From data to action in flood forecasting leveraging graph neural networks and digital twin visualization.

Forecasting floods encompasses significant complexity due to the nonlinear nature of hydrological systems, which involve intricate interactions among precipitation, landscapes, river systems, and hydrological networks. Recent efforts in hydrology have aimed at predicting water flow, floods, and quality, yet most methodologies overlook the influence of adjacent areas and lack advanced visualization for water level assessment. Our contribution is two-fold: firstly, we introduce a graph neural network model (LocalFLoodNet) equipped with a graph learning module to capture the interconnections of water systems and the connectivity between stations to predict future water levels.

Consolidation Osimertinib Versus Durvalumab Versus Observation After Concurrent Chemoradiation in Unresectable EGFR-Mutant NSCLC: A Multicenter Retrospective Cohort Study.

Introduction: Durvalumab improves survival when used as consolidation therapy after chemoradiation (CRT) in patients with stage III NSCLC. The optimal consolidation therapy for patients with EGFR-mutant (EGFRmut) stage III NSCLC remains unknown.

Methods: In this multi-institutional, international retrospective analysis across 24 institutions, we evaluated outcomes in patients with stage III EGFRmut NSCLC treated with concurrent CRT followed by consolidation therapy with osimertinib, durvalumab, or observation between 2015 and 2022.

Green Synthesis of Cerium Oxide Nanoparticles, Characterization, and Their Neuroprotective Effect on Hydrogen Peroxide-Induced Oxidative Injury in Human Neuroblastoma (SH-SY5Y) Cell Line.

Cerium oxide nanoparticles (CeONPs) have a broad scale of applications in the biomedical field due to their excellent physicochemical and catalytic properties. The present study aims to synthesize the CeONPs from () leaf extract, which has been used in Indian traditional medicine for its neuroprotective properties. The CeONPs were characterized by ultraviolet-visible, X-ray diffraction, Fourier transform infrared, Raman spectroscopy, scanning electron microscopy- energy dispersive X-ray spectroscopy, and high-resolution transmission electron microscopy.

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up.