Deep learning-based Monte Carlo dose prediction for heavy-ion online adaptive radiotherapy and fast quality assurance: A feasibility study.

Background: Online adaptive radiotherapy (OART) and rapid quality assurance (QA) are essential for effective heavy ion therapy (HIT). However, there is a shortage of deep learning (DL) models and workflows for predicting Monte Carlo (MC) doses in such treatments.

Purpose: This study seeks to address this gap by developing a DL model for independent MC dose (MCDose) prediction, aiming to facilitate OART and rapid QA implementation for HIT.

The trajectory of crime: Integrating mouse-tracking into concealed memory detection.

The autobiographical implicit association test (aIAT) is an approach of memory detection that can be used to identify true autobiographical memories. This study incorporates mouse-tracking (MT) into aIAT, which offers a more robust technique of memory detection. Participants were assigned to mock crime and then performed the aIAT with MT.

Kdm2a inhibition in skeletal muscle improves metabolic flexibility in obesity.

Skeletal muscle is a critical organ in maintaining homoeostasis against metabolic stress, and histone post-translational modifications are pivotal in those processes. However, the intricate nature of histone methylation in skeletal muscle and its impact on metabolic homoeostasis have yet to be elucidated. Here, we report that mitochondria-rich slow-twitch myofibers are characterized by significantly higher levels of H3K36me2 along with repressed expression of Kdm2a, an enzyme that specifically catalyses H3K36me2 demethylation.

Research on the impact of the digital economy on carbon emissions based on the dual perspectives of carbon emission reduction and carbon efficiency.

China's digital economy is currently thriving, with the "dual carbon" targets representing a significant pursuit of economic development. The role of the digital economy in achieving these targets warrants detailed discussion. Using urban panel data from China spanning 2011 to 2021, this paper empirically examines the impact of the digital economy on urban carbon emissions.

Ocean wave-driven covalent organic framework/ZnO heterostructure composites for piezocatalytic uranium extraction from seawater.

Piezoelectric catalysis possesses the potential to convert ocean wave energy into and holds broad prospects for extracting uranium from seawater. Herein, the Z-type ZnO@COF heterostructure composite with excellent piezoelectric properties was synthesized through in situ growth of covalent organic frameworks (COFs) on the surface of ZnO and used for efficient uranium extraction. The designed COFs shell enables ZnO with stability, abundant active sites and high-speed electron transport channels.