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Search Results (19)
  • Open Access

    REVIEW

    Hypoxia-inducible factor 1alpha and vascular endothelial growth factor in Glioblastoma Multiforme: a systematic review going beyond pathologic implications

    DIMITRA P. VAGELI1,2,*, PANAGIOTIS G. DOUKAS3, KERASIA GOUPOU2, ANTONIOS D. BENOS2, KYRIAKI ASTARA2,4, KONSTANTINA ZACHAROULI2, SOTIRIS SOTIRIOU5, MARIA IOANNOU2

    Oncology Research, Vol.32, No.8, pp. 1239-1256, 2024, DOI:10.32604/or.2024.052130

    Abstract Glioblastoma multiforme (GBM) is an aggressive primary brain tumor characterized by extensive heterogeneity and vascular proliferation. Hypoxic conditions in the tissue microenvironment are considered a pivotal player leading tumor progression. Specifically, hypoxia is known to activate inducible factors, such as hypoxia-inducible factor 1alpha (HIF-1α), which in turn can stimulate tumor neo-angiogenesis through activation of various downward mediators, such as the vascular endothelial growth factor (VEGF). Here, we aimed to explore the role of HIF-1α/VEGF immunophenotypes alone and in combination with other prognostic markers or clinical and image analysis data, as potential biomarkers of GBM prognosis… More >

  • Open Access

    ARTICLE

    IKIP downregulates THBS1/FAK signaling to suppress migration and invasion by glioblastoma cells

    ZHAOYING ZHU1,#, YANJIA HU2,#, FENG YE2, HAIBO TENG2, GUOLIANG YOU1, YUNHUI ZENG2, MENG TIAN2, JIANGUO XU2, JIN LI2, ZHIYONG LIU2, HAO LIU2,*, NIANDONG ZHENG1,*

    Oncology Research, Vol.32, No.7, pp. 1173-1184, 2024, DOI:10.32604/or.2024.042456

    Abstract Background: Inhibitor of NF-κB kinase-interacting protein (IKIP) is known to promote proliferation of glioblastoma (GBM) cells, but how it affects migration and invasion by those cells is unclear. Methods: We compared levels of IKIP between glioma tissues and normal brain tissue in clinical samples and public databases. We examined the effects of IKIP overexpression and knockdown on the migration and invasion of GBM using transwell and wound healing assays, and we compared the transcriptomes under these different conditions to identify the molecular mechanisms involved. Results: Based on data from our clinical samples and from public databases, More >

  • Open Access

    ARTICLE

    Developing a Model for Parkinson’s Disease Detection Using Machine Learning Algorithms

    Naif Al Mudawi*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4945-4962, 2024, DOI:10.32604/cmc.2024.048967

    Abstract Parkinson’s disease (PD) is a chronic neurological condition that progresses over time. People start to have trouble speaking, writing, walking, or performing other basic skills as dopamine-generating neurons in some brain regions are injured or die. The patient’s symptoms become more severe due to the worsening of their signs over time. In this study, we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk factors. The research worked on the publicly available dataset on PD, and the dataset consists of a set of significant characteristics of PD. We aim to apply… More >

  • Open Access

    REVIEW

    Molecularly Targeted Drugs Plus Radiotherapy and Temozolomide Treatment for Newly Diagnosed Glioblastoma: A Meta-Analysis and Systematic Review

    Jiahao Su*, Meiqin Cai*, Wensheng Li*, Bo Hou, Haiyong He, Cong Ling,Tengchao Huang, Huijiao Liu, Ying Guo*

    Oncology Research, Vol.24, No.2, pp. 117-128, 2016, DOI:10.3727/096504016X14612603423511

    Abstract Glioblastoma (GBM) is the most common primary malignant brain tumor that nearly always results in a bad prognosis. Temozolomide plus radiotherapy (TEM+RAD) is the most common treatment for newly diagnosed GBM. With the development of molecularly targeted drugs, several clinical trials were reported; however, the efficacy of the treatment remains controversial. So we attempted to measure the dose of the molecularly targeted drug that could improve the prognosis of those patients. The appropriate electronic databases (PubMed, MEDLINE, EMBASE, and the Cochrane Library) were searched for relevant studies. A meta-analysis was performed after determining which studies… More >

  • Open Access

    ARTICLE

    Knockdown of Ras-Related Protein 25 (Rab25) Inhibits the In Vitro Cytotoxicity and In Vivo Antitumor Activity of Human Glioblastoma Multiforme Cells

    Bingqian Ding1, Bei Cui1, Ming Gao, Zhenjiang Li, Chenyang Xu, Shaokang Fan, Weiya He

    Oncology Research, Vol.25, No.3, pp. 331-340, 2017, DOI:10.3727/096504016X14736286083065

