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  • Open Access

    ARTICLE

    Pharmacologic Inhibition of β-Catenin With Pyrvinium Inhibits Murine and Human Models of Wilms Tumor

    Dina Polosukhina*, Harold D. Love*†, Harold L. Moses‡§¶#, Ethan Lee**††, Roy Zent†§**‡‡, Peter E. Clark*‡

    Oncology Research, Vol.25, No.9, pp. 1653-1664, 2017, DOI:10.3727/096504017X14992942781895

    Abstract Wilms tumor (WT) is the most common renal malignancy in children and the fourth most common pediatric solid malignancy in the US. Although the mechanisms underlying the WT biology are complex, these tumors most often demonstrate activation of the canonical Wnt/β-catenin pathway. We and others have shown that constitutive activation of β-catenin restricted to the renal epithelium is sufficient to induce primitive renal epithelial tumors, which resemble human WT. Here we demonstrate that pharmacologic inhibition of β-catenin gene transcription with pyrvinium inhibits tumor growth and metastatic progression in a murine model of WT. Cellular invasion More >

  • Open Access

    ARTICLE

    Self-Reported Adherence to Capecitabine on XELOX Treatment as Adjuvant Therapy for Colorectal Cancer

    Kazuyoshi Kawakami*, Takashi Yokokawa*, Kazuo Kobayashi*, Takahito Sugisaki*, Kenichi Suzuki*, Mitsukuni Suenaga, Kensei Yamaguchi, Ayaka Inoue, Yoshiaki Machida, Toshiharu Yamaguchi, Toshihiro Hama*

    Oncology Research, Vol.25, No.9, pp. 1625-1631, 2017, DOI:10.3727/096504017X15012905098071

    Abstract Adherence has become an important issue in modern oncology treatment. Most studies have included heterogeneous target tumor types, regimens, and therapy settings. Our study focused on capecitabine during capecitabine plus oxaliplatin (XELOX) treatment as an adjuvant therapy for colorectal cancer. The main aims of this study were to evaluate real-life adherence to capecitabine and to investigate candidate factors that might decrease adherence. We studied 338 consecutive patients who received XELOX treatment between December 1, 2011, and April 30, 2015, at the Cancer Institute Hospital of the Japanese Foundation for Cancer Research. Our study assessed adherence… More >

  • Open Access

    ARTICLE

    Long Noncoding RNA PVT1 Facilitates Cervical Cancer Progression via Negative Regulating of miR-424

    Ya-Li Gao*1, Zi-Shen Zhao†1, Ming-Yun Zhang*, Li-Jie Han*, Yu-Jin Dong, Bo Xu

    Oncology Research, Vol.25, No.8, pp. 1391-1398, 2017, DOI:10.3727/096504017X14881559833562

    Abstract Emerging evidence suggests that the long noncoding RNA (lncRNA) plasmacytoma variant translocation 1 (PVT1) gene is involved in the pathogenesis of cervical cancer. However, the potential mechanism is rarely reported. Our study found that PVT1 was upregulated in cervical cancer tissue and cell lines. After transfecting PVT1 siRNA, the proliferation, migration, and invasion of cervical cancer cells were markedly decreased. miRNA expression profiles demonstrate that miR-424 was markedly downregulated in cervical cancer tissue. Bioinformatics analysis revealed that miR-424 was potentially targeted by PVT1, which was confirmed by dual-luciferase reporter assay. Pearson’s correlation analysis showed that More >

  • Open Access

    ARTICLE

    MicroRNA-598 Inhibits Cell Proliferation and Invasion of Glioblastoma by Directly Targeting Metastasis Associated in Colon Cancer-1 (MACC1)

    Ning Wang*1, Yang Zhang†1, Huaxin Liang

    Oncology Research, Vol.26, No.8, pp. 1275-1283, 2018, DOI:10.3727/096504018X15185735627746

    Abstract The dysregulation of microRNA (miRNA) expression is closely related with tumorigenesis and tumor development in glioblastoma (GBM). In this study, we found that miRNA-598 (miR-598) expression was significantly downregulated in GBM tissues and cell lines. Restoring miR-598 expression inhibited cell proliferation and invasion in GBM. Moreover, we validated that metastasis associated in colon cancer-1 (MACC1) is a novel target of miR-598 in GBM. Restoring MACC1 expression reversed the inhibitory effects of miR-598 overexpression on GBM cells. In addition, miR-598 overexpression suppressed Met/ AKT pathway activation in GBM. Our results provided compelling evidence that miR-598 serves More >

  • Open Access

    REVIEW

    The Peritoneal Macrophages in Inflammatory Diseases and Abdominal Cancers

    Ting Liu1, Fang Liu1, Lei-Wen Peng, Li Chang, Yong-Mei Jiang

    Oncology Research, Vol.26, No.5, pp. 817-826, 2018, DOI:10.3727/096504017X15130753659625

