Kuwait Journal of Science最新文献_第5页

In vitro assessment of the biochemical activities of leaves extracted from Senna italica against cancerous cell lines and gram-positive bacteria 番泻叶对癌细胞和革兰氏阳性菌体外生化活性的研究

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-09-23 DOI: 10.1016/j.kjs.2025.100498

Akram A. Alfuraydi , Abdulrahman Alhashimi , Abdalrhaman M. Salih , Salim Manoharadas , Almohannad Baabbad , Nawaf D. Almoutiri , Ayman Mubarak

Senna italica is an important herbal plant that is native to Saudi Arabia, and it is traditionally used to cure various diseases. This study was performed to analyze the in vitro antioxidant, antimicrobial, and anticancer activities and phytochemical compounds of different extracts of S. italica. The leaf extract was tested against Bacillus subtilis and methicillin-resistant staphylococcus aureus (MRSA) via the broth dilution method. These extracts presented bactericidal activity, and the methanol extract significantly affected the growth of B. subtilis compared with the ethyl acetate extract (p < 0.05). The minimum inhibitory concentration (MIC) values ranged from 48 ± 3 μg/mL to 192 ± 2 μg/mL. Similarly, the methanol extract had relatively high bactericidal activity toward B. subtilis, whereas the ethyl acetate extract had high bactericidal activity towards MRSA. The minimum bactericidal concentration (MBC) values ranged between 64 ± 7.5 μg/mL and 256 ± 3 μg/mL. Compared to the methanol extract, the ethyl acetate extract presented the maximum 2,2-diphenyl-1-picrylhydrazyl (DPPH) activity, and it was concentration dependent. The chloroform extract exhibited significant cytotoxic activity against the MDA-MB-231 and HepG2 cell lines, with a half-maximal inhibitory concentration (IC₅₀) of 292 μg/mL and 784 μg/mL, respectively. The gas chromatography-mass spectrometry (GC‒MS) analysis was performed to detect chemical compounds. A total of 11 compounds were detected in the ethyl acetate extract, and 14 compounds were detected in the methanolic extract. Senna italica presents useful bioactive secondary metabolites with antioxidant, antimicrobial, and anticancer properties. The results of this study validate the traditional use of S. italica in folk medicine and underscore its potential for further exploration as a source of therapeutic agents.

意大利塞纳河是一种重要的草本植物，原产于沙特阿拉伯，传统上用于治疗各种疾病。本研究对意大利葡萄不同提取物的体外抗氧化、抑菌、抗癌活性及植物化学成分进行了分析。采用肉汤稀释法检测叶提取物对枯草芽孢杆菌和耐甲氧西林金黄色葡萄球菌（MRSA）的抑制作用。与乙酸乙酯提取物相比，甲醇提取物对枯草芽孢杆菌的生长有显著影响（p < 0.05）。最小抑制浓度（MIC）为48±3 μg/mL ~ 192±2 μg/mL。同样，甲醇提取物对枯草芽孢杆菌具有较高的杀菌活性，而乙酸乙酯提取物对MRSA具有较高的杀菌活性。最小杀菌浓度（MBC）范围为64±7.5 μg/mL ~ 256±3 μg/mL。与甲醇提取物相比，乙酸乙酯提取物的DPPH（2,2-二苯基-1-苦味酰肼）活性最高，且具有浓度依赖性。氯仿提取物对MDA-MB-231和HepG2细胞株具有显著的细胞毒活性，半数抑制浓度（IC50）分别为292 μg/mL和784 μg/mL。采用气相色谱-质谱联用（GC-MS）分析检测化学成分。乙酸乙酯提取物中共检出11种化合物，甲醇提取物中共检出14种化合物。番泻草具有抗氧化、抗菌和抗癌的特性，是有用的生物活性次生代谢物。本研究结果证实了意大利菜在民间医学中的传统用途，并强调了其作为治疗药物来源的进一步开发潜力。

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引用次数: 0

CRAXNet: Credit Rating via Advanced XGBoost and Neural Networks CRAXNet：信用评级通过先进的XGBoost和神经网络

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-09-16 DOI: 10.1016/j.kjs.2025.100490

Muhammed Golec , Maha AlabdulJalil

One of the most important criteria for evaluating corporate creditworthiness in the financial services sector is credit risk analysis. This paper presents a new two-stage model CRAXNet for corporate credit rating. CRAXNet combines the feature selection of XGBoost and the nonlinear pattern learning ability of Neural Networks (NN) to make high-accuracy credit score predictions. CRAXNet, unlike the studies in the literature, provides a unique architecture that provides the class probabilities generated by XGBoost as inputs for the classifier in the NN model. Thus, CRAXNet can successfully model relationships in complex financial data with linear and nonlinear patterns. Experimental results using two different public datasets confirm that CRAXNet outperforms five State of the Art (SOTA) baselines (KNN, FIKNN, AF, Doc2Vec, and CART) with up to 4.74% accuracy and 9.86% F1-Score performance improvement. The datasets and source code used in the paper are publicly available for future researchers.

