VIGNESH BALAJI E¹, DIVYA RAMESH², MANISHA CHUNGAN SHAJU³, AKSHARA KUMAR⁴, SAMYAK PANDEY¹, RAKSHA NAYAK¹, V. ALKA⁵, SRISHTI MUNJAL⁶, AMIR SALIMI⁷, K. SREEDHARA RANGANATH PAI^1,*, SHANKAR M. BAKKANNAVAR²

Oncology Research, Vol.32, No.1, pp. 73-94, 2024, DOI:10.32604/or.2023.030401

Abstract Exosomes, small tiny vesicle contains a large number of intracellular particles that employ to cause various diseases and prevent several pathological events as well in the human body. It is considered a “double-edged sword”, and depending on its biological source, the action of exosomes varies under physiological conditions. Also, the isolation and characterization of the exosomes should be performed accurately and the methodology also will vary depending on the exosome source. Moreover, the uptake of exosomes from the recipients’ cells is a vital and initial step for all the physiological actions. There are different mechanisms present in the exosomes’ cellular… More > Graphic Abstract

JIAWEI FU^1,2,3,#, CHUNSHUAI WU^1,2,3,#, GUANHUA XU^1,2,3, JINLONG ZHANG¹, YIQIU LI¹, CHUNYAN JI^1,2,3, ZHIMING CUI^1,2,3,*

BIOCELL, Vol.47, No.4, pp. 739-749, 2023, DOI:10.32604/biocell.2023.026881

Abstract Spinal cord injury (SCI), a complex neurological disorder, triggers a series of devastating neuropathological events such as ischemia, oxidative stress, inflammatory events, neuronal apoptosis, and motor dysfunction. However, the classical necrosome, which consists of receptor-interacting protein (RIP)1, RIP3, and mixed-lineage kinase domain-like protein, is believed to control a novel type of programmed cell death called necroptosis, through tumour necrosis factor-alpha/tumour necrosis factor receptor-1 signalling or other stimuli. Several studies reported that necroptosis plays an important role in neural cell damage, release of intracellular pro-inflammatory factors, lysosomal dysfunction and endoplasmic reticulum stress. Recent research indicates that necroptosis is crucial to the… More >

LI YANG^1,2, KUN DENG³, ZHIQIANG MOU^1,2, PINGFU XIONG^1,2, JIAN WEN^1,2, JING LI^1,2,*

Oncology Research, Vol.30, No.5, pp. 243-258, 2022, DOI: 10.32604/or.2022.027958

Abstract Background: Considering the great heterogeneity of Hepatocellular carcinoma (HCC), more accurate prognostic models are urgently needed. This paper combined the advantages of genomics and pathomics to construct a prognostic model. Methods: First, we collected data from hepatocellular carcinoma patients with complete mRNA expression profiles and clinical annotations from the TCGA database. Then, based on immune-related genes, we used random forest plots to screen prognosis-related genes and build prognostic models. Bioinformatics was used to identify biological pathways, evaluate the tumor microenvironment, and perform drug susceptibility testing. Finally, we divided the patients into different subgroups according to the gene model algorithm. Pathological… More >

M. Muthalakshmi^1,*, T. Merlin Inbamalar², C. Chandravathi³, K. Saravanan⁴

Computer Systems Science and Engineering, Vol.46, No.1, pp. 735-747, 2023, DOI:10.32604/csse.2023.032449

Abstract This research work develops new and better prognostic markers for predicting Childhood MedulloBlastoma (CMB) using a well-defined deep learning architecture. A deep learning architecture could be designed using ideas from image processing and neural networks to predict CMB using histopathological images. First, a convolution process transforms the histopathological image into deep features that uniquely describe it using different two-dimensional filters of various sizes. A 10-layer deep learning architecture is designed to extract deep features. The introduction of pooling layers in the architecture reduces the feature dimension. The extracted and dimension-reduced deep features from the arrangement of convolution layers and pooling… More >

Sukhendra Singh¹, Sur Singh Rawat, Manoj Gupta³, B. K. Tripathi⁴, Faisal Alanazi⁵, Arnab Majumdar⁶, Pattaraporn Khuwuthyakorn⁷, Orawit Thinnukool^7,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3063-3083, 2023, DOI:10.32604/cmc.2023.032363

Abstract Currently, breast cancer has been a major cause of deaths in women worldwide and the World Health Organization (WHO) has confirmed this. The severity of this disease can be minimized to the large extend, if it is diagnosed properly at an early stage of the disease. Therefore, the proper treatment of a patient having cancer can be processed in better way, if it can be diagnosed properly as early as possible using the better algorithms. Moreover, it has been currently observed that the deep neural networks have delivered remarkable performance for detecting cancer in histopathological images of breast tissues. To… More >

