Immunostimulatory potential of extruded plant-based meat: effect of extrusion moisture level on macrophage activation.

In this study, the effect of different moisture levels in extruded plant-based meat on macrophage immunostimulation, and the potential of this meat as a protein source and a solution to environmental and economic challenges associated with conventional meat was investigated. To determine the effects of the extruded plant-based meat, cell viability assay, enzyme-linked immunosorbent assay, flow cytometry, and western blotting were performed. Low-moisture (LMME) and high-moisture meat extracts (HMME) showed higher potential to activate macrophages and regulate cytokine production than raw material extract. Treatment with LMME and HMME resulted in increased expression of CD80, CD86, and MHC class I/II proteins, indicating their potential to activate macrophages. Western blotting suggested that the immune activation observed in a previous study of macrophages was because of the phosphorylation of MAPKs and NF-κB. These findings suggest that extruded plant-based meat can potentially be used as an immunostimulatory food ingredient.

The semicircular canal function is preserved with little impact on falls in patients with mild Parkinson's disease.

INTRODUCTION: Postural instability is a cardinal symptom of Parkinson's disease (PD), which suggests the vestibular system may be affected in PD. This study aimed to determine whether vestibular dysfunction is associated with the risk of falls in PD. METHODS: We prospectively recruited patients with de-novo PD at a tertiary medical center between December 2019 and March 2023. During initial assessment, each patient was queried about falls within the preceding year. All patients underwent evaluation of video head-impulse tests (video-HITs), motion analysis, mini-mental state examination (MMSE), and Montreal Cognitive Assessment (MOCA). We determined whether head impulse gain of the vestibulo-ocular reflex (VOR) was associated with clinical severity of PD or risk of falls. RESULTS: Overall, 133 patients (mean age ± SD = 68 ± 10, 59 men) were recruited. The median Movement Disorder Society-Unified Parkinson's Disease Rating Scale motor part (MDS-UPDRS-III) was 23 (interquartile range = 16-31), and 81 patients (61 %) scored 2 or less on the Hoehn and Yahr scale. Fallers were older (p = 0.001), had longer disease duration (p = 0.001), slower gait velocity (p = 0.009), higher MDS-UPDRS-III (p < 0.001) and H&Y scale (p < 0.001), lower MMSE (p = 0.018) and MOCA scores (p = 0.001) than non-fallers. Multiple logistic regression showed that MDS-UPDRS-III had a positive association with falling (p = 0.004). Falling was not associated with VOR gain (p = 0.405). The VOR gain for each semicircular canal showed no correlation with the MDS-UPDRS-III or disease duration. CONCLUSIONS: The semicircular canal function, as determined by video-HITs, is relatively spared and has little effect on the risk of falls in patients with mild-to-moderate PD.

Federated Learning in Small-Cell Networks: Stochastic Geometry-Based Analysis on the Required Base Station Density.

Recently, federated learning (FL) has been receiving great attention as an effective machine learning method to avoid the security issue in raw data collection, as well as to distribute the computing load to edge devices. However, even though wireless communication is an essential component for implementing FL in edge networks, there have been few works that analyze the effect of wireless networks on FL. In this paper, we investigate FL in small-cell networks where multiple base stations (BSs) and users are located according to a homogeneous Poisson point process (PPP) with different densities. We comprehensively analyze the effects of geographic node deployment on the model aggregation in FL on the basis of stochastic geometry-based analysis. We derive the closed-form expressions of coverage probability with tractable approximations and discuss the minimum required BS density for achieving a target model aggregation rate in small-cell networks. Our analysis and simulation results provide insightful information for understanding the behaviors of FL in small-cell networks; these can be exploited as a guideline for designing the network facilitating wireless FL.

Shaping micro-clusters via inverse jamming and topographic close-packing of microbombs.

Designing topographic clusters is of significant interest, yet it remains challenging as they often lack mobility or deformability. Here we exploit the huge volumetric expansion (up to 3000%) of a new type of building block, thermally expandable microbombs. They consist of a viscoelastic polymeric shell and a volatile gas core, which, within structural confinement, create micro-clusters via inverse jamming and topographical close-packing. Upon heating, microbombs anchored in rigid confinement underwent balloon-like blowing up, allowing for dense clusters via soft interplay between viscoelastic shells. Importantly, the confinement is unyielding against the internal pressure of the microbombs, thereby enabling self-assembled clusters, which can be coupled with topographic inscription to introduce structural hierarchy on the clusters. Our strategy provides densely packed yet ultralight clusters with a variety of complex shapes, cleavages, curvatures, and hierarchy. In turn, these clusters will enrich our ability to explore the assemblies of the ever-increasing range of microparticle systems.Self-assembled systems are normally composed of incompressible building blocks, which constrain their space filling efficiency. Yu et al. show programmable, densely packed clusters using thermally expandable soft microparticles, whereby the self-assembling process is realized via a jamming transition.