Amorphous Solid Dispersions of Lidocaine and Lidocaine HCl Produced by Ball Milling with Well-Defined RAFT-Synthesised Methacrylic Acid Polymers

This study focuses on the use of methacrylic acid polymers synthesised via the Reversible Addition Fragmentation chain Transfer (RAFT) polymerisation method for the production of amorphous solid dispersions (ASDs) by ball milling, to kinetically solubilize a poorly water-soluble model drug. The solid-state characteristics and the physical stability of the formulations were investigated using X-ray diffraction, differential scanning calorimetry, and infrared spectroscopy. This was followed by dissolution studies in different media. It was discovered that the acidic polymers of methacrylic acid were capable of interacting with the weakly basic drug lidocaine and its hydrochloride salt form to produce ASDs when a polymer to drug ratio of 70:30 w/w was used. The ASDs remained amorphous following storage under accelerated aging conditions (40 °C and 75% relative humidity) over 8 months. Fast dissolution and increased lidocaine solubility in different media were obtained from the ASDs owing to the reduced microenvironment pH and enhanced solubilization of the drug caused by the presence of the acidic polymer in the formulation. Production of ASDs using well-defined RAFT-synthesised acidic polymers is a promising formulation strategy to enhance the pharmaceutical properties of basic poorly water-soluble drugs

Effect of Thermal Bridge in Light-Frame Wood Wall

The presence of thermal bridges in a wall increases local heat conduction of the building envelope, resulting in a decrease in the wall’s average thermal resistance. Simultaneously, the internal surface temperature of thermal bridge is lower than that of the surrounding areas and shows a tendency of condensation. Therefore, it is necessary to employ thermal bridges in the stage of construction design. In the research, a two-dimensional steady-state numerical simulation was performed targeting thermal bridges with light-frame wood wall. Meanwhile, the heat bridge effect was simulated under different circumstances by changing the types of insulation and cladding materials, the number of the studs, and the framing factor. The results showed that the linear heat transfer coefficient increased linearly as the studs and framing factor rose. After the test was validated, the relative error rate between the simulated correction coefficients and the experimentally derived correction coefficients was 11.4%, indicating that the correction coefficients can be simulated

Three-Dimensional Prediction and Evaluation of Baiyanghe Uranium Deposit in the Xuemistan Volcanic Belt, Xinjiang

Taking the Baiyanghe uranium deposit in Xinjiang as an example, the authors used the 3D geologic modeling and analysis software SKUA-GOCAD to establish a 3D geologic model of its topography, structure, stratum, granite, and ore body based on the study and knowledge of the geologic background, characteristics, and metallogenic rules of the deposit. Meanwhile, the authors summarized the 3D prediction model, conducted a quantitative extraction and analysis of favorable metallogenic information, and carried out the 3D prediction and study on the Baiyanghe uranium deposit by combining the 3D weights of the evidence method and the 3D informational method. Based on the analysis and prediction results, the deep prospecting target area was delineated. The 3D metallogenic prediction of the uranium deposit was achieved, which has provided technical support for the exploration of the Baiyanghe uranium deposit and a beneficial reference for the 3D metallogenic prediction of other minerals. Such a practice can provide a certain practical application value and a reference value for the research in this field

Prediction and evaluation of concealed ore body in 3D environment

3D models of stratigraphy、 rock、 tectonic、 mineralization and so on are established, based on the data of digital uranium exploration achievement, focusing on 3D modeling of uranium deposit、 evaluation of deep uranium resource. Exploration achievement model are formed by the result above accompany with geophysical geochemical prospecting data and Interpretation. The prediction and evaluation of deep deposits which delineated metallogenic advantageous target area are carried out by weights of evidence method. The applications of digital uranium exploration achievement are realized by the application research above, which improving efficiency and broadening application range and depth of digital exploration achievement

Drought Stress-Related Gene Identification in Rice by Random Walk with Restart on Multiplex Biological Networks

Drought stress-related gene identification is vital in revealing the drought resistance mechanisms underlying rice and for cultivating rice-resistant varieties. Traditional methods, such as Genome-Wide Association Studies (GWAS), usually identify hundreds of candidate stress genes, and further validation by biological experiements is then time-consuming and laborious. However, computational and prioritization methods can effectively reduce the number of candidate stress genes. This study introduces a random walk with restart algorithm (RWR), a state-of-the-art guilt-by-association method, to operate on rice multiplex biological networks. It explores the physical and functional interactions between biological molecules at different levels and prioritizes a set of potential genes. Firstly, we integrated a Protein–Protein Interaction (PPI) network, constructed by multiple protein interaction data, with a gene coexpression network into a multiplex network. Then, we implemented the RWR on multiplex networks (RWR-M) with known drought stress genes as seed nodes to identify potential drought stress-related genes. Finally, we conducted association analysis between the potential genes and the known drought stress genes. Thirteen genes were identified as rice drought stress-related genes, five of which have been reported in the recent literature to be involved in drought stress resistance mechanisms

A Novel Prognostic Model for Gastric Cancer with EP_Dis-Based Co-Expression Network Analysis

