Beni-Suef University Journal of Basic and Applied Sciences最新文献

Background

The rapid expansion of Internet of Things applications in healthcare has created new opportunities for improving patient care through real-time monitoring and data sharing. However, this growth also introduces significant challenges related to data security, privacy, and system efficiency, especially for devices with limited processing power and energy resources. To address these issues, this study introduces a blockchain-based lightweight hashing system specifically designed for healthcare environments with resource-constrained devices. The goal is to ensure secure, efficient, and scalable handling of sensitive medical data without overwhelming the capabilities of connected devices.

Results

The proposed system combines a collision-resistant, lightweight hash function with blockchain technology to enhance data integrity, authentication, and privacy. The hash function minimizes computational demands, making it ideal for wearable and embedded healthcare devices. Blockchain integration enables decentralized data management, preventing unauthorized access and tampering. The system generates unique, immutable patient identifiers and protects electronic health information from common security threats, including collision attacks, Sybil attacks, and cryptographic analysis. Simulation results show improved computational efficiency, lower latency, and effective handling of high transaction volumes with minimal resource usage.

Conclusions

This research presents a secure and efficient framework for managing medical data in healthcare Internet of Things applications. By leveraging lightweight cryptographic techniques and decentralized data structures, the system addresses key limitations in current solutions while supporting scalability and real-world deployment. Potential applications include secure patient monitoring, real-time sharing of health data, and decentralized management of medical records. The proposed approach provides a foundation for future advancements in digital healthcare systems, particularly in remote care, emergency response, and wearable health technologies.

Background

The present study was conducted at the CerealMed project farm during the 2021–2022 and 2022–2023 growing seasons using a strip plot design with two replications. The objective was to evaluate durum wheat hybrids and six durum wheat cultivars as parents under normal irrigation and water deficit stress. The study aimed to assess the tolerance of six durum wheat cultivars to water deficit stress, develop new tolerant durum wheat hybrids, and detect gene expressions to tolerance water deficit stress, using start codon-targeted (SCoT) markers. The traits studied included grain weight per plant, number of spikes per plant, number of kernels per spike, and 1000-kernel weight.

Results

The most tolerant parent genotypes to water deficit stress were BENI-SUEF 1 (56.98 g/plant), BENI-SUEF 6 (46.31 g/plant), BENI-SUEF 7 (45.54 g/plant), and SOHAG 5 (45.52 g/plant). The most tolerant hybrids were BENI-SUEF 1 × BENI-SUEF 6 (55.33 g/plant) and BENI-SUEF 7 × SOHAG 4 (50.16 g/plant), based on LSD at 5%. The SCoT analysis revealed variations in gene expression patterns among the different genotypes in response to water deficit stress.

Conclusion

This study highlighted the utility of SCoT markers in analyzing the genetic basis of drought tolerance in durum wheat. By identifying variations in gene expression patterns (like TaBTF3 gene for primer1), the study provided a deeper understanding of the complex mechanisms underlying plant responses to water deficit stress. The best durum wheat genotypes (BENI-SUEF 1, BENI-SUEF 6, BENI-SUEF 7, and SOHAG 5) are recommended for use in breeding programs targeting water deficit stress. Selection in segregating populations will be effective for the hybrids BENI-SUEF 1 × BENI-SUEF 6 and BENI-SUEF 7 × SOHAG 4.

Background

One of the most prevalent non-communicable diseases in the world today is diabetes. Diabetic kidney disease (DKD) is the predominant etiology of chronic kidney disease (CKD) and a major side effect of diabetes. Diagnosis of DKD is challenging and imprecise; thus, new diagnostic modalities are necessary to address this problem. The aim of the present study is to assess the role of the combined diagnostic performance of serum levels of MBL and imaging techniques, Doppler ultrasonographic renal resistive index (RRI) and shear wave elastography as a diagnostic tool for diabetic nephropathy. This case–control study included 450 type 2 diabetes mellitus (T2DM) patients, 225 without nephropathy and 225 diagnosed with diabetic nephropathy. We evaluated serum mannose-binding lectin (MBL) by enzyme-linked immunosorbent assay (ELISA) as a marker of diabetes-related inflammation, Doppler ultrasonographic renal resistive index (RRI) as a tool for assessment of blood flow in the kidney and shear wave elastography (SWE) as an imaging technique for detection of kidney fibrosis.

