The subterranean life cycle of Orobanche crenata hampers its management in Vicia faba. In this study, two experiments, greenhouse and in vitro, were conducted to investigate the dual efficacy of selected biotreatments against the parasite O. crenata and Vicia faba plants. At 90 days of seed sowing, O. crenata markedly impaired host plant growth, causing significant reductions in shoot distribution and density (42–50%), biomass (67-87%), total chlorophyll (36%), mesophyll conductance (95%). Ultimately, infection resulted in a complete loss of pod and seed yield in faba bean. Powders of Trigonella, Zygophyllum, Helianthus, Chenopodium, Allium, and Pleurotus spp. reduced these negative effects. In contrast, infection increased leaf succulence and saturation water deficit by approximately 150% and 88%, respectively. These adverse effects were successfully mitigated by most of the applied biotreatments. Chenopodium powder showed the highest improvement in total chlorophyll content, reaching approximately 86% of the control value. Trigonella powders exhibited the greatest enhancement in the host mesophyll conductance, shoot dry weight, and harvest index compared with untreated infected plants. Most of these biotreatments significantly reduced total number of Orobanche plants. Membrane stability was restored by all applied biotreatments with the highest recovery rate observed following treatment with Trigonella and Chenopodium (94%). In vitro germination assays demonstrated strong inhibitory effects of the biotreatments on Orobanche seed germination. Chenopodium powders showed the highest inhibition (99%), followed by Trigonella (96%) and Zygophyllum (89%). The finding showed the promising effects of Zygophyllum and Chenopodium fine powders against O. crenata infestation.
Observations from the Pioneer Venus Orbiter and Venus Express have shown that the region roughly 1000–2000 km above Venus's surface hosts a complex particle environment, where cold hydrogen and oxygen ions from the upper atmosphere coexist with energetic electrons produced by direct solar wind interaction with the unmagnetized planet. Understanding energy transport here matters for ion escape, since particles need enough kinetic energy to overcome gravity over long timescales. This work investigates kinetic Alfvén waves, which carry a field-aligned electric field capable of accelerating ions parallel to the magnetic field and potentially driving escape. The key question is whether these waves can steepen into localized nonlinear solitons in this region, and what controls their amplitude and width. The Sagdeev pseudopotential method was used, since it captures fully nonlinear structures without the amplitude limits of perturbative approaches. The plasma model includes hydrogen and oxygen ions at densities matching spacecraft data, with electrons described by a regularized kappa distribution that better reproduces the observed suprathermal tail than a Maxwellian or standard kappa distribution, which breaks down at low spectral indices. Numerical results show the Mach number strongly controls soliton amplitude: lower Mach numbers produce deeper pseudopotential wells and taller solitons. Propagation angle also matters — near-parallel propagation yields the tallest, most compact solitons, while oblique propagation widens them without increasing amplitude. Ion thermal pressure, via the hydrogen and oxygen beta parameters, further shapes the pseudopotential, with oxygen's effect being especially strong due to its greater mass.
Radiofrequency radiation (RF) covers a range of electromagnetic waves with frequencies typically ranging between 3 kHz and 300 GHz. Radiofrequencies included in mobile communications, Wi-Fi networks, and industrial systems have prompted inquiry into their biological effects on pathogenic bacteria. This study investigated the effects of 1–5 GHz radiofrequency radiation (RF) on the growth and antibiotic susceptibility of Escherichia coli and Klebsiella pneumoniae. Bacterial sensitivity to different classes of antibiotics was assessed, and the growth rate was evaluated by measuring the optical density (OD). Bacterial growth was sensitive to RF electromagnetic radiation, with the effect dependent on both frequency and exposure duration. Our research revealed that the extended exposure to radiofrequency radiation, reaching 6 hours, induced a transient decrease in antibiotic sensitivity (reflected by a reduction of up to 19 and 15 mm in inhibition zones of Escherichia coli and Klebsiella pneumoniae, respectively, particularly at 4–5 GHz, which raises questions about the potential effects on treatment effectiveness and public health. Whereas longer exposure durations (9 and 12 h) resulted in a gradual, partial restoration of baseline sensitivity. Growth kinetics tracked via optical density (OD at 600 nm) demonstrated frequency-dependent bacterial growth inhibition, with the most significantly pronounced retardation observed at the 5 GHz frequency. These findings support the hypothesis that RF fields in the 1–5 GHz range may transiently modulate bacterial physiology under controlled laboratory conditions, pointing toward a reversible physiological stress response and highlighting the need for further research to elucidate the underlying mechanisms and explore potential public health implications.
