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.

Brachytherapy Seed Placement by Robotic Bronchoscopy with Cone-Beam CT Guidance for Peripheral Lung Cancer: A Human Cadaveric Feasibility Pilot.

Purpose: This study evaluates the feasibility of utilizing robotic-assisted bronchoscopy with cone beam computed tomography (RB-CBCT) platform to perform low-dose-rate brachytherapy implants (LDR-BT) in a mechanically ventilated human cadaveric model. Post-implant dosimetry was compared to standard stereotactic body radiation therapy plans (SBRT).

Materials And Methods: The RB-CBCT platform was used to place inert LDR-BT seeds into mechanically ventilated human cadavers with percutaneously injected pseudotumors.

A cationic liposome-formulated Toll Like Receptor (TLR)7/8 agonist enhances the efficacy of a vaccine against fentanyl toxicity.

The U.S. opioid epidemic is an extraordinary public health crisis that started in 1990 and significantly accelerated in the last decade.

Plant Adaptation and Soil Shear Strength: Unraveling the Drought Legacy in .

Climate change has led to an increasing frequency of droughts, potentially undermining soil stability. In such a changing environment, the shallow reinforcement effect of plant roots often fails to meet expectations. This study aims to explore whether this is associated with the alteration of plant traits as a response to environmental change.

Research on Fire Detection of Cotton Picker Based on Improved Algorithm.

According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.