Search Results (29)

Background/Objectives: Natural therapeutics for the treatment of diabetes mellitus represent a common challenge for many researchers. Thus, the aim of this study was to evaluate the antihyperglycemic and anti-inflammatory effects and the hepatic antioxidant activities of both diosmin and linagliptin on nicotinamide/streptozotocin-induced diabetes mellitus in rats. Methods: Induction of diabetes mellitus was produced by injecting an intraperitoneal dose of nicotinamide (60 mg/kg) to 16-hour-fasted rats, then after 15 min, an intraperitoneal dose of streptozotocin (60 mg/kg) was injected. The rats with diabetes were orally treated with linagliptin (1 mg/kg), diosmin (10 mg/kg), and both of them every other day for 4 weeks. Results: The elevated hepatic glucose-6-phosphatase and glycogen phosphorylase activities, the lowered concentrations of serum insulin, C-peptide, and hepatic glycogen, and the diminished hepatic antioxidant defense system of nicotinamide/streptozotocin-induced diabetic rats were all potentially improved by the therapies. The treatments also improved the deteriorated adiponectin and resistin mRNA expression in visceral adipose tissue of nicotinamide/streptozotocin-induced diabetic rats. In addition, the treatments induced a recovery of damaged islets of Langerhans and a regeneration of islet cells in association with the enhancement of the formation of insulin granules in β-cells and the improvement of kidney function; the combined effect was the most potent. Conclusions: Diosmin alone or in combination with linagliptin has potent antidiabetic effects, which were managed through their insulinotropic and insulin-improving actions. The diosmin in combination with linagliptin has the most potent antihyperglycemic effects. Full article

Background/Objectives: The most used antipyretic and pain relief treatment is paracetamol (acetaminophen), also known as N-acetyl-para-aminophenol (APAP). However, it is considered potentially hazardous if consumed repeatedly in large doses or over prolonged periods. This investigation explores the effectiveness of hesperidin (Hesp) and Hesp loaded on layered double hydroxide nanoparticles (Hesp-NPs) in inhibiting the progression of acute hepatotoxicity in rats induced by APAP. Methods: LDH-Hesp-NPs were prepared and characterized. Male Wistar rats were orally treated with Hesp and Hesp-NPs at the same adjusted dose (100 mg/kg) every other day for six weeks. After 2 h of the first doses of Hesp and Hesp-NPs, the rats received one oral dose of APAP (750 mg/kg). Results: Administering of Hesp and Hesp-NPs to APAP-treated rats significantly reduced oxidant parameter (malondialdehyde) and serum enzymes (ALT, AST, LDH, and ALP) associated with liver function. Antioxidant markers in the liver, such as catalase and glutathione, also increased notably. Moreover, Hesp and Hesp-NPs enhanced the mRNA expression of liver UGT1A6, IL-10, and HO-1. Conversely, the mRNA expressions of liver CYP1A1, KEAP1, TGF-β, P53, and BAX decreased. These improvements in biochemical and molecular markers were corroborated by liver histopathology. Conclusions: Hesp and Hesp-NPs protect significantly against APAP-induced hepatotoxicity in male Wistar rats. Hesp-NPs treatment was more potent. The protective effects may be mediated via modulation of APAP biotransformation, oxidative stress, inflammation and apoptosis. Full article

This study investigated the effects of the β-mannanase enzyme and soyhulls on production performance, economics, egg quality, hematology and serum biochemistry, nutrient digestibility, gut morphology, digesta viscosity, and excreta consistency in laying hens during the late peak production phase (37 to 40 weeks of age). Golden brown hens (RIR × Fayoumi; n = 200) were fed a control diet (no soyhulls or enzymes) and diets containing four combinations, i.e., 3% soyhulls with 20 mg/kg β-mannanase (D1), 3% soyhulls with 30 mg/kg β-mannanase (D2), 9% soyhulls with 20 mg/kg β-mannanase (D3), and 9% soyhulls with 30 mg/kg β-mannanase (D4), for four weeks in four replicates of 10 birds each. Overall, a significantly higher (p < 0.05) feed intake, weight gain, feed conversion ratio, and water intake were calculated in the D2 group as compared to the control and remaining combinations of soyhulls and β-mannanase. No mortality was recorded during the entire experiment. Economically, the D1 and D2 groups showed the best results as compared to the D3 and D4 groups. Egg quality parameters like egg weight, shell weight and shell thickness, yolk weight, albumen weight and height, and the Haugh unit remained unchanged (p > 0.05). Similarly, the D2 group showed significantly lower total cholesterol, LDL, and VLDL levels and enhanced gut morphology with greater villus width, height, crypt depth, and surface area across intestinal segments. Crude protein (CP), crude fiber (CF), crude fat, and ash digestibility were higher (p < 0.05) in the D1 and D2 groups compared to the control. Digesta viscosity, excreta consistency, and other egg quality parameters remained unaffected. In conclusion, the dietary inclusion of a combination of 3% soyhulls and 30 mg/kg β-mannanase may have potential benefits for laying hens by improving some production performance and egg quality indicators and economics, lowering blood cholesterol, LDL, and VLDL levels, enhancing nutrient digestibility, and improving gut morphology without affecting egg quality. Full article

