Journal of Radiation Research and Applied Sciences最新文献

{"title":"Impact of nonlinear thermal radiation on peristaltic pumping of different shaped nanoparticles of copper in curved wavy channel","authors":"Sami Ul Haq ,&nbsp;Muhammad Bilal Ashraf ,&nbsp;Jongsuk Ro ,&nbsp;Fuad A. Awwad ,&nbsp;Emad A.A. Ismail","doi":"10.1016/j.jrras.2025.101359","DOIUrl":"10.1016/j.jrras.2025.101359","url":null,"abstract":"<div><div>The main objective of this research is to investigate the experimental [28] verified correlations of the thermophysical characteristics of copper nanoparticles of different shapes that are incorporated in the equations. It is a vital mechanism in many physiological processes, including blood circulation and digestion. The rhythmic contractions and relaxations of a tube define this biological phenomenon. This study investigates the electrical conducting nanofluids flow in a curved channel in the presence of natural convection. Furthermore, the different shapes of copper nanoparticles, such as spheres, blades, and platelets, are examined. A modification of the energy equation is accomplished by the use of viscous dissipation, joule heating, and nonlinear thermal radiation. The modelled equation of the problems is a highly nonlinear partial differential equation. These equations are converted into nonlinear dimensionless ordinary differential equations by using dimensional variables, assuming a small Reynolds number, and a long wavelength. The numerical technique is employed in Mathematica via NDSolve to obtain the results. Results indicate that platelet-shaped nanoparticles have a substantial influence on temperature, pressure, and velocity compared to spherical and blade-shaped nanoparticles. For the platelet-shaped nanoparticle, the nonlinear thermal radiation and Hartmann number exhibit opposite behavior for fluid and heat flow.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101359"},"PeriodicalIF":1.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic handover optimization in 5G heterogeneous networks","authors":"Ibrahim Elbatal ,&nbsp;Umar Danjuma Maiwada ,&nbsp;Kamaluddeen Usman Danyaro ,&nbsp;Aliza Bt Sarlan","doi":"10.1016/j.jrras.2025.101411","DOIUrl":"10.1016/j.jrras.2025.101411","url":null,"abstract":"<div><div>With the rapid proliferation of 5G and internet of things devices, seamless mobility and ubiquitous connectivity have become paramount. 5G networks, characterized by their heterogeneous nature, integrating diverse network environments like macro cells, small cells, and Wi-Fi hotspots, pose significant challenges to maintaining uninterrupted connectivity for mobile users. Efficient handover mechanisms are crucial for ensuring a smooth transition between these diverse networks and guaranteeing optimal quality of service. Existing static handover techniques often struggle to adapt to the dynamic conditions of heterogeneous networks, leading to suboptimal performance and disruptions in connectivity. This research gap necessitates the development of more intelligent and adaptive handover solutions. This paper proposes a novel dynamic handover approach designed to optimize seamless connectivity in heterogeneous 5G wireless networks. The proposed method leverages real-time 5G network analytics, analyses user mobility patterns, and incorporates QoS requirements to make intelligent handover decisions. Hence, there is need in dynamically adjusting handover parameters based on current network conditions and user contexts, the approach aims to minimize latency, reduce packet loss, and ultimately enhance the overall user experience. In Seamless Mobility in Heterogeneous Mobile Networks, improvements to handover performance based on factors such as power level, user velocity, and target cell load have been discussed. The performance of the proposed dynamic handover approach was evaluated through extensive simulations. The results demonstrate significant improvements in key performance indicators compared to traditional static handover techniques. Specifically, the proposed approach achieves a 95% improvement in handover success rates and a substantial reduction in downtime, compared to the 80% success rate of existing static methods as seen from table 2. Moreover, the dynamic approach leads to better utilization of network resources. Also, there is a highlight on the need for mobility management schemes in heterogeneous environments to address the diverse needs of users. This work contributes to the ongoing development of adaptive and resilient connectivity solutions essential for the evolving landscape of 5G and beyond.