML-enhanced magnetic targeting can significantly enhance the precision and effectiveness of nanoparticle-mediated drug delivery, offering a new paradigm in cancer treatment strategies. This approach has the potential to revolutionize the field by providing personalized and highly efficient therapeutic solutions for cancer patients.

Abstract Asthma and chronic obstructive pulmonary disease (COPD) are the most common diagnoses for adults and children with respiratory tract inflammation. Recently, a novel fixed dose combination consisting of Ipratropium and Fenoterol has been released for the management and control of the symptoms of such disorders. The current research has newly developed and optimized three smart, accurate, simple, cost-effective, and eco-friendly spectrophotometric methods that enabled the simultaneous determination of the drugs under study in their combined inhaler dosage form, without the need for any previous separation steps, using water as a green solvent. The strategy employed was based on calculating one or two factors as a numerical spectrum or constant, which provided the complete removal of any component in the mixture that might overlap and the mathematical filtration of the targeted analyte. The methods developed could be classified into two types of spectrophotometric windows. Window I; involved absorption spectrum in their original zero-order forms (°D), which included recently designed methods named induced concentration subtraction (ICS) and induced dual wavelength (IDW). While window III focused on the ratio spectrum as the induced amplitude modulation (IAM) method. The extremely low absorptivity and lack of distinct absorption maximum in the zero-order absorption spectrum of Ipratropium were two intrinsic challenges that were better overcome by the proposed spectrophotometric methods than by the conventionally used ones. According to ICH guidelines, the proposed methods were validated using unified regression over range 2.0–40.0 µg/mL in the ICS method, while the linearity ranges for the IDW and IAM methods were 5.0–40.0 µg/mL of Ipratropium and 2.0–40.0 µg/mL of Fenoterol. Moreover, the three proposed methods were effectively used to assay the co-formulated marketed inhaler and further expanded to confirm the delivered dose uniformity in compliance with the USP guidelines. Finally, the established methods were evaluated for their greenness and blueness, in comparison to the official and reported analysis methods, using advanced cutting edge software metrics. Furthermore, the suggested techniques adhered well to the white analytical chemistry postulates that were recently published.

Abstract Kojic acid (KA) has gained significant attention due to its widespread use in the food and cosmetics industries. However, concerns about its potential carcinogenic effects have heightened the need for sensitive detection methods. This study introduces a fluorescence-based optical sensor for the quantification of KA in food samples, utilizing fluorescent carbon dots (CDs) synthesized from pomegranate peel via a hydrothermal method. The Stern–Volmer plot demonstrated a linear response for KA in the range of 120 to 1200 µM, with a Pearson correlation coefficient (r) of 0.9999 and. The sensor exhibited a detection limit of 30 ± 0.04 µM and a limit of quantification (LOQ) of 90 ± 0.14 µM. Application of the developed method to soy sauce and vinegar samples yielded accurate KA determinations, with recoveries of 103.11 ± 0.96% and 104.45 ± 2.15%, respectively. These findings highlight the potential of the proposed sensor for practical applications in food quality and safety assessment, offering valuable insights into the presence of KA in food products.

Abstract Proton exchange membrane fuel cell (PEMFC) parameter extraction is an important issue in modeling and control of renewable energies. The PEMFC problem’s main objective is to estimate the optimal value of unknown parameters of the electrochemical model. The main objective function of the optimization problem is the sum of the square errors between the measured voltages and output voltages of the proposed electrochemical optimized model at various loading conditions. Natural rabbit survival strategies such as detour foraging and random hiding are influenced by Artificial rabbit optimization (ARO). Meanwhile, rabbit energy shrink is mimicked to control the smooth switching from detour foraging to random hiding. In this work, the ARO algorithm is proposed to find the parameters of PEMFC. The ARO performance is verified using experimental results obtained from conducting laboratory tests on the fuel cell test system (SCRIBNER 850e, LLC). The simulation results are assessed with four competitive algorithms: Grey Wolf Optimization Algorithm, Particle Swarm Optimizer, Salp Swarm Algorithm, and Sine Cosine Algorithm. The comparison aims to prove the superior performance of the proposed ARO compared with the other well-known competitive algorithms.

Abstract Impaired wound healing in diabetic individuals creates huge social and financial burdens for both diabetic patients and the health system. Unfortunately, the current treatment has not resulted in consistently lower amputation rates. Quinoxalines are heterocyclic compounds with multiple important pharmacological properties. Their effect on wound healing have not been closely studied. In the current work, the wound healing effect of 3-hydrazinylquinoxaline-2-thiol hydrogel is tested topically in a full-thickness excision wound in streptozotocin-induced type 1 diabetic rats. We examined the wound closure rate, expression of inflammatory factors, growth factors in addition to the histological analysis. The results revealed a significant acceleration in wound closure in the treated group compared with the control experimental animals. Histological data demonstrated enhanced re-epithelialization and collagen disposition. The healing effect was additionally evaluated by the inhibition of the inflammatory response of interleukin (IL)—1β interleukin (IL)—6, tumor necrosis factor (TNF-α) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) with a marked improvement of the transforming growth factor beta (TGFβ-1), antioxidant markers and collagen-1. In silico study indicated a favorable drug-like properties and toxicity profile. The present work showed that 3-hydrazinylquinoxaline-2-thiol holds great potential for the treatment of diabetic wounds.

Abstract Cell adhesion to the extracellular matrix and its natural outcome of cell spreading, along with the maintenance of barrier activity, are essential behaviors of epithelial cells, including retinal pigment epithelium (RPE). Disruptions in these characteristics can result in severe vision-threatening diseases such as diabetic macular edema and age-related macular degeneration. However, the precise mechanisms underlying how RPE cells regulate their barrier integrity and cell spreading are not fully understood. This study aims to elucidate the relative importance of upper glycolytic components in governing these cellular behaviors of RPE cells. Electric Cell-Substrate Impedance Sensing (ECIS) technology was utilized to assess in real-time the effects of targeting various upper glycolytic enzymes on RPE barrier function and cell spreading by measuring cell resistance and capacitance, respectively. Specific inhibitors used included WZB117 for Glut1 inhibition, Lonidamine for Hexokinase inhibition, PFK158 for PFKFB3/PFK axis inhibition, and TDZD-8 for Aldolase inhibition. Additionally, the viability of RPE cells was evaluated using a lactate dehydrogenase (LDH) cytotoxicity assay. The most significant decrease in electrical resistance and increase in capacitance of RPE cells were observed due to dose-dependent inhibition of Glut1 using WZB117, as well as Aldolase inhibition with TDZD-8. LDH level analysis at 24–72 h post-treatment with WZB117 (1 and 10 μM) or TDZD-8 (1 μM) showed no significant difference compared to the control, indicating that the disruption of RPE functionality was not attributed to cell death. Lastly, inhibition of other upper glycolytic components, including PFKFB3/PFK with PFK158 or Hexokinase with Lonidamine, did not significantly affect RPE cell behavior. This study provides insights into the varied roles of upper glycolytic components in regulating the functionality of RPE cells. Specifically, it highlights the critical roles of Glut1 and Aldolase in preserving barrier integrity and promoting RPE cell adhesion and spreading. Such understanding will guide the development of safe interventions to treat RPE cell dysfunction in various retinal disorders.

