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.

Unlocking the Potential of Porous Bi2Te3-Based Thermoelectrics Using Precise Interface Engineering through Atomic Layer Deposition.

Porous thermoelectric materials offer exciting prospects for improving the thermoelectric performance by significantly reducing the thermal conductivity. Nevertheless, porous structures are affected by issues, including restricted enhancements in performance attributed to decreased electronic conductivity and degraded mechanical strength. This study introduces an innovative strategy for overcoming these challenges using porous Bi0.4Sb1.6Te3 (BST) by combining porous structuring and interface engineering via atomic layer deposition (ALD). Porous BST powder was produced by selectively dissolving KCl in a milled mixture of BST and KCl; the interfaces were engineered by coating ZnO films through ALD. This novel architecture remarkably reduced the thermal conductivity owing to the presence of several nanopores and ZnO/BST heterointerfaces, promoting efficient phonon scattering. Additionally, the ZnO coating mitigated the high resistivity associated with the porous structure, resulting in an improved power factor. Consequently, the ZnO-coated porous BST demonstrated a remarkable enhancement in thermoelectric efficiency, with a maximum zT of approximately 1.53 in the temperature range of 333-353 K, and a zT of 1.44 at 298 K. Furthermore, this approach plays a significant role in enhancing the mechanical strength, effectively mitigating a critical limitation of porous structures. These findings open new avenues for the development of advanced porous thermoelectric materials and highlight their potential for precise interface engineering through the ALD.

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.

Selective Dissolution-Derived Nanoporous Design of Impurity-Free Bi2 Te3 Alloys with High Thermoelectric Performance.

Thermoelectric technology, which has been receiving attention as a sustainable energy source, has limited applications because of its relatively low conversion efficiency. To broaden their application scope, thermoelectric materials require a high dimensionless figure of merit (ZT). Porous structuring of a thermoelectric material is a promising approach to enhance ZT by reducing its thermal conductivity. However, nanopores do not form in thermoelectric materials in a straightforward manner; impurities are also likely to be present in thermoelectric materials. Here, a simple but effective way to synthesize impurity-free nanoporous Bi0.4 Sb1.6 Te3 via the use of nanoporous raw powder, which is scalably formed by the selective dissolution of KCl after collision between Bi0.4 Sb1.6 Te3 and KCl powders, is proposed. This approach creates abundant nanopores, which effectively scatter phonons, thereby reducing the lattice thermal conductivity by 33% from 0.55 to 0.37 W m-1 K-1 . Benefitting from the optimized porous structure, porous Bi0.4 Sb1.6 Te3 achieves a high ZT of 1.41 in the temperature range of 333-373 K, and an excellent average ZT of 1.34 over a wide temperature range of 298-473 K. This study provides a facile and scalable method for developing high thermoelectric performance Bi2 Te3 -based alloys that can be further applied to other thermoelectric materials.

A lignan from Alnus japonica inhibits glioblastoma tumorspheres by suppression of FOXM1.

Forkhead Box M1 (FOXM1) is known to regulate cell proliferation, apoptosis and tumorigenesis. The lignan, (-)-(2R,3R)-1,4-O-diferuloylsecoisolariciresinol (DFS), from Alnus japonica has shown anti-cancer effects against colon cancer cells by suppressing FOXM1. The present study hypothesized that DFS can have anti-cancer effects against glioblastoma (GBM) tumorspheres (TSs). Immunoprecipitation and luciferase reporter assays were performed to evaluate the ability of DFS to suppress nuclear translocation of ß-catenin through ß-catenin/FOXM1 binding. DFS-pretreated GBM TSs were evaluated to assess the ability of DFS to inhibit GBM TSs and their transcriptional profiles. The in vivo efficacy was examined in orthotopic xenograft models of GBM. Expression of FOXM1 was higher in GBM than in normal tissues. DFS-induced FOXM1 protein degradation blocked ß-catenin translocation into the nucleus and consequently suppressed downstream target genes of FOXM1 pathways. DFS inhibited cell viability and ATP levels, while increasing apoptosis, and it reduced tumorsphere formation and the invasiveness of GBM TSs. And DFS reduced the activities of transcription factors related to tumorigenesis, stemness, and invasiveness. DFS significantly inhibited tumor growth and prolonged the survival rate of mice in orthotopic xenograft models of GBM. It suggests that DFS inhibits the proliferation of GBM TSs by suppressing FOXM1. DFS may be a potential therapeutic agent to treat GBM.