信用风险分析是评价金融服务业企业信誉的最重要标准之一。本文提出了一种新的两阶段企业信用评级模型CRAXNet。CRAXNet结合了XGBoost的特征选择和神经网络（NN）的非线性模式学习能力来进行高精度的信用评分预测。与文献中的研究不同，CRAXNet提供了一种独特的架构，该架构将XGBoost生成的类概率作为NN模型中分类器的输入。因此，CRAXNet可以成功地用线性和非线性模式对复杂金融数据中的关系进行建模。使用两个不同的公共数据集的实验结果证实，CRAXNet优于五个最先进的（SOTA）基线（KNN， FIKNN， AF， Doc2Vec和CART），准确率高达4.74%，F1-Score性能提高9.86%。论文中使用的数据集和源代码是公开的，可供未来的研究人员使用。

引用次数: 0

Double diffusive convection in flow along heated and non-uniform cylinder with nonlinear kinematics 具有非线性运动学的加热非均匀圆柱体流动中的双扩散对流

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-09-10 DOI: 10.1016/j.kjs.2025.100489

Nadeem Jan , Dil Nawaz Khan Marwat , Ali Althobaiti , Ahmed shafee , Asfandyar Khan , Fazal Ghani

This study investigates double diffusive convection in viscous fluid flow over a vertically aligned, heated, porous, and non-uniform cylinder exhibiting nonlinear stretching and shrinking. The field variables velocity, temperature, and concentration are modeled using nonlinear algebraic functions. By applying similarity transformations, the governing partial differential equations are reduced to a system of four coupled nonlinear ordinary differential equations, solved using MATLAB’s bvp4c scheme. The results show that increasing the thermal and solutal Grashof numbers by a factor of 2 leads to an increase of approximately 58% in the axial velocity near the cylinder surface, enhancing assisting flow behavior. An increase in the nonlinear stretching parameter reduces the thermal boundary layer thickness by up to 35%, while the mass transfer rate increases by over 40% in highly porous conditions. Skin friction coefficients and Nusselt and Sherwood numbers display strong nonlinear sensitivity to surface roughness and porosity. Notably, overshoot in velocity profiles is observed under specific parameter conditions, whereas temperature and concentration profiles remain monotonic. This model generalizes previous studies by encompassing both uniform and non-uniform surface properties and provides a versatile tool for simulating practical heat and mass transfer processes.

本研究研究了粘性流体在垂直排列、加热、多孔和非均匀圆柱体上流动时的双扩散对流，该圆柱体表现出非线性拉伸和收缩。用非线性代数函数对场变量速度、温度和浓度进行建模。通过相似变换，将控制偏微分方程简化为四个耦合的非线性常微分方程，利用MATLAB的bvp4c格式求解。结果表明，将热格拉西夫数和溶质格拉西夫数增加2倍，可以使圆柱表面附近的轴向速度提高约58%，增强了辅助流动性能。在高孔隙条件下，非线性拉伸参数的增加可使热边界层厚度减少35%，而传质率增加40%以上。表面摩擦系数、Nusselt数和Sherwood数对表面粗糙度和孔隙度表现出很强的非线性敏感性。值得注意的是，在特定参数条件下，可以观察到速度剖面的超调，而温度和浓度剖面仍然是单调的。该模型通过涵盖均匀和非均匀表面特性来推广以前的研究，并为模拟实际的传热和传质过程提供了一个通用的工具。

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引用次数: 0

Anomaly detection for live streaming graphs using copula based student-t process regression 基于copula的学生-t过程回归的实时流图异常检测

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-08-25 DOI: 10.1016/j.kjs.2025.100488

Mir Salma Amin, Hare Krishna Maity

In a time dependent streaming graph, detecting unusual activities such as intrusions by unregistered users (anomalous nodes) or unauthorized high value transactions (anomalous edges) presents a significant challenge. To address this, a time-evolving Laplacian graph energy was introduced to help identify specific anomalous nodes and edges. The weights of the streaming nodes and edges are captured using student-t process regression over time, enabling prediction of the expected graph energy. Significant deviations in graph energy from expected values, based on new observations, indicate potential anomalies, allowing us to identify unusual nodes or edges precisely. The kernel function’s hyperparameters are tuned using a copula function over an observation window, allowing the model to integrate historical behavior with emerging patterns. To validate this approach, real-world data from the UCI messages, Bitcoin OTC, DARPA and DGraphFin datasets were used for evaluation.