Abstract Conscious sedation is widely considered one of the techniques most commonly used to manage anxiety in both children and adults during dental procedures. The application of procedural sedation exhibits considerable variation globally. The purpose of the study was to determine the prevalence of conscious sedation in the current situation in the dental healthcare sector in Egypt and to identify the factors influencing it. An online cross-sectional analytical survey, consisting of nine multiple choice questions, was distributed through the contact lists of national dentists and social media platforms. 163 respondents completed the survey. Regarding the use of conscious sedation, only 25 (15.3%),95% confidence interval (10–21) utilized it. The percentage of participants who used conscious sedation was higher among dentists practicing pediatric dental specialists (n = 19, 76%). Academic qualification correlates significantly with the practice of conscious sedation (P = 0.002), but this was not reflected in multiple logistic regression. Indeed, while conscious sedation is part of the dental study curriculum in Egypt, its application rate is relatively low compared to other countries. This discrepancy could be attributed to a variety of factors, including resource availability, lack of training, reflecting the need to develop strategies to improve the implementation of conscious sedation in Egyptian dental practices.

Abstract This article presents a novel approach for parameters estimation of photovoltaic cells/modules using a recent optimization algorithm called quadratic interpolation optimization algorithm (QIOA). The proposed formula is dependent on variable voltage resistances (VVR) implementation of the series and shunt resistances. The variable resistances reduced from the effect of the electric field on the semiconductor conductivity should be included to get more accurate representation. Minimizing the mean root square error (MRSE) between the measured (I–V) dataset and the extracted (V–I) curve from the proposed electrical model is the main goal of the current optimization problem. The unknown parameters of the proposed PV models under the considered operating conditions are identified and optimally extracted using the proposed QIOA. Two distinct PV types are employed with normal and low radiation conditions. The VVR TDM is proposed for (R.T.C. France) silicon PV operating at normal radiation, and eleven unknown parameters are optimized. Additionally, twelve unknown parameters are optimized for a Q6-1380 multi-crystalline silicon (MCS) (area 7.7 cm2) operating under low radiation. The efficacy of the QIOA is demonstrated through comparison with four established optimizers: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Sine Cosine Algorithm (SCA). The proposed QIO method achieves the lowest absolute current error values in both cases, highlighting its superiority and efficiency in extracting optimal parameters for both Single-Crystalline Silicon (SCS) and MCS cells under varying irradiance levels. Furthermore, simulation results emphasize the effectiveness of QIO compared to other algorithms in terms of convergence speed and robustness, making it a promising tool for accurate and efficient PV parameter estimation.

Abstract Municipal wastewater treatment systems use the chemical oxygen demand test (COD) to identify organic contaminants in industrial effluents that impede treatment due to their high concentration. This study reduced the COD levels in tannery wastewater using a multistage treatment process that included Fenton oxidation, chemical coagulation, and nanotechnology based on a synthetic soluble COD standard solution. At an acidic pH of 5, Fenton oxidation reduces the COD concentration by approximately 79%. It achieves this by combining 10 mL/L of H2O2 and 0.1 g/L of FeCl2. Furthermore, the author selected the FeCl3 coagulant for the coagulation process based on the best results of comparisons between different coagulants. At pH 8.5, the coagulation dose of 0.15 g/L achieved the maximum COD removal efficiency of approximately 56.7%. Finally, nano bimetallic Fe/Cu was used to complete the degradation and adsorption of the remaining organic pollutants. The XRD, SEM, and EDX analyses proved the formation of Fe/Cu nanoparticles. A dose of 0.09 g/L Fe/Cu NPs, 30 min of contact time, and a stirring rate of 200 rpm achieve a maximum removal efficiency of about 93% of COD at pH 7.5. The kinetics studies were analyzed using pseudo-first-order P.F.O., pseudo-second-order P.S.O., and intraparticle diffusion models. The P.S.O. showed the best fit among the kinetic models, with an R2 of 0.998. Finally, the authors recommended that technique for highly contaminated industrial effluents treatment for agriculture or industrial purposes.

Abstract Porous asphalt mixture is conventional hot mix asphalt (HMA) with substantially decreased fines, which produces an open-graded mixture that enables the water to flow through an interconnected void space. Porous asphalt is a permeable system that has a lot of benefits. However, because of its open structure, the durability of this mixture decreases, and both its stability and resilient modulus are much lower compared to the dense conventional asphalt mixtures. Also, the high void percentage may lead to an increase in the draindown proportion. Fibers (cellulose or mineral) and polymer-modified binders are recommended for porous asphalt mixtures, especially in hot and moderate climates. The objective of this study is to improve the porous asphalt mixture's performance by using ethylene–vinyl acetate (EVA) polymer-modified bitumen. Two types of fibers (cellulose fibers and glass wool fibers) were used, separately to determine the control mixture. Four different proportions of EVA polymer were added to the bitumen (1%, 2%, 3%, and 4%) and Scanning Electron Microscopy (SEM) was used for better investigating of the bitumen microstructure, then The Marshall mix design was used to determine the optimum EVA content (OEC) for the porous asphalt mixture. Several performance tests were conducted to investigate the characteristics of the porous asphalt mixture, such as the infiltration rate, binder draindown, the wheel track and the cantabro abrasion tests. The findings of the study conclude that the addition of EVA polymer to the porous asphalt mixtures enhances the performance as it increases stability by 20.8% and the infiltration rate by 20.6%. It decreases binder draindown proportion by 33.3%, cantabro abrasion loss by 25.1% and the rut depth at 5,000 cycles and 10,000 cycles by 29.8% and 19.7%, respectively.

Abstract Photocatalysis is a promising technique to reduce hazardous organic pollutants using semiconductors under visible light. However, previous studies have been concerned with the behavior of silver phosphate (Ag3PO4) as n-type semiconductors, and the problem of their instability is still under investigation. Herein, 4,4′-(((oxalylbis(azanediyl)) bis(carbonothioyl)) bis(azanediyl)) dibenzoic acid is synthesized by green method and used to enhance the photocatalytic behavior for Ag3PO4. The incorporated Ag3PO4 core–shell is prepared and characterized via XRD, FT-IR, Raman, TEM and BET. Besides, the thermal stability of the prepared core shell was investigated via TGA and DSC measurements. The optical properties and the energy band gap are determined using photoluminescence and DRS measurements. The photodegradation of methylene blue in the presence of the synthesized Ag3PO4 core–shell under visible light is examined using UV/Vis measurements. The effect of initial dye concentration and contact time are studied. In addition, the kinetic behavior of the selected dye during the photodegradation process shows a pseudo-first order reaction with rate constant of 0.015 min−1 for ZAg. The reusability of the Ag3PO4 core shell is evaluated, and the efficiency changed from 96.76 to 94.02% after three cycles, indicating efficient photocatalytic behavior with excellent stability.

Abstract The volatile particles and molecules in our dry exhaled breath can reveal enormous information about the health of any person, such as the person’s respiratory and metabolic functioning. Beyond the carbon dioxide level is an indicator of life, it provides important health-related data like people’s metabolic rate. This study considers periodic open and closed resonators for measuring carbon dioxide concentration in dry exhaled breath. Transfer matrix and green methods are used to simulate the interaction between acoustic waves and the proposed sensor. The band gaps using the green method coincide with the transmittance spectra by the transfer matrix. The suggested sensor recorded a sensitivity of $$5.3 Hz.{m}^{-1}.s$$ 5.3 H z . m - 1 . s , a figure of merit of 10,254 $${m}^{-1}.s$$ m - 1 . s , a detection limit of $$5\times {10}^{-6} m.{s}^{-1}$$ 5 × 10 - 6 m . s - 1 , and a quality factor of $$3\times {10}^{6}$$ 3 × 10 6 . Furthermore, the efficiency shows that the proposed design is appropriate as a diagnostic sensor for different diseases such as chronic obstructive pulmonary. Besides, cylindrical-adapted sensors are urgently needed in medicine, industry, and biology because they can simultaneously be used for fluid transport and detection.

