Jonathan E. Heinlen

Canadian Journal of Urology, Vol.30, No.3, pp. 11545-11545, 2023

Abstract This article has no abstract. More >

John V. Dudinec^1,*, Sabrina M. Wang^1,*, Srinath Kotamarti¹, Kostantinos E. Morris², Thomas J. Polascik¹, Judd W. Moul¹

Canadian Journal of Urology, Vol.30, No.3, pp. 11538-11544, 2023

Abstract Introduction: The clinical utility of concurrent Prostate Health Index (PHI) and ExosomeDx Prostate Intelliscore (EPI) testing is unclear. We sought to examine the performance of combined PHI and EPI testing on men undergoing elevated PSA work up.
Materials and methods: Patients who received both EPI and PHI testing were identified from an institutional database of men referred to urology for an elevated total PSA. Cut points of EPI > 15.6 and PHI ≥ 36 were used to denote a positive test. Patients were placed into one of four groups determined by combination of EPI and PHI results.… More >

JIE DUAN, AIDONG GU^*, WEI CHEN, CHANGHAO CHEN, FANGNAN SONG, FAXI CHEN, FANGFANG JIANG, HUIWEN XING

BIOCELL, Vol.47, No.12, pp. 2609-2615, 2023, DOI:10.32604/biocell.2023.042472 - 27 December 2023

Abstract Objective: This study aims to analyze the clinical significance and mechanism of nuclear factor erythroid 2-related factor 2 (NRF2) and glutathione peroxidase 4 (GPX4) in primary hepatic carcinoma (PHC). Methods: The expression of NRF2 and GPX4 in peripheral blood of patients with PHC was determined to analyze the diagnostic value of the two combined for PHC. The prognostic significance of NRF2 and GPX4 was evaluated by 3-year follow-up. Human liver epithelial cells THLE-2 and human hepatocellular carcinoma cells HepG2 were purchased, and the expression of NRF2 and GPX4 in the cells was determined. NRF2 and GPX4… More > Graphic Abstract

MUNEEBA MALIK¹, MAMOONA MAQBOOL², TOOBA NISAR³, TAZEEM AKHTER⁴, JAVED AHMED UJAN^5,6, ALANOOD S. ALGARNI⁷, FAKHRIA A. AL JOUFI⁸, SULTAN SHAFI K. ALANAZI⁹, MOHAMMAD HADI ALMOTARED¹⁰, MOUNIR M. SALEM BEKHIT¹¹, MUHAMMAD JAMIL^12,*

Oncology Research, Vol.31, No.6, pp. 899-916, 2023, DOI:10.32604/or.2023.030760 - 15 September 2023

Abstract The low survival rate of Kidney renal clear cell carcinoma (KIRC) patients is largely attributed to cisplatin resistance. Rather than focusing solely on individual proteins, exploring protein-protein interactions could offer greater insight into drug resistance. To this end, a series of in silico and in vitro experiments were conducted to identify hub genes in the intricate network of cisplatin resistance-related genes in KIRC chemotherapy. The genes involved in cisplatin resistance across KIRC were retrieved from the National Center for Biotechnology Information (NCBI) database using search terms as “Kidney renal clear cell carcinoma” and “Cisplatin resistance”. The genes… More >

Hachemi Bennaceur, Meznah Almutairy, Norah Alhussain^*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2687-2706, 2023, DOI:10.32604/iasc.2023.038723 - 11 September 2023

Abstract The dimensionality of data is increasing very rapidly, which creates challenges for most of the current mining and learning algorithms, such as large memory requirements and high computational costs. The literature includes much research on feature selection for supervised learning. However, feature selection for unsupervised learning has only recently been studied. Finding the subset of features in unsupervised learning that enhances the performance is challenging since the clusters are indeterminate. This work proposes a hybrid technique for unsupervised feature selection called GAk-MEANS, which combines the genetic algorithm (GA) approach with the classical k-Means algorithm. In… More >

Yuhang Wang^1,2, Gaojin Li^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-2, 2023, DOI:10.32604/icces.2023.09895

Abstract The chemically active droplets, which converts the chemical energy into a localized fluid flow at the interfaces by generating a concentration gradients of surfactant, can realize self-propulsion with complex trajectories and have been widely studied to mimic the swimming behavior of micro-organisms. In reality, the motion of chemically active droplets is influenced by a combination of diffusiophoresis and Marangoni effect under concentration gradients of surfactant. However, the interaction between these two effects has been only studied for a drop under the constraint of the axial-symmetric motion. To understand the hydrodynamics of the unconstraint motion, we… More >

Ruifeng Zhao¹, Zhijun Wu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09814

Abstract The combined finite-discrete element method (FDEM) can effectively simulate the continuousdiscontinuous failure process of rocks, and is now widely adopted to investigate the issues related to rock mechanics and engineering. The conventional FDEM requires pre-defines constitutive models to calculate the element stress from element deformations [1]. However, the constitutive model used in conventional FDEM is obtained by empirical fitting of rock mechanics test data, and large amount of rock physical and mechanical information present in the test data, such as the nonlinear properties of rock presented in the initial compaction stage, are lost in the… More >

Hong Zhang^1,*, Jiaming Zhou¹, Qi Wang¹, Chengxi Zhu¹, Haijian Shao²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1551-1572, 2023, DOI:10.32604/cmes.2023.027035 - 26 June 2023

Abstract Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity, pseudo-defect interference, and random elastic deformation. This study evaluates the approach for detecting scratches on a metal surface in order to address a problem in the detection process. This paper proposes an improved Gauss-Laplace (LoG) operator combined with a deep learning technique for metal surface scratch identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear when utilizing existing edge detection algorithms. In the process of scratch… More >

Fulu Wei¹, Xin Li¹, Yongqing Guo^1,*, Zhenyu Wang², Qingyin Li¹, Xueshi Ma³

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2001-2018, 2023, DOI:10.32604/iasc.2023.035799 - 21 June 2023

Abstract Traffic flow prediction plays an important role in intelligent transportation systems and is of great significance in the applications of traffic control and urban planning. Due to the complexity of road traffic flow data, traffic flow prediction has been one of the challenging tasks to fully exploit the spatiotemporal characteristics of roads to improve prediction accuracy. In this study, a combined flow direction level traffic flow prediction graph convolutional network (GCN) and long short-term memory (LSTM) model based on spatiotemporal characteristics is proposed. First, a GCN model is employed to capture the topological structure of… More >

WEI LIANG^1,2,*, ZONGWEI ZHANG^1,2, KEJU YANG^1,2,3, HONGTU HU^1,2, QIANG LUO^1,2, ANKANG YANG^1,2, LI CHANG⁴, YUANYUAN ZENG⁴

BIOCELL, Vol.47, No.6, pp. 1253-1263, 2023, DOI:10.32604/biocell.2023.027373 - 19 May 2023

Abstract Background: Diabetic nephropathy (DN) is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide. Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN. Kidney biopsy is the gold standard for diagnosing DN; however, its invasive character is its primary limitation. The machine learning approach provides a non-invasive and specific criterion for diagnosing DN, although traditional machine learning algorithms need to be improved to enhance diagnostic performance. Methods: We applied high-throughput RNA sequencing to obtain the genes… More >