MOHAMMAD-TAGHI MORADI¹, DHIYA ALTEMEMY², MAJID ASADI-SAMANI^3,*, PEGAH KHOSRAVIAN¹, MARZIYEH SOLTANI³, LEILA HASHEMI¹, AZADEH SAMIEI-SEFAT³

Oncology Research, Vol.32, No.7, pp. 1231-1237, 2024, DOI:10.32604/or.2024.047187

Abstract Background: Despite the availability of chemotherapy drugs such as 5-fluorouracil (5-FU), the treatment of some cancers such as gastric cancer remains challenging due to drug resistance and side effects. This study aimed to investigate the effect of celastrol in combination with the chemotherapy drug 5-FU on proliferation and induction of apoptosis in human gastric cancer cell lines (AGS and EPG85-257). Materials and Methods: In this in vitro study, AGS and EPG85-257 cells were treated with different concentrations of celastrol, 5-FU, and their combination. Cell proliferation was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. The synergistic effect… More >

Zhenyu Qian¹, Yizhang Jiang¹, Zhou Hong¹, Lijun Huang², Fengda Li³, KhinWee Lai⁶, Kaijian Xia^4,5,6,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4741-4762, 2024, DOI:10.32604/cmc.2024.050920

Abstract In this paper, we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering (MAS-DSC) algorithm, aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data, particularly in the field of medical imaging. Traditional deep subspace clustering algorithms, which are mostly unsupervised, are limited in their ability to effectively utilize the inherent prior knowledge in medical images. Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process, thereby enhancing the discriminative power of the feature representations. Additionally, the multi-scale feature extraction… More > Graphic Abstract

Monerah Alawadh^*, Ahmed Barnawi

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4995-5015, 2024, DOI:10.32604/cmc.2024.048762

Abstract Association rule learning (ARL) is a widely used technique for discovering relationships within datasets. However, it often generates excessive irrelevant or ambiguous rules. Therefore, post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors. Recently, several post-processing methods have been proposed, each with its own strengths and weaknesses. In this paper, we propose THAPE (Tunable Hybrid Associative Predictive Engine), which combines descriptive and predictive techniques. By leveraging both techniques, our aim is to enhance the quality of analyzing generated rules. This includes removing irrelevant… More >

Yue Cao^1,2, Longsheng Bao¹, Xiaowei Zhang^1,*, Zhanfei Wang¹, Bingqian Li¹

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 485-503, 2024, DOI:10.32604/sdhm.2024.049698

Abstract This study addresses the issue of inaccurate single damage fingerprint recognition during the process of bridge damage identification. To improve accuracy, the proposed approach involves fusing displacement mode difference and curvature mode difference data for single damage identification, and curvature mode difference and displacement mode wavelet coefficient difference data for two damage identification. The methodology begins by establishing a finite element model of the cable-stayed bridge and obtaining the original damage fingerprints, displacement modes, curvature modes, and wavelet coefficient differences of displacement modes through modal analysis. A fusion program based on the D-S evidence theory… More > Graphic Abstract

Ting Zhang¹, Lei Ye¹, Lingfei Han, Qizhi He, Jianlong Zhu

Oncology Research, Vol.24, No.3, pp. 189-196, 2016, DOI:10.3727/096504016X14641336229602

Abstract Ovarian cancer is highly malignant with a gradually increasing incidence and a high mortality rate. Immunosuppression is induced in ovarian cancer, although the mechanism detail is not clear. It has been indicated that HVEM (herpesvirus entry mediator) B- and T-lymphocyte attenuator (BTLA) negatively regulates the immune responses of T lymphocytes. Here, HVEM mRNA was found to be elevated in ovarian cancer tissue samples and primary ovarian cancer cells in comparison with benign tissue samples. We then knocked down HVEM expression in an ovarian cancer cell line, OVCAR3, by lentivirus-based small hairpin RNA (shRNA). Cell Counting… More >

Ting Zhang¹, Lei Ye¹, Qizhi He, Jianlong Zhu

Oncology Research, Vol.25, No.9, pp. 1665-1665, 2017, DOI:10.3727/096504017X15078984695565