Abstract This study was divided into two parts. The first part involved the isolation, and detection of the prevalence and antimicrobial resistance profile of Aeromonas hydrophila, Pseudomonas aeruginosa, and Vibrio species from Nile tilapia fish and marine aquatic water. One hundred freshly dead Nile tilapia fish were collected from freshwater aquaculture fish farms located in Al-Abbassah district, Sharkia Governorate, and 100 samples of marine aquatic water were collected from fish farms in Port Said. The second part of the study focused on determining the in vitro inhibitory effect of dual-combination of AgNPs-H2O2 on bacterial growth and its down regulatory effect on crucial virulence factors using RT-PCR. The highest levels of A. hydrophila and P. aeruginosa were detected in 43%, and 34% of Nile tilapia fish samples, respectively. Meanwhile, the highest level of Vibrio species was found in 37% of marine water samples. Additionally, most of the isolated A. hydrophila, P. aeruginosa and Vibrio species exhibited a multi-drug resistance profile. The MIC and MBC results indicated a bactericidal effect of AgNPs-H2O2. Furthermore, a transcriptional modulation effect of AgNPs-H2O2 on the virulence-associated genes resulted in a significant down-regulation of aerA, exoU, and trh genes in A. hydrophila, P. aeruginosa, and Vibrio spp., respectively. The findings of this study suggest the effectiveness of AgNPs-H2O2 against drug resistant pathogens related to aquaculture.

Abstract Hydroxychloroquine (HCQ) is prescribed to treat malaria and certain autoimmune diseases. Recent studies questioned its efficiency in relieving COVID-19 symptoms and improving clinical outcomes. This work presents a quality-by-design approach to develop, optimize, and validate a potentiometric sensor for the selective analysis of HCQ in the presence of its toxic impurities (key starting materials), namely 4,7-Dichloroquinoline (DCQ) and hydroxynovaldiamine (HND). The study employed a custom experimental design of 16 sensors with different ion exchangers, plasticizers, and ionophores. We observed the Nernstian slopes, correlation coefficients, quantification limit, response time, and selectivity coefficient for DCQ and HND. The computer software constructed a prediction model for each response. The predicted responses strongly correlate to the experimental ones, indicating model fitness. The optimized sensor achieved 93.8% desirability. It proved a slope of 30.57 mV/decade, a correlation coefficient of 0.9931, a quantification limit of 1.07 × 10–6 M, a detection limit of 2.18 × 10–7 M, and a fast response of 6.5 s within the pH range of 2.5–8.5. The sensor was successfully used to determine HCQ purity in its raw material. The sensor represents a potential tool for rapid, sensitive, and selective monitoring of HCQ purity during industrial production from its starting materials.

Abstract This paper aims to increase the performance and improve the safety of an ageing Nuclear Facility (NF). Good power quality extends the life of electrical equipment at NF and thus protects it from premature aging. The first stage of this paper presents a measurement and analysis of various power quality events for a real-world case of a NF under different conditions of operation. In the previous work for this group, a new proposed technique based on partial swarm optimization is presented to find the allocation of the UPFC to enhance the power quality within the specified limit. The technique is tested by IEEE33 bus. This step is to assess system performance and find the best solutions to ensure the normal and safe operation of NF. In this paper, the simulink-matlab programme was used to simulate a real NF based on a new vision of UPFC. The results indicate that the strategy is an effective way to improve the safety of power quality and ageing NF using UPFC.

Abstract Avocado fruit is a climacteric fruit that has a short life after harvest. Chitosan (Ch) and Arabic gum (AG) have a pronounced effect on the storability of fruits. This investigation aimed to determine the effect of individual or combined use of Ch and AG as well as Ch/AG enriched with 2, 4, 8% Zn–NPs on physio-biochemical attributes and antioxidant capacity of Hass avocado fruit during cold storage (7 °C). The result showed that Ch or AG alone succeeded in maintaining fruit quality of Hass fruit during cold storage. Also, combined application of Ch/AG was more effective than individual application of Ch or AG in reducing fruit weight and polyphenol oxidase activity (PPO) as well as increasing total antioxidant capacity (TAC) and malondialdehyde (MDA). Moreover, Ch/AG coating enriched with 8% Zn–NPs recorded the lowest fruit weight loss, fruit decay %, TSS fruit content, fruit firmness and improved fruit skin and pulp color significantly compared to Ch/AG and control. Coating with Ch/AG/2%Zn NPs recorded the highest peroxidase (POD) activity, while Ch/AG/8% Zn–NPs recorded the highest TAC and the lowest PPO activity. Moreover, enriched Ch/GA with Zn–NPs recorded the highest CAT and POD activity compared to the control. This study shows the efficiency of Ch/AG enriched with Zn–NPs on preserving Hass avocado fruit quality during cold storage by delaying ripening process and activating enzymatic defense mechanisms.

Abstract In the sugar industry, eliminating side impurities throughout the manufacturing process is the most significant obstacle to clarifying sugar solutions. Herein, magnetic chitosan (MCS) nanocomposite was Fabricated to be used as a biodegradable, environmentally friendly clarifying agent throughout the cane juice and sugar refining processes. Fe3O4 was synthesized using the coprecipitation procedure, and then MCS was combined using a cross-linking agent. Furthermore, 14.76 emu g−1 was the maximum saturation magnetization (Ms) value. Because MCS is magnetically saturated, it may be possible to employ an external magnetic field to separate the contaminant deposited on its surface. Additionally, zeta potential analysis showed outstanding findings for MCS with a maximum value of (+) 20.7 mV, with improvement in color removal % up to 44.8% using MCS with more than 24% in color removal % compared to the traditional clarification process. Moreover, utilizing MCS reduced turbidity from 167 to 1 IU. Overall, we determined that MCS nanocomposite exhibits considerable effectiveness in the clarifying process for different sugar solutions, performing as an eco-friendly bio-sorbent and flocculating material.

Abstract This study investigates using the phononic crystal with periodically closed resonators as a greenhouse gas sensor. The transfer matrix and green methods are used to investigate the dispersion relation theoretically and numerically. A linear acoustic design is proposed, and the waveguides are filled with gas samples. At the center of the structure, a defect resonator is used to excite an acoustic resonant peak inside the phononic bandgap. The localized acoustic peak is shifted to higher frequencies by increasing the acoustic speed and decreasing the density of gas samples. The sensitivity, transmittance of the resonant peak, bandwidth, and figure of merit are calculated at different geometrical conditions to select the optimum dimensions. The proposed closed resonator gas sensor records a sensitivity of 4.1 Hz m−1 s, a figure of merit of 332 m−1 s, a quality factor of 113,962, and a detection limit of 0.0003 m s−1. As a result of its high performance and simplicity, the proposed design can significantly contribute to gas sensors and bio-sensing applications.

Abstract Partial discharge (PD) could lead to the formation of small arcs or sparks within the insulating material, which can cause damage and degradation to the insulator over time. In ceramic insulators, there are several factors that can cause PD including manufacturing defects, aging, and exposure to environmental conditions such as moisture and temperature extremes. As a result, detecting and monitoring PD in ceramic insulators is important for ensuring the reliability and safety of electrical systems that rely on these insulators. In this study, acoustic emission technique is introduced for PD detection and condition monitoring of defective ceramic insulators. A sequence of data processing techniques is performed on the captured signals to extract and select the most significant signatures for classification of defects in insulator strings. Artificial neural network (ANN) has been used to build an intelligent classifier for easily and accurately classification of defective insulators. The overall recognition rate of the classifier was obtained at 96.03% from discrete wavelet transform analysis and 88.65% from fast Fourier transform analysis. This obtained result indicates high accuracy and performance classification. The outcomes of ANN were verified by SVM and KNN algorithms.

