A radiomics and deep learning nomogram developed and validated for predicting no-collapse survival in patients with osteonecrosis after multiple drilling.

Purpose: Identifying patients who may benefit from multiple drilling are crucial. Hence, the purpose of the study is to utilize radiomics and deep learning for predicting no-collapse survival in patients with femoral head osteonecrosis.

Methods: Patients who underwent multiple drilling were enrolled.

A tunable metamaterial microwave absorber inspired by chameleon's color-changing mechanism.

A metamaterial absorber capable of swiftly altering its electromagnetic response in the microwave range offers adaptability to changing environments, such as tunable stealth capabilities. Inspired by the chameleon's ability to change color through the structural transformation of photonic lattice crystals, which shift the bandgaps of reflection and transmission of visible light, we designed a crisscross structure that transforms from an expanded to a collapsed form. This transformation enables a switch between broadband absorption and peak transmission in the microwave range (4 to 18 gigahertz).

Exploring the Chiral Match-Mismatch Effect in the Chiral Discrimination of Nitriles.

This study tackles the challenge of enantiodifferentiation of nitrile compounds, which is typically difficult to resolve using nuclear magnetic resonance (NMR) due to the significant distance between the chiral center and the nitrogen atom involved in molecular interactions. We have developed novel chiral F-labeled probes, each featuring two chiral centers, to exploit the "match-mismatch" effect, thereby enhancing enantiodiscrimination. This strategy effectively differentiates chiral analytes with quaternary chiral carbon centers as well as those with similar substituents at the chiral center.

Cu-Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and TEM Study.

The development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)45° missing row reconstruction (MRR).

Cardiovascular events observed among patients in the etrasimod clinical programme: an integrated safety analysis of patients with moderately to severely active ulcerative colitis.

Objective: Etrasimod is an oral, once-daily, selective sphingosine 1-phosphate (S1P) receptor modulator for the treatment of moderately to severely active ulcerative colitis (UC). S1P receptor expression on cardiac cells is involved in cardiac conduction. We report cardiovascular treatment-emergent adverse events (TEAEs) associated with S1P receptor modulators and other cardiovascular events in the etrasimod UC clinical programme.