Comprehension of the long-term effects of irrigation on basic soil characteristics and quality is essential for sustainable land management and agricultural production, particularly in arid regions where water availability is limited. This study aimed to investigate long-term irrigation effects on soil quality, soil organic carbon (SOC), and nitrogen (N) stocks in the arid lands of Egypt. Seventy soil samples were collected and analyzed to determine various soil properties. A soil quality index (SQI), SOC, and N stocks were computed. ANOVA and PCA analyses were used to identify significant differences between alluvial soils in the southwest part of the investigated area and coastal marine soils in the northeast of the study area. The results demonstrated that most of the studied soil parameters had significantly greater values in alluvial compared to coastal marine soils. Long-term irrigation led to an 8.00% increase in SOC and 7.22% increase in N stocks compared to coastal marine soils production. Furthermore, a 39.53% increase was found in the SQI upon long-term irrigation practice. These results suggest that shifting from rain-fed in coastal marine areas to irrigated production systems in alluvial fields can improve soil quality, SOC, and N stocks. Therefore, further studies are required to investigate the impact of additional factors, such as irrigation method and salinity status of sub-surface soil layers, to enhance agricultural productivity and sustainable land use. Full article

The COVID-19 epidemic poses a worldwide threat that transcends provincial, philosophical, spiritual, radical, social, and educational borders. By using a connected network, a healthcare system with the Internet of Things (IoT) functionality can effectively monitor COVID-19 cases. IoT helps a COVID-19 patient recognize symptoms and receive better therapy more quickly. A critical component in measuring, evaluating, and diagnosing the risk of infection is artificial intelligence (AI). It can be used to anticipate cases and forecast the alternate incidences number, retrieved instances, and injuries. In the context of COVID-19, IoT technologies are employed in specific patient monitoring and diagnosing processes to reduce COVID-19 exposure to others. This work uses an Indian dataset to create an enhanced convolutional neural network with a gated recurrent unit (CNN-GRU) model for COVID-19 death prediction via IoT. The data were also subjected to data normalization and data imputation. The 4692 cases and eight characteristics in the dataset were utilized in this research. The performance of the CNN-GRU model for COVID-19 death prediction was assessed using five evaluation metrics, including median absolute error (MedAE), mean absolute error (MAE), root mean squared error (RMSE), mean square error (MSE), and coefficient of determination (R²). ANOVA and Wilcoxon signed-rank tests were used to determine the statistical significance of the presented model. The experimental findings showed that the CNN-GRU model outperformed other models regarding COVID-19 death prediction. Full article

The paper focuses on the hepatitis C virus (HCV) infection in Egypt, which has one of the highest rates of HCV in the world. The high prevalence is linked to several factors, including the use of injection drugs, poor sterilization practices in medical facilities, and low public awareness. This paper introduces a hyOPTGB model, which employs an optimized gradient boosting (GB) classifier to predict HCV disease in Egypt. The model’s accuracy is enhanced by optimizing hyperparameters with the OPTUNA framework. Min-Max normalization is used as a preprocessing step for scaling the dataset values and using the forward selection (FS) wrapped method to identify essential features. The dataset used in the study contains 1385 instances and 29 features and is available at the UCI machine learning repository. The authors compare the performance of five machine learning models, including decision tree (DT), support vector machine (SVM), dummy classifier (DC), ridge classifier (RC), and bagging classifier (BC), with the hyOPTGB model. The system’s efficacy is assessed using various metrics, including accuracy, recall, precision, and F1-score. The hyOPTGB model outperformed the other machine learning models, achieving a 95.3% accuracy rate. The authors also compared the hyOPTGB model against other models proposed by authors who used the same dataset. Full article