Abstract The advent of flow micro-power generation has resparked the interest in researching the galloping instability with the objective of determining the shape of the bluff body that is most prone to galloping. Such shape, which is sought to maximize the efficacy of galloping micro-power generators (GMPGs), must possess a very low cut-in flow speed while achieving large-amplitude steady-state oscillations beyond it. Additionally, since GMPGs can operate in environments with fluctuating flow conditions, the optimal shape must also have a very short rise time to its steady-state amplitude. In this work, we utilize computational fluid dynamics in conjunction with machine learning to optimize the shape of the bluff body of GMPGs for both steady-state and transient performance. We investigate a continuum shape description which encapsulates most of the cases studied earlier in the literature. The continuum has a straight frontal and dorsal faces with varying lengths, and side faces described by surfaces of different curvatures. The optimization study reveals that a curved-trapezoidal bluff body with the highest side surface curvature and frontal-to-dorsal ratio is the perfect shape for steady flow conditions. On the other hand, a square profile with the highest side surface curvature is the ideal choice for highly-fluctuating flow conditions because of its shortest rise time. The theoretical findings are replicated experimentally using wind tunnel tests.

Abstract Metamaterial absorbers have diverse applications in the terahertz range. In this paper, a metallic metamaterial absorber is designed to work as a narrowband, wideband, or ultrawideband according to application. A systematic method with minimal computational requirements for the design is developed. The method is efficient since the only information required is the operating frequency and required bandwidth. A condition for zero reflection which ensures matching with free space is derived. The proposed design method is used for the design of narrowband, wideband, and ultrawideband absorbers. For each case the design parameters are different. The narrow bandwidth is less than 5%, while the wide band lies between 5 and 20%, and the ultrawideband is larger than 20%. The dimensions of the designed structure and material properties (εr″) are different for each case. The designed absorber is wide-angle and polarization-independent. The sensitivity of the designed material due to changes of physical dimensions and permittivity is studied. To validate results, reflectivity and absorptivity are calculated using CST package. The dimensions obtained from the developed method are a bit modified using trial and error. The results from the developed method and CST are in excellent agreement.

Abstract Hybrid nanofluids offer higher stability, synergistic effects, and better heat transfer compared to simple nanofluids. Their higher thermal conductivity, lower viscosity, and interaction with magnetic fields make them ideal for various applications, including materials science, transportation, medical technology, energy, and fundamental physics. The governing partial differential equations are numerically solved by employing a finite volume approach, and the effects of various parameters on the nanofluid flow and thermal characteristics are systematically examined from the simulations based on a self-developed MATLAB code. The parameters included magnetic field strength, the Reynolds number, the nanoparticle volume fraction, and the number and position of the strips in which the magnetic field is localized. It has been noted that the magnetized field induces the spinning of the tri-hybrid nanoparticles, which generates the intricate structure of vortices in the flow. The local skin friction (CfRe) and the Nusselt number (Nu) increase significantly when the magnetic field is intensified. Moreover, adding more nanoparticles in the flow enhances both Nu and CfRe, but with different effects for different nanoparticles. Silver (Ag) shows the highest increase in both Nu (52%) and CfRe (110%), indicating strong thermal-fluid coupling. Alumina (Al2O3) and Titanium Dioxide (TiO2) show lower increases in both Nu (43% and 34%) and CfRe (14% and 10%), indicating weaker coupling in the flow. Finally, compared with the localized one, the uniform magnetic field has a minor effect on the flow and temperature distributions.

Abstract The present study applies the improved stratigraphic modified Lorenz (ISML) technique to divide the Matulla Formation in Muzhil Oil Field in the Gulf of Suez into some hydraulic flow units (HFUs) and to check the flow efficiency contribution of each hydraulic flow unit (HFU) to the total bulk flow capacity of the reservoir in 3 wells (Muzhil-4, 7, and 8). The output of the ISML plot is applied in integration with the vertical plot of the porosity (∅), permeability (k), and effective pore radius (R35) against depth to measure the efficiency of each HFU contribution to the total flow capacity of the Matulla reservoir, and to delineate the main attributor to the flow capacity. It is indicated that the Matulla sandstone reservoirs can be subdivided into 7 HFUs to the NW of the field, while it is subdivided into four and five HFUs in the center and to the SE of the field; i.e., its heterogeneity increases to the NW at Muzhil-7 well. On the other side, the best reservoir quality is assigned to the southeast at Muzhil-4 well (av. ∅ = 20.8%, av. k = 596.6 md, and R35 = 12.1 μm). The efficiency of the obtained HFUs was estimated and described both mathematically and graphically. Also, the measured porosity and permeability values indicate relatively low reservoir properties to the NW of the field. The reservoir heterogeneity is also measured using the Dykstra-Parsons technique which indicates extremely high heterogeneity (0.89 ≤ V ≤ 0.98).

Abstract The impact of bio-organic amendments on crop production is poorly understood in saline calcareous soils. The aim in the present study was to determine the effects of the application of organic manure along with lactic acid bacteria (LAB) on soil quality, and morpho-physio-biochemical responses, seed yield (SY) and essential oil yield (EOY) of fennel plants (Foeniculum vulgare Mill.) grown in saline calcareous soils. Eight treatments of farmyard manure (FM) or poultry manure (PM) individually or combined with Lactobacillus plantarum (Lp) and/or Lactococcus lactis (Ll) were applied to saline calcareous soil in two growing seasons. Either FM or PM combined with LAB had beneficial effects on lowering ECe, pH and bulk density and increasing total porosity, organic matter, and water and nutrient retention capacities in addition to total bacterial population in the soil. Growth, nutrient uptake, SY and EOY of plants were also enhanced when fennel seeds were inoculated with Lp and/or Ll and the soil was amended with any of the organic manures under unfavorable conditions. Compared to control (no bio-organic amendments), FM + Lp + Lt or PM + Lp + Lt treatment signficantlly (P ≤ 0.05) increased plant height by 86.2 or 65.0%, total chlorophyll by 73 or 50%, proline by 35 or 45%, glutathione by 100 or 138%, SY by 625 or 463% and EOY by 300 or 335%, respectively, in fennel plants. Co-application of the naturally occurring microorganisms (i.e., LAB) and organically-derived, nutrient-rich fertilizer (i.e., FM or PM) is recommended to improve yield of fennel plants in saline calcareous soils.

Abstract The breakthrough infection following COVID-19 vaccination has been a subject of concern recently. Evidence suggests that COVID-19 vaccine efficacy diminishes over time due to multiple factors related to the host, and vaccine. Coinfection with other pathogens was claimed earlier as a contributing cause for this phenomenon. Hence, we aimed to stratify the association of post-COVID-19 vaccination breakthrough coinfection with Toxoplasma gondii (T. gondii) and its impact on disease severity. This cross-sectional study included 330 COVID-19-vaccinated patients confirmed by RT-PCR. They were also screened for anti- T. gondii antibodies using ELISA. Toxoplasma seropositive cases’ whole blood was screened for DNA using PCR to correlate results with COVID-19 severity. Out of 330 COVID-19 vaccinated patients with breakthrough infection, 34.5% (114 patients) showed positivity for Toxoplasma IgG by ELISA, and none of the cases was IgM positive. Eleven patients (9.6%) of the IgG-positive cases were positive by PCR. Positive PCR cases correlated positively with the Toxoplasma IgG titer (P

Abstract A commercial carbon cloth (CC) was oxidized by HNO3 acid and the features of the plain and oxidized CC were evaluated. The results of characterization illustrated that HNO3 oxidization duplicated the oxygen-containing functional groups and the surface area of the CC. The adsorption performance of the plain and oxidized CC (Oxi-CC) toward benzotriazole (BTR) was compared. The results disclosed that the uptake of BTR by oxidized CC was greater than the plain CC. Thence, the affinity of oxidized CC toward BTR was assessed at different conditions. It was found that the adsorption was quick, occurred at pH 9 and improved by adding NaCl or CaCl2 to the BTR solution. The kinetic and isotherm studies revealed that the surface of Oxi-CC is heterogeneous and the adsorption of BTR follows a physical process and forms multilayer over the Oxi-CC surface. The regenerability and reusability study illustrated that only deionized water can completely regenerate the Oxi-CC and that the Oxi-CC can be reused for five cycles without any loss of performance. The high maximum adsorption capacity of Dubinin–Radushkevich isotherm model (252 mg/g), ease of separation and regeneration, and maintaining the adsorption capacity for several cycles revealed the high efficiency and economical and environmental feasibility of Oxi-CC as an adsorbent for BTR.