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101411"},"PeriodicalIF":1.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced detection of female breast cancer from digital mammography employing transfer deep learning neural networks","authors":"Tareg M. Al Mansour ,&nbsp;Mohammed Sallah ,&nbsp;Roxana Rusu-Both ,&nbsp;Ghada A. Khouqeer ,&nbsp;Tamer Medhat ,&nbsp;Ahmed Elgarayhi ,&nbsp;Elmetwally M. Abdelrazek","doi":"10.1016/j.jrras.2025.101392","DOIUrl":"10.1016/j.jrras.2025.101392","url":null,"abstract":"<div><div>Early detection of breast cancer (BrC) is one of the best strategies to prevent the disease's spread. This makes an autonomous diagnosis system based on deep learning (DL) attractive for improving the accuracy of detection and prediction. This study suggests employing transfer DL models to categorize BrC from mammograms. Furthermore, to identify BrC detection architectures, transfer DL models are applied to various well-known convolutional neural networks (CNNs). Three CNNs (NasNetMobile, EfficientNet-b0, and MobileNetV2) are adjusted in particular ways before being used. All systems use two types of optimizers: root mean square propagation (RMSP) and adaptive moment estimation (ADAM). The EfficientNet-b0 network attains 96.45% accuracy, 96.63% sensitivity, and 97.18% F1-score when using the ADAM optimizer. The experimental results demonstrate that EfficientNet-b0 outperforms other sophisticated CNN techniques and offers a number of advantages. Additionally, the EfficientNet-b0 obtained an F1-score of 96.00%, a sensitivity of 96.55%, and an accuracy of 95.04% utilizing the RMSprop optimizer. To sum up, this work improves the identification of BrC by applying transfer DL models to digital mammography scans. The best-performing CNN among the three (NasNetMobile, EfficientNet-b0, and MobileNetV2) was EfficientNet-b0 optimized with ADAM and RMSprop. These results show how these structures could improve healthcare and increase the accuracy of BrC detection.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101392"},"PeriodicalIF":1.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Significance of thermal radiation on MHD stagnation point flow of Powell Eyring fluid: A heat and mass transfer problem","authors":"S. Karthik ,&nbsp;D. Iranian ,&nbsp;A. Ariana ,&nbsp;Sultan Alshehery ,&nbsp;Ilyas Khan","doi":"10.1016/j.jrras.2025.101383","DOIUrl":"10.1016/j.jrras.2025.101383","url":null,"abstract":"<div><div>The current study investigates the impact of radiation and stagnation point flow on a porous shrinking surface, with a particular focus on the mass and heat transfer processes influenced by viscous dissipation, heat source/sink effects, and mass diffusion. The governing equations for velocity, temperature, and concentration are transformed from partial differential equations into a system of nonlinear ordinary differential equations using appropriate similarity transformations. These equations are then solved under specified boundary conditions incorporating energy equations with radiation and heat source/sink effects using the BVP4C solver alongside the shooting method in MATLAB. Key physical parameters, including mass and heat transpiration, Prandtl number, thermal radiation, viscous dissipation, and Lewis number, are analyzed through both tabular and graphical methods. The main findings reveal that an increased magnetic field intensity significantly amplifies the local skin friction, as depicted in the corresponding contour plots. Moreover, escalating levels of thermal radiation, viscous dissipation, and Lewis number result in an expanded thermal boundary layer, which in turn leads to diminished concentration and temperature contours. These results have substantial implications across engineering, biological, and physical sciences and present practical utility in applications such as engine lubricant purification and thrust bearing technologies.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101383"},"PeriodicalIF":1.