DNeuroMAT: A Deep-Learning-Based Neuron Morphology Analysis Toolbox.

Digital reconstruction of neuronal structures from 3D neuron microscopy images is critical for the quantitative investigation of brain circuits and functions. Currently, neuron reconstructions are mainly obtained by manual or semiautomatic methods. However, these ways are labor-intensive, especially when handling the huge volume of whole brain microscopy imaging data.

Local and Global Context-Enhanced Lightweight CenterNet for PCB Surface Defect Detection.

Printed circuit board (PCB) surface defect detection is an essential part of the PCB manufacturing process. Currently, advanced CCD or CMOS sensors can capture high-resolution PCB images. However, the existing computer vision approaches for PCB surface defect detection require high computing effort, leading to insufficient efficiency.

The State of Systematic Therapies in Clinic for Hepatobiliary Cancers.

Hepatobiliary cancer (HBC) includes hepatocellular carcinoma and biliary tract carcinoma (cholangiocarcinoma and gallbladder carcinoma), and its morbidity and mortality are significantly correlated with disease stage. Surgery is the cornerstone of curative therapy for early stage of HBC. However, a large proportion of patients with HBC are diagnosed with advanced stage and can only receive systemic treatment.

TIF1γ and SMAD4 regulation in colorectal cancer: impact on cell proliferation and liver metastasis.

We investigated the effects of transcriptional intermediary factor 1γ (TIF1γ) and SMAD4 on the proliferation and liver metastasis of colorectal cancer (CRC) cells through knockdown of TIF1γ and/or SMAD4 and knockdown of TIF1γ and/or restoration of SMAD4 expression. Furthermore, we examined TIF1γ and SMAD4 expression in human primary CRC and corresponding liver metastatic CRC specimens. TIF1γ promoted but SMAD4 inhibited the proliferation of CRC cells by competitively binding to activated SMAD2/SMAD3 complexes and then reversely regulating c-Myc, p21, p27, and cyclinA2 levels.

Deep learning in mesoscale brain image analysis: A review.

Mesoscale microscopy images of the brain contain a wealth of information which can help us understand the working mechanisms of the brain. However, it is a challenging task to process and analyze these data because of the large size of the images, their high noise levels, the complex morphology of the brain from the cellular to the regional and anatomical levels, the inhomogeneous distribution of fluorescent labels in the cells and tissues, and imaging artifacts. Due to their impressive ability to extract relevant information from images, deep learning algorithms are widely applied to microscopy images of the brain to address these challenges and they perform superiorly in a wide range of microscopy image processing and analysis tasks.

Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma.

Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance.

Foreign Object Detection in Railway Images Based on an Efficient Two-Stage Convolutional Neural Network.

Foreign object intrusion is one of the main causes of train accidents that threaten human life and public property. Thus, the real-time detection of foreign objects intruding on the railway is important to prevent the train from colliding with foreign objects. Currently, the detection of railway foreign objects is mainly performed manually, which is prone to negligence and inefficient.

The state of therapy modalities in clinic for biliary tract cancer.

Biliary tract cancers (BTCs) include intrahepatic cholangiocarcinoma (iCCA), perihilar and distal cholangiocarcinoma (pCCA and dCCA), and gallbladder carcinoma based on the epithelial site of origin. BTCs are highly aggressive tumors associated with poor prognosis due to widespread metastasis and high recurrence. Surgery is the typical curative-intent treatment, yet the cornerstone of cure depends on the anatomical site of the primary tumor, and only a minority of patients (approximately 30%) has an indication necessitating surgery.

Primary spindle cell sarcoma of gallbladder: An unusual case report and a literature review.

Introduction: Primary spindle cell sarcoma of the gallbladder is a rare condition.

Patient Concerns: A 67-year-old woman was admitted to a local hospital with a chief complaint of abdominal pain in the right upper quadrant for the past 2 months.

Diagnosis And Intervention: Surgical resection was performed following the diagnosis of primary gallbladder sarcoma with local hepatic metastasis.

Deep-Learning-Based Automated Neuron Reconstruction From 3D Microscopy Images Using Synthetic Training Images.

Digital reconstruction of neuronal structures from 3D microscopy images is critical for the quantitative investigation of brain circuits and functions. It is a challenging task that would greatly benefit from automatic neuron reconstruction methods. In this paper, we propose a novel method called SPE-DNR that combines spherical-patches extraction (SPE) and deep-learning for neuron reconstruction (DNR).

DeepRayburst for Automatic Shape Analysis of Tree-Like Structures in Biomedical Images.

Precise quantification of tree-like structures from biomedical images, such as neuronal shape reconstruction and retinal blood vessel caliber estimation, is increasingly important in understanding normal function and pathologic processes in biology. Some handcrafted methods have been proposed for this purpose in recent years. However, they are designed only for a specific application.

Downregulation of lncRNA SBF2-AS1 inhibits hepatocellular carcinoma proliferation and migration by regulating the miR-361-5p/TGF-β1 signaling pathway.

SBF2-AS1 is an oncogenic long non-coding RNA (lncRNA). However, its role and mechanism in hepatocellular carcinoma (HCC) is still not completely clear. The HepG2, Hep3B, Bel-7402 and HL-7702 cell lines were used in our experiments.

An extremely atypical presentation of esophageal squamous cell carcinoma with pancreatic and hepatic metastases: A case report and overview of the literature.