Abstract Dietary components have recently received rapidly expanding attention for their potential to halt or reverse the development of many oxidative stress-mediated diseases after exposure to environmental toxicants. 7, 12 dimethylbenz(a)anthracene (DMBA) is one of the most common environmental pollutants. The present study aimed to evaluate the chemo-preventive effects of broccoli as a nutritional component against DMBA intoxication in rats. A daily dose of aqueous (1 ml/rat) and methanolic (150 mg/kg) broccoli extracts, respectively, was given to 50-day-old female rats for 26 successive weeks after carcinogen intoxication with a single dose of 20 mg/ml of DMBA. DMBA intoxication resulted in a redox imbalance (a decreased GSH level and an increased MDA level) and increased DNA fragmentation in the liver, kidney, and brain. Besides, it affected the level of expression of the bcl2 gene in the liver, kidney, and brain tissue but didn’t affect cfos gene expression accompanied by histopathological changes. The aqueous and methanolic broccoli extract supplements ameliorated the adverse effects by increasing the level of GSH, decreasing the MDA level, and reducing DNA fragmentation. Besides, broccoli extracts decreased the expression of bcl2 in the liver and brain and up-regulated bcl2 expression in the kidney, accompanied by lowering NF-κβ 65 expression in the liver and brain and γ-catenin expression in the liver and kidney. In conclusion, broccoli as a dietary component had a strong chemoprotective effect against oxidative stress, DNA damage, and genotoxicity induced by DMBA intoxication in rats.

Abstract Proliferative diabetic retinopathy (PDR) remains a leading cause of blindness despite progress in screening and treatment. Recently, the Warburg effect, a metabolic alteration affecting amino acid (AA) metabolism in proliferating cells, has drawn attention regarding its role in PDR. This study aimed to investigate the impact of the Warburg effect on AA metabolism in human retinal endothelial cells (HRECs) subjected to PDR-associated risk factors and validate the findings in patients with PDR. In vitro experiments exposed HRECs to high glucose (HG) and/or hypoxia (Hyp), known inducers of the Warburg effect. The HG + Hyp group of HRECs exhibited significant differences in non-essential AAs with aliphatic non-polar side chains, mainly driven by elevated glycine concentrations. Pathway enrichment analysis revealed several glycine metabolism-related pathways significantly altered due to the Warburg effect induced by HG + Hyp. Crucially, vitreous humor samples from PDR patients displayed higher glycine levels compared to non-diabetic and diabetic patients without PDR. The odds ratio for PDR patients with glycine levels above the cut-off of 0.0836 µM was 28 (p = 0.03) compared to non-PDR controls. In conclusion, this study provides mechanistic insights into how a specific Warburg effect subtype contributes to glycine accumulation in PDR and supports glycine's potential as a biomarker for PDR pathogenesis.

Abstract Herein, adsorption of Rose Bengal dye (RB) from aqueous solution was investigated. Nano raw orange peel (OP) activated carbon (AC) coated with nano chitosan (Cs) to obtain nano chitosan/activated carbon (AC/Cs) composite which cross-linked with functionalized multi-walled carbon nanotubes (MWCNTs-COOH) to create a novel composite (AC/Cs/MWCNTs) with high surface area (1923 m2/g). The examined parameters such as concentration (1–7 ppm), pH (6.5–9.5) and temperature (295–323 K) were traversed. The maximum removal efficiency was at pH 6.5, increased from 70.4% for nano OP to 94.7% for AC/Cs/MWCNTs nano composite. Langmuir isotherm model was the best fitting to acquired data (R2 ≥ 0.99). Also, the adsorption of RB matched with pseudo-second order model, t0.5 results for pseudo-second order was 4.4672 for nano OP and 1.2813 for AC/Cs/MWCNTs at 303 K. Thermodynamic studies showed that the adsorption of RB dye is exothermic and spontaneous due to the negative value of ΔG and ΔH.

Abstract The aromatic fennel plant (Foeniculum vulgare Miller) is cultivated worldwide due to its high nutritional and medicinal values. The aim of the current study was to determine the effect of the application of bio-organic fertilization (BOF), farmyard manure (FM) or poultry manure (PM), either individually or combined with Lactobacillus plantarum (LP) and/or Lactococcus lactis (LL) on the yield, chemical composition, and antioxidative and antimicrobial activities of fennel seed essential oil (FSEO). In general, PM + LP + LL and FM + LP + LL showed the best results compared to any of the applications of BOF. Among the seventeen identified FSEO components, trans-anethole (78.90 and 91.4%), fenchone (3.35 and 10.10%), limonene (2.94 and 8.62%), and estragole (0.50 and 4.29%) were highly abundant in PM + LP + LL and FM + LP + LL, respectively. In addition, PM + LP + LL and FM + LP + LL exhibited the lowest half-maximal inhibitory concentration (IC50) values of 8.11 and 9.01 μg mL−1, respectively, compared to l-ascorbic acid (IC50 = 35.90 μg mL−1). We also observed a significant (P > 0.05) difference in the free radical scavenging activity of FSEO in the triple treatments. The in vitro study using FSEO obtained from PM + LP + LL or FM + LP + LL showed the largest inhibition zones against all tested Gram positive and Gram negative bacterial strains as well as pathogenic fungi. This suggests that the triple application has suppressive effects against a wide range of foodborne bacterial and fungal pathogens. This study provides the first in-depth analysis of Egyptian fennel seeds processed utilizing BOF treatments, yielding high-quality FSEO that could be used in industrial applications.

Abstract This paper described a four-band implantable RF rectifier with simplified circuit complexity. Each RF-rectifier cell is sequentially matched to the four operational frequencies to accomplish the proposed design. The proposed RF rectifier can harvest RF signals at 1.830, 2.100, and white space Wi-Fi bands between 2.38 to 2.68 GHz, respectively. At 2.100 GHz, the proposed RF harvester achieved a maximum (radio frequency direct current) RF-to-DC power conversion efficiency (PCE) of 73.00% and an output DC voltage $$V_{DC}$$ V DC of 1.61 V for an RF power of 2 dBm. The outdoor performance of the rectenna shows a $$V_{DC}$$ V DC of 0.440 V and drives a low-power bq25504-674 evaluation module (EVM) at 1.362 V. The dimension of the RF-rectifier on the FR-4 PCB board is 0.27 $$\lambda _{g}$$ λ g $$\times$$ × 0.29 $$\lambda _{g}$$ λ g . The RF-rectifier demonstrates the capacity to effectively utilize the frequency domain by employing multi-band operation and exhibiting a good impedance bandwidth through a sequential matching technique. Thus, by effectively controlling the rectenna’s ambient performance, the proposed design holds the potential for powering a range of low-power biomedical implantable devices. (BIDs).