在时间依赖的流图中，检测异常活动（如未注册用户的入侵（异常节点）或未经授权的高价值交易（异常边缘））是一项重大挑战。为了解决这个问题，引入了一个随时间变化的拉普拉斯图能量来帮助识别特定的异常节点和边缘。流式节点和边的权重是使用student-t过程随时间回归捕获的，从而能够预测预期的图能量。基于新的观测值，图能量与期望值的显著偏差表明潜在的异常，使我们能够精确地识别异常节点或边缘。核函数的超参数通过观察窗口上的copula函数进行调优，从而允许模型将历史行为与新出现的模式集成在一起。为了验证这种方法，使用了来自UCI消息、比特币OTC、DARPA和DGraphFin数据集的真实数据进行评估。

引用次数: 0

Solitary wave solutions and stability analysis of notable nonlinear evolution model via two analytical methods 用两种解析方法分析显著非线性演化模型的孤波解和稳定性

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-08-22 DOI: 10.1016/j.kjs.2025.100482

Saima Arshed, Ghazala Akram, Maasoomah Sadaf, Minal Irshad

The primary goal of this research is to find solitary wave solutions to the (3 + 1)-dimensional Sakovich equation. The modified F-expansion method and the Sardar sub-equation method are employed to construct solitary wave solutions. Through the applications of modified F-expansion method and Sardar sub-equation method, new and novel soliton-like solutions, trigonometric solutions, rational function solutions, and exponential function solutions have been successfully obtained. In order to visualize their physical behavior, some of these solutions are graphically shown using contour plots, 2D profiles, and 3D surfaces. In addition, the modulation instability of the equation is examined using the linear stability analysis, which offers important information on the stability properties of the obtained wave solutions. This work contributes to a deeper analytical understanding of the Sakovich equation by deriving and analyzing its solitary wave solutions.

本研究的主要目标是找到（3 + 1）维Sakovich方程的孤波解。采用改进的f展开法和Sardar子方程法构造孤波解。通过应用改进的f展开法和Sardar子方程法，成功地得到了新的类孤子解、三角解、有理函数解和指数函数解。为了可视化它们的物理行为，其中一些解决方案使用等高线图、2D轮廓和3D表面进行图形化显示。此外，利用线性稳定性分析对方程的调制不稳定性进行了检验，这为所得到的波解的稳定性提供了重要信息。通过推导和分析Sakovich方程的孤立波解，这项工作有助于对Sakovich方程进行更深入的分析理解。

引用次数: 0

Machine learning model for predicting cyber-criminal characteristics 预测网络犯罪特征的机器学习模型

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-08-14 DOI: 10.1016/j.kjs.2025.100487

Hesham A. Almansouri, Mohammad M. Khajah, Nasser B. Alsnayen

This study aims to predict investigation outcomes of individual cybercrime cases using the most relevant information provided by complainants. We curated a dataset on solved hacking cases from 2019 to 2022 from the cyber-crime combating department (3CD) in the State of Kuwait. Each case has a set of information provided by the complainants (input features), and a corresponding set of investigation results (outputs). For each output, several machine learning models, such as decision trees and feed-forward neural networks, were evaluated, via nested 5-fold cross-validation to measure how well they could predict the output, given the input features. Input feature sets were either selected from all possible input feature combinations (brute force) or from a limited set of officer-provided combinations (officer-guided). Finally, a post-hoc analysis of the results was performed to identify a single set of features that can be used to build reasonably predictive models for all collected outputs. Depending on the output, the brute force and officer-guided approaches have a median relative advantage of 92% and 53% over the baseline models and worst-officer score respectively. On almost all outputs, the brute-force approach is just as good, if not better, than the officer-guided approach. No relationship was observed between officer rank and the predictive power of the combination of features they selected. Different outputs require different sets of features, and there is a significant overlap between brute force and officer-guided features in five out of the 10 outputs. Most selected features have a reliable negative impact on prediction performance when perturbed, with some outputs relying on a few critical features and others on a spectrum of features. Finally, a single set of features can predict most outputs almost as well as output-specific features.

