Cathepsin B modulates lysosomal biogenesis and host defense against Francisella novicida infection

Lysosomal cathepsins regulate an exquisite range of biological functions, and their deregulation is associated with inflammatory, metabolic, and degenerative diseases in humans. In this study, we identified a key cell-intrinsic role for cathepsin B as a negative feedback regulator of lysosomal biogenesis and autophagy. Mice and macrophages lacking cathepsin B activity had increased resistance to the cytosolic bacterial pathogen Francisella novicida. Genetic deletion or pharmacological inhibition of cathepsin B down-regulated mechanistic target of rapamycin activity and prevented cleavage of the lysosomal calcium channel TRP ML1. These events drove transcription of lysosomal and autophagy genes via transcription factor EB, which increased lysosomal biogenesis and activation of autophagy initiation kinase ULK1 for clearance of the bacteria. Our results identified a fundamental biological function of cathepsin B in providing a checkpoint for homeostatic maintenance of lysosome populations and basic recycling functions in the cell

Temporal Aware Mixed Attention-based Convolution and Transformer Network (MACTN) for EEG Emotion Recognition

Emotion recognition plays a crucial role in human-computer interaction, and electroencephalography (EEG) is advantageous for reflecting human emotional states. In this study, we propose MACTN, a hierarchical hybrid model for jointly modeling local and global temporal information. The model is inspired by neuroscience research on the temporal dynamics of emotions. MACTN extracts local emotional features through a convolutional neural network (CNN) and integrates sparse global emotional features through a transformer. Moreover, we employ channel attention mechanisms to identify the most task-relevant channels. Through extensive experimentation on two publicly available datasets, namely THU-EP and DEAP, our proposed method, MACTN, consistently achieves superior classification accuracy and F1 scores compared to other existing methods in most experimental settings. Furthermore, ablation studies have shown that the integration of both self-attention mechanisms and channel attention mechanisms leads to improved classification performance. Finally, an earlier version of this method, which shares the same ideas, won the Emotional BCI Competition's final championship in the 2022 World Robot Contest

Generalized Regular Quadrilateral Mesh Generation based on Surface Foliation

This work introduces a novel algorithm for quad-mesh generation based on surface foliation theory. The algorithm is based on the equivalence among colorable quad-meshes, measure foliations and holomorphic differentials. The holomorphic differentials can be obtained by graph-valued harmonic maps. The algorithm has several merits: it can be applied for surfaces with general topologies; the resulting quad-meshes have global tensor product structure and the least number of singularities; the algorithmic pipeline is fully automatic. The experimental results demonstrate the efficiency and efficacy of the proposed method

Thermo-Responsive Molecularly Imprinted Hydrogels for Selective Adsorption and Controlled Release of Phenol From Aqueous Solution

In this study, thermo-responsive molecularly imprinted hydrogels (T-MIHs) were developed as an effective potential adsorbent for selectively adsorption phenol from wastewater. During the process, N-isopropyl acrylamide (NIPAm) was used as thermal responsive monomer. The obtained materials were characterized in detail by fourier transform infrared (FT-IR) spectrometer, scanning electron microscope (SEM), and thermo gravimetric analysis (TGA). A series of static adsorption studies were performed to investigate the kinetics, specific adsorption equilibrium, and selective recognition ability of phenol. Reversible adsorption and release of phenol were realized by changing temperatures. Three type of phenols, namely 3-chlorophenols (3-CP), 2,4-dichlorophenol (2,4-DCP), and 2,4,6-trichlorophenol (2,4,6-TCP) were selected as model analytes to evaluate the selective recognition performance of T-MIHs. The T-MIHs have good selectivity, temperature response, and reusability, making them ideal in applying in the controlled separation and release of phenol pollutants

Application of Flexible Bronchoscopy in Inhalation Lung Injury

Background: As acute inhalational injury is an uncommon presentation to most institutions, a standard approach to its assessment and management, especially using flexible bronchoscopy, has not received significant attention. Methods: The objective of this study is to evaluate the value of using flexible bronchoscopy as part of the evaluation and management of patients with inhalational lung injury. Twenty-three cases of inhalational lung injury were treated in our three hospitals after a fire in a residential building. The twenty cases that underwent bronchoscopy as part of their management are included in this analysis. After admission, the first bronchoscopy was conducted within 18-72 hours post inhalational injury. G2-level patients were reexamined 24 hours after the first bronchoscopy, while G1-level patients were reexamined 72 hours later. Subsequently, all patients were re-examined every 2-3 days until recovered or until only tunica mucosa bronchi congestion was identified by bronchoscopy. Results: Twenty patients had airway injury diagnosed by bronchoscopy including burns to the larynx and glottis or large airways. Bronchoscopic classification of the inhalation injury was performed, identifying 12 cases of grade G1 changes and 8 cases of grade G2. The airway injury in the 12 cases of grade G1 patients demonstrated recovery in 2-8 days, in the airway injury of the 8 cases of grade G2 patients had a prolonged recovery with airway injury improving in 6-21 days averaged. The difference in recovery time between the two groups was significant (P Conclusions: The use of flexible bronchoscopy has great value in the diagnosis of inhalational injury without any complications. Its use should be incorporated into clinical practice

Characterization and structural basis of a lethal mouse-adapted SARS-CoV-2.

There is an urgent need for animal models to study SARS-CoV-2 pathogenicity. Here, we generate and characterize a novel mouse-adapted SARS-CoV-2 strain, MASCp36, that causes severe respiratory symptoms, and mortality. Our model exhibits age- and gender-related mortality akin to severe COVID-19. Deep sequencing identified three amino acid substitutions, N501Y, Q493H, and K417N, at the receptor binding domain (RBD) of MASCp36, during in vivo passaging. All three RBD mutations significantly enhance binding affinity to its endogenous receptor, ACE2. Cryo-electron microscopy analysis of human ACE2 (hACE2), or mouse ACE2 (mACE2), in complex with the RBD of MASCp36, at 3.1 to 3.7 Å resolution, reveals the molecular basis for the receptor-binding switch. N501Y and Q493H enhance the binding affinity to hACE2, whereas triple mutations at N501Y/Q493H/K417N decrease affinity and reduce infectivity of MASCp36. Our study provides a platform for studying SARS-CoV-2 pathogenesis, and unveils the molecular mechanism for its rapid adaptation and evolution