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal radiation and local thermal non-equilibrium effects on MHD chemical reactive flow of tetra hybrid nanofluid with velocity slip conditions","authors":"Ahmed M. Galal ,&nbsp;Ilyas Khan ,&nbsp;Munawar Abbas ,&nbsp;Abdullah A. Faqihi ,&nbsp;Mohammad Saqlain Sajjad","doi":"10.1016/j.jrras.2025.101405","DOIUrl":"10.1016/j.jrras.2025.101405","url":null,"abstract":"<div><div>The current article examines the impact of thermal radiation and velocity slip condition on the chemical reactive flow of MHD in tetra hybrid nanofluid across an inclined spinning disk with local thermal non-equilibrium conditions. The current work has been improved by taking slip flow into account more. The latest study examines the properties of heat transmission in the absenteeism of local thermal equilibrium conditions using a basic scientific model. Two distinct fundamental thermal gradients are produced by the local thermal equilibrium effects classical for both the solid and liquid phases. Tetra hybrid nanofluid containing, aluminum oxide (<span><math><mrow><msub><mrow><mi>A</mi><msub><mi>l</mi><mn>2</mn></msub><mi>O</mi></mrow><mn>3</mn></msub><mo>)</mo></mrow></math></span> , titanium dioxide <span><math><mrow><mrow><mo>(</mo><mrow><mspace></mspace><mi>T</mi><mi>i</mi><msub><mi>O</mi><mn>2</mn></msub><mspace></mspace></mrow><mo>)</mo></mrow><mo>,</mo><mtext>silver</mtext><mspace></mspace><mrow><mo>(</mo><mrow><mi>A</mi><mi>g</mi></mrow><mo>)</mo></mrow></mrow></math></span> and cobalt ferrite (<span><math><mrow><msub><mrow><mtext>COF</mtext><msub><mi>e</mi><mn>2</mn></msub><mi>O</mi></mrow><mn>4</mn></msub><mo>)</mo></mrow></math></span> nanoparticles, and based fluid water is used. Through heat transfer process optimization in complicated fluids, it can improve heat exchanger efficiency in thermal engineering. Chemical engineers may be able to construct more efficient reactors for chemical reactions with its insights into reaction kinetics and thermal distributions. Numerical solutions to effectively converted governing equations have been obtained using the bvp4c technique. The findings indicate that as the interphase heat transmission and velocity parameter increase the solid phase's thermal field and the liquid phase's ratio of heat transmission, velocity distribution drop, while the fluid phase's thermal profile and increasing rate of heat transfer.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101405"},"PeriodicalIF":1.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The heat radiation of Darcy-Forchheimer flow of nanomaterial with active/passive comprising microorganisms framed by a curved surface","authors":"Ahmed M. Galal ,&nbsp;Syed Sohaib Zafar ,&nbsp;A. Zaib ,&nbsp;Farhan Ali ,&nbsp;M. Faizan Ahmed ,&nbsp;Umair Khan ,&nbsp;Samia Elattar","doi":"10.1016/j.jrras.2025.101403","DOIUrl":"10.1016/j.jrras.2025.101403","url":null,"abstract":"<div><div>The curved surface has garnered significant interest owing to its prevalence in numerous engineering and technology including roof sheet and fiberglass. So, this analysis examined the characteristics of Darcian bioconvection flow on nanofluid through a heated curved surface. It is thought that the curve sheet will stretch in a circle. Energy and concentration are communicated by applying thermal radiation, heat source/sink and chemical reaction. The surface of nanoparticles that are exposed to thermophoresis and Brownian diffusion is controlled in both passive and active ways. Using the suitable transformations, the constitutive expressions are transformed into nonlinear ordinary differential equations. Afterwards, the nonlinear ordinary differential equations is derived by the shooting technique utilizing the Bvp4c technique. Careful consideration was given to the plotting of graphs showing the properties of various parameters against distributions of velocity, heat, and mass. The results demonstrate that the Darcy-Forchheimer number is a decreasing function of the velocity field. In addition, a higher fluid temperature is achieved when the Biot number is higher for the active and passive control. In comparison to a previously published result in the literature, the analysis's outcomes are supported. In this respect, an exceptional match is made.