The investigation of plasma biomarkers for Alzheimer’s disease (AD) has gained increasing attention. Plasma phosphorylated tau (p-tau) is a promising biomarker because elevated levels can be detected years before clinical symptom onset. These findings highlight the potential of p-tau assays as the accessible and cost-effective tools for identifying individuals who may benefit from early intervention. This study examined the relationships between plasma p-tau levels, oxidative stress markers by detecting (MDA) against (GSTpx) , complete blood count (CBC) parameters, and liver function tests in patients with AD, non-AD dementia, and healthy controls. Malondialdehyde (MDA), a marker of oxidative stress, was significantly higher in AD patients than controls (p < 0.001) and was also elevated in non-AD dementia (p = 0.029). Significant differences were observed between family history (FH) subgroups and both dementia groups, whereas no significant difference was found between positive and negative FH groups. Glutathione peroxidase (GSTpx) activity differed significantly between AD and controls (p < 0.001) and between non-AD dementia and controls (p < 0.001), indicating reduced antioxidant capacity in dementia. Hematological analysis revealed lower lymphocyte counts and higher neutrophil counts in both dementia groups compared with controls (p < 0.001). The neutrophil-to-lymphocyte ratio (NLR), a marker of systemic inflammation, was significantly elevated in AD and non-AD dementia patients (p < 0.001), with no significant difference between the two groups. These findings demonstrate significant associations between plasma p-tau, oxidative stress, and inflammatory markers, supporting their role in dementia pathophysiology and their potential utility as accessible biomarkers for early detection.
Mangrove sediments exposed to hypersaline stress and localized pollution gradients represent complex biogeochemical systems in which species-level microbial responses remain poorly resolved in the northern Red Sea. This study employed Next-Generation Sequencing (NGS)-based long-read full-length 16S rRNA gene sequencing using the Oxford Nanopore MinION platform to characterize the sediment microbiome at species-level resolution and integrate microbial community structure with detailed sediment geochemistry in the El Gouna mangrove ecosystem. The sediments exhibited hypersaline conditions (EC = 42.5 dS m⁻¹; Na⁺ = 297.7 meq L⁻¹; Cl⁻ = 305 meq L⁻¹; SO₄²⁻ = 129 meq L⁻¹), near-neutral pH (7.66), elevated nutrient concentrations (Total N = 2440 mg kg⁻¹; P = 207 mg kg⁻¹; K = 1867 mg kg⁻¹), measurable trace metal loads (Fe = 3048.2 mg kg⁻¹; Pb = 21.5 mg kg⁻¹; Cd = 0.60 mg kg⁻¹), and a silty clay loam texture (53.4% silt; 35.5% clay). Sequencing analysis revealed high microbial richness (5,585 taxa), with a Shannon diversity index of 6.85 and a Simpson index of 0.996, indicating substantial diversity and community evenness. Salinity-associated marine taxa, particularly Woeseia oceani (n = 1262) and Methyloceanibacter caenitepidi (n = 589), predominated, while sulfate-reducing and hydrocarbon-associated taxa such as Desulfosarcina alkanivorans (n = 441) and Desulfatitalea tepidiphila (n = 359) were strongly enriched under sulfate-rich conditions. Collectively, these findings establish a species-level microbial bioindicator framework linking salinity–metal geochemistry with sulfur-reducing functional guilds, providing a robust baseline for environmental monitoring and management of hypersaline Red Sea mangrove ecosystems, with important implications for environmental conservation and sustainability.
