Susan Azizmohammadi^*, Sima Azizmohammadi^*, Aghdas Safari^†, Maria Kaghazian^‡, Mina Sadrkhanlo^§, Vahid Behnod^¶, Mehri Seifoleslami^#

Oncology Research, Vol.25, No.4, pp. 495-501, 2017, DOI:10.3727/096504016X14749735594687

Abstract The investigation of specific genes will establish more useful biomarkers for accurate detection and management of gynecological cancers, especially patients with cervical cancer (CCP). The aim of this study was to evaluate the expression level of RIPK4 and EZH2 messenger RNA (RIPK4 and EZH2 mRNA) in CCP. Expression of RIPK4 and EZH2 in the tissues was determined by immunohistochemistry and qRT-PCR methods. Correlations of RIPK4 and EZH2 mRNA with clinical and pathological parameters were analyzed using the Fisher’s exact test. The mRNA level of RIPK4 was significantly upregulated in tumor tissues compared with matched adjacent… More >

Sanae Haga^*, Takeaki Ozawa^†, Naoki Morita^‡, Mami Asano^§, Shigeki Jin^¶, Yimin^#, Michitaka Ozaki^*§¶

Oncology Research, Vol.26, No.3, pp. 467-472, 2018, DOI:10.3727/096504017X15040166233313

Abstract Akt is commonly overexpressed and activated in cancer cells and plays a pivotal role in cell survival, protection, and chemoresistance. Therefore, Akt is one of the target molecules in understanding characters of cancer cells and developing anticancer drugs. Here we examined whether a newly developed photo-activatable Akt (PA-Akt) probe, based on a light-inducible protein interaction module of plant cryptochrome2 (CRY2) and cryptochrome-interacting basic helix–loop–helix (CIB1), can regulate Akt-associated cell functions. By illuminating blue light to the cells stably transfected with PA-Akt probe, CRY2-Akt (a fusion protein of CRY2 and Akt) underwent a structural change and… More >

Kun Yang^1,2,3, Shilong Chang¹, Yucheng Wang¹, Minghui Wang¹, Jiahui Yang¹, Shuang Liu^1,2,3, Kun Liu^1,2,3, Linyan Xue^1,2,3,*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 393-410, 2024, DOI:10.32604/cmc.2023.044994

Abstract Clear cell renal cell carcinoma (ccRCC) represents the most frequent form of renal cell carcinoma (RCC), and accurate International Society of Urological Pathology (ISUP) grading is crucial for prognosis and treatment selection. This study presents a new deep network called Multi-scale Fusion Network (MsfNet), which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images. The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity. The model was trained and tested using 90 Hematoxylin and Eosin (H&E) stained whole slide images (WSIs), which… More >

Manas Ranjan Prusty¹, Rishi Dinesh², Hariket Sukesh Kumar Sheth², Alapati Lakshmi Viswanath², Sandeep Kumar Satapathy^2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3077-3094, 2023, DOI:10.32604/cmc.2023.042718

Abstract This paper presents a novel computerized technique for the segmentation of nuclei in hematoxylin and eosin (H&E) stained histopathology images. The purpose of this study is to overcome the challenges faced in automated nuclei segmentation due to the diversity of nuclei structures that arise from differences in tissue types and staining protocols, as well as the segmentation of variable-sized and overlapping nuclei. To this extent, the approach proposed in this study uses an ensemble of the UNet architecture with various Convolutional Neural Networks (CNN) architectures as encoder backbones, along with stain normalization and test time… More >

Arslan Akram^1,2, Javed Rashid^2,3,4, Fahima Hajjej⁵, Sobia Yaqoob^1,6, Muhammad Hamid⁷, Asma Irshad⁸, Nadeem Sarwar^9,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1081-1101, 2023, DOI:10.32604/cmc.2023.041558

Abstract Around one in eight women will be diagnosed with breast cancer at some time. Improved patient outcomes necessitate both early detection and an accurate diagnosis. Histological images are routinely utilized in the process of diagnosing breast cancer. Methods proposed in recent research only focus on classifying breast cancer on specific magnification levels. No study has focused on using a combined dataset with multiple magnification levels to classify breast cancer. A strategy for detecting breast cancer is provided in the context of this investigation. Histopathology image texture data is used with the wavelet transform in this… More >

