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

Patient-derived organoids in translational oncology and drug screening DOI Creative Commons
Ruixin Yang, Yingyan Yu

Cancer Letters, Journal Year: 2023, Volume and Issue: 562, P. 216180 - 216180

Published: April 13, 2023

Patient-derived organoids (PDO) are a new biomedical research model that can reconstruct phenotypic and genetic characteristics of the original tissue useful for on pathogenesis drug screening. To introduce progression in this field, we review key factors constructing derived from epithelial tissues cancers, covering culture medium matrix, morphological characteristics, profiles, high-throughput screening, application potential. We also discuss co-culture system cancer with tumor microenvironment (TME) associated cells. The is widely used evaluating crosstalk cells TME components, such as fibroblasts, endothelial cells, immune microorganisms. article provides prospective standardized cultivation mode, automatic evaluation, sensitivity screening using methods.

Language: Английский

Citations

58
Comparative analysis between 2D and 3D colorectal cancer culture models for insights into cellular morphological and transcriptomic variations DOI Creative Commons
Zaid Nsaif Abbas, Ali Z. Al‐Saffar, Saba Mahdi Jasim

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Oct. 26, 2023

Drug development is a time-consuming and expensive process, given the low success rate of clinical trials. Now, anticancer drug developments have shifted to three-dimensional (3D) models which are more likely mimic tumor behavior compared traditional two-dimensional (2D) cultures. A comparative study among different aspects was conducted between 2D 3D cultures using colorectal cancer (CRC) cell lines, in addition, Formalin-Fixed Paraffin-Embedded (FFPE) block samples patients with CRC were used for evaluation. Compared culture, cells grown displayed significant (p < 0.01) differences pattern proliferation over time, death phase profile, expression tumorgenicity-related genes, responsiveness 5-fluorouracil, cisplatin, doxorubicin. Epigenetically, FFPE shared same methylation microRNA expression, while showed elevation altered expression. Lastly, transcriptomic depending on RNA sequencing thorough bioinformatic analyses (p-adj 0.05) dissimilarity gene profile involving thousands genes (up/down-regulated) multiple pathways each line. Taken together, provides insights into variations cellular morphologies cultured models.

Language: Английский

Citations

34
Drug resistance mechanisms in dopamine agonist-resistant prolactin pituitary neuroendocrine tumors and exploration for new drugs DOI
Jianhua Cheng, Weiyan Xie, Yiyuan Chen

et al.

Drug Resistance Updates, Journal Year: 2024, Volume and Issue: 73, P. 101056 - 101056

Published: Jan. 19, 2024

Language: Английский

Citations

10
Hepatocellular carcinoma and lipid metabolism: Novel targets and therapeutic strategies DOI

Lu-Qi Cao,

Yuhao Xie, Joshua S. Fleishman

et al.

Cancer Letters, Journal Year: 2024, Volume and Issue: 597, P. 217061 - 217061

Published: June 13, 2024

Language: Английский

Citations

10
A state-of-the-art review on the NRF2 in Hepatitis virus-associated liver cancer DOI Creative Commons
Leila Kalantari, Zahra Rostami Ghotbabadi,

Arsalan Gholipour

et al.

Cell Communication and Signaling, Journal Year: 2023, Volume and Issue: 21(1)

