Graphene Membrane for Water-Related Environmental Application: A Comprehensive Review and Perspectives.

Graphene-based materials can be potentially utilized for separation membranes due to their unique structural properties such as precise molecular sieving by interlayer spacing or pore structure and excellent stability in harsh environmental conditions. Therefore, graphene-based membranes have been extensively demonstrated for various water treatment applications, including desalination, water extraction, and rare metal ion recovery. While most of the utilization has still been limited to the laboratory scale, emerging studies have dealt with scalable approaches to show commercial feasibility.

Plasmon-Driven Gold Nanopillar Multiarrayed Gene Amplification Methodology for the High-Throughput Discrimination of Pathogens.

Molecular diagnosis limitations, including complex treatment processes, low cost-effectiveness, and operator-dependent low reproducibility, interrupt the timely prevention of disease spread and the development of medical devices for home and outdoor uses. A newly fabricated gold nanopillar array-based film is presented for superior photothermal energy conversion. Magnifying the metal film surface-to-volume ratio increases the photothermal energy conversion efficiency, resulting in a swift reduction in the gene amplification reaction time.

HDAC4/5 Inhibitor, LMK-235 Improves Animal Voluntary Movement in MPTP-Induced Parkinson's Disease Model.

Oxidation of dopamine can cause various side effects, which ultimately leads to cell death and contributes to Parkinson's disease (PD). To counteract dopamine oxidation, newly synthesized dopamine is quickly transported into vesicles via vesicular monoamine transporter 2 (VMAT2) for storage. VMAT2 expression is reduced in patients with PD, and studies have shown increased accumulation of dopamine oxidation byproducts and α-synuclein in animals with low VMAT2 expression.

Predictive Mortality and Gastric Cancer Risk Using Clinical and Socio-Economic Data: A Nationwide Multicenter Cohort Study.

Gastric cancer is a leading cause of cancer-related mortality, particularly in East Asia, with a notable burden in Republic of Korea. This study aimed to construct and develop machine learning models for the prediction of gastric cancer mortality and the identification of risk factors. All data were acquired from the Korean Clinical Data Utilization for Research Excellence by multiple medical centers in South Korea.