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Search Results (37)
  • Open Access

    REVIEW

    Engendered nanoparticles for treatment of brain tumors

    SOROUSH SOLEYMANI1, MOHAMMAD DOROUDIAN2,*, MAHDIEH SOEZI3,4, ALI BELADI5, KIARASH ASGARI2, ASO MOBARAKSHAHI2, ARYANA AGHAEIPOUR2, RONAN MACLOUGHLIN6,7,8,*

    Oncology Research, Vol.33, No.1, pp. 15-26, 2025, DOI:10.32604/or.2024.053069 - 20 December 2024

    Abstract Brain metastasis and primary glioblastoma multiforme represent the most common and lethal malignant brain tumors. Its median survival time is typically less than a year after diagnosis. One of the major challenges in treating these cancers is the efficiency of the transport of drugs to the central nervous system. The blood-brain barrier is cooperating with advanced stages of malignancy. The blood-brain barrier poses a significant challenge to delivering systemic medications to brain tumors. Nanodrug delivery systems have emerged as promising tools for effectively crossing this barrier. Additionally, the development of smart nanoparticles brings new hope More >

  • Open Access

    ARTICLE

    Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

    Suganya Athisayamani1, A. Robert Singh2, Gyanendra Prasad Joshi3, Woong Cho4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 155-183, 2025, DOI:10.32604/cmes.2024.056129 - 17 December 2024

    Abstract In radiology, magnetic resonance imaging (MRI) is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological structures. MRI is particularly effective for detecting soft tissue anomalies. Traditionally, radiologists manually interpret these images, which can be labor-intensive and time-consuming due to the vast amount of data. To address this challenge, machine learning, and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI scans. This manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning methods. There are three… More >

  • Open Access

    ARTICLE

    Enhanced Diagnostic Precision: Deep Learning for Tumors Lesion Classification in Dermatology

    Rafid Sagban1,2,*, Haydar Abdulameer Marhoon3,4, Saadaldeen Rashid Ahmed5,6,*

    Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1035-1051, 2024, DOI:10.32604/iasc.2024.058416 - 30 December 2024

    Abstract Skin cancer is a highly frequent kind of cancer. Early identification of a phenomenon significantly improves outcomes and mitigates the risk of fatalities. Melanoma, basal, and squamous cell carcinomas are well-recognized cutaneous malignancies. Malignant We can differentiate Melanoma from non-pigmented carcinomas like basal and squamous cell carcinoma. The research on developing automated skin cancer detection systems has primarily focused on pigmented malignant type melanoma. The limited availability of datasets with a wide range of lesion categories has hindered in-depth exploration of non-pigmented malignant skin lesions. The present study investigates the feasibility of automated methods for… More >

  • Open Access

    ARTICLE

    The Impact of Nursing Staff’s Work Attitude on the Fear of Patients Recovering from Benign Tumors: Family Support as a Mediating Variable

    Chengzhe Guo1, Aihua Cheng2,*, Jian Chen2, Gaojie Cheng3

    Psycho-Oncologie, Vol.18, No.4, pp. 291-303, 2024, DOI:10.32604/po.2024.054446 - 04 December 2024

    Abstract The perception of nursing staff’s attitude influences patient fear. Understanding this dynamic is crucial for fostering a supportive environment conducive to patient well-being and effective healthcare practices. The purpose of this research is to investigate how the attitudes and behaviours of nursing staff influence the fear and anxiety levels of patients recovering from benign tumors, aiming to improve patient care and recovery outcomes. Data was collected from a sample of 100 participants, comprising 20 nursing staff and 80 patients recovering from benign tumors. Surveys were administered to gather quantitative data on attitudes and fear levels.… More >

  • Open Access

    ARTICLE

    Segmentation of Head and Neck Tumors Using Dual PET/CT Imaging: Comparative Analysis of 2D, 2.5D, and 3D Approaches Using UNet Transformer

    Mohammed A. Mahdi1, Shahanawaj Ahamad2, Sawsan A. Saad3, Alaa Dafhalla3, Alawi Alqushaibi4, Rizwan Qureshi5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2351-2373, 2024, DOI:10.32604/cmes.2024.055723 - 31 October 2024

    Abstract The segmentation of head and neck (H&N) tumors in dual Positron Emission Tomography/Computed Tomography (PET/CT) imaging is a critical task in medical imaging, providing essential information for diagnosis, treatment planning, and outcome prediction. Motivated by the need for more accurate and robust segmentation methods, this study addresses key research gaps in the application of deep learning techniques to multimodal medical images. Specifically, it investigates the limitations of existing 2D and 3D models in capturing complex tumor structures and proposes an innovative 2.5D UNet Transformer model as a solution. The primary research questions guiding this study… More >

  • Open Access

    ARTICLE

    Fibroblast activation protein (FAP) as a prognostic biomarker in multiple tumors and its therapeutic potential in head and neck squamous cell carcinoma

    RUIFANG LI1, XINRONG NAN2,*, MING LI3,*, OMAR RAHHAL3

    Oncology Research, Vol.32, No.8, pp. 1323-1334, 2024, DOI:10.32604/or.2024.046965 - 17 July 2024

