Multiomics analyses decipher intricate changes in the cellular and metabolic landscape of steatotic livers upon dietary restriction and sleeve gastrectomy DOI Creative Commons
Shuai Chen, Qinghe Zeng, Xiurong Cai

et al.

International Journal of Biological Sciences, Journal Year: 2024, Volume and Issue: 20(11), P. 4438 - 4457

Published: Jan. 1, 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a chronic, progressive that encompasses spectrum of steatosis, steatohepatitis (or MASH), and fibrosis. Evidence suggests dietary restriction (DR) sleeve gastrectomy (SG) can lead to remission hepatic steatosis inflammation through weight loss, but it unclear whether these procedures induce distinct metabolic or immunological changes in MASLD livers. This study aims elucidate the intricate following DR, SG sham surgery rats fed high-fat diet as model obesity-related MASLD, comparison clinical cohort patients undergoing SG. Single-cell single-nuclei transcriptome analysis, spatial metabolomics, immunohistochemistry revealed landscape, while circulating biomarkers were measured serum samples. Artificial intelligence (AI)-assisted image analysis characterized distribution hepatocytes, myeloid cells lymphocytes. In experimental rats, improved body mass index, injury triglyceride levels. Both DR attenuated fibrosis rats. Metabolism-related genes (

Language: Английский

Diagnosis, clinical characteristics, and treatment of combined hepatocellular-cholangiocarcinoma DOI
Takeshi Terashima,

Kenichi Harada,

Taro Yamashita

et al.

Japanese Journal of Clinical Oncology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

Abstract The concept and definition of combined hepatocellular-cholangiocarcinoma (cHCC-CCA), an extremely rare condition accounting for only 1% all primary liver cancers, has shifted in recent years. latest World Health Organization Classification (fifth edition) includes two types cHCC-CCAs, (i) the classical type described previous edition, which contains a mixture distinctly differentiated components both hepatocellular carcinoma (HCC) intrahepatic cholangiocarcinoma (ICC) (ii) intermediate cell wherein cells comprising tumor express cholangiocellular features. However, pathogenesis cHCC-CCA, including its origins, remains controversial even among experts. Treatment strategies cHCC-CCA clinical practice have been determined based on imaging findings, markers, pathologically predominant either HCC or ICC, suggesting that yet to be established as independent disease entity. As with treatment strategy HCC-CCA involves initially considering resectability. Although systemic therapy considered patients unsuitable local treatment, no prospective trials evaluated efficacy safety could explain lack standard care. In years, however, studies demonstrated immune checkpoint inhibitors therapeutic results having reported cHCC-CCA. Hence, further accumulation cases is expected facilitate establishment consensus near future.

Language: Английский

Citations

0
Research trends and hotspots evolution of artificial intelligence for cholangiocarcinoma over the past 10 years: a bibliometric analysis DOI Creative Commons

Keheng Wang,

Yuting Li, Song Yang

et al.

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 14

Published: Feb. 13, 2025

Objective To analyze the research hotspots and potential of Artificial Intelligence (AI) in cholangiocarcinoma (CCA) through visualization. Methods A comprehensive search publications on application AI CCA from January 1, 2014, to December 31, 2023, within Web Science Core Collection, was conducted, citation information extracted. CiteSpace 6.2.R6 used for visualization analysis information. Results total 736 were included this study. Early primarily focused traditional treatment methods care strategies CCA, but since 2019, there has been a significant shift towards development optimization algorithms their early cancer diagnosis decision-making. China emerged as country with highest volume publications, while Khon Kaen University Thailand academic institution number publications. core group authors involved dense network international collaboration identified. HEPATOLOGY found be most influential journal field. The disciplinary pattern domain exhibits characteristic multiple disciplines intersecting integrating. Conclusion current revolve around three directions: classification preoperative assessment metastasis risk prediction postoperative recurrence CCA. complementarity interdependence among different applications will facilitate future

Language: Английский

Citations

0
Deciphering the Oncogenic Landscape of Hepatocytes Through Integrated Single‐Nucleus and Bulk RNA‐Seq of Hepatocellular Carcinoma DOI Creative Commons
Huanhou Su, Xiangtian Zhou, Guanchuan Lin

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Abstract Hepatocellular carcinoma (HCC) is a major cause of cancer‐related mortality, while the hepatocyte mechanisms driving oncogenesis remains poorly understood. In this study, single‐nucleus RNA sequencing samples from 22 HCC patients revealed 10 distinct subtypes, including beneficial Hep0, predominantly malignant Hep2, and immunosuppressive Hep9. These subtypes were strongly associated with patient prognosis, confirmed in TCGA‐LIHC Fudan cohorts through composition deconvolution. A quantile‐based scoring method developed to integrate data 29 public datasets, creating Quantile Distribution Model (QDM) excellent diagnostic accuracy (Area Under Curve, AUC = 0.968‐0.982). QDM was employed screen potential biomarkers, revealing that PDE7B functions as key gene whose suppression promotes progression. Guided by genes specific Hep0/2/9 categorized into metabolic, inflammatory, matrix classes, which are distinguishable mutation frequencies, survival times, enriched pathways, immune infiltration. Meanwhile, sensitive drugs three classes identified, namely ouabain, teniposide, TG‐101348. This study presents largest single‐cell dataset date, offering transformative insights hepatocarcinogenesis comprehensive framework for advancing diagnostics, prognostics, personalized treatment strategies.

