Inhibiting miRNA-146a suppresses mouse gallstone formation by regulating LXR/megalin/cubilin-media cholesterol absorption.

Background: miRNA has been implicated in regulating cholesterol homeostasis, a critical factor in gallstone formation. Here, we focused on elucidating the role of miR-146a in this pathological process.

Methods: C57BL/6 mice were fed with lithogenic diet (LD) and injected with miR-146 antagomir (anta-146) via the tail vein for various weeks.

Corosolic acid enhances oxidative stress-induced apoptosis and senescence in pancreatic cancer cells by inhibiting the JAK2/STAT3 pathway.

Background: Pancreatic cancer (PC) is a fatal human malignancy with a poor prognosis. Corosolic acid (CRA) is a triterpenoid, has been reported to have inhibitory effects on tumor growth. However, the role of CRA on PC has not been explored.

Multi-task deep learning for medical image computing and analysis: A review.

The renaissance of deep learning has provided promising solutions to various tasks. While conventional deep learning models are constructed for a single specific task, multi-task deep learning (MTDL) that is capable to simultaneously accomplish at least two tasks has attracted research attention. MTDL is a joint learning paradigm that harnesses the inherent correlation of multiple related tasks to achieve reciprocal benefits in improving performance, enhancing generalizability, and reducing the overall computational cost.

The Berberis vulgaris L. extract berberine exerts its anti-oxidant effects to ameliorate cholesterol overloading-induced cell apoptosis in the primary mice hepatocytes: an in vitro study.

Cholesterol overloading stress damages normal cellular functions in hepatocytes and induces metabolic disorders to facilitate the development of multiple diseases, including cardiovascular diseases, which seriously degrades the life quality of human beings. Recent data suggest that the Berberis vulgaris L. extract berberine is capable of regulating cholesterol homeostasis, which is deemed as potential therapeutic drug for the treatment of cholesterol overloading-associated diseases, but its detailed functions and molecular mechanisms are still largely unknown.

Artificial intelligence techniques for neuropathological diagnostics and research.

Artificial intelligence (AI) research began in theoretical neurophysiology, and the resulting classical paper on the McCulloch-Pitts mathematical neuron was written in a psychiatry department almost 80 years ago. However, the application of AI in digital neuropathology is still in its infancy. Rapid progress is now being made, which prompted this article.

An Open-Source AI Framework for the Analysis of Single Cells in Whole-Slide Images with a Note on CD276 in Glioblastoma.

Routine examination of entire histological slides at cellular resolution poses a significant if not insurmountable challenge to human observers. However, high-resolution data such as the cellular distribution of proteins in tissues, e.g.

COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment.

There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. In this paper, we present an end-to-end multitask learning (MTL) framework (COVID-MTL) that is capable of automated and simultaneous detection (against both radiology and NAT) and severity assessment of COVID-19.

Deciphering CT texture features of human visceral fat to evaluate metabolic disorders and surgery-induced weight loss effects.

Background: Metabolic syndrome (MetS) is highly related to the excessive accumulation of visceral adipose tissue (VAT). Quantitative measurements of VAT are commonly applied in clinical practice for measurement of metabolic risks; however, it remains largely unknown whether the texture of VAT can evaluate visceral adiposity, stratify MetS and predict surgery-induced weight loss effects.

Methods: 675 Chinese adult volunteers and 63 obese patients (with bariatric surgery) were enrolled.

PathoFusion: An Open-Source AI Framework for Recognition of Pathomorphological Features and Mapping of Immunohistochemical Data.

We have developed a platform, termed PathoFusion, which is an integrated system for marking, training, and recognition of pathological features in whole-slide tissue sections. The platform uses a bifocal convolutional neural network (BCNN) which is designed to simultaneously capture both index and contextual feature information from shorter and longer image tiles, respectively. This is analogous to how a microscopist in pathology works, identifying a cancerous morphological feature in the tissue context using first a narrow and then a wider focus, hence bifocal.

Identification of lncRNA Signature Associated With Pan-Cancer Prognosis.

Long noncoding RNAs (lncRNAs) have emerged as potential prognostic markers in various human cancers as they participate in many malignant behaviors. However, the value of lncRNAs as prognostic markers among diverse human cancers is still under investigation, and a systematic signature based on these transcripts that related to pan-cancer prognosis has yet to be reported. In this study, we proposed a framework to incorporate statistical power, biological rationale, and machine learning models for pan-cancer prognosis analysis.

Long Noncoding RNA Forms a Growth-Promoting Complex with HNRNPL in Human Glioblastoma through Stabilization of ACTN4 and Activation of NF-κB Signaling.

Purpose: Long noncoding RNAs (lncRNA) have essential roles in diverse cellular processes, both in normal and diseased cell types, and thus have emerged as potential therapeutic targets. A specific member of this family, the SWI/SNF complex antagonist associated with prostate cancer 1 (), has been shown to promote aggressive prostate cancer growth by antagonizing the SWI/SNF complex and therefore serves as a biomarker for poor prognosis. Here, we investigated whether plays a potential role in the development of human glioblastoma (GBM).

Treatment Efficacy of NGF Nanoparticles Combining Neural Stem Cell Transplantation on Alzheimer's Disease Model Rats.

Background: Alzheimer's disease (AD) is the most common type of dementia. It causes progressive brain disorder involving loss of normal memory and thinking skills. The transplantation of neural stem cells (NSCs) has been reported to improve learning and memory function of AD rats, and protects basal forebrain cholinergic neurons.

Andrographolide causes apoptosis via inactivation of STAT3 and Akt and potentiates antitumor activity of gemcitabine in pancreatic cancer.

Gemcitabine is a first-line drug utilised in the chemotherapy of pancreatic cancer; however, this drug induces chemo-resistance and toxicity to normal tissue during treatment. Here, we firstly report that andrographolide (ANDRO) alone not only has anti-pancreatic cancer activity, but it also potentiates the anti-tumour activity of gemcitabine. Treatment with ANDRO alone inhibits proliferation of the pancreatic cancer cell lines in a dose- and time-dependent manner in vitro.

Effects of legumain as a potential prognostic factor on gastric cancers.

Although legumain has been found to be a prognostic factor in both breast cancer and colorectal cancer, its effects on gastric cancer are unknown. In this study, we investigated effects of legumain on gastric cancer and the correlation between legumain expression and prognosis of gastric cancer patients. SGC7901 cells were transduced with legumain cDNA (SGC7901-hLeg) for overexpression of legumain or with legumain shRNA to knock down legumain.