Result

The average serum MBL levels, mean RI and SWE of both kidneys were significantly higher in DKD patients compared to T2DM patients without nephropathy. The integration of the aforementioned methodologies significantly enhanced diagnostic performance, achieving a sensitivity of 96.89% and a specificity of 95.11%.

Conclusion

Combined serum levels of MBL and imaging techniques, Doppler ultrasonographic renal RI and shear wave elastography are promising diagnostic tools of diabetic nephropathy.

Background

Acrylamide (AA), a probable human carcinogen (Group 2A) classified by the International Agency for Research on Cancer (IARC), has emerged as a significant food safety concern worldwide. Its formation during high-temperature cooking processes, such as frying, baking, and roasting of starchy foods, has spurred extensive research efforts to understand its toxicity and develop effective mitigation strategies. This study aims to provide a comprehensive bibliometric analysis of scientific literature on AA and its metabolite, glycidamide (GA), published from 1965 to the end of 2024, focusing on the evolving trends and research emphasis related to their toxicity and mitigation in food.

Results

A comprehensive bibliometric analysis of 3729 Scopus articles was conducted using VOSviewer. The analysis revealed a general increase in the number of annual research publications on AA. Most studies focused on various types of toxicity associated with AA, such as neurotoxicity, cytotoxicity, and nephrotoxicity, utilizing different models. The findings indicate a growing emphasis on research to mitigate AA formation in foods as a response to its toxicity.

Conclusions

The study concludes that both the quality and quantity of research articles on AA have significantly improved over time, with an anticipated continued increase in the future research. This trend reflects the ongoing global concern about AA’s toxicity and the importance of developing strategies to reduce its presence in foods, which has significant implications for public health and food safety.

Graphic abstract

Background

With an emphasis on current developments and potential future perspectives in therapeutic applications, this comprehensive review delves into the molecular mechanisms of signaling transduction pathways associated with pharmacological target molecules. Since these pathways are essential to the cellular response to pharmacological drugs, understanding them is necessary for developing effective treatments. The notion of cellular signaling and the range of signaling pathways that control important cellular functions are first explained in this chapter. It highlights the intricate interactions between the essential elements of signaling pathways, such as effectors, ligands, receptors, and intercellular messengers.

Main body

It explores the activation and subsequent signaling events of several receptors, including intracellular nuclear, t-kinase, GPCR (G-protein-coupled receptors), and ionic receptors. We reviewed innovative methods that have sped up the discovery of new drug targets and clarified intricate signaling networks, like X-ray crystallography, advanced Cryo-EM (Cryo-Electron Microscopy), high-throughput screening, allosteric modulations, Artificial intelligence, and machine learning. This review attempts to explain the clear pathway of drug target molecules for novel, focused treatments that improve patient outcomes and further the field of drug development by combining existing knowledge and suggesting future research avenues.

Conclusion

Prospects for the future highlight the value of interdisciplinary teams in addressing these issues, encouraging advancements in combination therapies and tailored delivery systems that can get around current drawbacks in traditional therapy. In a rapidly changing biomedical landscape, this review seeks to shed light on pathways toward more effective, customized therapies that address the underlying molecular mechanisms of disease. Ultimately, it hopes to improve patient care and therapeutic outcomes by synthesizing current knowledge and suggesting strategic research directions.

Graphical abstract

Background

Prediction of vehicle trajectories is a crucial task for automated driving systems to accurately take movement actions according to the dynamic traffic environment, especially the future positions of the surrounding vehicles. Predicting how road users will behave in the future is one of the most critical and complex challenges in autonomous driving. Different data types must be combined to accomplish this task using deep learning, such as sensor readings and maps. After that, this data is used to predict a range of possible future outcomes. Existing goal-driven approaches predict the final goal and use it to complete the trajectory; this requires accurate goal prediction, which is challenging. Short-Term Goal Network (STG) addresses this challenge using multiple short-term goals instead of a single final goal.