Abstract Upper Egypt experiences high temperatures during summer and low temperatures during winter, which significantly impacts the sowing dates of maize in this region. The productivity of maize crops and water use efficiency can be greatly affected by water stress and sowing dates (SDs). Therefore, it is crucial to determine the optimal irrigation level and SDs based on local conditions. To assess the effects, two irrigation levels were employed: (1) control (full irrigation water applied) and (2) 70% of irrigation water. Field experiments were conducted at the National Water Research Center's water studies and research complex station in Toshka. The aim was to evaluate two irrigation levels (full and limited irrigation) across five SDs (early: mid-February and March, normal: mid-June, and late: mid-August and September) in both 2019 and 2020, in order to identify the ideal sowing date (SD) and irrigation level. The normal SD resulted in an increased the growth season length between plant emergence and maturity. Conversely, the late SD reduced the number of days until plant maturity, resulting in higher grain yields and water use efficiency (WUE). Notably, the SD in September, coupled with the 70% irrigation level, yielded the highest productivity and WUE, with a productivity of 7014 kg ha−1 and a WUE of 0. 9 kg m−3. Based on the findings, it is recommended that regions with similar conditions consider cultivating maize seeds in September, adopting a 70% irrigation level, to achieve optimal N uptake, growth traits (plant height, ear length, ear weight, number of rows per ear, and grain index weight), yield, and WUE.

Abstract The control of malaria parasite transmission from mosquitoes to humans is hampered by decreasing efficacies of insecticides, development of drug resistance against the last-resort antimalarials, and the absence of effective vaccines. Herein, the anti-plasmodial transmission blocking activity of a recombinant Aspergillus oryzae (A. oryzae-R) fungus strain, which is used in human food industry, was investigated in laboratory-reared Anopheles stephensi mosquitoes. The recombinant fungus strain was genetically modified to secrete two anti-plasmodial effector peptides, MP2 (midgut peptide 2) and EPIP (enolase-plasminogen interaction peptide) peptides. The transstadial transmission of the fungus from larvae to adult mosquitoes was confirmed following inoculation of A. oryzae-R in the water trays used for larval rearing. Secretion of the anti-plasmodial effector peptides inside the mosquito midguts inhibited oocyst formation of P. berghei parasites. These results indicate that A. oryzae can be used as a paratransgenesis model carrying effector proteins to inhibit malaria parasite development in An. stephensi. Further studies are needed to determine if this recombinant fungus can be adapted under natural conditions, with a minimal or no impact on the environment, to target mosquito-borne infectious disease agents inside their vectors.

Abstract Biomass waste streams are a possible feedstock for a range of eco-friendly products and a crucial alternative energy source for achieving carbon neutrality; therefore, the efficient management of biomass waste has taken on a greater significance in recent years. Due to its well-comparable physic-chemical properties with fossil diesel, biodiesel is a potential substitute for fossil fuel. This study aimed to synthesize biodiesel from the widely available non-edible seed oil of Sisymbrium irio L. (a member of the Brassicaceae family) via a transesterification procedure over a homemade TiO2 catalyst. At 1:16 oil to methanol ratio, 93% biodiesel yield was obtained over 20 mg catalyst at 60 °C and 60 min. The ASTM methods were used to analyze the fuel properties. The quantitative and qualitative analysis was performed by FT-IR, GC-MS, and NMR spectroscopy. GC-MS study confirms 16 different types of fatty acids of methyl esters. FT-IR analysis showed important peaks that confirm the successful occurrence of biodiesel. 1H-NMR and 13C-NMR showed important peaks for converting triglycerides into corresponding FAMEs. The acid value (0.42 mg KOH/mg/kg), flash point (106 °C), and water content (0.034) of biodiesel are below the specified limit of ASTM D6751 whereas kinetic viscosity (3.72 mm2/s), density (0.874 kg/L), cloud point (− 4.3 °C) and pour point (− 9.6 °C) and high heating value (41.62 MJ/kg) fall within the specified range of ASTM D6751 test limit. The Unsaturation degree and oxidative stability of biodiesel are above ASTM D6751 test limit. The physic-chemical properties of the SIB confirm that it is eco-friendly fuel and a competitive source for manufacturing biodiesel on a commercial scale. Furthermore, the SIB is engine friendly and has good fuel efficacy.

Abstract Studying the power quality (PQ) is an essential issue to ensure the safe and accurate operation of sensitive equipment particularly for nuclear installations. Assessment of PQ involves collecting and analysing data resources and then evaluating it with reference to PQ standards. There are many alternatives for PQ and it is difficult to make an appropriate selection among them in the existence of their multiple criteria which are usually conflicted. So this selection subject can be classified as a Multi Criteria Decision Making (MCDM) problem. To do so, a reliable and scientific method for studying and evaluating the overall system PQ is required. This study aims to assess performance of PQ for the electrical power system at a Nuclear Research Reactor (NRR) during a certain period using multiple measures for the most decisive PQ phenomena. It focuses on a number of the most important PQ phenomena namely frequency fluctuation (deviation), unbalances of current and voltage, current and voltage harmonic distortion, flicker and power factor. After combining all results into six samples (alternatives), the criteria weights are determined based on an objective method for weighting which is called CRITIC method. Then, the alternatives are ranked using compromise MCDM method-VIKOR method. The obtained results are analyzed and discussed to evaluate performance of NRR electrical system from the PQ view. It showed that the compromise solution that obtained by CRITIC-VIKOR can be a guide to facilitate the PQ evaluation of nuclear installation electrical system. Also, it can empower the operators with the benefits of benchmarking and monitoring a single index instead of several indices. Moreover, it is very useful for helping stakeholders to understand how the PQ performance changes under a certain operating condition of the facility. Finally, it is can be considered as a good model to weight each PQ phenomena and identify the time intervals for best and worst total PQ in NRR.

Abstract This paper investigates the ability to use a finite one-dimensional phononic crystal composed of branched open resonators with a horizontal defect to detect the concentration of harmful gases such as CO2. This research investigates the impact of periodic open resonators, defect duct at the center of the structure, and geometrical parameters such as cross-sections and length of the primary waveguide and resonators on the model's performance. As far as we know, this research is unique in the sensing field. Furthermore, these simulations show that the investigated finite one-dimensional phononic crystal composed of branched open resonators with a horizontal defect is a promising sensor.

Abstract The Eastern Mediterranean region, extending from the Offshore Nile Delta Cone of Egypt to the Levant Basin, is a confirmed hydrocarbon-rich territory with several giant gas discoveries. Numerous gas fields have been discovered in the Miocene reservoirs within the Nile Delta Cone, and the Levant Basin. The Miocene sedimentary sequences in this region are extremely heterogeneous, consisting mainly of turbiditic slope deposits, channels, and basin floor fans that were capped by evaporites formed during the Messinian Salinity Crisis. As a result, the seismic characteristics and interpreted properties of this heterogeneous section are ambiguous. The study area is located in the Offshore North Sinai Basin, where a thick Early Miocene section was deposited midway between the Nile Delta province, which includes the El-Fayrouz discovery, and the Levant Basin, which includes Tamar, Tanin, and several other discoveries. This study uses quantitative seismic interpretations methods, such as amplitude variations with offset and fluid replacement modeling, to assess the seismic acoustic impedance trend with depth. Also, determine the seismic amplitude response for the brine and gas sands reservoir of the Early and Late Miocene section to link the unexplored study area within the North Sinai Offshore Basin with the explored Nile Delta and Levant Basins. In addition to evaluate direct hydrocarbon indicator (DHI) of the dimming seismic amplitude that is compatible with the structure’s last closed contour of the Syrian Arc anticline of the Early Miocene reservoirs (EMT-1 prospect). Different vintages of 2D and 3D seismic data, six wells, and various published data were used in this study. The quantitative interpretation shows the pitfalls of the acoustic impedance trend and seismic response dependency on depth for gas and brine sand, which led to the drilling of the EMT-1 dry well. Also, the fluid replacement, P-wave velocity (Vp), and density (ρ) modeling confirmed that the seismic dimming amplitude was due to a seismic processing artifact, which was corrected by readjusting the overburden Messinian salt processing velocity model. This research concludes that the seismic quantitative interpretations are successfully used to assess the acoustic impedance versus depth and understand DHI pitfalls, as well as the processing workflow that could enhance the seismic image.