Abstract Ovarian cancer is highly malignant with a gradually increasing incidence and a high mortality rate. Immunosuppression is induced in ovarian cancer, although the mechanism detail is not clear. It has been indicated that HVEM (herpesvirus entry mediator) B- and T-lymphocyte attenuator (BTLA) negatively regulates the immune responses of T lymphocytes. Here, HVEM mRNA was found to be elevated in ovarian cancer tissue samples and primary ovarian cancer cells in comparison with benign tissue samples. We then knocked down HVEM expression in an ovarian cancer cell line, OVCAR3, by lentivirus-based small hairpin RNA (shRNA). Cell Counting… More >

MAHER KURDI^1,*, ALAA ALKHOTANI², ABDULRAHMAN SABBAGH³, EYAD FAIZO⁴, AHMED I. LARY⁵, AHMED K. BAMAGA⁶, MAJID ALMANSOURI⁷, BADR HAFIZ⁸, THAMER ALSHARIF⁹, SALEH BAEESA⁸

Oncology Research, Vol.32, No.6, pp. 1037-1045, 2024, DOI:10.32604/or.2024.051112

Abstract Background: The dysregulation of Isocitrate dehydrogenase (IDH) and the subsequent production of 2-Hydroxyglutrate (2HG) may alter the expression of epigenetic proteins in Grade 4 astrocytoma. The interplay mechanism between IDH, O-6-methylguanine-DNA methyltransferase (MGMT)-promoter methylation, and protein methyltransferase proteins-5 (PRMT5) activity, with tumor progression has never been described. Methods: A retrospective cohort of 34 patients with G4 astrocytoma is classified into IDH-mutant and IDH-wildtype tumors. Both groups were tested for MGMT-promoter methylation and PRMT5 through methylation-specific and gene expression PCR analysis. Inter-cohort statistical significance was evaluated. Results: Both IDH-mutant WHO grade 4 astrocytomas (n = 22, 64.7%) and IDH-wildtype… More > Graphic Abstract

Di Wang, Yuefei Zhu, Jinlong Fei^*, Maohua Guo

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2253-2276, 2024, DOI:10.32604/cmc.2024.049504

Abstract Website fingerprinting, also known as WF, is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination, even when using the Tor anonymity network. While advanced attacks based on deep neural network (DNN) can perform feature engineering and attain accuracy rates of over 98%, research has demonstrated that DNN is vulnerable to adversarial samples. As a result, many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success. However, these methods suffer from high bandwidth overhead or require access to the target… More >

Yaming Kang^1,*, Peishun Ye¹, Yuxiu Bai¹, Shi Qiu²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2151-2168, 2024, DOI:10.32604/cmc.2024.049360

Abstract Hyperspectral imagery encompasses spectral and spatial dimensions, reflecting the material properties of objects. Its application proves crucial in search and rescue, concealed target identification, and crop growth analysis. Clustering is an important method of hyperspectral analysis. The vast data volume of hyperspectral imagery, coupled with redundant information, poses significant challenges in swiftly and accurately extracting features for subsequent analysis. The current hyperspectral feature clustering methods, which are mostly studied from space or spectrum, do not have strong interpretability, resulting in poor comprehensibility of the algorithm. So, this research introduces a feature clustering algorithm for hyperspectral… More >

Yulei Chen¹, Zhaojun Chen^1,2, Shichao Wang¹, Yang Hang¹, Jianpeng Guo^1,*

International Journal of Mental Health Promotion, Vol.26, No.4, pp. 303-315, 2024, DOI:10.32604/ijmhp.2024.046863

Abstract Social-Emotional Competency (SEC), regarded as a critical psychological resource for individuals to adapt to social environments, is an effective protective factor for students’ mental health, impacting their future success and well-being. Analyzing the impact of SEC on university students’ mental health can offer valuable insights for nurturing talents with healthy psychological and physical development. Based on data from two large-scale surveys of Chinese university students, this study designed two comprehensive Multiple Mediation Models involving SEC, stress, coping strategies, and stress reaction to explore the pathway of emotion nurturing mentality. Study 1 utilized a parallel mediation model… More >