Results

The proposed STG network is evaluated on the Argoverse motion forecasting dataset, and the results show significantly better performance than other goal-driven approaches. STG demonstrated a substantial improvement of over 6% in average displacement error and more than 8% in final displacement error.

Conclusion

This article presents an improved algorithm for predicting vehicle trajectories using short-term goals. The proposed STG algorithm is based on long short-term memory (LSTM) and attention mechanism for predicting trajectories. This work verifies that predicting more than one goal along the trajectory improves the accuracy of the predicted goal and the whole trajectory accordingly.

Background

Integrating phytomedicine with glass ionomer cements (GICs) offers a promising avenue for improving dental restoratives. This review comprehensively discusses the incorporation of plant extracts and derivatives into GICs to enhance their antimicrobial, mechanical, and aesthetic properties.

Main text

The addition of plant extracts, such as propolis, miswak, and grape seed, and the respective disinfecting derivatives of gallic acid, epigallocatechin-3-gallate, and curcumin improved both the antibacterial and mechanical properties of GICs. Furthermore, the incorporation of these derivatives is in line with current practices, which emphasize the use of natural products to minimize the use of synthetic preservatives in dental applications. In addition, this review discussed the role of these plant extracts in the green synthesis of nanoparticles (NPs), providing insights into how these sustainable approaches can fill existing gaps in dental material technology. This intersection of plant-based compounds and nanotechnology not only paves the way for innovative dental materials but also supports the broader movement toward sustainable practices in dentistry. This review revealed that the incorporation of plant extracts may significantly improve the antimicrobial properties of GICs and maintain or slightly improve their mechanical properties; however, the disparate methodologies and extraction concentrations used in these studies call for further standardized research.

Conclusion

This review highlights the potential of phytomedicine to optimize the performance of GICs in clinical settings and calls for further research to establish the most effective formulations.

Background

Archaeological limestone artifacts are subject to several deterioration factors that can cause harm while they are buried in soil, such as wet salt soil. Thus, one of the biggest challenges is restoring limestone artifacts that have been discovered from excavations. Understanding the nature of limestone after extraction and the resulting alterations, such as the stone’s structural instability and the high salt content of the artifacts, are prerequisites for the restorer. In 1974 AD, King Ramesses III’s gate was excavated from the ancient Heliopolis Temple in Cairo. The stones were removed from the soil and left on display outdoors at the same excavation site, where they were subject to seasonal variations in temperature and environmental changes. The main objective of the research is to select the best consolidating materials suitable for the pieces of limestone stone artifacts discovered from archaeological excavations due to their special nature, which affects them as a result of their presence in burial soil for long time. Selecting appropriate consolidating materials with appropriate characteristics was important. In order to withstand a range of environmental circumstances. The characteristics of the ancient stones at the King Ramesses III Gate site were investigated and analyzed to ascertain their true state, and their percentage of damage was calculated by contrasting them with the identical natural limestone that had not been subjected to any harmful influences. After that, experimental samples were used, and the efficacy of the treatment materials was assessed.

Result

Experimental study aims to evaluate the effectiveness of some traditional and nano composites materials to improving the properties of stone artifacts extracted from archaeological excavations. Three consolidating solutions were used as follows, paraloid B72 dissolved in acetone 3%, and Calcium hydroxide nanoparticles dissolved in paraloid polymer with acetone at concentrations of 1% and 3%, in addition to nano calcium carbonate dissolved in paraloid polymer with acetone 1% and 3%. The efficiency of the consolidate materials were evaluated using a scanning electron microscope SEM, as well as measuring the water contact angle, in addition to color change testing and measuring the physical and mechanical properties.

Conclusion

Nano materials are considered better than paraloid B72 as a consolidated material and the best outcomes results were obtained with a nano calcium carbonate dissolved in paraloid polymer with acetone 3%.

Graphical abstract

Background

This study explores a sustainable method for biofuel production from leather tanning waste (LTW) using a novel single-step, catalyst-free supercritical methanolysis (SpCM) process. Traditional biodiesel production methods often require catalysts and involve complex purification steps, whereas this study aims to optimize process parameters to enhance biodiesel yield while reducing energy and material consumption.