本研究旨在利用投诉人提供的最相关资料，预测个别网络犯罪案件的调查结果。我们整理了科威特网络犯罪打击部门（3CD）从2019年到2022年解决的黑客案件的数据集。每宗个案都有一组由投诉人提供的资料（输入特征），以及一组相应的调查结果（输出）。对于每个输出，通过嵌套的5倍交叉验证来评估几个机器学习模型，如决策树和前馈神经网络，以衡量它们在给定输入特征的情况下预测输出的效果。输入特征集要么从所有可能的输入特征组合中选择（蛮力），要么从一组有限的军官提供的组合中选择（军官指导）。最后，对结果进行事后分析，以确定一组可用于为所有收集的输出构建合理预测模型的特征。根据输出，蛮力和军官引导的方法分别比基线模型和最差军官得分有92%和53%的中位数相对优势。在几乎所有的输出中，暴力方法与军官指导的方法一样好，如果不是更好的话。没有观察到军官等级和他们选择的特征组合的预测能力之间的关系。不同的输出需要不同的特征集，在10个输出中，有5个在蛮力和军官指导的特征之间存在显著的重叠。当受到干扰时，大多数选择的特征对预测性能有可靠的负面影响，一些输出依赖于几个关键特征，而另一些则依赖于一系列特征。最后，一组特征几乎可以预测大多数输出以及特定于输出的特征。

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引用次数: 0

Exact and approximate solutions of the fractional dynamical system via transform techniques 用变换技术求分数阶动力系统的精确和近似解

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-08-13 DOI: 10.1016/j.kjs.2025.100485

Maalee Almheidat , Azzh Saad Alshehry , Abdulkafi Mohammed Saeed , Musaad S. Aldhabani , Ahmad Shafee

This study investigates the Jaulent–Miodek system of partial differential equations (PDEs) using two powerful analytical techniques: the iteration transform method (ITM) and the residual power series transform method (RPSTM). These methods are employed to derive approximate and exact solutions for the system under the framework of the fractional Caputo operator. The fractional formulation provides a more generalized and flexible approach to modeling complex physical phenomena, particularly in nonlinear wave propagation and fluid dynamics. The effectiveness of the proposed methods is demonstrated through numerical examples, where solutions are analyzed for different fractional orders. Comparative analysis highlights the accuracy and efficiency of ITM and RPSTM in handling fractional PDEs. The results confirm that these techniques offer a robust and reliable means for solving nonlinear fractional models, paving the way for further research into their applications in mathematical physics and engineering.

本文利用迭代变换法（ITM）和残差幂级数变换法（RPSTM）这两种强大的分析技术研究了Jaulent-Miodek偏微分方程组（PDEs）。利用这些方法，在分数阶Caputo算子的框架下，得到了系统的近似解和精确解。分数公式提供了一种更广义和灵活的方法来模拟复杂的物理现象，特别是在非线性波传播和流体动力学中。通过数值算例证明了所提方法的有效性，并对不同分数阶的解进行了分析。对比分析表明ITM和RPSTM处理分数阶偏微分方程的准确性和效率。结果证实，这些技术为求解非线性分数模型提供了一种鲁棒和可靠的方法，为进一步研究其在数学物理和工程中的应用铺平了道路。

引用次数: 0

Seismic site characterization of Malang Regency (Indonesia) using HVSR inversion 利用HVSR反演反演印尼玛琅县地震场特征

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-08-07 DOI: 10.1016/j.kjs.2025.100486

Adi Susilo , Siti Zulaikah , Ahmad Fauzi , Ilham , Ma'muri , Ken Wirawan , Saffanatul Haniyyah , Ahmad Zarkoni , Yoga Dharma Persada , Andy Anderson Bery , Muhammad Fathur Rouf Hasan