KAI WANG^2,#, FENGTIAN ZHANG^1,3,4,#, CHANGLONG WEN⁵, ZHIHUA HUANG⁶, ZHIHAO HU¹, YUWEN ZHANG¹, FUQIANG HU^2,*, LIJUAN WEN^1,6,*

Oncology Research, Vol.29, No.5, pp. 351-363, 2021, DOI:10.32604/or.2022.025696

Abstract The blood-brain barrier (BBB) is an essential component in regulating and maintaining the homeostatic microenvironment of the central nervous system (CNS). During the occurrence and development of glioblastoma (GBM), BBB is pathologically destroyed with a marked increase in permeability. Due to the obstruction of the BBB, current strategies for GBM therapeutics still obtain a meager success rate and may lead to systemic toxicity. Moreover, chemotherapy could promote pathological BBB functional restoration, which results in significantly reduced intracerebral transport of therapeutic agents during multiple administrations of GBM and the eventual failure of GBM chemotherapy. The effective delivery of intracerebral drugs still… More >

K. Shankar¹, E. Laxmi Lydia², Sachin Kumar^1,*, Ali S. Abosinne³, Ahmed alkhayyat⁴, A. H. Abbas⁵, Sarmad Nozad Mahmood⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4541-4557, 2022, DOI:10.32604/cmc.2022.031247

Abstract Oral Squamous Cell Carcinoma (OSCC) is a type of Head and Neck Squamous Cell Carcinoma (HNSCC) and it should be diagnosed at early stages to accomplish efficient treatment, increase the survival rate, and reduce death rate. Histopathological imaging is a wide-spread standard used for OSCC detection. However, it is a cumbersome process and demands expert’s knowledge. So, there is a need exists for automated detection of OSCC using Artificial Intelligence (AI) and Computer Vision (CV) technologies. In this background, the current research article introduces Improved Slime Mould Algorithm with Artificial Intelligence Driven Oral Cancer Classification (ISMA-AIOCC) model on Histopathological images… More >

Chiara Dalle Fratte^*, Silvia Mezzalira^*, Jerry Polesel^†, Elena De Mattia^*, Antonio Palumbo^‡, Angela Buonadonna^§, Elisa Palazzari^¶, Antonino De Paoli^¶, Claudio Belluco^#, Vincenzo Canzonieri^‡** , Giuseppe Toffoli^*, Erika Cecchin^*

Oncology Research, Vol.28, No.9, pp. 847-855, 2020, DOI:10.3727/096504021X16232280278813

Abstract Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients is related to a favorable prognosis. The identification of early biomarkers predictive of pathological complete response would help optimize the multimodality management of the patients. A panel of 11 tumor-related proteins was investigated by immunohistochemistry in the pretreatment biopsy of a group of locally advanced rectal cancer patients to identify early biomarkers of pathological complete response to neoadjuvant chemoradiotherapy. A mono-institutional retrospective cohort of 95 stage II/III locally advanced rectal cancer patients treated with neoadjuvant chemoradiotherapy and surgery was selected based on clinical–pathological characteristics and the availability of… More >

Vasumathi Devi Majety¹, N. Sharmili², Chinmaya Ranjan Pattanaik³, E. Laxmi Lydia⁴, Subhi R. M. Zeebaree⁵, Sarmad Nozad Mahmood⁶, Ali S. Abosinnee⁷, Ahmed Alkhayyat^8,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4393-4406, 2022, DOI:10.32604/cmc.2022.031109

Abstract Histopathology is the investigation of tissues to identify the symptom of abnormality. The histopathological procedure comprises gathering samples of cells/tissues, setting them on the microscopic slides, and staining them. The investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s knowledge. At the same time, deep learning (DL) techniques are able to derive features, extract data, and learn advanced abstract data representation. With this view, this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification (EHCDL-HIC) model. The proposed EHCDL-HIC technique initially performs Weiner filtering based noise removal technique. Once the… More >

Mahmoud Ragab^1,2,3,*, Alaa F. Nahhas⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2849-2864, 2022, DOI:10.32604/cmc.2022.028855

Abstract Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate. One of the commonly utilized imaging modalities for breast cancer is histopathological images. Since manual inspection of histopathological images is a challenging task, automated tools using deep learning (DL) and artificial intelligence (AI) approaches need to be designed. The latest advances of DL models help in accomplishing maximum image classification performance in several application areas. In this view, this study develops a Deep Transfer Learning with Rider Optimization Algorithm for Histopathological Classification of Breast Cancer (DTLRO-HCBC) technique. The proposed DTLRO-HCBC technique aims to categorize… More >