    Abstract Background: Fibroblast activation protein (FAP), a cell surface serine protease, plays roles in tumor invasion and immune regulation. However, there is currently no pan-cancer analysis of FAP. Objective: We aimed to assess the pan-cancer expression profile of FAP, its molecular function, and its potential role in head and neck squamous cell carcinoma (HNSC). Methods: We analyzed gene expression, survival status, immune infiltration, and molecular functional pathways of FAP in The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) tumors. Furthermore, to elucidate the role of FAP in HNSC, we performed proliferation, migration, and invasion assays… More >

  • Open Access

    REVIEW

    Targeting brain tumors with innovative nanocarriers: bridging the gap through the blood-brain barrier

    KARAN WADHWA1, PAYAL CHAUHAN1, SHOBHIT KUMAR2, RAKESH PAHWA3,*, RAVINDER VERMA4, RAJAT GOYAL5, GOVIND SINGH1, ARCHANA SHARMA6, NEHA RAO3, DEEPAK KAUSHIK1,*

    Oncology Research, Vol.32, No.5, pp. 877-897, 2024, DOI:10.32604/or.2024.047278 - 23 April 2024

    Abstract Background: Glioblastoma multiforme (GBM) is recognized as the most lethal and most highly invasive tumor. The high likelihood of treatment failure arises from the presence of the blood-brain barrier (BBB) and stem cells around GBM, which avert the entry of chemotherapeutic drugs into the tumor mass. Objective: Recently, several researchers have designed novel nanocarrier systems like liposomes, dendrimers, metallic nanoparticles, nanodiamonds, and nanorobot approaches, allowing drugs to infiltrate the BBB more efficiently, opening up innovative avenues to prevail over therapy problems and radiation therapy. Methods: Relevant literature for this manuscript has been collected from a comprehensive More > Graphic Abstract

    Targeting brain tumors with innovative nanocarriers: bridging the gap through the blood-brain barrier

  • Open Access

    ARTICLE

    Gastric cancer secreted miR-214-3p inhibits the anti-angiogenesis effect of apatinib by suppressing ferroptosis in vascular endothelial cells

    WEIXUE WANG#, TONGTONG WANG#, YAN ZHANG, TING DENG, HAIYANG ZHANG*, YI BA*

    Oncology Research, Vol.32, No.3, pp. 489-502, 2024, DOI:10.32604/or.2023.046676 - 06 February 2024

    Abstract Different from necrosis, apoptosis, autophagy and other forms of cell death, ferroptosis is a mechanism that catalyzes lipid peroxidation of polyunsaturated fatty acids under the action of iron divalent or lipoxygenase, leading to cell death. Apatinib is currently used in the third-line standard treatment of advanced gastric cancer, targeting the anti-angiogenesis pathway. However, Apatinib-mediated ferroptosis in vascular endothelial cells has not been reported yet. Tumor-secreted exosomes can be taken up into target cells to regulate tumor development, but the mechanism related to vascular endothelial cell ferroptosis has not yet been discovered. Here, we show that More >

  • Open Access

    ARTICLE

    High-throughput computational screening and in vitro evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl) phenyl]-1H-isoindole-1,3(2H)-dione (C3), as a novel EGFR—HER2 dual inhibitor in gastric tumors

    MESFER AL SHAHRANI, REEM GAHTANI, MOHAMMAD ABOHASSAN, MOHAMMAD ALSHAHRANI, YASSER ALRAEY, AYED DERA, MOHAMMAD RAJEH ASIRI, PRASANNA RAJAGOPALAN*

    Oncology Research, Vol.32, No.2, pp. 251-259, 2024, DOI:10.32604/or.2023.043139 - 28 December 2023

    Abstract Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation, adhesion, angiogenesis, and metastasis. Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations. Hence, dual inhibition strategies are recommended to increase potency and reduce cytotoxicity. In this study, we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities. Diversity-based High-throughput Virtual Screening (D-HTVS) was used to screen the whole ChemBridge small molecular… More > Graphic Abstract

    High-throughput computational screening and <i>in vitro</i> evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl) phenyl]-1H-isoindole-1,3(2H)-dione (C3), as a novel EGFR—HER2 dual inhibitor in gastric tumors

  • Open Access

    ARTICLE

    Advancing Brain Tumor Analysis through Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis

    S. Kannan1,*, S. Anusuya2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3835-3851, 2023, DOI:10.32604/cmc.2023.042465 - 26 December 2023

    Abstract Gliomas, the most prevalent primary brain tumors, require accurate segmentation for diagnosis and risk assessment. In this paper, we develop a novel deep learning-based method, the Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis (DHA-ISSP) model. The DHA-ISSP model combines a three-band 3D convolutional neural network (CNN) U-Net architecture with dynamic hierarchical attention mechanisms, enabling precise tumor segmentation and survival prediction. The DHA-ISSP model captures fine-grained details and contextual information by leveraging attention mechanisms at multiple levels, enhancing segmentation accuracy. By achieving remarkable results, our approach surpasses 369 competing teams in the 2020 Multimodal… More >

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