Based on Indonesia's active fault map, this study focuses on the Eurasian and Indo-Australian plate subduction zone in the southern sea of Java, an area that is highly susceptible to earthquake risk and soil vulnerability. This study aims to determine soil vulnerability based on average shear wave velocity of the top 30 m (Vs30) and sediment thickness (z_1.0) parameters to map areas at risk of earthquake in the study area. From both parameters, the most vulnerable and safest area in Purwodadi Village, Indoensia will be determined. The method used in this research is microtremor measurement with a portable miniature broad band (MBB-2) seismograph. Measurements were conducted at 19 points spaced approximately 500 m apart. Horizontal vertical spectral ratio (HVSR) inversion was applied to obtain shear wave velocity profiles at each point. Soil assessment was performed using Vs30 parameters, classified according to the American society of civil engineers (ASCE) standards. The results show that areas with relatively high earthquake vulnerability, indicated by low Vs30 values, are located near measurement points RKI08 and RKI18 in residential areas and RKI04 on slopes with Vs30 values are 219.0 m/s, 248.9 m/s, and 230.2 m/s respectively. Besides that, these points have high z_1.0 value, these values are 388.0 m, 517.8 m, and 46.6 m respectively. Meanwhile, areas with lower vulnerability are found at RKI10 and RKI09 in residential areas and RKI05 on slopes, with Vs30 values are 502.0 m/s, 481.1 m/s, and 416.0 m/s respectively. These points have Vs30 values classified as “very dense soil” and have low z_1.0 values (60.3 m, 109.6 m, and 43.9 m respectively). Based on data processing, there is a fault that stretches straight from RKI04, RKI11, to RKI14. However, more research needs to be conducted using alternate methods to confirm the existence of the fault. This mapping is expected to provide local authorities valuable input for disaster mitigation planning.

基于印度尼西亚的活动断层图，本研究将重点放在爪哇海南部的欧亚和印澳板块俯冲带，这是一个高度易受地震风险和土壤脆弱性影响的地区。本研究的目的是通过地表30 m平均横波速度（Vs30）和沉积物厚度（z1.0）参数确定土壤易损性，绘制研究区地震危险区域图。根据这两个参数，将确定印度尼西亚Purwodadi村最脆弱和最安全的地区。本研究采用便携式微型宽带（MBB-2）地震仪测量微震。测量在相隔约500米的19个点进行。利用水平垂直谱比（HVSR）反演得到各测点的横波速度剖面。采用Vs30参数进行土壤评价，按照美国土木工程师学会（ASCE）标准进行分类。结果表明，地震易损性较高的地区位于居民区RKI08和RKI18测点附近，位于Vs30分别为219.0 m/s、248.9 m/s和230.2 m/s的斜坡上RKI04测点附近，Vs30值较低。此外，这些点的z1.0值较高，分别为388.0 m、517.8 m和46.6 m。民居区RKI10、RKI09和斜坡区RKI05的Vs30值分别为502.0 m/s、481.1 m/s和416.0 m/s，脆弱性较低。这些点的Vs30值被归类为“非常致密的土壤”，z1.0值较低（分别为60.3 m， 109.6 m和43.9 m）。根据数据处理，在RKI04、RKI11、RKI14之间存在一条断层。然而，需要使用替代方法进行更多的研究来确认故障的存在。预计绘制地图将为地方当局提供减灾规划方面的宝贵投入。

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引用次数: 0

Analysis of magnetohydrodynamic flow of Jeffrey-Hamel fluid in convergent/divergent channels using the numerical algorithm 用数值算法分析杰弗里-哈默尔流体在收敛/发散通道中的磁流体动力流动

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-07-30 DOI: 10.1016/j.kjs.2025.100479

Mohsin Ul Haq , Dolat khan , Zeeshan Ali , Subhan Ullah , Walid Emam , Dragan Pamucar , Yusra Tashkandy

This study explores the magnetohydrodynamic (MHD) flow of a Jeffrey-Hamel fluid within a convergent/divergent channel, a scenario relevant to both physical and biological sciences. The flow dynamics between nonparallel inclined walls are governed by highly nonlinear differential equations derived through conservation laws and similarity transformations. By applying similarity transformations, the governing partial differential equations (PDEs) are converted into ordinary differential equations (ODEs). The NDSolve approach is then utilized to obtain numerical solutions for these equations. A comparison with existing methods in the literature confirms the accuracy and reliability of the results. Additionally, the impact of various dimensionless physical parameters, such as the influence of the magnetic parameter, angle alpha, and the Deborah number on the velocity profile is investigated. The parameters angle alpha, Eckert number, and volume friction are examined on the temperature profile, followed by a detailed discussion of the findings.