    Abstract Ras-related protein 25 (Rab25) is a member of the Rab family, and it has been reported to play an important role in tumorigenesis. However, its direct involvement in human glioblastoma multiforme (GBM) is still unclear. The aim of the current study was to investigate the potential role of Rab25 in the growth, proliferation, invasion, and migration of human GBM. Our results showed that Rab25 expression was significantly higher in human GBM cell lines compared with a normal astrocyte cell line. In vitro functional studies revealed that knockdown of Rab25 reduced cell proliferation and inhibited invasion More >

  • Open Access

    ARTICLE

    Predicting Rock Burst in Underground Engineering Leveraging a Novel Metaheuristic-Based LightGBM Model

    Kai Wang1, Biao He2,*, Pijush Samui3, Jian Zhou4

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 229-253, 2024, DOI:10.32604/cmes.2024.047569

    Abstract Rock bursts represent a formidable challenge in underground engineering, posing substantial risks to both infrastructure and human safety. These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock, leading to severe seismic events and structural damage. Therefore, the development of reliable prediction models for rock bursts is paramount to mitigating these hazards. This study aims to propose a tree-based model—a Light Gradient Boosting Machine (LightGBM)—to predict the intensity of rock bursts in underground engineering. 322 actual rock burst cases are collected to constitute an exhaustive… More >

  • Open Access

    REVIEW

    Underlying mechanisms and clinical potential of circRNAs in glioblastoma

    LEI ZHANG*, YUAN ZHANG, HUIJUAN GAO, XIN LI, PEIFENG LI*

    Oncology Research, Vol.31, No.4, pp. 449-462, 2023, DOI:10.32604/or.2023.029062

    Abstract Glioblastoma (GBM) is the most malignant form of glioma and is difficult to diagnose, leading to high mortality rates. Circular RNAs (circRNAs) are noncoding RNAs with a covalently closed loop structure. CircRNAs are involved in various pathological processes and have been revealed to be important regulators of GBM pathogenesis. CircRNAs exert their biological effects by 4 different mechanisms: serving as sponges of microRNAs (miRNAs), serving as sponges of RNA binding proteins (RBPs), modulating parental gene transcription, and encoding functional proteins. Among the 4 mechanisms, sponging miRNAs is predominant. Their good stability, broad distribution and high More > Graphic Abstract

    Underlying mechanisms and clinical potential of circRNAs in glioblastoma

  • Open Access

    ARTICLE

    Securing Cloud Computing from Flash Crowd Attack Using Ensemble Intrusion Detection System

    Turke Althobaiti1,2, Yousef Sanjalawe3,*, Naeem Ramzan4

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 453-469, 2023, DOI:10.32604/csse.2023.039207

    Abstract Flash Crowd attacks are a form of Distributed Denial of Service (DDoS) attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing (CC). Botnets are often used by attackers to perform a wide range of DDoS attacks. With advancements in technology, bots are now able to simulate DDoS attacks as flash crowd events, making them difficult to detect. When it comes to application layer DDoS attacks, the Flash Crowd attack that occurs during a Flash Event is viewed as the most intricate issue. This is… More >

  • Open Access

    ARTICLE

    LuNet-LightGBM: An Effective Hybrid Approach for Lesion Segmentation and DR Grading

    Sesikala Bapatla1, J. Harikiran2,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 597-617, 2023, DOI:10.32604/csse.2023.034998

    Abstract Diabetes problems can lead to an eye disease called Diabetic Retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated early, DR becomes a significant reason for blindness. To identify the DR and determine the stages, medical tests are very labor-intensive, expensive, and time-consuming. To address the issue, a hybrid deep and machine learning technique-based autonomous diagnostic system is provided in this paper. Our proposal is based on lesion segmentation of the fundus images based on the LuNet network. Then a Refined Attention Pyramid Network (RAPNet) is used for extracting global… More >

  • Open Access

    ARTICLE

    Probe Attack Detection Using an Improved Intrusion Detection System

    Abdulaziz Almazyad, Laila Halman, Alaa Alsaeed*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4769-4784, 2023, DOI:10.32604/cmc.2023.033382

    Abstract The novel Software Defined Networking (SDN) architecture potentially resolves specific challenges arising from rapid internet growth of and the static nature of conventional networks to manage organizational business requirements with distinctive features. Nevertheless, such benefits lead to a more adverse environment entailing network breakdown, systems paralysis, and online banking fraudulence and robbery. As one of the most common and dangerous threats in SDN, probe attack occurs when the attacker scans SDN devices to collect the necessary knowledge on system susceptibilities, which is then manipulated to undermine the entire system. Precision, high performance, and real-time systems… More >

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