The global energy transition requires a decisive shift from fossil fuels and first-generation (1G) biofuels toward advanced third- (3G) and fourth-generation (4G) pathways. However, the technological complexity needed to convert wastes into liquid fuels often demands intensive energy and chemical inputs that compromise intended environmental benefit. This study investigates the "Green Transition Paradox," hypothesizing that the processing intensity of advanced biofuels creates a "Hidden Environmental Burden" (HEB) that undermines their net sustainability. A comparative Life Cycle Assessment (LCA) was conducted under a strict Cradle-to-Gate boundary to evaluate the Net Environmental Burden (NEB) of three pathways: resource-efficient biogas, energy-intensive algal biodiesel, and energy-intensive lignocellulosic bioethanol. Key impact categories — Global Warming Potential (GWP), Fossil Depletion Potential (FDP), and Human Toxicity Potential (HTP) — were normalized to a functional unit of 1 MJ. Results showed that refinery gate-to-tank stages contribute up to 77% of environmental degradation in lignocellulosic pathways. Biogas consistently outperformed alternatives, with the lowest GWP score (0.01083 points) and a 76% reduction in fossil resource scarcity. Bioethanol exhibited high thermal intensity (52.5 MJ/L for distillation), while biogas recorded the lowest toxicity (35.017 kg 1,4-DB eq) compared with bioethanol (51.58 kg 1,4-DB eq). The study concludes that process simplicity is the primary determinant of sustainability, identifying waste-derived biogas as the superior pathway. Policy frameworks must prioritize FDP reduction and mandatory multi-criteria assessment to prevent harmful externalization of critical environmental burdens. These findings highlight the need to embed processing-stage impacts within renewable energy policy and ensure genuine rather than illusory environmental gains.
This systematic literature review investigates strategic interventions for reducing the carbon footprint of higher education institutions (HEIs) in Egypt, directly supporting the nation’s sustainable development agenda. Following a PRISMA-aligned protocol, comprehensive searches were conducted across four major academic databases—Web of Science, Scopus, ScienceDirect, and Google Scholar—covering literature published between 2005 and 2025. From an initial yield of 1,240 records, 312 full-text articles were rigorously assessed for eligibility, ultimately including 58 core studies alongside relevant national policy documents. The review synthesizes conceptual frameworks of climate change and greenhouse gas accounting applicable to university campuses, examining their alignment with Egypt Vision 2030 and specific UN Sustainable Development Goals (SDGs 4, 7, 11, 12, 13, and 17). It systematically identifies major campus emission sources, categorising them across buildings, transport, waste management, and food services, while concurrently documenting critical Egypt-specific data gaps and extracting transferable lessons from global best-practice case studies. The findings indicate that energy consumption, particularly purchased electricity, constitutes the largest share of institutional carbon footprints. However, execution is frequently hindered by structural barriers, including limited technical capacity, insufficient regulatory enforcement, and deep-rooted behavioral inertia. To overcome these challenges, the review advocates for a data-driven, integrated approach. Key recommendations include executing infrastructure retrofits prioritized by (carbon dioxide) CO 2 reduction per unit cost, deploying renewable energy systems backed by structured maintenance protocols, and implementing stakeholder education. Ultimately, the study concludes that achieving national sustainability targets requires establishing mandatory Scope 1, 2, and 3 carbon reporting frameworks for Egyptian universities and higher institutes.
