Loureirin A Promotes Cell Differentiation and Suppresses Migration and Invasion of Melanoma Cells via WNT and AKT/mTOR Signaling Pathways.

Resina Draconis is a traditional Chinese medicine, with the in-depth research, its medicinal value in anti-tumor has been revealed. Loureirin A is extracted from Resina Draconis, however, research on the anti-tumor efficacy of Loureirin A is rare. Herein, we investigated the function of Loureirin A in melanoma.

Four uncommon cycloamphilectane-type diterpenoids with antibacterial activity from the South China Sea soft coral Sinularia brassica.

The chemical investigation on the soft coral Sinularia brassica collected off Xuwen Country, Guangdong Province, China, has resulted in the isolation and characterization of three uncommon cycloamphilectane-type diterpenoids, namely sinucycloamtin A-C (1-3), along with two known analogues (5 and 6). In addition, compounds 2 and 3 were hydrolyzed and their hydrolytic derivative sinucycloamtin D (4) was obtained. The structures of these previously undescribed compounds were established on the basis of extensive spectroscopic analysis, X-ray diffraction analysis, chemical conversion, as well as the comparison with the literature reported data.

Lobosteroids A-F: Six New Highly Oxidized Steroids from the Chinese Soft Coral sp.

To explore the steroidal constituents of the soft coral sp. at the coast of Xuwen County, Guangdong Province, China, a chemical investigation of the above-mentioned soft coral was carried out. After repeated column chromatography over silica gel, Sephadex LH-20, and reversed-phase HPLC, six new steroids, namely lobosteroids A-F (-), along with four known compounds -, were obtained.

Gamabufotalin Induces Apoptosis and Cytoprotective Autophagy through the mTOR Signaling Pathway in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with a high rate of recurrence and a poor prognosis. Here, we investigated the effect and the potential antitumor mechanism of Gamabufotalin (CS-6) against HCC. Our results show that CS-6 strikingly reduced cell viability, inhibited colony formation, and promoted apoptosis in Hep3B and Huh7 cells.

Precise anatomical localization and classification of rib fractures on CT using a convolutional neural network.

Objective: To develop a convolutional neural network (CNN) model for the detection, precise anatomical localization (right 1-12th and left 1-12th) and classification (fresh, healing and old fractures) of rib fractures automatically, and to compare the performance with the experienced radiologists.

Materials And Methods: A total of 640 rib fracture patients with 340,501 annotations were retrospectively collected from three hospitals. They consisted of a classification training dataset (n = 482), a localization training dataset (n = 30), an internal testing dataset (n = 90) and an external testing dataset (n = 38).

Assessment of kidney function in chronic kidney disease by combining diffusion tensor imaging and total kidney volume.

Objective: This study aimed to investigate the value and feasibility of combining fractional anisotropy (FA) values from diffusion tensor imaging (DTI) and total kidney volume (TKV) for the assessment of kidney function in chronic kidney disease (CKD).

Materials And Methods: Fifty-one patients were included in this study. All MRI examinations were performed with a 3.

Automatic detection and classification of rib fractures based on patients' CT images and clinical information via convolutional neural network.

Objective: To develop a convolutional neural network (CNN) model for the automatic detection and classification of rib fractures in actual clinical practice based on cross-modal data (clinical information and CT images).

Materials: In this retrospective study, CT images and clinical information (age, sex and medical history) from 1020 participants were collected and divided into a single-centre training set (n = 760; age: 55.8 ± 13.

Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility.

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images.

Materials And Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report.