Prediction method of pharmacokinetic parameters of small molecule drugs based on GCN network model.

Context: Accurately predicting plasma protein binding rate (PPBR) and oral bioavailability (OBA) helps to better reveal the absorption and distribution of drugs in the human body and subsequent drug design. Although machine learning models have achieved good results in prediction accuracy, they often suffer from insufficient accuracy when dealing with data with irregular topological structures.

Methods: In view of this, this study proposes a pharmacokinetic parameter prediction framework based on graph convolutional networks (GCN), which predicts the PPBR and OBA of small molecule drugs.

Exploring Radiomics Features Based on H&E Images as Potential Biomarkers for Evaluating Muscle Atrophy: A Preliminary Study.

Radiomics features have been widely used as novel biomarkers in the diagnosis of various diseases, but whether radiomics features derived from hematoxylin and eosin (H&E) images can evaluate muscle atrophy has not been studied. Therefore, this study aims to establish a new biomarker based on H&E images using radiomics methods to quantitatively analyze H&E images, which is crucial for improving the accuracy of muscle atrophy assessment. Firstly, a weightless muscle atrophy model was established by laying macaques in bed, and H&E images of the shank muscle fibers of the control and bed rest (BR) macaques were collected.

MF-Net: Automated Muscle Fiber Segmentation From Immunofluorescence Images Using a Local-Global Feature Fusion Network.

Histological assessment of skeletal muscle slices is very important for the accurate evaluation of weightless muscle atrophy. The accurate identification and segmentation of muscle fiber boundary is an important prerequisite for the evaluation of skeletal muscle fiber atrophy. However, there are many challenges to segment muscle fiber from immunofluorescence images, including the presence of low contrast in fiber boundaries in immunofluorescence images and the influence of background noise.

Application of radiomics in precision prediction of diagnosis and treatment of gastric cancer.

Gastric cancer is one of the most common malignant tumors. Although some progress has been made in chemotherapy and surgery, it is still one of the highest mortalities in the world. Therefore, early detection, diagnosis and treatment are very important to improve the prognosis of patients.

Muscle Atrophy Evaluation via Radiomics Analysis Using Ultrasound Images: A Cohort Data Study.

Objective: Existing methods for muscle atrophy evaluation based on muscle size measures from ultrasound images are inadequate in precision. Radiomics has been widely used in various medical studies, but its validity for the evaluation of muscle atrophy has not been fully explored.

Methods: This study presents a radiomics analysis for muscle atrophy evaluation using ultrasound images.

Construction of Biocompatible Dual-Drug Loaded Complicated Nanoparticles for Improvement of Synergistic Chemotherapy in Esophageal Cancer.

Combination chemotherapy is a routine treatment for esophageal cancer, but some shortcomings, such as drug toxicity and side effects, greatly limit the clinical application of combination therapy. To overcome these shortcomings, we have developed a mesoporous silica nanoparticle system that was used to load doxorubicin and β-elemene. β-elemene was encapsulated in the pore of mesoporous silica nanoparticle and doxorubicin was electrostatically adsorbed on the surface of mesoporous silica nanoparticle by hyaluronic acid to construct dual drugs synergistic nanoparticles (bMED NPs, ~77.

Bioluminescence Imaging-Based Assessment of the Anti-Triple-Negative Breast Cancer and NF-Kappa B Pathway Inhibition Activity of Britanin.

Britanin has been reported to have therapeutic effects on neurodegenerative and inflammation-based diseases. However, whether it is involved in the regulation of triple-negative breast cancer development has not been elucidated. In this study, we investigated the anti-tumor activity against triple-negative breast cancer tumor of Britanin by bioluminescence imaging using athymic (nu/nu) mice implanted with MDA-MB-231 and SUM-159 cells expressing a luciferase reporter gene, and explored the anti-tumor mechanism of Britanin.

GMBP1-conjugated manganese oxide nanoplates for monitoring of gastric cancer MDR using magnetic resonance imaging.

Multidrug resistance (MDR) is a huge challenge for gastric cancer chemotherapy. Therefore, MDR accurate monitoring is of great significance for the treatment of gastric cancer. GMBP1, an extracellular internalization peptide, can target MDR gastric cancer cells through specific binding to GRP78, which is an MDR-related protein that is overexpressed in gastric cancer cells.

The Antitumor Effects of Britanin on Hepatocellular Carcinoma Cells and its Real-Time Evaluation by In Vivo Bioluminescence Imaging.

Background: Hepatocellular carcinoma is cancer with many new cases and the highest mortality rate. Chemotherapy is the most commonly used method for the clinical treatment of hepatocellular carcinoma. Natural products have become clinically important chemotherapeutic drugs due to their great potential for pharmacological development.

In vivo antitumour activity of Britanin against gastric cancer through nuclear factor-κB-mediated immune response.

Objectives: Britanin was explored for the antitumour effect on gastric cancer, which is a sesquiterpene lactone (SL) extracted from Inula japonica.

Methods: In the present study, cell viability assays were performed to evaluate the antiproliferation effect of Britanin on gastric cancer cells. Tumour development in BGC-823 cell-bearing nude mice was monitored in real-time after Britanin treatment via a bioluminescent imaging method.