Deep Equilibrium Unfolding Learning for Noise Estimation and Removal in Optical Molecular Imaging.

In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.

Synergistic Electrode and Electrolyte Polarities Lead to Outstanding Organic Potassium-based Batteries.

Organic materials are promising as battery electrodes due to their flexible design, low cost, and sustainability. Although high electrolyte concentrations are known to suppress organic cathode dissolution, the organic cathode solubility depends on the interplay between the electrode and electrolyte polarities, which remains unexplored. Here, we elucidate the delicate interplay of electrode and electrolyte polarities to achieve stable cycling of organic cathode.

Dietary limonin alleviates Typhimurium-induced colitis dual targeting virulence SopB and SopE2 and inhibiting RAC1/CDC42/Arp2/3 pathway and regulating gut microbiota.

serovar Typhimurium (STM) causes severe colitis, necessitating the development of effective drugs. Here, the dockings of limonin with the STM T3SS-1 virulence factor SopB or SopE2 showed strong binding activity and was verified by CETSA and DARTS assays . Limonin inhibited the enzyme activities and expression of SopB and SopE2 .

The potential function of chalcone isomerase (CHI) gene on flavonoid accumulation in Amomum tsao-ko fruit by transcriptome and metabolome.

Flavonoids are the major medicinally active ingredients that exert potential effects in Amomum tsao-ko. In total, 277 flavonoid metabolites were identified in fresh and dried fruits of three different accessions of A. tsao-ko (Amomum tsao-ko), which could be classified into eight classes with more metabolites classified as flavonol.

EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder.

Background: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to explore the functional changes and interrelationships of multiple brain networks on a millisecond scale. This study aimed to explore the pathological changes of whole-brain functional networks in patients with obsessive-compulsive disorders (OCD) through microstate analysis and further to explore its potential value as an auxiliary diagnostic index.

Methods: Forty-eight OCD patients (33 with more than moderate anxiety symptoms, 15 with mild anxiety symptoms) and 52 healthy controls (HCs) were recruited.