Published: Nov. 9, 2023

Abstract According to a paper released and submitted WHO by IARC scientists, there would be 905,700 new cases of liver cancer diagnosed globally in 2020, with 830,200 deaths expected as direct result. Hepatitis B virus (HBV) hepatitis C (HCV), D (HDV) all play critical roles the pathogenesis hepatocellular carcinoma (HCC), despite rising prevalence HCC due non-infectious causes. Liver cirrhosis are devastating consequences HBV HCV infections, which widespread worldwide. Associated high mortality rate, these infections cause about 1.3 million annually primary globally. In addition causing insertional mutations viral gene integration, epigenetic alterations inducing chronic immunological dysfunction methods viruses turn hepatocytes into cancerous ones. While expanding our knowledge illness, identifying pathways also give possibilities for novel diagnostic treatment methods. Nuclear factor erythroid 2-related 2 (NRF2) activation is gaining popularity option oxidative stress (OS), inflammation, metabolic abnormalities. Numerous studies have shown that elevated Nrf2 expression linked HCC, providing more evidence HCC. This aberrant signaling drives cell proliferation, initiates angiogenesis invasion, imparts drug resistance. As result, this master regulator may promising target addition, common effect contributes pathogenesis, development, chronicity infection. However, certain suppress activity, helpful maintaining cellular homeostasis. paper, we discussed influence deregulation on life cycle associated HCV. We summed up mechanisms modulation deregulated viruses. Moreover, describe molecular mechanism modulated cancer, stem cells (LCSCs), caused

Language: Английский

Citations

18
Harnessing CD8+ T cell dynamics in hepatitis B virus‐associated liver diseases: Insights, therapies and future directions DOI Creative Commons
Bing Yue, Yuxia Gao, Yi Hu

et al.

Clinical and Translational Medicine, Journal Year: 2024, Volume and Issue: 14(7)

Published: June 27, 2024

Abstract Hepatitis B virus (HBV) infection playsa significant role in the etiology and progression of liver‐relatedpathologies, encompassing chronic hepatitis, fibrosis, cirrhosis, eventual hepatocellularcarcinoma (HCC). Notably, HBV stands as primary etiologicalfactor driving development HCC. Given contribution ofHBV to liver diseases, a comprehensive understanding immunedynamics microenvironment, spanning infection,fibrosis, HCC, is essential. In this review, we focused on thefunctional alterations CD8 + T cells within pathogenic livermicroenvironment from We thoroughly reviewed roles ofhypoxia, acidic pH, metabolic reprogramming, amino acid deficiency, inhibitory checkpointmolecules, immunosuppressive cytokines, gut‐liver communication shapingthe dysfunction microenvironment. Thesefactors significantly impact clinical prognosis. Furthermore, comprehensivelyreviewed cell‐based therapy strategies for diseases,encompassing infection, Strategies includeimmune checkpoint blockades, T‐cell targeting therapy, therapeuticT‐cell vaccination, adoptive transfer genetically engineered cells, along with combined usage programmed cell death protein‐1/programmeddeath ligand‐1 (PD‐1/PD‐L1) inhibitors mitochondria‐targeted antioxidants.Given that at various stages hepatitis Bvirus‐induced hepatocellular carcinoma (HBV HCC) shows promise, reviewedthe ongoing need research elucidate complex interplay between microenvironment toHCC. also discussed personalized treatment regimens, combining therapeuticstrategies harnessing gut microbiota modulation, which holds potential forenhanced benefits. conclusion, review delves into changes, during HCC progression, andrelated diseases.

Language: Английский

Citations

7
Application of 3D Bioprinting in Liver Diseases DOI Creative Commons
Wenhui Li,

Zhaoyue Liu,

Fengwei Tang

et al.

Micromachines, Journal Year: 2023, Volume and Issue: 14(8), P. 1648 - 1648

Published: Aug. 21, 2023

Liver diseases are the primary reason for morbidity and mortality in world. Owing to a shortage of organ donors postoperative immune rejection, patients routinely suffer from liver failure. Unlike 2D cell models, animal organoids, 3D bioprinting can be successfully employed print living tissues organs that contain blood vessels, bone, kidney, heart, so on. is mainly classified into four types: inkjet bioprinting, extrusion-based laser-assisted (LAB), vat photopolymerization. Bioinks composed hydrogels cells. For hepatic parenchymal cells (hepatocytes) nonparenchymal (hepatic stellate cells, sinusoidal endothelial Kupffer cells) commonly used. Compared conventional scaffold-based approaches, marked by limited functionality complexity, achieve accurate settlement, high resolution, more efficient usage biomaterials, better mimicking complex microstructures native tissues. This method will make contributions disease modeling, drug discovery, even regenerative medicine. However, limitations challenges this cannot ignored. Limitation include requirement diverse fabrication technologies, observation dynamic response under perfusion culture, resolution reproduce microenvironment, Despite this, still promising innovative biofabrication strategy creation artificial multi-cellular tissues/organs.