This paper presents a comprehensive study of advanced classes of Stirling numbers within combinatorial analysis and discrete mathematics. The first class examined is the Comtet non-central Stirling numbers of the first and second kinds, which extend the classical Stirling numbers through the introduction of a non-central parameter. This extension is significant as it enriches the classical combinatorial structure by incorporating additional flexibility in modeling weighted and shifted combinatorial configurations, thereby broadening the scope of applicability beyond the standard framework. The second class focuses on the extended multiparameter noncentral Stirling numbers of both kinds. This construction further generalizes the previous framework by introducing multiple parameters together with a non-central factor, which allows for a finer control over structural variations. This added level of generalization is essential, as it enables the representation of more complex combinatorial systems and unifies several existing extensions under a single coherent formulation. Moreover, for both classes, we systematically derive recurrence relations, exponential and generating functions, and combinatorial identities, highlighting novel connections to factorials, binomial coefficients, and other combinatorial constructs. Additionally, a matrix representation is developed for these numbers, which not only enhances computational efficiency but also provides deeper structural insight into their algebraic behavior. Finally, the relationships between these generalized classes and other recognized families, including classical, weighted, and r-variants, are thoroughly established, demonstrating that the proposed framework serves as a unifying and strictly more general setting.
Freshwater aquaculture in Lake Manzala, Egypt, is increasingly affected by drainage inflows and environmental pollution. This study evaluated the physicochemical and microbiological water quality at five aquaculture sites between April 2021 and January 2022. Sites 1 and 2 were located near the Bahr Al-Baqar drain, sites 3 and 4 near Boghaz Al-Gamil, and site 5 near the Al-Kapouty Canal. Heavy metals (Cu, Zn, Cd, Pb) were determined using atomic absorption spectrophotometry, while microbiological quality was assessed using total viable count (TVC) and total coliforms (TC).Clear spatial variation was observed among sites. Dissolved oxygen ranged from 0.15–0.17 mg/L at sites 1 and 2 to 7.9 mg/L at sites 3 and 4. Total nitrogen reached 37.9 mg/L and total phosphorus 2.78 mg/L near the Bahr Al-Baqar drain, exceeding permissible limits. Mean concentrations of Cu (22.0–22.3 mg/L), Zn (65.4–66.6 mg/L), and Cd (31.2–31.5 mg/L) were elevated at most sites, whereas Pb remained within guideline values (0.02–0.03 mg/L). Microbial indicators were markedly increased, with TVC reaching approximately 9.3×10⁵ CFU/mL and total coliforms up to 5.4×10⁵ MPN/100 mL in the most impacted locations.This study provides an integrated seasonal assessment of physicochemical, heavy metal, and microbiological contamination across major aquaculture zones of Lake Manzala. The findings identify Bahr Al-Baqar–influenced farms as key pollution hotspots and offer a quantitative baseline to support targeted monitoring and sustainable management of brackish aquaculture systems in northern Egypt.
This study aims to assess researchers' awareness of the programs offered by the Research Center to develop researchers' skills and their perception of the benefits associated with educational and training activities at the Scientific Research Center in Prince Sultan City that play a pivotal role in fostering innovation, knowledge transfer, and human capital development, directly contributing to Saudi Vision 2030's ambitious goals of economic diversification and sustainable societal progress. The focus will be on identifying the perceived benefits of these activities from the researchers' perspective by identifying the impact of the research produced by the center on society, evaluating the impact of educational and training activities on the productivity and quality of research, and the extent to which the center contributes to developing the knowledge society and achieving these goals. This will be done to gather proposals for future educational and training programs based on researchers' needs and preferences to enhance their skills and knowledge. The study applied a descriptive-analytical approach to investigate researchers' awareness of the benefits of research educational and training activities at Saudi tertiary hospitals, utilizing an online questionnaire. Analytical findings highlighted significant correlations between experience (p<0.05) and awareness, underscoring barriers like workload while confirming the approach's effectiveness in providing actionable insights for policy improvement.