本研究探讨了杰弗里-哈默尔流体在收敛/发散通道内的磁流体动力学（MHD）流动，这是一个与物理和生物科学相关的场景。非平行倾斜壁面间的流动动力学是由守恒定律和相似变换导出的高度非线性微分方程控制的。通过相似变换，将控制偏微分方程转化为常微分方程。然后利用NDSolve方法获得这些方程的数值解。通过与文献中已有方法的比较，证实了所得结果的准确性和可靠性。此外，还研究了各种无量纲物理参数，如磁参数、角α和黛博拉数对速度剖面的影响。参数角alpha， Eckert数和体积摩擦在温度剖面上进行了检查，然后对结果进行了详细的讨论。

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引用次数: 0

Comparative assessment of physicochemical and biological properties of silver nanoparticles (AgNPs) synthesized from aerial and underground parts of Arnebia benthamii 从空中和地下部分合成银纳米粒子（AgNPs）的物理化学和生物特性的比较评估

IF 1.1 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science

Pub Date : 2025-07-28 DOI: 10.1016/j.kjs.2025.100478

Yasmeen Mukhtar , Munazza Nazir , Shumaila Naz , Rizwan Taj khan , Wasim Akhtar , Laiba Abdul , Asif Kamal , Abdulwahed Fahad Alrefaei , Eman Alshehri , Maximilian Lackner

Arnebia benthamii is a source of secondary metabolites with significant medicinal potential. This work studied the biogenic synthesis of silver nanoparticles (AgNPs) by A. benthamii root and inflorescence extracts. The novelty of this research lies in the comparative assessment of nanoparticles derived from aerial and underground plant parts, highlighting differences in physicochemical and biological properties. A 1:5 ratio of plant extract to silver nitrate (AgNO₃) solution (1 mM) was used in the formation of NPs, and they were characterized by UV-Vis spectroscopy (UV), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction spectroscopy (XRD). UV-Vis analysis confirmed AgNP formation by an absorbance peak at 432 nm (root-mediated) and 436 nm (inflorescence-mediated). XRD confirmed their crystalline nature, while SEM revealed that root-derived AgNPs were irregular (40 nm) and inflorescence-derived AgNPs were spherical (23 nm). FTIR showed the part of secondary metabolites that serve as natural capping agents. For antibacterial activity, the well diffusion method was employed, where AgNPs were tested against Acinetobacter calcoaceticus and Enterobacter hormaechei subsp. xiangfangensis. Inflorescence-mediated AgNPs were found to exhibit superior antibacterial activity, likely due to smaller NP size. For antioxidant assays, these AgNPs also demonstrated enhanced 2,2-diphenyl-1-picrylhydrzyl (DPPH) of 83 % and 2,2-azino-bis(ethylbenzothiazoline-6-suphonic acid) (ABTS) of 61 % compared to root-mediated AgNPs (DPPH 80 %, ABTS 57 %). The findings suggest that A. benthamii-mediated AgNPs possess a significant potential for biological applications. Enhanced bioactivity of inflorescence-derived AgNPs highlights their promise in antimicrobial and antioxidant therapies, supporting their future use in pharmaceutical and nanotechnological advancements.

本胺是一种具有重要药用潜力的次生代谢物来源。本文研究了以香草根和花序提取物为原料合成纳米银的生物源性。这项研究的新颖之处在于对来自地上和地下植物部分的纳米颗粒进行了比较评估，突出了物理化学和生物特性的差异。采用植物提取物与硝酸银（AgNO3）溶液（1 mM）的比例为1:5形成NPs，并通过紫外可见光谱（UV）、傅里叶变换红外光谱（FTIR）、扫描电镜（SEM）和x射线衍射光谱（XRD）对NPs进行了表征。紫外-可见分析证实AgNP形成的吸收峰在432 nm（根介导）和436 nm（花序介导）。XRD证实了AgNPs的结晶性质，SEM显示根源AgNPs为不规则型（40 nm），花序源AgNPs为球形（23 nm）。FTIR显示部分次生代谢物作为天然封顶剂。采用孔扩散法测定AgNPs对钙酸不动杆菌和霍马切肠杆菌的抑菌活性。xiangfangensis。发现花序介导的AgNPs具有优越的抗菌活性，可能是由于较小的NP大小。在抗氧化实验中，与根介导的AgNPs （DPPH为80%，ABTS为57%）相比，这些AgNPs还显示出2,2-二苯基-1-吡啶基羟基（DPPH为83%）和2,2-氮基-双（乙基苯并噻唑-6-亚磺酸）（ABTS为61%）的增强。研究结果表明，a . benthami介导的AgNPs具有重要的生物学应用潜力。花序衍生AgNPs的生物活性增强凸显了它们在抗菌和抗氧化治疗中的前景，支持它们未来在制药和纳米技术进步中的应用。

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引用次数: 0