Nanotechnology has proven advantageous in numerous scientific applications, one being to enhance the delivery of chemotherapeutic agents. This present study aims to evaluate the mechanisms underlying the chemopreventive action of naringin–dextrin nanocomposites (Nar-Dx-NCs) against diethylnitrosamine (DEN)/2-acetylaminofluorene (2AAF)-induced lung carcinogenesis in male Wistar rats. DEN was administered intraperitoneally (i.p.) (150 mg/kg/week) for two weeks, followed by the oral administration of 2AAF (20 mg/kg) four times a week for three weeks. Rats receiving DEN/2AAF were concurrently treated with naringin or Nar-Dx-NCs orally at a dose of 10 mg/kg every other day for 24 weeks. Naringin and Nar-Dx-NCs treatments prevented the formation of tumorigenic cells within the alveoli of rats exposed to DEN/2AAF. These findings were associated with a significant decrease in lipid peroxidation, upregulation of antioxidant enzyme (glutathione peroxidase and superoxide dismutase) activity, and enhanced glutathione and nuclear factor erythroid 2–related factor 2 expression in the lungs. Naringin and Nar-Dx-NCs exerted anti-inflammatory actions manifested by a decrease in lung protein expression of tumor necrosis factor-α and interleukin-1β and mRNA expression of interleukin-6, interferon-γ, nuclear factor-κB, and inducible nitric oxide synthase, with a concurrent increase in interleukin-10 expression. The anti-inflammatory effect of Nar-Dx-NCs was more potent than naringin. Regarding the effect on apoptosis, both naringin and Nar-Dx-NCs significantly reduced Bcl-2 and increased Bax and P53 expressions. Moreover, naringin or Nar-Dx-NCs induced a significant decrease in the expression of the proliferator marker, Ki-67, and the effect of Nar-Dx-NCs was more marked. In conclusion, Nar-Dx-NCs improved naringin’s preventive action against DEN/2AAF-induced lung cancer and exerted anticarcinogenic effects by suppressing oxidative stress and inflammation and improving apoptotic signal induction and propagation. Full article

In this study, cobalt neurotoxicity was investigated in human astrocytoma and neuroblastoma (SH-SY5Y) cells using proliferation assays coupled with LC–MS-based metabolomics and transcriptomics techniques. Cells were treated with a range of cobalt concentrations between 0 and 200 µM. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay revealed cobalt cytotoxicity and decreased cell metabolism in a dose and time-dependent manner was observed by metabolomics analysis, in both cell lines. Metabolomic analysis also revealed several altered metabolites particularly those related to DNA deamination and methylation pathways. One of the increased metabolites was uracil which can be generated from DNA deamination or fragmentation of RNA. To investigate the origin of uracil, genomic DNA was isolated and analyzed by LC–MS. Interestingly, the source of uracil, which is uridine, increased significantly in the DNA of both cell lines. Additionally, the results of the qRT-PCR showed an increase in the expression of five genes Mlh1, Sirt2, MeCP2, UNG, and TDG in both cell lines. These genes are related to DNA strand breakage, hypoxia, methylation, and base excision repair. Overall, metabolomic analysis helped reveal the changes induced by cobalt in human neuronal-derived cell lines. These findings could unravel the effect of cobalt on the human brain. Full article

Cannabis use is widespread and is one of the most common drugs encountered in forensic-related analysis (antemortem and postmortem cases). However, the correlation between illicit cannabis use and death is rarely investigated, even while taking into consideration its role in the central nervous system depression and cardiovascular disorders. Few studies have discussed other non-blood specimens; this has brought a special interest in analyzing THC and its metabolites in different body parts in order to make precise forensic decisions. Herein, we are investigating the presence of Δ⁹-tetrahydrocannabinol (THC) and its metabolites:(11-hydroxy-Δ⁹-tetrahydrocannabinol (THC-OH) and 11-nor-Δ⁹- tetrahydrocannabinol-9-carboxy (THC-COOH)) in different postmortem specimens. Forty-three cases of bodily fluids and tissue post-mortem samples, previously found to be cannabinoid-positive were analyzed in the current investigation using alkaline hydrolysis followed by solid phase extraction and LC-MS/MS for THC and its metabolites concentration. In the current study, the highest median THC-COOH and THC-OH concentrations were detected in bile samples (1380 ng/mL and 8 ng/mL, respectively), while the highest THC median concentration was detected in gastric contents (48 ng/mL). This can be explained due to the postmortem distribution of blood to other bodily fluids and tissues and the accumulation in bile following multiple doses. Furthermore, high THC levels in gastric contents can be explained by the undergoing cycles of entero-hepatic circulation which resulted in a significant increase in THC in gastric contents. THC-COOH can be the best indicator to detect cannabinoids in toxicology studies, thus the inclusion of active THC metabolites is essential in death investigations. Additionally, THC-OH concentrations in postmortem cases could be influenced by body mass index. In this study, all types were specimens found to be suitable for testing cannabinoid metabolites, except for vitreous humor which showed low rates of detectability for cannabinoid metabolites. Full article