This study aimed at evaluating the antifungal potential of two metabolite fractions extracted from the antagonistic Bacillus amyloliquefaciens (IS5) culture filtrate using ethyl acetate (EAF) and ammonium sulfate precipitate (ASF) on ultrastructure and protein profile of Aspergillus flavus (A115). The results indicated that EAF exhibited more antifungal potential on A. flavus than ASF. Likewise, TEM examination of EAF-treated mycelium revealed disintegrated cell membranes and vast cytoplasmic disorganization. Whereas ASF-treated mycelium showed a dismantled outermost cell wall layer and granular cytoplasmic foci, seemingly stress granules (SGs), accompanied by extensive vacuolation indicating an autophagy-like mechanism. Non-targeting shotgun proteomic analysis was adopted using NanoLC-ESI-MS/MS. Mycelium treated with EAF showed increased abundance of ROS-related proteins such as glutathione S-transferase, superoxide dismutase and elevated fold change (FC) of redoxin and thioredoxin domain-containing protein in respect to control. On the other side, despite ASF treatment exerting a common down-regulation for the central carbon and energy metabolism, ATP synthesis and transport machinery have not followed this trend except for a few cases such as ATP-dependent RNA helicase eIF4A that was down-regulated, implying the inhibition of translation process. Then significant abundance was observed for ribosomal proteins (RPs), polyadenylate-binding protein, and GTP-binding protein, which are well documented as stress granules (SGs) constituents. Taken together, while EAF treatment-indicated a typical oxidative stress in A. flavus mycelium, ASF treatment induced translation inhibition resulted in SGs constitution, then autophagy was triggered to clear SGs. Further studies are so far needed to uncover the exact constituents of both extracted fractions (EAF and ASF).
Quality of human sperms has been declined over the prior little decades leading to infertility. Data analysis from the recent studies indicated that man fertility is influenced with many reasons and factors. Genetic, hormonal disturbance, lifestyle and environmental issues, anatomical obstruction, infections, and idiopathic factors are the most common causes preceding to infertility. Treatment strategies of this illness included modulation of lifestyle and behavioral related habits. Pharmacological treatments play a crucial role in enhancing spermatogenesis and testicular function. Hormonal therapy, estrogen receptor modulators, aromatase inhibitors, and dopamine agonists are used to initiate the cascade promotes spermatogenesis. Antioxidant therapy like glutathione, vitamin C, ubiquinone (CoQ10), and L-carnitine has shed light as an efficient treatment approach which can reduce oxidative stress leading to sperm quality enhancement. Despite improvements in advanced medication, pharmaceuticals originating from animal or plant sources continue to contribute significantly to treating the disease. Apitherapy is a member of replacement medicine by using products specifically, pollen, honey, propolis, royal jelly, and bee venom (BV) collected, processed, and released by bees for disease management. It has been informed that BV has more than 40 pharmaceutically active components which are mostly peptides and enzymes. Because of the anti-inflammatory, anticoagulant and antioxidant characteristics of BV along with its bioactive compounds, BV is mainly utilized in the treatment of various disorders. BV can improve several reproductive traits, including increasing the concentration of sperm bundles within the lumen of seminiferous tubule, along with preserving and supporting certain sexual effectiveness parameters.
The urgent need to decarbonize the global energy sector, especially considering climate overshoot and escalating greenhouse gas (GHG) emissions, has intensified interest in renewable alternatives such as biofuels derived from organic waste. These biofuels offer dual environmental benefits, mitigating waste-related methane emissions and providing a sustainable energy source. However, their environmental performance, particularly in terms of carbon footprint, varies significantly depending on numerous factors across their life cycle. This review critically examines the sources of variability in carbon emissions from organic waste-derived biofuels. Key influences include feedstock characteristics, conversion technologies (thermochemical, biochemical, and chemical), logistical factors, energy inputs, and the management of co-products and waste. Life Cycle Assessment (LCA) emerges as an essential framework for accurately quantifying these impacts, yet methodological inconsistencies and data gaps often hinder reliable comparisons across studies. Factors such as system boundary selection, functional unit definition, and data quality significantly shape LCA outcomes and subsequent carbon accounting. The paper also highlights strategies to enhance sustainability and reduce footprint variability, including improved feedstock selection, process optimization, renewable energy integration, and standardized LCA methodologies. Policy recommendations focus on clear carbon accounting standards, incentives for low-carbon biofuel development, and alignment with circular economy principles. Future research should address techno-economic trade-offs, harmonize LCA practices, and adopt digital tools for real-time emissions tracking. Ultimately, transforming organic waste into biofuels offers a promising pathway toward climate mitigation and sustainable energy systems, provided challenges in measurement, policy, and scalability are adequately addressed.