    Abstract Peritoneal macrophages (PMs) are the major cell type of peritoneal cells that participate in multiple aspects of innate and acquired immunity in the peritoneal cavity. PMs have an ability to release a large amount of proinflammatory and anti-inflammatory cytokines and therefore play a critical role in regulating the differentiation of innate immune cells and inflammatory T cells. Accumulating studies demonstrate that the immunological reactions and inflammatory responses of PMs are strongly related to the pathogenic processes of various inflammatory diseases and abdominal cancers. Consequently, the regulation of PM activation has gradually emerged as a promising More >

  • Open Access

    ARTICLE

    Contrast Normalization Strategies in Brain Tumor Imaging: From Preprocessing to Classification

    Samar M. Alqhtani1, Toufique A. Soomro2,*, Faisal Bin Ubaid3, Ahmed Ali4, Muhammad Irfan5, Abdullah A. Asiri6

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1539-1562, 2024, DOI:10.32604/cmes.2024.051475

    Abstract Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries. Magnetic resonance imaging (MRI) and computed tomography (CT) are utilized to capture brain images. MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders. Typically, manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention. However, early diagnosis of brain tumors is intricate, necessitating the use of computerized methods. This research introduces an innovative approach for… More > Graphic Abstract

    Contrast Normalization Strategies in Brain Tumor Imaging: From Preprocessing to Classification

  • Open Access

    ARTICLE

    Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

    Awais Khan1, Chomyong Kim2, Jung-Yeon Kim2, Ahsan Aziz1, Yunyoung Nam3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1729-1755, 2024, DOI:10.32604/cmes.2024.049618

    Abstract Sleep posture surveillance is crucial for patient comfort, yet current systems face difficulties in providing comprehensive studies due to the obstruction caused by blankets. Precise posture assessment remains challenging because of the complex nature of the human body and variations in sleep patterns. Consequently, this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification, thereby enhancing the analysis of body position and comfort. This method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras, which depict six commonly adopted postures: supine,… More > Graphic Abstract

    Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

  • Open Access

    ARTICLE

    Predicting the Mechanical Behavior of a Bioinspired Nanocomposite through Machine Learning

    Xingzi Yang1, Wei Gao2, Xiaodu Wang1, Xiaowei Zeng1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1299-1313, 2024, DOI:10.32604/cmes.2024.049371

    Abstract The bioinspired nacre or bone structure represents a remarkable example of tough, strong, lightweight, and multifunctional structures in biological materials that can be an inspiration to design bioinspired high-performance materials. The bioinspired structure consists of hard grains and soft material interfaces. While the material interface has a very low volume percentage, its property has the ability to determine the bulk material response. Machine learning technology nowadays is widely used in material science. A machine learning model was utilized to predict the material response based on the material interface properties in a bioinspired nanocomposite. This model More >

  • Open Access

    ARTICLE

    A Hybrid Approach for Predicting the Remaining Useful Life of Bearings Based on the RReliefF Algorithm and Extreme Learning Machine

    Sen-Hui Wang1,2,*, Xi Kang1, Cheng Wang1, Tian-Bing Ma1, Xiang He2, Ke Yang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1405-1427, 2024, DOI:10.32604/cmes.2024.049281

    Abstract Accurately predicting the remaining useful life (RUL) of bearings in mining rotating equipment is vital for mining enterprises. This research aims to distinguish the features associated with the RUL of bearings and propose a prediction model based on these selected features. This study proposes a hybrid predictive model to assess the RUL of rolling element bearings. The proposed model begins with the pre-processing of bearing vibration signals to reconstruct sixty time-domain features. The hybrid model selects relevant features from the sixty time-domain features of the vibration signal by adopting the RReliefF feature selection algorithm. Subsequently,… More >

  • Open Access

    ARTICLE

    Advanced Machine Learning Methods for Prediction of Blast-Induced Flyrock Using Hybrid SVR Methods

    Ji Zhou1,2, Yijun Lu3, Qiong Tian1,2, Haichuan Liu3, Mahdi Hasanipanah4,5,*, Jiandong Huang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1595-1617, 2024, DOI:10.32604/cmes.2024.048398

    Abstract Blasting in surface mines aims to fragment rock masses to a proper size. However, flyrock is an undesirable effect of blasting that can result in human injuries. In this study, support vector regression (SVR) is combined with four algorithms: gravitational search algorithm (GSA), biogeography-based optimization (BBO), ant colony optimization (ACO), and whale optimization algorithm (WOA) for predicting flyrock in two surface mines in Iran. Additionally, three other methods, including artificial neural network (ANN), kernel extreme learning machine (KELM), and general regression neural network (GRNN), are employed, and their performances are compared to those of four More >

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