Rationale: Esophageal carcinoma is an aggressive cancer with extremely poor therapeutic outcomes due to its high metastatic potential and a significant risk of recurrence after radical resection. Liver is the most common metastatic target organ of esophageal carcinoma, followed by the lungs, bones, and brain. Few cases of solitary pancreatic and hepatic metastases of esophageal carcinoma have been reported.

Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images.

Digital reconstruction of neuronal structures is very important to neuroscience research. Many existing reconstruction algorithms require a set of good seed points. 3D neuron critical points, including terminations, branch points and cross-over points, are good candidates for such seed points.

3D Neuron Microscopy Image Segmentation via the Ray-Shooting Model and a DC-BLSTM Network.

The morphology reconstruction (tracing) of neurons in 3D microscopy images is important to neuroscience research. However, this task remains very challenging because of the low signal-to-noise ratio (SNR) and the discontinued segments of neurite patterns in the images. In this paper, we present a neuronal structure segmentation method based on the ray-shooting model and the Long Short-Term Memory (LSTM)-based network to enhance the weak-signal neuronal structures and remove background noise in 3D neuron microscopy images.

Neuron Image Segmentation via Learning Deep Features and Enhancing Weak Neuronal Structures.

Neuron morphology reconstruction (tracing) in 3D volumetric images is critical for neuronal research. However, most existing neuron tracing methods are not applicable in challenging datasets where the neuron images are contaminated by noises or containing weak filament signals. In this paper, we present a two-stage 3D neuron segmentation approach via learning deep features and enhancing weak neuronal structures, to reduce the impact of image noise in the data and enhance the weak-signal neuronal structures.

Significant response to anti-PD-1 based immunotherapy plus lenvatinib for recurrent intrahepatic cholangiocarcinoma with bone metastasis: A case report and literature review.

Introduction: The prognosis for recurrent intrahepatic cholangiocarcinoma with bone metastasis remains dismal and its treatment poses a challenge for oncologists. To date, only 2 cases were reported in which pembrolizumab, an agent against programmed cell death protein-1 (PD-1), combined with chemotherapy led to a complete response. The safety and efficacy of nivolumab-based immunotherapy combined with lenvatinibin intrahepatic cholangiocarcinoma is unknown.

DeepBranch: Deep Neural Networks for Branch Point Detection in Biomedical Images.

Morphology reconstruction of tree-like structures in volumetric images, such as neurons, retinal blood vessels, and bronchi, is of fundamental interest for biomedical research. 3D branch points play an important role in many reconstruction applications, especially for graph-based or seed-based reconstruction methods and can help to visualize the morphology structures. There are a few hand-crafted models proposed to detect the branch points.

Development and validation of a CIMP-associated prognostic model for hepatocellular carcinoma.

Background: CpG island methylator phenotype (CIMP), a common biological phenomenon characterized by a subset of concurrently methylated genes, can have an influence on the progression of multiple cancers. However, the potential mechanism of CIMP in hepatocarcinogenesis and its clinical relevance remains only partially understood.

Methods: We used a methylation array from the cancer genome atlas (TCGA) to stratify HCC patients into different CIMP subtypes, and evaluated their correlation with clinical characteristics.

Genome-wide identification of a competing endogenous RNA network in cholangiocarcinoma.

Cholangiocarcinoma (CCA) is the second widespread liver tumor with relatively poor survival. Increasing evidence in recent studies showed long noncoding RNAs (lncRNAs) exert a crucial impact on the development and progression of CCA based on the mechanism of competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-regulated ceRNA in CCA, are only partially understood.

A Multiscale Ray-Shooting Model for Termination Detection of Tree-Like Structures in Biomedical Images.

Digital reconstruction (tracing) of tree-like structures, such as neurons, retinal blood vessels, and bronchi, from volumetric images and 2D images is very important to biomedical research. Many existing reconstruction algorithms rely on a set of good seed points. The 2D or 3D terminations are good candidates for such seed points.

Integrative analysis of DNA methylation and gene expression identify a six epigenetic driver signature for predicting prognosis in hepatocellular carcinoma.

DNA methylation is a crucial regulator of gene transcription in the etiology and pathogenesis of hepatocellular carcinoma (HCC). Thus, it is reasonable to identify DNA methylation-related prognostic markers. Currently, we aimed to make an integrative epigenetic analysis of HCC to identify the effectiveness of epigenetic drivers in predicting prognosis for HCC patients.

Activin A-Smad Signaling Mediates Connective Tissue Growth Factor Synthesis in Liver Progenitor Cells.

Liver progenitor cells (LPCs) are activated in chronic liver damage and may contribute to liver fibrosis. Our previous investigation reported that LPCs produced connective tissue growth factor (CTGF/CCN2), an inducer of liver fibrosis, yet the regulatory mechanism of the production of CTGF/CCN2 in LPCs remains elusive. In this study, we report that Activin A is an inducer of CTGF/CCN2 in LPCs.

An integrin beta4-EGFR unit promotes hepatocellular carcinoma lung metastases by enhancing anchorage independence through activation of FAK-AKT pathway.

Anoikis, a form of programmed cell death, occurs when the cells are detached from the appropriate extracellular matrix. Anoikis resistance or anchorage independence is necessary for distant metastases of cancer. The mechanisms by which hepatocellular carcinoma (HCC) cells become resistant to anoikis are not fully understood.