Worldwide, fish is a reliable source for efficient protein, vitamins and essential nutrients required by the human body to maintain balance and overall health. This research aims to investigate the proximate composition (moisture, protein, lipid and ash levels) in two species of spinefoot fish, Siganus rivulatus and Siganus luridus, in some Egyptian marine waters. S. rivulatus samples were obtained by fishermen from Hurghada (representing the Red Sea), and from Suez, Ismailia and Port Said (representing the Gulf of Suez, the Suez Canal, and the Mediterranean Sea, respectively). Whereas, S. luridus samples were collected from Port Said on the Mediterranean Sea, Egypt. The muscle tissue (flesh) of the samples was removed, weighed, and dried to measure moisture content, then prepared for proximate analysis of protein, lipid, and ash on an air-dry basis. The results indicated that the percentages of moisture and protein of S. rivulatus and S. luridus collected from the Mediterranean Sea was insignificantly higher compared to other studied areas. Ash content percentages showed differences across the study areas, with a small range of 5.173% for S. rivulatus in the Mediterranean Sea and 6.12% at the Suez Canal. Lipid percentages were displayed much significantly higher in S. rivulatus collected from the Mediterranean Sea (13.509%) and the Suez Canal (12.05%) and in S. luridus from the Mediterranean Sea (9.741%) compared to that in S. rivulatus from the Gulf of Suez (3.517%) and the Red Sea (2.783%).
During the past decade, the rapid expansion of diverse data sources has transformed medical practice and led to the emergence of Medical Big Data (MBD). This domain encompasses heterogeneous healthcare information derived from electronic health records, diagnostic imaging, genetic sequencing, and large-scale biomedical measurements. However, the sheer volume and complexity of MBD present significant analytical challenges, particularly because traditional visualization techniques often fail to capture the multidimensional and numerical depth of such data. To address this limitation, this paper proposes a multi-dimensional visualization framework built using the Visualization Toolkit (VTK). The framework integrates several analytical components into a single interactive 3D environment. These components include regression analysis with confidence interval estimation, kernel density estimation for probabilistic modeling, age-based clustering for demographic stratification, and weight-informed glyph encoding for enriched visual representation. Together, these elements enhance data interpretation by reflecting underlying Pearson correlation patterns. Additionally, the framework supports interactive filtering and dynamic clustering, enabling real-time segmentation and pattern discovery. By combining these advanced visualization capabilities, the proposed system aims to provide healthcare professionals with deeper insights, ultimately improving the accuracy and effectiveness of clinical decision-making.
This study evaluates eggshells as a cost-effective and eco-friendly alternative source of calcium in chicken feed versus traditional sources of calcium supplements based on their effect on chicken growth, egg weight, and egg production. The experiment was conducted for six weeks in which chickens were divided into an experimental treatment group (receiving eggshell calcium) and a control group (receiving traditional sources of calcium). Information was gathered on six-week body weight of chickens, weekly egg weight from weeks 36 to 40, and overall egg production for the duration. Statistical analysis was conducted using One-Sample T-Test under SPSS, which indicated significant difference (Sig. = 0.000) in all parameters recorded. The treatment group was heavier (411.39g vs. 185.55g in the control group) but compared to the latter, had better egg weight relatively (63.20g vs. 60.70g) and moderately improved egg yield (5.35 vs. 4.70 eggs/bird). Findings of the study confirm eggshell calcium can be used effectively and inexpensively as a supplement in poultry feeds to boost development and production with ease while it promotes efficient schemes of waste disposal in poultry business.