Language: Английский

Citations

0
A deep learning model of histologic tumor differentiation as a prognostic tool in hepatocellular carcinoma DOI
Ameya Patil, Bashar Hasan, Byoung Uk Park

et al.

Modern Pathology, Journal Year: 2025, Volume and Issue: unknown, P. 100747 - 100747

Published: March 1, 2025

Language: Английский

Citations

0
Comprehensive overview of artificial intelligence in surgery: a systematic review and perspectives DOI

Olivia Chevalier,

Gérard Dubey,

Amine Benkabbou

et al.

Pflügers Archiv - European Journal of Physiology, Journal Year: 2025, Volume and Issue: unknown

Published: March 15, 2025

Language: Английский

Citations

0
BiliQML: a supervised machine-learning model to quantify biliary forms from digitized whole slide liver histopathological images DOI
Dominick J. Hellen, Meredith E. Fay,

David H. Lee

et al.

AJP Gastrointestinal and Liver Physiology, Journal Year: 2024, Volume and Issue: 327(1), P. G1 - G15

Published: April 23, 2024

BiliQML is the first comprehensive machine-learning platform for biliary form analysis in whole slide histopathological images. This provides clinical and basic science researchers with a novel tool improved quantification characterization of tract disorders.

Language: Английский

Citations

3
Combined hepatocellular cholangiocarcinoma: A clinicopathological update DOI Creative Commons
Mukul Vij, Fadl H. Veerankutty, Ashwin Rammohan

et al.

World Journal of Hepatology, Journal Year: 2024, Volume and Issue: 16(5), P. 766 - 775

Published: May 22, 2024

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer associated with an appalling prognosis. The diagnosis and management of this entity have been challenging to physicians, radiologists, surgeons, pathologists, oncologists alike. diagnostic prognostic value biomarkers such as the immunohistochemical expression nestin, progenitor cell marker, explored recently. With better understanding biology clinical course cHCC-CCA, newer treatment modalities like immune checkpoint inhibitors are being tried improve survival patients disease. In review, we give account recent developments in pathology, approach, cHCC-CCA.

Language: Английский

Citations

3
Neural Network Enables High Accuracy for Hepatitis B Surface Antigen Detection with a Plasmonic Platform DOI

Weihong Sun,

Jingjie Nan, Hongqin Xu

et al.

Nano Letters, Journal Year: 2024, Volume and Issue: 24(28), P. 8784 - 8792

Published: July 8, 2024

The detection of hepatitis B surface antigen (HBsAg) is critical in diagnosing virus (HBV) infection. However, existing clinical technologies inevitably cause certain inaccuracies, leading to delayed or unwarranted treatment. Here, we introduce a label-free plasmonic biosensing method based on the thickness-sensitive coupling, combined with supervised deep learning (DL) using neural networks. strategy utilizing networks process output data can reduce limit (LOD) sensor and significantly improve accuracy (from 93.1%-97.4% 99%-99.6%). Compared widely used emerging technologies, our platform achieves accurate decisions higher sensitivity short assay time (∼30 min). integration DL models considerably simplifies readout procedure, resulting substantial decrease processing time. Our findings offer promising avenue for developing high-precision molecular tools point-of-care (POC) applications.

Language: Английский

Citations

3
Glycerophospholipid-driven lipid metabolic reprogramming as a common key mechanism in the progression of human primary hepatocellular carcinoma and cholangiocarcinoma DOI Creative Commons

Yanran Bi,

Xihui Ying, Wanbin Chen

et al.

Lipids in Health and Disease, Journal Year: 2024, Volume and Issue: 23(1)

Published: Oct. 1, 2024

Language: Английский

Citations

3
Key requirements for advancing machine learning approaches in single entity electrochemistry DOI Creative Commons
Viacheslav Shkirskiy, Frédéric Kanoufi

Current Opinion in Electrochemistry, Journal Year: 2024, Volume and Issue: 46, P. 101526 - 101526

Published: April 26, 2024

Despite the noteworthy progress in Single Entity Electrochemistry (SEE) last decade, field still must undergo further advancements to attain requisite maturity for facilitating and propelling machine learning (ML)-based discoveries. This mini-review presents an analysis of required developments domain, using success AlphaFold biology as a benchmark future progress. The first essential requirement is creation support high-quality, centralized, open-access databases on electrochemical properties single entities. should be facilitated through automation standardization experiments, promoting high-throughput output comparison between datasets. Finally, new type interdisciplinary specialist, trained pinpoint critical issues SEE implement solutions from applied informatics, vital ML approaches flourish field.

Language: Английский

Citations

2