Abstract Molnupiravir (MPV) is the first direct-acting oral antiviral drug that effectively decreases nasopharyngeal infections with SARS-CoV-2 virus. The stability of MPV was tested by subjecting the drug to various stress conditions. The drug is liable to oxidative, acidic, and alkaline degradation and showed significant stability against thermal degradation. Mass spectrometry identified the degradation products and guided suggestion of the degradation patterns. Interestingly, while inspecting the UV-absorption spectra, we observed no absorbance at 270 nm for the products of the three degradation pathways (c.f. intact MPV). Direct spectrophotometry seemed a solution that perfectly fit the purpose of the stability assay method in our case. It avoids sophisticated instrumentation and complex mathematical data manipulation. The method determined MPV accurately (100.32% ± 1.62) and selectively (99.49% ± 1.63) within the linear range of 1.50 × 10–5–4.0 × 10–4 M and down to a detection limit of 0.48 × 10–5 M. The proposed method is simple and does not require any preliminary separation or derivatization steps. The procedure proved its validity as per the ICH recommendations. The specificity was assessed in the presence of up to 90% degradation products. The study evaluated the greenness profile of the proposed analytical procedure using the National Environmental Methods Index (NEMI), the Analytical Eco-Scale, and the Green Analytical Procedure Index (GAPI). The three metrics unanimously agreed that the developed procedure results in a greener profile than the reported method. The method investigated the degradation reactions' kinetics and evaluated the reaction order, rate constant, and half-life time for each degradation process.

Abstract Adoptive immune therapies based on the transfer of antigen-specific T cells have been used successfully to treat various cancers and viral infections, but improved techniques are needed to identify optimally protective human T cell receptors (TCRs). Here we present a high-throughput approach to the identification of natively paired human TCRα and TCRβ (TCRα:β) genes encoding heterodimeric TCRs that recognize specific peptide antigens bound to major histocompatibility complex molecules (pMHCs). We first captured and cloned TCRα:β genes from individual cells, ensuring fidelity using a suppression PCR. We then screened TCRα:β libraries expressed in an immortalized cell line using peptide-pulsed antigen-presenting cells and sequenced activated clones to identify the cognate TCRs. Our results validated an experimental pipeline that allows large-scale repertoire datasets to be annotated with functional specificity information, facilitating the discovery of therapeutically relevant TCRs.

Abstract This study examined the effect of varying concentrations of Ocimum basilicum aqueous extract, which was done via the green synthesis of Silver nanoparticles (AgNPs), on the identification of the most effective concentration for bacteria inhibitory activity. Different concentrations of the aqueous Ocimum basilicum extract (0.25, 0.50, 0.75 and 1.00 mM) were used as reducing and stabilizing agent to synthesize AgNPs by means of the reduction method. The crystal structure and morphology of the NPs were characterized UV–Vis spectra, X-ray diffraction (XRD) and scanning electron microscopy (SEM). The antibacterial efficacy of AgNPs was studied against E. coli ATCC 35218 using well diffusion, MIC, MBC, and time-kill curve. The dark yellow color of the Ocimum basilicum aqueous solution indicates the successful synthesis process of the AgNPs. UV-spectra of the AgNPs display a gradual increase of absorption in sequence with concentration increase of aqueous Ocimum basilicum extract solution from 0.25 to 1.00 mM. This, in turn, led to a shift in the wavelength from 488 to 497 nm, along with a change in the nanoparticle size from 52 to 8 nm. The tests also showed a high activity of the particles against bacteria (E. coli), ranging between 15.6 and 62.5 µg/ml. Based on AgNPs, it was confirmed that an aqueous Ocimum basilicum extract can be used as an effective, reducing and stabilizing agent for the synthesis of different sizes of AgNPs based on the solvent concentration. The AgNPs also proved to be effective in inhibiting and killing bacteria.

Abstract This paper introduces a multi-input multiple-output (MIMO) antenna array system that provides improved radiation diversity for multi-standard/multi-mode 5G communications. The introduced MIMO design contains four pairs of miniaturized self-complementary antennas (SCAs) fed by pairs of independently coupled structures which are symmetrically located at the edge corners of the smartphone mainboard with an overall size of 75 × 150 (mm2). Hence, in total, the design incorporates four pairs of horizontally and vertically polarized resonators. The elements have compact profiles and resonate at 3.6 GHz, the main candidate bands of the sub-6 GHz 5G spectrum. In addition, despite the absence of decoupling structures, adjacent elements demonstrate high isolation. To the best of the authors’ knowledge, it is the first type of smartphone antenna design using dual-polarized self-complementary antennas that could possess anti-interference and diversity properties. In addition to exhibiting desirable radiation coverage, the presented smartphone antenna also supports dual polarizations on different sides of the printed circuit board (PCB). It also exhibits good isolation, high-gain patterns, improved radiation coverage, low ECC/TARC, and sufficient channel capacity. The introduced antenna design was manufactured on a standard smartphone board and its main characteristics were experimentally measured. Simulations and measurement results are generally in good agreement with each other. Moreover, the presented antenna system delivers low SAR with adequate efficiency when it comes to the appearance of the user. Hence, the design could be adapted to 5G hand-portable devices. As an additional feature, a new ultra-compact phased array millimeter-wave antenna with super-wide bandwidth and end-fire radiation is being introduced for integration into the MIMO antenna systems. As a result, the proposed antenna system design with improved radiation and multi-standard operation is a good candidate for future multi-mode 5G cellular applications.

Abstract Breast cancer (BC) is spreading more and more every day. Therefore, a patient's life can be saved by its early discovery. Mammography is frequently used to diagnose BC. The classification of mammography region of interest (ROI) patches (i.e., normal, malignant, or benign) is the most crucial phase in this process since it helps medical professionals to identify BC. In this paper, a hybrid technique that carries out a quick and precise classification that is appropriate for the BC diagnosis system is proposed and tested. Three different Deep Learning (DL) Convolution Neural Network (CNN) models—namely, Inception-V3, ResNet50, and AlexNet—are used in the current study as feature extractors. To extract useful features from each CNN model, our suggested method uses the Term Variance (TV) feature selection algorithm. The TV-selected features from each CNN model are combined and a further selection is performed to obtain the most useful features which are sent later to the multiclass support vector machine (MSVM) classifier. The Mammographic Image Analysis Society (MIAS) image database was used to test the effectiveness of the suggested method for classification. The mammogram's ROI is retrieved, and image patches are assigned to it. Based on the results of testing several TV feature subsets, the 600-feature subset with the highest classification performance was discovered. Higher classification accuracy (CA) is attained when compared to previously published work. The average CA for 70% of training is 97.81%, for 80% of training, it is 98%, and for 90% of training, it reaches its optimal value. Finally, the ablation analysis is performed to emphasize the role of the proposed network’s key parameters.