This study highlights the use of ⁸⁹Zr-oxalate in diagnostic applications with the help of WinAct and IDAC2.1 software. It presents the biodistribution of the drug in various organs and tissues, including bone, blood, muscle, liver, lung, spleen, kidneys, inflammations, and tumors, and analyzes the maximum amount of nuclear transformation per Bq intake for each organ. The retention time of the maximum nuclear transformation and the absorbed doses of the drug in various organs and tissues are also examined. Data from clinical and laboratory studies on radiopharmaceuticals are used to estimate the coefficients of transition. The accumulation and excretion of the radiopharmaceutical in the organs is assumed to follow an exponential law. The coefficients of transition from the organs to the blood and vice versa are estimated using a combination of statistical programs and digitized data from the literature. WinAct and IDAC 2.1 software are used to calculate the distribution of the radiopharmaceutical in the human body and to estimate the absorbed doses in organs and tissues. The results of this study can provide valuable information for the biokinetic modeling of wide-spectrum diagnostic radiopharmaceuticals. The results show that ⁸⁹Zr-oxalate has a high affinity for bones and a relatively low impact on healthy organs, making it helpful in targeting bone metastases. This study provides valuable information for further research on the development of this drug for potential clinical applications. Full article

Solar cells in superstrate arrangement need a protective cover glass as one of its main components. The effectiveness of these cells is determined by the cover glass’s low weight, radiation resistance, optical clarity, and structural integrity. Damage to the cell covers brought on by exposure to UV irradiation and energetic radiation is thought to be the root cause of the ongoing issue of a reduction in the amount of electricity that can be generated by solar panels installed on spacecraft. Lead-free glasses made of xBi₂O₃–(40 − x)CaO-60P₂O₅ (x = 5, 10, 15, 20, 25, and 30 mol%) were created using the usual approach of melting at a high temperature. The amorphous nature of the glass samples was confirmed using X-ray diffraction. At energies of 81, 238, 356, 662, 911, 1173, 1332, and 2614 keV, the impact of various chemical compositions on gamma shielding in a phospho-bismuth glass structure was measured. The evaluation of gamma shielding revealed that the results of the mass attenuation coefficient of glasses increase as the Bi₂O₃ content increases but decrease as the photon energy increases. As a result of the study conducted on the radiation-deflecting properties of ternary glass, a lead-free low-melting phosphate glass that exhibited outstanding overall performance was developed, and the optimal composition of a glass sample was identified. The 60P₂O₅–30Bi₂O₃–10CaO glass combination is a viable option for use in radiation shielding that does not include lead. Full article

Blue carbon has made significant contributions to climate change adaptation and mitigation while assisting in achieving co-benefits such as aquaculture development and coastal restoration, winning international recognition. Climate change mitigation and co-benefits from blue carbon ecosystems are highlighted in the recent Intergovernmental Panel on Climate Change Special Report on Ocean and Cryosphere in a Changing Climate. Its diverse nature has resulted in unprecedented collaboration across disciplines, with conservationists, academics, and politicians working together to achieve common goals such as climate change mitigation and adaptation, which need proper policy regulations, funding, and multi-prong and multi-dimensional strategies to deal with. An overview of blue carbon habitats such as seagrass beds, mangrove forests, and salt marshes, the critical role of blue carbon ecosystems in mitigating plastic/micro-plastic pollution, as well as the utilization of the above-mentioned blue carbon resources for biofuel production, are critically presented in this research. It also highlights the concerns about blue carbon habitats. Identifying and addressing these issues might help preserve and enhance the ocean’s ability to store carbon and combat climate change and mitigate plastic/micro-plastic pollution. Checking out their role in carbon sequestration and how they act as the major carbon sinks of the world are integral parts of this study. In light of the global frameworks for blue carbon and the inclusion of microalgae in blue carbon, blue carbon ecosystems must be protected and restored as part of carbon stock conservation efforts and the mitigation of plastic/micro-plastic pollution. When compared to the ecosystem services offered by terrestrial ecosystems, the ecosystem services provided by coastal ecosystems, such as the sequestration of carbon, the production of biofuels, and the remediation of pollution, among other things, are enormous. The primary purpose of this research is to bring awareness to the extensive range of beneficial effects that can be traced back to ecosystems found in coastal environments. Full article