Skin cancer is one of the major and fastest growing global public health issues. The most crucial factor for the patient's survival is the early and accurate detection of skin cancer. Unfortunately, it is still challenging for dermatologists to distinguish skin cancer lesions from skin benign ones visually since lesion types look very similar and medical professionals are overloaded with diagnostic cases. As a result of these challenges, many intelligent computers aided diagnostic systems that use deep learning techniques for medical image analysis have been developed. This paper presents a hybrid deep learning method designed to perform skin lesion classification automatically from images, which combines Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). The model utilizes CNNs for extracting local spatial features and the Vision Transformers abilities to obtain global contextual information. The proposed method has been trained and validated on a public dermoscopic image benchmark dataset HAM10000 containing a total of 10015 images. From the experimental results, the single model controlled to reach the classification accuracy of 94.24% which makes it a very promising computer aided tool for the early detection of skin cancer.
Concerns over veterinary drug residues in the food supply chain pose significant risks to consumer health. This study aimed to quantify growth-promoting hormone residues (17α-methyltestosterone and progesterone) in 33 local and imported meat samples (muscle, liver, kidney) on the Egyptian market and to assess the mitigating effect of thermal processing. Using HPLC and LC-MS/MS, significant differences in hormone concentrations were found based on the country of origin, with imported organ meats showing the highest levels. American and Brazilian meats showed the highest 17α-methyltestosterone and progesterone, respectively. Crucially, the impact of thermal processing was found to be highly hormone-specific: grilling (200°C) significantly reduced progesterone concentrations (up to 80% reduction), whereas 17α-methyltestosterone proved remarkably stable (only ~27% reduction). These findings provide empirical evidence that cooking is an effective mitigation strategy for some, but not all, hormone residues and underscore the urgent need for stringent regulatory monitoring of imported meats to ensure consumer safety.
It has been long standing attention to find out the most efficient anti-cancer drug. Despite the discovery of the many synthetic anti-cancer drugs, most of them is still lacking specificity to cancer. Therefore, there was a pressing need to discover novel and specific drugs to selectively target cancer cell. Hence. Many of researchers tended to investigate the natural sources to find out natural therapeutic agents with limited side but cancer specific. Many herbs in traditional medicine have demonstrated anticancer properties, and some may evolve into tumor-inhibiting agents by constraining the pathways implicated in cancer progression, repairing DNA, and prompting antioxidant effects. Despite their different chemical diversity, natural products are good reservoir of bioactive compounds with therapeutic impact. Between 1981 and 2019, 25% of newly approved anti-cancer drugs had natural product connections. In this review, we focused on the major compounds of three genera, Zingiber, Curcuma and Alpinia from the family Zingiberaceae, which is a large plant family in Southeast Asia with 52 genera because these plants are potential candidates for developing novel chemotherapeutics. We also concluded the reports which concluded the mechanistic pathways and the major compounds with anticancer properties based on the cancer type and the type of the study either in vitro or in vivo.
This study presents a comprehensive comparison of three advanced techniques for solving different systems of ordinary differential equations (ODEs), which include both linear and nonlinear systems. The proposed methods are the Multi-Step Differential Transform Method (MSDTM), the Adomian Decomposition Method (ADM), and the Residual Power Series Method (RPSM). These methods present the solutions without requiring discretization, linearization, or perturbation. Moreover, their solutions take the form of rapidly convergent series with easily computable components. The theoretical foundation, computational effectiveness, and suitability for various ODE systems are examined for each method. All algorithms are implemented entirely in MATLAB (version R2016b) using custom-built functions, without relying on built-in solvers or symbolic computation. The proposed methods were tested on a number of real-world problems, showing their superior performance over other existing methods. The paper discusses the strengths and limitations of each method, focusing on their performance in terms of convergence, stability, and ease of implementation. The findings provide useful insights for researchers and practitioners in selecting approximate solution techniques for certain ODE systems, hence contributing to the improvement of numerical and semi-analytical methods in applied mathematics.
