Current applications and research trends of ultrasound examination in acute kidney injury assessment: a bibliometric analysis.

Background: Acute kidney injury (AKI) is a significant clinical condition, and ultrasound examination has emerged as a crucial non-invasive imaging method for assessing kidney status, especially in its diagnosis and management. This study aims to perform a bibliometric analysis to clarify current research trends in ultrasound assessment of AKI.

Methods: We conducted a literature search in the Web of Science database using keywords related to ultrasound examinations of acute kidney injury, up to November 15, 2023.

Improving rupture status prediction for intracranial aneurysms using wall shear stress informatics.

Background: Wall shear stress (WSS) plays a crucial role in the natural history of intracranial aneurysms (IA). However, spatial variations among WSS have rarely been utilized to correlate with IAs' natural history. This study aims to establish the feasibility of using spatial patterns of WSS data to predict IAs' rupture status (i.

Photo-Rechargeable Sodium-Ion Batteries with a Two-Dimensional MoSe Crystal Cathode.

Combining energy harvesting with energy storage systems in a single device could offer great advantages for continuous power supply in both indoor and outdoor electric applications. In this work, we demonstrate a photochargeable sodium-ion battery (PSIB) based on a photoactive cathode of two-dimensional crystals of MoSe. This photocathode enables spontaneous photodriven charging of a sodium-ion battery cathode under illumination and an increase in the reversible capacity to 29% at 600 mA g compared to that under dark conditions during galvanostatic cycling.

Ultrafast Synthesis of Nanoscale Metal Borides for Efficient Hydrogen Evolution.

Nanoscale metal borides, with exceptional physicochemical properties, have been attracted widespread attention. However, traditional synthesis methods of metal borides often lead to surface coking and large particle sizes. Herein, we have employed a flash Joule heating (FJH) technique to enable the ultrafast synthesis of metal boride nanomaterials.

Toward a Generalizable Machine-Learned Potential for Metal-Organic Frameworks.

Machine-learned potentials (MLPs) have transformed the field of molecular simulations by scaling "quantum-accurate" potentials to linear time complexity. While they provide more accurate reproduction of physical properties as compared to empirical force fields, it is still computationally costly to generate their training data sets from ab initio calculations. Despite the emergence of foundational or general MLPs for organic molecules and dense materials, it is unexplored if one general MLP can be effectively developed for a wide variety of nanoporous metal-organic frameworks (MOFs) with different chemical moieties and geometric properties.