Automatic Liver Cancer Detection Using Deep Convolution Neural Network DOI Creative Commons
Kiran Malhari Napte, Anurag Mahajan, Shabana Urooj

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 94852 - 94862

Published: Jan. 1, 2023

Automatic liver cancer detection (ALCD) is very crucial in automatic biomedical image analysis diagnosis as it the largest organ body and plays a significant role metabolic process well elimination of toxins. In last decade, various machine deep learning schemes have been investigated for ALCD using computed tomography (CT) images. However, CT images challenging because noise, intricate structure abdominal images, textural changes throughout making segmentation vital challenge that may result both under-segmentation (u-seg) over-segmentation (o-seg) organ. This paper presents based on proposed Edge Strengthening Parallel UNet (ESP-UNet) to avoid u-seg o-seg Further, offered lightweight sequential Deep Convolution Neural Networks (DCNN). The consequences ESP-UNet DCNN-based are evaluated accuracy, recall, precision, F1-score. suggested approach provides noteworthy improvement over traditional state arts.

Language: Английский

Mechanisms of HRAS regulation of liver hepatocellular carcinoma for prognosis prediction DOI Creative Commons

Xingbao Fang,

Yan Cai, Zixiao Zhao

et al.

BMC Cancer, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 28, 2025

Liver hepatocellular carcinoma (LIHC) often has a poor prognosis. Since the relationship between HRas proto-oncogene, GTPase (HRAS) and LIHC not been elucidated, aim of this study was to explore mechanisms by which HRAS is involved in regulating prognosis LIHC. We usedThe Cancer Genome Atlas (TCGA) database characterize differences gene expression patients healthy individuals. In addition, we analysed relationships levels clinicopathological characteristics patients. Next, used univariate multivariate Cox regression analyses identify prognostic factors. Differentially expressed genes were identified low- high-expression groups, KEGG GO GSEA performed underlying mechanisms. The effects high low on determined according CIBERSORT. subsequently assayed at cellular level, these data validated tumour xenograft model. established as signature features. Patients categorized into groups. that associated with carbon metabolism, PPAR signalling pathway, small molecule catabolism cancer. Furthermore, conclude results from elevated immune cell infiltration. LASSO + KNN build an AI classification model shows good performance distinguishing liver cancer tissues form normal tissues. Finally, verified highly cells promotes growth. role assess can be applied predict survival, for personalized treatment strategies, provide information development potential targeted therapies new ideas patient treatment.

Language: Английский

Citations

0
Developing Liver Microphysiological Systems for Biomedical Applications DOI
Jinglin Wang,

Xiangyi Wu,

Junqi Zhao

et al.

Advanced Healthcare Materials, Journal Year: 2023, Volume and Issue: 13(21)

Published: Nov. 21, 2023

Microphysiological systems (MPSs), also known as organ chips, are micro-units that integrate cells with diverse physical and biochemical environmental cues. In the field of liver MPSs, cellular components have advanced from simple planar cell cultures to more sophisticated 3D formations such spheroids organoids. Additionally, progress in microfluidic devices, bioprinting, engineering matrix materials, interdisciplinary technologies significant promise for producing MPSs biomimetic structures functions. This review provides a comprehensive summary including their clinical applications future developmental potential. First, key principal types engineered utilized cultivation, briefly introduced. Subsequently, biomedical creation disease models, drug absorption, distribution, metabolism, excretion, toxicity, discussed. Finally, challenges encountered by summarized, research directions development proposed.

Language: Английский

Citations

9
The Prospect of Hepatic Decellularized Extracellular Matrix as a Bioink for Liver 3D Bioprinting DOI Creative Commons

Wen Shi,

Zhe Zhang, Xiaohong Wang

et al.

Biomolecules, Journal Year: 2024, Volume and Issue: 14(8), P. 1019 - 1019

Published: Aug. 16, 2024

The incidence of liver diseases is high worldwide. Many factors can cause fibrosis, which in turn lead to cirrhosis and even cancer. Due the shortage donor organs, immunosuppression, other factors, only a few patients are able undergo transplantation. Therefore, how construct bioartificial that be transplanted has become global research hotspot. With rapid development three-dimensional (3D) bioprinting field tissue engineering regenerative medicine, researchers have tried use various 3D technologies livers vitro. In terms choice bioinks, decellularized extracellular matrix (dECM) many advantages over materials for cell-laden hydrogel bioprinting. This review mainly summarizes acquisition dECM its application as bioink with respect availability, printability, biocompatibility aspects puts forward current challenges prospects.