Language: Английский

Citations

14
Automatic Liver Tumor Segmentation from CT Images Using Graph Convolutional Network DOI Creative Commons

Maryam Khoshkhabar,

Saeed Meshgini,

Reza Afrouzian

et al.

Sensors, Journal Year: 2023, Volume and Issue: 23(17), P. 7561 - 7561

Published: Sept. 1, 2023

Segmenting the liver and tumors in computed tomography (CT) images is an important step toward quantifiable biomarkers for a computer-aided decision-making system precise medical diagnosis. Radiologists specialized physicians use CT to diagnose classify organs tumors. Because these have similar characteristics form, texture, light intensity values, other internal such as heart, spleen, stomach, kidneys confuse visual recognition of tumor division. Furthermore, identification time-consuming, complicated, error-prone, incorrect diagnosis segmentation can hurt patient's life. Many automatic semi-automatic methods based on machine learning algorithms recently been suggested organ segmentation. However, there are still difficulties due poor precision speed lack dependability. This paper presents novel deep learning-based technique segmenting identifying maps. Based LiTS17 database, comprises four Chebyshev graph convolution layers fully connected layer that accurately segment Thus, accuracy, Dice coefficient, mean IoU, sensitivity, precision, recall obtained proposed method according dataset around 99.1%, 91.1%, 90.8%, 99.4%, 91.2%, respectively. In addition, effectiveness was evaluated noisy environment, network could withstand wide range environmental signal-to-noise ratios (SNRs). at SNR = -4 dB, accuracy remained 90%. The model has satisfactory favorable results compared previous research. According positive results, expected be used assist radiologists specialist doctors near future.

Language: Английский

Citations

12
CUEDC1 promotes the growth, migration, epithelial-mesenchymal transition and inhibits apoptosis of hepatocellular carcinoma cells via the TGF-β/Smad signaling pathway DOI
An Zhou, Fuyu Chen,

Zhongchao Chen

et al.

Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, Journal Year: 2025, Volume and Issue: 830, P. 111900 - 111900

Published: Jan. 1, 2025

Language: Английский

Citations

0
Global landscape of hepatic organoid research: A bibliometric and visual study DOI
Tao Li,

Rongqiang Bo,

Jun Yan

et al.

World Journal of Hepatology, Journal Year: 2025, Volume and Issue: 17(2)

Published: Feb. 20, 2025

BACKGROUND Hepatic organoid-based modelling, through the elucidation of a range in vivo biological processes and recreation intricate liver microenvironment, is yielding groundbreaking insights into pathophysiology personalized medicine approaches for diseases. AIM This study was designed to analyse global scientific output hepatic organoid research assess current achievements future trends bibliometric analysis. METHODS Articles were retrieved from Web Science Core Collection, CiteSpace 6.3.R1 employed literature, including outputs, journals, countries, among others. RESULTS Between 2010 2024, total 991 articles pertaining published. The journal Hepatology published greatest number papers, journals with an impact factor greater than 10 constituted 60% top journals. United States Utrecht University identified as most prolific country institution, respectively. Clevers H emerged author, whereas Huch M had highest cocitations, suggesting that both are ideal candidates academic collaboration. Research on organoids has exhibited progressive shift focus, evolving initial investigations model building, differentiation stem cells, bile ducts, progenitor broader spectrum encompassing lipid metabolism, single-cell RNA sequencing, therapeutic applications. phrases exhibiting citation bursts 2022 2024 include “drug resistance”, “disease model”, “patient-derived tumor organoids”. CONCLUSION increased over past decade expected continue grow. Key areas applications diseases drug development. Future likely gain focus patient-derived tumour organoids, disease medicine.

Language: Английский

Citations

0