Improving oxidation stability of 2D MXenes: synthesis, storage media, and conditions.

Understanding and preventing oxidative degradation of MXene suspensions is essential for fostering fundamental academic studies and facilitating widespread industrial applications. Owing to their outstanding electrical, electrochemical, optoelectronic, and mechanical properties, MXenes, an emerging class of two-dimensional (2D) nanomaterials, show promising state-of-the-art performances in various applications including electromagnetic interference (EMI) shielding, terahertz shielding, electrochemical energy storage, triboelectric nanogenerators, thermal heaters, light-emitting diodes (LEDs), optoelectronics, and sensors. However, MXene synthesis using harsh chemical etching causes many defects or vacancies on the surface of the synthesized MXene flakes. Defective sites are vulnerable to oxidative degradation reactions with water and/or oxygen, which deteriorate the intrinsic properties of MXenes. In this review, we demonstrate the nature of oxidative degradation of MXenes and highlight the recent advancements in controlling the oxidation kinetics of MXenes with several promising strategic approaches, including careful control of the quality of the parent MAX phase, chemical etching conditions, defect passivation, dispersion medium, storage conditions, and polymer composites.

Fitting unbranching skeletal structures to objects.

Representing an object by a skeletal structure can be powerful for statistical shape analysis if there is good correspondence of the representations within a population. Many anatomic objects have a genus-zero boundary and can be represented by a smooth unbranching skeletal structure that can be discretely approximated. We describe how to compute such a discrete skeletal structure ("d-s-rep") for an individual 3D shape with the desired correspondence across cases. The method involves fitting a d-s-rep to an input representation of an object's boundary. A good fit is taken to be one whose skeletally implied boundary well approximates the target surface in terms of low order geometric boundary properties: (1) positions, (2) tangent fields, (3) various curvatures. Our method involves a two-stage framework that first, roughly yet consistently fits a skeletal structure to each object and second, refines the skeletal structure such that the shape of the implied boundary well approximates that of the object. The first stage uses a stratified diffeomorphism to produce topologically non-self-overlapping, smooth and unbranching skeletal structures for each object of a population. The second stage uses loss terms that measure geometric disagreement between the skeletally implied boundary and the target boundary and avoid self-overlaps in the boundary. By minimizing the total loss, we end up with a good d-s-rep for each individual shape. We demonstrate such d-s-reps for various human brain structures. The framework is accessible and extensible by clinical users, researchers and developers as an extension of SlicerSALT, which is based on 3D Slicer.

Anomalous absorption of electromagnetic waves by 2D transition metal carbonitride Ti3CNT x (MXene).

Lightweight, ultrathin, and flexible electromagnetic interference (EMI) shielding materials are needed to protect electronic circuits and portable telecommunication devices and to eliminate cross-talk between devices and device components. Here, we show that a two-dimensional (2D) transition metal carbonitride, Ti3CNT x MXene, with a moderate electrical conductivity, provides a higher shielding effectiveness compared with more conductive Ti3C2T x or metal foils of the same thickness. This exceptional shielding performance of Ti3CNT x was achieved by thermal annealing and is attributed to an anomalously high absorption of electromagnetic waves in its layered, metamaterial-like structure. These results provide guidance for designing advanced EMI shielding materials but also highlight the need for exploring fundamental mechanisms behind interaction of electromagnetic waves with 2D materials.

Ultralight and Mechanically Robust Ti3C2Tx Hybrid Aerogel Reinforced by Carbon Nanotubes for Electromagnetic Interference Shielding.

Lightweight materials with high electrical conductivity and robust mechanical properties are highly desirable for electromagnetic interference (EMI) shielding in modern portable and highly integrated electronics. Herein, a three-dimensional (3D) porous Ti3C2Tx/carbon nanotube (CNT) hybrid aerogel was fabricated via a bidirectional freezing method for lightweight EMI shielding application. The synergism of the lamellar and porous structure of the MXene/CNT hybrid aerogels contributed extensively to their excellent electrical conductivity (9.43 S cm-1) and superior electromagnetic shielding effectiveness (EMI SE) value of 103.9 dB at 3 mm thickness at the X-band frequency, the latter of which is the best value reported for synthetic porous nanomaterials. The CNT reinforcement in the MXene/CNT hybrid aerogels enhanced the mechanical robustness and increased the compressional modulus by 9661% relative to that of the pristine MXene aerogel. The hybrid aerogel with high electrical conductivity, good mechanical strength, and superior EMI shielding performance is a promising material for inhibiting EMI pollution.