Language: Английский

Citations

3
Projected epidemiological trends and burden of liver cancer by 2040 based on GBD, CI5plus, and WHO data DOI Creative Commons
Qianqian Guo, Xiaorong Zhu, Narasimha M. Beeraka

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 15, 2024

Incidence of liver cancer as one the most common cancers worldwide and become significant contributor for mortality among patients. The disease burden, risk factors, trends in incidence globally was described subsequently estimated projections or by 2040. Data regarding age-standardized rates obtained from multiple databases, including GLOBOCAN 2020, CI5 volumes I–XI, WHO database, Global Burden Disease (GBD)-2019. Concentrating on variations, this thorough analysis offers insights into patterns based gender age. Our findings encompass indicators, (ASRs), average annual percentage change (AAPC), future extending up to year Liver holds sixth position terms frequently diagnosed stands leading cause cancer-related deaths accounting 905,677 new cases 782,000 fatalities. Additionally, contributed 12,528,421 disability-adjusted life years (DALYs), with an DALYs rate 161.92 2019 worldwide. age-specific exhibited variations across different regions, showing a fivefold difference males females. A increase observed North Europe Asia, while African countries reported higher burden (ASR, 10 per 100,000) compared developed countries. Since last few years, have increased attained Annual Average Percentage Change (AAPC) 7.7 (95% CI 3.9–11.6) men highest AAPC 12.2 9.5–15.0) women. In 2019, Western emerged high-risk region related smoking alcohol consumption, high-income America carried high associated body-mass index. projected trend indicates surge incident cases, expected rise around 905,347 1,392,474 This study evidence pertinent cancer, particularly both young older adults, encompassing females, well those who are HIV-infected HBsAg positive. population poses public health concern that warrants attention healthcare professionals prioritize promotion awareness development effective prevention strategies, many developing

Language: Английский

Citations

3
Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer DOI Creative Commons

S. K. Pande,

Pala Kalyani,

S Nagendram

et al.

BMC Medical Imaging, Journal Year: 2025, Volume and Issue: 25(1)

Published: Feb. 3, 2025

Liver cancer detection is critically important in the discipline of biomedical image testing and diagnosis. Researchers have explored numerous machine learning (ML) techniques deep (DL) approaches aimed at automated recognition liver disease by analysing computed tomography (CT) images. This study compares two frameworks, Deep Convolutional Neural Network (DCNN) Hierarchical Fusion Networks (HFCNN), to assess their effectiveness segmentation. The contribution includes enhancing edges textures CT images through filtering achieve precise Additionally, an existing DL framework was employed for strengths this paper include a clear emphasis on criticality imaging diagnostics. It also highlights challenges associated with segmentation provides comprehensive summary recent literature. However, certain difficulties arise during process due overlapping structures, such as bile ducts, blood vessels, noise, textural changes, size location variations, inherent heterogeneity. These factors may lead errors subsequently different analyses. research analysis advanced methodologies, DCNN HFCNN, detection. evaluation HFCNN conducted using multiple performance metrics, including precision, F1-score, recall, accuracy. assessment detailed these models' compared other state-of-the-art methods identifying cancer.

Language: Английский

Citations

0
WGCNA combined with machine learning to find potential biomarkers of liver cancer DOI Creative Commons

Jiahao Lv,

Ajiao Hou,

Shi-Hao Zhang

et al.

Medicine, Journal Year: 2023, Volume and Issue: 102(50), P. e36536 - e36536

Published: Dec. 15, 2023

The incidence of hepatocellular carcinoma (HCC) has been increasing in recent years. With the development various detection technologies, machine learning is an effective method to screen disease characteristic genes. In this study, weighted gene co-expression network analysis (WGCNA) and are combined find potential biomarkers liver cancer, which provides a new idea for future prediction, prevention, personalized treatment. “limma” software package was used. P < .05 log2 |fold-change| > 1 standard screening differential genes, then module genes obtained by WGCNA crossed obtain key Gene Ontology Kyoto Genome Encyclopedia performed on 3 methods including lasso, support vector machine-recursive feature elimination, RandomForest were used Finally, validation set verify GeneMANIA (http://www.genemania.org) database perform protein–protein interaction networks SPIED3 small molecule drugs. 187 associated with HCC screened using WGCNA. After that, 6 (AADAT, APOF, GPC3, LPA, MASP1, NAT2) selected RandomForest, Absolute Shrinkage Selection Operator, elimination algorithms. These also significantly different external dataset follow same trend as training set. our findings may provide insights into targets diagnosis, treatment HCC. AADAT, NAT2 be cancer future.