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101403"},"PeriodicalIF":1.7,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global inflation forecasting and Uncertainty Assessment: Comparing ARIMA with advanced machine learning","authors":"Ghadah Alomani ,&nbsp;Mohamed Kayid ,&nbsp;Mohamed F. Abd El-Aal","doi":"10.1016/j.jrras.2025.101402","DOIUrl":"10.1016/j.jrras.2025.101402","url":null,"abstract":"<div><div>This study analyzes the effectiveness of two techniques for forecasting global inflation rates. The first is the Autoregressive Integrated Moving Average, and the second is the gradient-boosted regression based on machine learning. It is worth noting that the study introduces the Gradient Boosting for univariate time series analysis. The results reveal that the Autoregressive Integrated Moving Average performs better than the cross-validation using the Autoregressive Integrated Moving Average, with the root mean square coefficient of 2.53, the mean average moving average error of 2.21, and the mean average moving average error of 0.48. Conversely, the gradient-boosted regression outperforms in testing on train and test datasets, achieving the root mean square coefficient of 0.078, the mean average moving average error of 0.27, and the mean average moving average error of 0.22, highlighting its potential for predictive tasks. The study concentrates on short-term forecasts of global inflation rates, thereby minimizing exposure to long-term macroeconomic risks (political and economic shocks). Both models expect global inflation rates to remain stable or decline from 2023 to 2025, providing stability in decision-making among stakeholders such as consumers and producers.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101402"},"PeriodicalIF":1.7,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 3D residual network-based approach for accurate lung nodule segmentation in CT images","authors":"V.G. Anisha Gnana Vincy ,&nbsp;Haewon Byeon ,&nbsp;Divya Mahajan ,&nbsp;Anu Tonk ,&nbsp;J. Sunil","doi":"10.1016/j.jrras.2025.101407","DOIUrl":"10.1016/j.jrras.2025.101407","url":null,"abstract":"<div><div>Finding cancerous tumors before they spread is very beneficial and might potentially save patients' lives. The availability of reliable and automated lung cancer detection devices is crucial for both cancer diagnosis and radiation treatment planning. Because of the abundance of data, the tumor's size fluctuation, and its location, a CT scan of a lung tumor will show poor contrast. Using deep learning for medical image processing to segment CT images for cancer detection is no easy feat. The malignant lung region shall be effectively separated from the healthy chest area by using an optimization approach with the 3D residual network ResNet50. A dense-feature extraction module takes all of the encoded feature maps and uses them to extract multiscale features. A U-Net model decoder solves the vanishing gradient problem, and a residual network encodes the input lung CT slices into feature maps. Several encoders work in tandem with the suggested design. No matter how severe a lung anomaly is, we have trained a model to extract dense characteristics from it. Even under difficult conditions, the experimental results show that the proposed technique swiftly and correctly produces explicit lung areas without post-processing. The improved segmentation result may also aid in reducing the risk, according to the available data. Evaluation results on the LUNA16 public dataset showed that the provided technique successfully segmented images of lung nodules using accuracy, recall rate, dice coefficient index, and Hausdroff.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101407"},"PeriodicalIF":1.7,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart polymers as gamma ray Shields:Experimental evaluation of shielding performance","authors":"Priyanka G. Ghuge ,&nbsp;Chaitali V. More ,&nbsp;M.I. Sayyed ,&nbsp;Yasser Maghrbi ,&nbsp;Pravina P. Pawar","doi":"10.1016/j.jrras.2025.101398","DOIUrl":"10.1016/j.jrras.2025.101398","url":null,"abstract":"<div><div>The findings of this study will further our understanding of the potential of smart polymers to enhance gamma ray shielding, which will lead to new opportunities for the development of protective materials that are more efficient, adaptable, and lightweight. This work has investigated the shielding properties against gamma and neutrons of six different types of smart polymers: polyurethane, silicon carbide, polypropylene, polytetrafluoroethylene, polyvinylidene fluoride, and poly (vinylidene fluoride-co-hexafluoropropylene). We have calculated the mass attenuation