Ferroptosis is a regulated form of cell death that involves iron-dependent lipid peroxidation. Ferroptosis-related genes (FRGs) play an essential role in the tumorigenesis of gastric cancer (GC), which is one of the most common and lethal cancers worldwide. Understanding the prognostic significance of FRGs in GC can shed light on GC treatment and diagnosis. In this study, we proposed a new gene co-expression network analysis method, namely EP-WGCNA. This method used Euclidean and Pearson weighted distance (EP_dis) to construct a weighted gene co-expression network instead of the Pearson’s correlation coefficient used in the original WGCNA method. The aim was to better capture the interactions and functional associations among genes. We used EP-WGCNA to identify the FRGs related to GC phenotype and applied bioinformatics methods to select the FRGs associated with the prognosis (P-FRGs) of GC patients. Firstly, we screened the FRGs that were differentially expressed based on the TCGA and GTEx databases. Then, we selected the P-FRGs using EP-WGCNA, Cox regression, and Kaplan–Meier analysis. The prognostic model based on P-FRGs-Cox (ALB, BNIP3, DPEP1, GLS2, MEG3, PDK4, TF, and TSC22D3) was constructed on the TCGA-GTEx dataset. According to the median risk score, all patients in the TCGA training dataset and GSE84426 testing dataset were classified into a high- or low-risk group. GC patients in the low-risk group showed higher survival probability than those in the high-risk group. The time-dependent receiver operating characteristic (timeROC) showed that EP-WGCNA-Cox predicted 0.77 in the training set and 0.64 in the testing set for the 5-year survival rate of GC patients, which was better than traditional WGCNA-Cox (P-WGCNA-Cox). In addition, we validated that the P-FRGs were significantly differentially expressed in the adjacent non-tumor gastric tissues and tumor tissues by immunohistochemical staining from the Human Protein Atlas (HPA) database. We also found that the P-FRGs were enriched in tumorigenic pathways by enrichment analysis. In conclusion, our study demonstrated that EP-WGCNA can mine the key FRGs related to the phenotype of GC and is superior to the P-WGCNA. The EP-WGCNA-Cox model based on P-FRGs is reliable in predicting the survival rate of GC patients and can provide potential biomarkers and therapeutic targets for GC

Discovery of a Highly Potent Oxysterol Receptor GPR183 Antagonist Bearing the Benzo[<i>d</i>]thiazole Structural Motif for the Treatment of Inflammatory Bowel Disease (IBD)

Accumulating evidence has demonstrated a critical pathological role of oxysterol receptor GPR183 in various inflammatory and autoimmune diseases, including inflammatory bowel disease (IBD). However, the currently reported GPR183 antagonists are very limited and not qualified for in vivo studies due to their inferior druglike properties. Herein, we conducted a structural elaboration focusing on improving its PK and safety profile based on a reference antagonist NIBR189. Of note, compound 33, bearing an aminobenzothiazole motif, exhibited reduced hERG inhibition, improved PK properties, and robust antagonistic activity (IC50 = 0.82 nM) with high selectivity against GPR183. Moreover, compound 33 displayed strong in vitro antimigration and anti-inflammatory activity in monocytes. Oral administration of compound 33 effectively improved the pathological symptoms of DSS-induced experimental colitis. All of these findings demonstrate that compound 33 is a novel and promising GPR183 antagonist suitable for further investigation to treat IBD

Discovery of a Highly Potent Oxysterol Receptor GPR183 Antagonist Bearing the Benzo[<i>d</i>]thiazole Structural Motif for the Treatment of Inflammatory Bowel Disease (IBD)

Accumulating evidence has demonstrated a critical pathological role of oxysterol receptor GPR183 in various inflammatory and autoimmune diseases, including inflammatory bowel disease (IBD). However, the currently reported GPR183 antagonists are very limited and not qualified for in vivo studies due to their inferior druglike properties. Herein, we conducted a structural elaboration focusing on improving its PK and safety profile based on a reference antagonist NIBR189. Of note, compound 33, bearing an aminobenzothiazole motif, exhibited reduced hERG inhibition, improved PK properties, and robust antagonistic activity (IC50 = 0.82 nM) with high selectivity against GPR183. Moreover, compound 33 displayed strong in vitro antimigration and anti-inflammatory activity in monocytes. Oral administration of compound 33 effectively improved the pathological symptoms of DSS-induced experimental colitis. All of these findings demonstrate that compound 33 is a novel and promising GPR183 antagonist suitable for further investigation to treat IBD

Discovery of a Highly Potent Oxysterol Receptor GPR183 Antagonist Bearing the Benzo[<i>d</i>]thiazole Structural Motif for the Treatment of Inflammatory Bowel Disease (IBD)

Accumulating evidence has demonstrated a critical pathological role of oxysterol receptor GPR183 in various inflammatory and autoimmune diseases, including inflammatory bowel disease (IBD). However, the currently reported GPR183 antagonists are very limited and not qualified for in vivo studies due to their inferior druglike properties. Herein, we conducted a structural elaboration focusing on improving its PK and safety profile based on a reference antagonist NIBR189. Of note, compound 33, bearing an aminobenzothiazole motif, exhibited reduced hERG inhibition, improved PK properties, and robust antagonistic activity (IC50 = 0.82 nM) with high selectivity against GPR183. Moreover, compound 33 displayed strong in vitro antimigration and anti-inflammatory activity in monocytes. Oral administration of compound 33 effectively improved the pathological symptoms of DSS-induced experimental colitis. All of these findings demonstrate that compound 33 is a novel and promising GPR183 antagonist suitable for further investigation to treat IBD