Language: Английский

Citations

8
Investigating the mechanism of tricyclic decyl benzoxazole -induced apoptosis in liver Cancer cells through p300-mediated FOXO3 activation DOI Creative Commons

Shuhong Tian,

Keyan Zhong,

Zhaoxin Yang

et al.

Cellular Signalling, Journal Year: 2024, Volume and Issue: 121, P. 111280 - 111280

Published: July 2, 2024

To investigate whether tricyclic decylbenzoxazole (TDB) regulates liver cancer cell proliferation and apoptosis through p300-mediated FOXO acetylation.

Language: Английский

Citations

2
Liver and bile duct organoids and tumoroids DOI Open Access

Xuanming Luo,

Yuda Gong,

Zijun Gong

et al.

Biomedicine & Pharmacotherapy, Journal Year: 2024, Volume and Issue: 178, P. 117104 - 117104

Published: July 17, 2024

Organoids refer to 3D cultures established recapitulate histology, pathology, architecture, and genetic traits of various organs tissues in the body, thereby replacing 2D cell cultures, xenograft, animal models. form a vitro mimic original like liver are derived from embryonic or adult tissue stem cells. Liver bile duct tumor organoids, also called, tumoroids capture diversity, cellular, pathophysiological properties tumors. Moreover, co-culture techniques along with modulation organoids allow for using cancer research drug screening/testing. Therefore, promising platforms studying cancer, which paves way new era personalized therapies. In current review, we aimed discuss special emphasis on their applications, advantages, shortcomings.

Language: Английский

Citations

2
Integrating 3D Bioprinting and Organoids to Better Recapitulate the Complexity of Cellular Microenvironments for Tissue Engineering DOI Open Access
Yan Hu,

Tong Zhu,

Haitao Cui

et al.

Advanced Healthcare Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 8, 2024

Abstract Organoids, with their capacity to mimic the structures and functions of human organs, have gained significant attention for simulating pathophysiology been extensively investigated in recent past. Additionally, 3D bioprinting, as an emerging bio‐additive manufacturing technology, offers potential constructing heterogeneous cellular microenvironments, thereby promoting advancements organoid research. In this review, latest developments bioprinting technologies aimed at enhancing engineering are introduced. The commonly used methods materials organoids, a particular emphasis on advantages combining organoids summarized. These include achieving high cell concentrations form large aggregates, precise deposition building blocks create complex functions, automation throughput ensure reproducibility standardization culture. Furthermore, review provides overview relevant studies from years discusses current limitations prospects future development.

Language: Английский

Citations

2
Clinical significance of RNA methylation in hepatocellular carcinoma DOI Creative Commons

Qiongling Bao,

Yifan Zeng,

Qizhuo Lou

et al.

Cell Communication and Signaling, Journal Year: 2024, Volume and Issue: 22(1)

Published: April 2, 2024

Abstract Hepatocellular carcinoma (HCC) is a primary liver malignancy with high mortality rates and poor prognosis. Recent advances in high-throughput sequencing bioinformatic technologies have greatly enhanced the understanding of genetic epigenetic changes cancer. Among these changes, RNA methylation, most prevalent internal modification, has emerged as significant contributor development progression HCC. Growing evidence reported significantly abnormal levels methylation dysregulation RNA-methylation-related enzymes HCC tissues cell lines. These alterations play crucial role regulation various genes signaling pathways involved HCC, thereby promoting tumor progression. Understanding pathogenesis would help developing prognostic biomarkers targeted therapies for Targeting molecules shown promising potential management terms novel Exploring clinical application may provide new insights approaches Further research this field warranted to fully understand functional roles underlying mechanisms In review, we described multifaceted Moreover, prospects are discussed, which basis subsequent in-depth on

Language: Английский

Citations

1