coefficient (MAC) using the NaI (Tl) scintillation detector and the WinXCom tool. The MAC is then used to calculate the linear attenuation coefficient (LAC), half and tenth value layer (HVL &amp; TVL), mean free path (MFP), and effective atomic number (Z_eff) for total photon interaction over the 122–1330 keV energy range. Furthermore, the macroscopic effective removal cross-sections (∑_R) for fast neutrons were calculated. Polyurethane exhibited the highest mass attenuation coefficient (0.141 cm²/g at 122 keV) and a quicker neutron removal cross-section of 0.12 cm⁻¹. This characteristic emphasizes its superior performance in attenuating gamma and neutron radiation. The relative differences between experimental and theoretical mass attenuation coefficient values indicate that the discrepancies range from 1% to 5%, with noteworthy agreement between theoretical and experimental results.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101398"},"PeriodicalIF":1.7,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The potential mechanism of antifluorescent lung cancer by Chinese medicine Huang Qin: Based on bioinformatics molecular, network pharmacology and imaging histology analysis","authors":"Shi Su ,&nbsp;Jianghan Luo ,&nbsp;Fuling Wang ,&nbsp;Siming Li ,&nbsp;Yuan Gao ,&nbsp;Lijun Yan","doi":"10.1016/j.jrras.2025.101381","DOIUrl":"10.1016/j.jrras.2025.101381","url":null,"abstract":"<div><div>This study provides a deep analysis of the potential mechanisms and effects of the traditional Chinese medicine Scutellaria baicalensis in the treatment of non-small cell lung cancer (NSCLC). By integrating public databases and clinical resources, we adopted a comprehensive strategy combining bioinformatics, network pharmacology, and machine learning techniques to screen out tumor biomarkers closely related to the prognosis of NSCLC, and constructed an accurate predictive model to comprehensively elucidate the complex interactions between the active components of Scutellaria baicalensis and the prognosis of NSCLC. The incorporation of radiomics technology enabled us to extract high-throughput radiological features from medical images, achieving non-invasive prediction of tumor biomarker expression status, further enriching our research methods. We constructed a Scutellaria baicalensis-NSCLC interaction network, accurately calculating the intersection of drug-specific targets and disease-related targets, and utilized protein-protein interaction (PPI) networks and functional enrichment analyses to deeply explore the potential mechanisms of action between Scutellaria baicalensis components and NSCLC. With the help of machine learning tools, we successfully identified key hub genes and verified their importance in lung cancer treatment protocols through immune infiltration analysis and molecular docking studies. The study results showed that 45 active components were screened out, with 628 active component-related target sites, 3076 differentially expressed genes, and 5628 co-expressed genes related to the disease Module genes, intersecting targets 98; GO functional enrichment analysis mainly enriched to BP entries 581, cell composition CC entries 23, molecular function MF entries 30 (p.adj &lt;0.01); KEGG pathway enrichment analysis screened out 111 significant signaling pathways (P &lt; 0.05), mainly involving IL-17 Signaling Pathway, TNF Pathway, AGE-RAGE Signaling Pathway in diabaetic,P53 Signaling Pathway, Toll-like rector et al.; molecular docking showed that compounds have good affinity with the screened core targets GAPDHIL6, TNF, JUN, MMP9, CDH1. Machine learning predicted the intersection of core target genes, among which 5 (FABP4, XDH, GPBAR1, CA4, CDH1) were identified as key target genes for drug therapy. This study not only revealed the significant potential and mechanism of action of Scutellaria baicalensis in anti-non-small cell lung cancer but also provided new perspectives and insights for the development of multi-target drug therapy strategies. By integrating various advanced technologies and methods, we have provided a solid theoretical basis and practical guidance for precision treatment and personalized medication for NSCLC, offering new hope for lung cancer patients.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 2","pages":"Article 101381"},"PeriodicalIF":1.7,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}