Methods

The research employed a Box–Behnken experimental design integrated with response surface modeling (RSM) to optimize key process variables, including alcohol-to-LTW molar ratio (r_mo), operating temperature, pressure, and reaction duration. The produced biodiesel was characterized according to EN 14214 standards. Kinetic studies of the transesterification reaction were conducted, and a robust reactor model was developed in Aspen Plus to estimate the kinetic parameters.

Results

The activation energy (E_a) and pre-exponential factor (A) were determined to be 45.085 kJ/mol and 86.24 s⁻¹, respectively, with a rate constant (k) of 0.0098 s⁻¹ at an optimized temperature of 322.938 °C. The optimized conditions using RSM achieved a biodiesel yield of 89.35% at an r_mo of 32.35:1, a temperature of 322.938 °C, a pressure of 219.073 bar, and a reaction time of 14.26 min. The simulation model under the same conditions predicted a biodiesel yield of 89.49%, demonstrating excellent agreement with experimental results, with a maximum error of 0.54%.

Conclusions

This study presents a comprehensive approach to biodiesel production from LTW, demonstrating an efficient and sustainable alternative to conventional methods. The optimized catalyst-free SpCM process minimizes energy input and material usage while achieving high biodiesel yields. These findings contribute to waste valorization in the leather industry and support environmental sustainability efforts.

Graphical abstract

Background

In recent efforts to address the critical need for clean and portable water, we have focused on innovative methods to eliminate pathogenic microorganisms. To this aim, the N-Glycyl-L-leucine (Gly-Leu) peptide ligand was complexed with different transition metal ions [Cu(II), Ni(II), and Cd(II)] as new peptide metalloantibiotics. The compounds were characterized and examined using various analytical methods, including elemental analysis (CHN), Fourier transform infrared spectroscopy (FTIR), assessments of magnetic properties, molar conductivity, ¹HNMR, thermogravimetric analysis (TGA), and mass spectroscopy. The ligand acted as a di-anionic molecule using the carboxylate and the deprotonated amide nitrogen atom. The coordination sites were completed with carbonyl oxygen atoms and a water molecule. The complexes showed polymeric structures using bridging carboxylate groups.

Results

The antibacterial properties of the synthesized metal chelate were evaluated using disk diffusion and minimum inhibitory concentration methods on bacterial organisms identified from water samples taken from the Nile River. At a 1 mg/mL dose, the Cu(II)-chelate showed the biggest inhibitory zone of 27 mm against Klebsiella pneumonia, with a MIC value of 62.5 μg/mL, greater than that of the common gentamicin medication. Molecular docking investigations supported these findings, showing that Cu(II)-chelate had the lowest binding energy of − 6.16 kcal/mol, indicating significant, beneficial interactions with the amino acids in the active region of bacterial proteins. Furthermore, the Cu(II) complex and the COVID-19 main protease showed encouraging results in the docking analysis, indicating that the complex may have antiviral properties and be able to inhibit viral propagation successfully. The metal chelates demonstrated noteworthy antioxidant activity, especially against 1,1-diphenyl-2-picrylhydrazyl (DPPH radicals). The IC₅₀ values of the antioxidant assay for Ni(II) and Cu(II) chelates were extremely similar to ascorbic acid, a common antioxidant. Their notable antioxidant capacity was demonstrated by the IC₅₀ values of (14.4, 15.5, and 18 µg/mL) for ascorbic acid, Ni(II), and Cu(II) chelates, respectively.

Conclusions

Our study successfully demonstrated the potential of a new Gly-Leu peptide ligand complexed with transition metal ions, particularly Cu(II), in eliminating pathogenic microorganisms from water. Cu(II)-chelate exhibited superior antibacterial properties, as confirmed by both experimental and molecular docking results. The chelates also displayed noteworthy antioxidant capacity, comparable to that of ascorbic acid. Additionally, the Cu(II)-chelate demonstrated promising antiviral potential, theoretically interacting effectively with the COVID-19 main protease, which suggests its ability to inhibit viral replication. These results underscore the potential of