Abstract Both gallic and citrate are well-established antioxidants that show promise as new selective anti-cancer drugs. Gold nanoparticles (AuNPs) as well can be developed as flexible and nontoxic nano-carriers for anti-cancer drugs. This article evaluating the efficiency and biocompatibility of gallic acid and citrate capping gold nanoparticles to be used as anti-cancer drug. The biosafety and therapeutic efficiency of prepared nano-formulations were tested on Hela and normal BHK cell line. Gold nanospheres coated with citrate and gallate were synthesized via wet chemical reduction method. The prepared nano-formulations, citrate and gallate coated gold nanospheres (Cit-AuNPs and Ga-AuNPs), were characterized with respect to their morphology, FTIR spectra, and physical properties. In addition, to assess their cytotoxicity, cell cycle arrest and flow cytometry to measure biological response were performed. Cit-Au NPs and Ga-Au NPs were shown to significantly reduce the viability of Hela cancer cells. Both G0/G cell cycle arrest and comet assay results showed that genotoxic effect was induced in Hela cells by Cit-Au NPs and Ga-Au NPs. The results of this study showed that Cit-Au NPs and Ga-AuNPs inhibit the growth of metastatic cervical cancer cells, which could have therapeutic implications.

Abstract The study was aimed to evaluate the performance of a newly developed spectroscopy-based non-invasive and noncontact device (SAMIRA) for the simultaneous measurement of hemoglobin, bilirubin and oxygen saturation as an alternative to the invasive biochemical method of blood sampling. The accuracy of the device was assessed in 4318 neonates having incidences of either anemia, jaundice, or hypoxia. Transcutaneous bilirubin, hemoglobin and blood saturation values were obtained by the newly developed instrument which was corroborated with the biochemical blood tests by expert clinicians. The instrument is trained using Artificial Neural Network Analysis to increase the acceptability of the data. The artificial intelligence incorporated within the instrument determines the disease condition of the neonate. The Pearson’s correlation coefficient, r was found to be 0.987 for hemoglobin estimation and 0.988 for bilirubin and blood gas saturation respectively. The bias and the limits of agreement for the measurement of all the three parameters were within the clinically acceptance limit.

Abstract Wound healing is a well-organized dynamic process involving coordinated consecutive phases: homeostasis, inflammation, proliferation and resolution. Fibroblasts play major roles in skin wound healing such as in wound contraction and release of growth factors which are of importance in angiogenesis and tissue remodeling. Abnormal fibroblast phenotypes have been identified in patients with chronic wounds. In this work, we analyzed scRNA-seq datasets of normal and wounded skin from mice at day 4 post-wound to investigate fibroblast heterogeneity during the proliferative phase of wound healing. Compositional analysis revealed a specific subset of fibroblast (cluster 3) that primarily increased in wounded skin (14%) compared to normal skin (3.9%). This subset was characterized by a gene signature marked by the plasma membrane proteins Sfrp2 + Sfrp4 + Sfrp1 + and the transcription factors Ebf1 + Prrx1 + Maged1 + . Differential gene expression and enrichment analysis identified epithelial to mesenchymal transition (EMT) and angiogenesis to be upregulated in the emerging subset of fibroblasts of the wounded skin. Using two other datasets for murine wounded skin confirmed the increase in cluster 3-like fibroblasts at days 2, 7 and 14 post-wounding with a peak at day 7. By performing a similarity check between the differential gene expression profile between wounded and normal skin for this emerging fibroblast subset with drug signature from the ConnectivityMap database, we identified drugs capable of mimicking the observed gene expression change in fibroblasts during wound healing. TTNPB, verteprofin and nicotinic acid were identified as candidate drugs capable of inducing fibroblast gene expression profile necessary for wound healing. On the other hand, methocarbamol, ifosfamide and penbutolol were recognized to antagonize the identified fibroblast differential expression profile during wound healing which might cause delay in wound healing. Taken together, analysis of murine transcriptomic skin wound healing datasets suggested a subset of fibroblasts capable of inducing EMT and further inferred drugs that might be tested as potential candidates to induce wound closure.

Abstract This study characterized population-level trends and associations with hepatitis C virus (HCV) antibody (Ab) prevalence in the Middle East and North Africa (MENA). Data source was the standardized and systematically gathered MENA HCV Epidemiology Synthesis Project Database. Random-effects univariable and multivariable meta-regressions were conducted. 2,621 HCV Ab prevalence measures on 49,824,108 individuals were analyzed. In the analysis including all populations, 71% of the variation in prevalence was explained, mostly by at-risk population type. Compared to the general population, prevalence was 23-fold higher among people who inject drugs, and 14-fold higher among high-risk clinical populations. In the analysis including only the general population, 67% of the variation in prevalence was explained, mostly by country/subregion. Compared to Afghanistan, prevalence was highest in Egypt and Pakistan. Prevalence in the general population was declining at a rate of 4% per year, but outside the general population, the decline was at only 1% per year. HCV Ab prevalence in MENA is declining rapidly, but this decline is largely occurring in the general population following introduction of blood and injection safety measures. The decline in populations at higher risk of exposure is slow and below the level needed to achieve HCV elimination by 2030.

Abstract Metabolic syndrome (MetS) is a phenotype caused by the interaction of host intrinsic factors such as genetics and gut microbiome, and extrinsic factors such as diet and lifestyle. To demonstrate the interplay of intestinal microbiota with obesity, MetS markers, and some dietary ingredients among samples of Egyptian women. This study was a cross-sectional one that included 115 Egyptian women; 82 were obese (59 without MetS and 23 with MetS) and 33 were normal weight. All participants were subjected to anthropometric assessment, 24 h dietary recall, laboratory evaluation of liver enzymes (AST and ALT), leptin, short chain fatty acids (SCFA), C-reactive protein, fasting blood glucose, insulin, and lipid profile, in addition to fecal microbiota analysis for Lactobacillus, Bifidobacteria, Firmicutes, and Bacteroid. Data showed that the obese women with MetS had the highest significant values of the anthropometric and the biochemical parameters. Obese MetS women consumed a diet high in calories, protein, fat, and carbohydrate, and low in fiber and micronutrients. The Bacteroidetes and Firmicutes were the abundant bacteria among the different gut microbiota, with low Firmicutes/Bacteroidetes ratio, and insignificant differences between the obese with and without MetS and normal weight women were reported. Firmicutes/Bacteroidetes ratio significantly correlated positively with total cholesterol and LDL-C and negatively with SCFA among obese women with MetS. Findings of this study revealed that dietary factors, dysbiosis, and the metabolic product short chain fatty acids have been implicated in causing metabolic defects.

Abstract An intact epithelium is key to maintaining corneal integrity and barrier function which can lead to impaired ocular defense and sight-threatening opacity when compromised. Electrical cell-substrate impedance sensing or ECIS is a non-invasive method to measure real-time cellular behaviors including barrier function and cell migration. The current study uses ECIS technology to assess and optimize human telomerase-immortalized corneal epithelial cells to generate quantifiable measurements that accurately reflect changes in cell behavior in vitro. Five cell densities were assessed in two different media to determine the optimal conditions for monitoring of cellular behavior over time. Parameters of evaluation included: overall impedance (Z), barrier resistance (R), cell capacitance (C), and mathematical modeling of the R data to further generate Rb (the electrical resistance between HUCLs), α (the resistance between the HUCLs and the substrate), and Cm (the capacitance of the cell membrane) measurements. All parameters of assessment strongly indicated DMEM/F12 at 60,000 cells as the optimal condition for ECIS assessment of HUCLs. Furthermore, this work highlights the ability of the sensitive ECIS biosensor technology to comprehensively and quantitatively assess corneal epithelial cell structure and function and the importance of optimizing not only cell density, but choice of media used for in vitro culturing.