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  • Open Access


    Roles of miR-214 in bone physiology and disease


    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 miR-214 by other ncRNAs, such… More >

  • Open Access


    A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

    Muhammad Junaid Umer1, Muhammad Sharif1, Majed Alhaisoni2, Usman Tariq3, Ye Jin Kim4, Byoungchol Chang5,*

    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 proposed a deep learning-based (DL)… More >

  • Open Access


    Biobanking in the digital pathology era


    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 being propose in order to… More >

  • Open Access


    MicroRNA-1277 Inhibits Proliferation and Migration of Hepatocellular Carcinoma HepG2 Cells by Targeting and Suppressing BMP4 Expression and Reflects the Significant Indicative Role in Hepatocellular Carcinoma Pathology and Diagnosis After Magnetic Resonance Imaging Assessment

    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 E-cadherin, -catenin, and vimentin, were… More >

  • Open Access


    A Stacked Ensemble-Based Classifier for Breast Invasive Ductal Carcinoma Detection on Histopathology Images

    Ali G. Alkhathami*

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 235-247, 2022, DOI:10.32604/iasc.2022.024952

    Abstract Breast cancer is one of the main causes of death in women. When body tissues start behaves abnormally and the ratio of tissues growth becomes asymmetrical then this stage is called cancer. Invasive ductal carcinoma (IDC) is the early stage of breast cancer. The early detection and diagnosis of invasive ductal carcinoma is a significant step for the cure of IDC breast cancer. This paper presents a convolutional neural network (CNN) approach to detect and visualize the IDC tissues in breast on histological images dataset. The dataset consists of 90 thousand histopathological images containing two categories: Invasive Ductal Carcinoma positive… More >

  • Open Access


    ResNet50-Based Effective Model for Breast Cancer Classification Using Histopathology Images

    Nishant Behar*, Manish Shrivastava

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 823-839, 2022, DOI:10.32604/cmes.2022.017030

    Abstract Breast cancer is considered an immense threat and one of the leading causes of mortality in females. It is curable only when detected at an early stage. A standard cancer diagnosis approach involves detection of cancer-related anomalies in tumour histopathology images. Detection depends on the accurate identification of the landmarks in the visual artefacts present in the slide images. Researchers are continuously striving to develop automatic machine-learning algorithms for processing medical images to assist in tumour detection. Nowadays, computer-based automated systems play an important role in cancer image analysis and help healthcare experts make rapid and correct inferences about the… More >

  • Open Access


    Automated Grading of Breast Cancer Histopathology Images Using Multilayered Autoencoder

    Shakra Mehak1, M. Usman Ashraf2, Rabia Zafar3, Ahmed M. Alghamdi4, Ahmed S. Alfakeeh5, Fawaz Alassery6, Habib Hamam7, Muhammad Shafiq8,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3407-3423, 2022, DOI:10.32604/cmc.2022.022705

    Abstract Breast cancer (BC) is the most widely recognized cancer in women worldwide. By 2018, 627,000 women had died of breast cancer (World Health Organization Report 2018). To diagnose BC, the evaluation of tumours is achieved by analysis of histological specimens. At present, the Nottingham Bloom Richardson framework is the least expensive approach used to grade BC aggressiveness. Pathologists contemplate three elements, 1. mitotic count, 2. gland formation, and 3. nuclear atypia, which is a laborious process that witness's variations in expert's opinions. Recently, some algorithms have been proposed for the detection of mitotic cells, but nuclear atypia in breast cancer… More >

  • Open Access


    Single-cell systems neuroscience: A growing frontier in mental illness


    BIOCELL, Vol.46, No.1, pp. 7-11, 2022, DOI:10.32604/biocell.2022.017680

    Abstract The development of effective treatments for psychiatric disease has been disappointing in recent decades given the advancements in neuroscience. Moreover, rising rates of mental illness such as addiction and depression compel scientists and physicians to discover novel and creative solutions. One such approach that has proven effective is systems neuroscience: A focus on networks as opposed to mechanism. Further, investigation at the single-cell and circuit level is likely to be fruitful in such endeavors as this resolution describes the functional psychopathology that allows for intervention. More >

  • Open Access


    Severity Grade Recognition for Nasal Cavity Tumours Using Décor CNN

    Prabhakaran Mathialagan*, Malathy Chidambaranathan

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 929-946, 2022, DOI:10.32604/iasc.2022.020163

    Abstract Nasal cavity and paranasal sinus tumours that occur in the respiratory tract are the most life-threatening disease in the world. The human respiratory tract has many sites which has different mucosal lining like frontal, parred, sphenoid and ethmoid sinuses. Nasal cavity tumours can occur at any different mucosal linings and chances of prognosis possibility from one nasal cavity site to another site is very high. The paranasal sinus tumours can metastases to oral cavity and digestive tracts may lead to excessive survival complications. Grading the respiratory tract tumours with dysplasia cases are more challenging using manual pathological procedures. Manual microscopic… More >

  • Open Access


    Role of GM3 ganglioside in the pathology of some progressive human diseases and prognostic importance of serum anti-GM3 antibodies


    BIOCELL, Vol.45, No.6, pp. 1485-1494, 2021, DOI:10.32604/biocell.2021.016250

    Abstract Glycosphingolipids (gangliosides) have been characterized as important biological molecules with a key role as regulators in many physiological processes on cellular, tissue, organ, and organism levels. The deviations in their normal amounts, production, and metabolism are very often related to the development of many multi-factor socially important diseases. GM3 ganglioside, as a small molecule, plays important roles in the cascade regulatory pathways in the pathology of many disorders like neurodegenerative diseases, autoimmune diseases, inflammation, diabetes, malignant transformation, and others. Ganglioside GM3 and its derivatives are membrane-bound glycosphingolipids composed of an oligosaccharide head structure containing one sialic acid residue. These molecules… More >

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