Tawfeeq Shawly¹, Ahmed A. Alsheikhy^2,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 731-751, 2023, DOI:10.32604/cmc.2023.039433

Abstract More than 500,000 patients are diagnosed with breast cancer annually. Authorities worldwide reported a death rate of 11.6% in 2018. Breast tumors are considered a fatal disease and primarily affect middle-aged women. Various approaches to identify and classify the disease using different technologies, such as deep learning and image segmentation, have been developed. Some of these methods reach 99% accuracy. However, boosting accuracy remains highly important as patients’ lives depend on early diagnosis and specified treatment plans. This paper presents a fully computerized method to detect and categorize tumor masses in the breast using two… More >

LAKSHANA SADU^#, R.HARI KRISHNAN^#, R.L. AKSHAYA, I. SARANYA, UDIPT RANJAN DAS, SNEHA SATISHKUMAR, N. SELVAMURUGAN^*

BIOCELL, Vol.47, No.4, pp. 751-760, 2023, DOI:10.32604/biocell.2023.026911

Abstract MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) that regulate the expression of their target mRNAs post-transcriptionally. Since their discovery, thousands of highly conserved miRNAs have been identified and investigated for their role in human health and diseases. MiR-214 has been increasingly reported to have an association with the regulation of bone metabolism. Reports suggested that miR-214 controls the critical aspects of osteoblasts (bone-forming cells), including their differentiation, proliferation, viability, and migration. Studies have also reported the functional significance of miR-214 in bone diseases and suggested its candidature as a diagnostic and therapeutic target. Further, targeting More >

Muhammad Junaid Umer¹, Muhammad Sharif¹, Majed Alhaisoni², Usman Tariq³, Ye Jin Kim⁴, Byoungchol Chang^5,*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1001-1016, 2023, DOI:10.32604/csse.2023.030463

Abstract Breast cancer (BC) is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every year. The BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6% of total cases. Early diagnosis and detection of breast cancer disease with proper treatment may reduce the number of deaths. The gold standard for BC detection is biopsy analysis which needs an expert for correct diagnosis. Manual diagnosis of BC is a complex and challenging task. This work… More >

GIUSEPPINA BONIZZI, LORENZO ZATTONI, NICOLA FUSCO^*

Oncology Research, Vol.29, No.4, pp. 229-233, 2021, DOI:10.32604/or.2022.024892

Abstract Digital Pathology is becoming more and more important to achieve the goal of precision medicine. Advances in whole-slide imaging, software integration, and the accessibility of storage solutions have changed the pathologists’ clinical practice, not only in terms of laboratory workflow but also for diagnosis and biomarkers analysis. In parallel with the pathology setting advancement, translational medicine is approaching the unprecedented opportunities unrevealed by artificial intelligence (AI). Indeed, the increased usage of biobanks’ datasets in research provided new challenges for AI applications, such as advanced algorithms, and computer-aided techniques. In this scenario, machine learning-based approaches are More >

Xinshan Cao^*, Ling Xu^†, Quanyuan Liu^*, Lijuan Yang^‡, Na Li^§, Xiaoxiao Li^*

Oncology Research, Vol.27, No.3, pp. 301-309, 2019, DOI:10.3727/096504018X15213058045841

Abstract Our study aimed to investigate the roles and possible regulatory mechanism of miR-1277 in the development of hepatocellular carcinoma (HCC). HCC patients were identified from patients who were diagnosed with focal liver lesions using magnetic resonance imaging (MRI). The expression levels of miR-1277 in the serum of HCC patients and HepG2 cells were measured. Then miR-1277 mimic, miR-1277 inhibitor, or scramble RNA was transfected into HepG2 cells. The effects of miR-1277 overexpression and suppression on HepG2 cell proliferation, migration, and invasion were then investigated. Additionally, the expression levels of epithelial– mesenchymal transition (EMT)-related markers, including… More >