The main objective of this work is to recycle unwanted industrial waste in order to produce innovative nanocomposites with improved mechanical, tribological, and thermal properties for use in various industrial purposes. In this context, powder metallurgy (PM) technique was used to fabricate iron (Fe)/copper (Cu)/niobium carbide (NbC)/granite nanocomposites having outstanding mechanical, wear and thermal properties. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) examinations were used to investigate the particle size, crystal size, and phase composition of the milled samples. Additionally, it was investigated how different volume percentages of the NbC and granite affected the sintered specimens in terms of density, microstructure, mechanical and wear properties, and coefficient of thermal expansion (CTE). According to the findings, the milled powders included particles that were around 55 nm in size and clearly contained agglomerates. The results showed that the addition of 4 vol.% NbC and 8 vol.% granite nanoparticles caused a reduction in the Fe–Cu alloy matrix particle sizes up to 47.8 nm and served as a barrier to the migration of dislocations. In addition, the successive increase in the hybrid concentrations led to a significant decrease in the crystal size of the samples prepared as follows: 29.73, 27.58, 22.69, 19.95 and 15.8 nm. Furthermore, compared with the base Fe–Cu alloy, the nanocomposite having 12 vol.% of hybrid reinforcement demonstrated a significant improvement in the microhardness, ultimate strength, Young’s modulus, longitudinal modulus, shear modulus, bulk modulus, CTE and wear rate by 94.3, 96.4, 61.1, 78.2, 57.1, 73.6, 25.6 and 61.9%, respectively. This indicates that both NbC and granite can actually act as excellent reinforcements in the Fe alloy. Full article

Forecasting is defined as the process of estimating the change in uncertain situations. One of the most vital aspects of many applications is temperature forecasting. Using the Daily Delhi Climate Dataset, we utilize time series forecasting techniques to examine the predictability of temperature. In this paper, a hybrid forecasting model based on the combination of Wavelet Decomposition (WD) and Seasonal Auto-Regressive Integrated Moving Average with Exogenous Variables (SARIMAX) was created to accomplish accurate forecasting for the temperature in Delhi, India. The range of the dataset is from 2013 to 2017. It consists of 1462 instances and four features, and 80% of the data is used for training and 20% for testing. First, the WD decomposes the non-stationary data time series into multi-dimensional components. That can reduce the original time series’ volatility and increase its predictability and stability. After that, the multi-dimensional components are used as inputs for the SARIMAX model to forecast the temperature in Delhi City. The SARIMAX model employed in this work has the following order: (4, 0, 1). (4, 0, [1], 12). The experimental results demonstrated that WD-SARIMAX performs better than other recent models for forecasting the temperature in Delhi city. The Mean Square Error (MSE), Mean Absolute Error (MAE), Median Absolute Error (MedAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and determination coefficient ($R^2$) of the proposed WD-SARIMAX model are 2.8, 1.13, 0.76, 1.67, 4.9, and 0.91, respectively. Furthermore, the WD-SARIMAX model utilized the proposed to forecast the temperature in Delhi over the next eight years, from 2017 to 2025. Full article

This research introduces a novel approach that combines the conformable double Laplace–Sumudu transform (CDLST) and the iterative method to handle nonlinear partial problems considering some given conditions, and we call this new approach the conformable Laplace–Sumudu iterative (CDLSI) method. Furthermore, we state and discuss the main properties and the basic results related to the proposed technique. The new method provides approximate series solutions that converge to a closed form of the exact solution. The advantage of using this method is that it produces analytical series solutions for the target equations without requiring discretization, transformation, or restricted assumptions. Moreover, we present some numerical applications to defend our results. The results demonstrate the strength and efficiency of the presented method in solving various problems in the fields of physics and engineering in symmetry with other methods. Full article