Precision Interface Engineering of an Atomic Layer in Bulk Bi2Te3 Alloys for High Thermoelectric Performance.

Grafting nanotechnology on thermoelectric materials leads to significant advances in their performance. Creation of structural defects including nano-inclusion and interfaces via nanostructuring achieves higher thermoelectric efficiencies. However, it is still challenging to optimize the nanostructure via conventional fabrication techniques. The thermal instability of nanostructures remains an issue in the reproducibility of fabrication processes and long-term stability during operation. This work presents a versatile strategy to create numerous interfaces in a thermoelectric material via an atomic-layer deposition (ALD) technique. An extremely thin ZnO layer was conformally formed via ALD over the Bi0.4Sb1.6Te3 powders, and numerous heterogeneous interfaces were generated from the formation of Bi0.4Sb1.6Te3-ZnO core-shell structures even after high-temperature sintering. The incorporation of ALD-grown ZnO into the Bi0.4Sb1.6Te3 matrix blocks phonon propagation and also provides tunability in electronic carrier density via impurity doping at the heterogeneous grain boundaries. The exquisite control in the ALD cycles provides a high thermoelectric performance of zT = 1.50 ± 0.15 (at 329-360 K). Specifically, ALD is an industry compatible technique that allows uniform and conformal coating over large quantities of powders. The study is promising in terms of the mass production of nanostructured thermoelectric materials with considerable improvements in performance via an industry compatible and reproducible route.

Skeletal Shape Correspondence Through Entropy.

We present a novel approach for improving the shape statistics of medical image objects by generating correspondence of skeletal points. Each object's interior is modeled by an s-rep, i.e., by a sampled, folded, two-sided skeletal sheet with spoke vectors proceeding from the skeletal sheet to the boundary. The skeleton is divided into three parts: the up side, the down side, and the fold curve. The spokes on each part are treated separately and, using spoke interpolation, are shifted along that skeleton in each training sample so as to tighten the probability distribution on those spokes' geometric properties while sampling the object interior regularly. As with the surface/boundary-based correspondence method of Cates et al., entropy is used to measure both the probability distribution tightness and the sampling regularity, here of the spokes' geometric properties. Evaluation on synthetic and real world lateral ventricle and hippocampus data sets demonstrate improvement in the performance of statistics using the resulting probability distributions. This improvement is greater than that achieved by an entropy-based correspondence method on the boundary points.

SlicerSALT: Shape AnaLysis Toolbox.

SlicerSALT is an open-source platform for disseminating state-of-the-art methods for performing statistical shape analysis. These methods are developed as 3D Slicer extensions to take advantage of its powerful underlying libraries. SlicerSALT itself is a heavily customized 3D Slicer package that is designed to be easy to use for shape analysis researchers. The packaged methods include powerful techniques for creating and visualizing shape representations as well as performing various types of analysis.

Non-Euclidean classification of medically imaged objects via s-reps.

Classifying medically imaged objects, e.g., into diseased and normal classes, has been one of the important goals in medical imaging. We propose a novel classification scheme that uses a skeletal representation to provide rich non-Euclidean geometric object properties. Our statistical method combines distance weighted discrimination (DWD) with a carefully chosen Euclideanization which takes full advantage of the geometry of the manifold on which these non-Euclidean geometric object properties (GOPs) live. Our method is evaluated via the task of classifying 3D hippocampi between schizophrenics and healthy controls. We address three central questions. 1) Does adding shape features increase discriminative power over the more standard classification based only on global volume? 2) If so, does our skeletal representation provide greater discriminative power than a conventional boundary point distribution model (PDM)? 3) Especially, is Euclideanization of non-Euclidean shape properties important in achieving high discriminative power? Measuring the capability of a method in terms of area under the receiver operator characteristic (ROC) curve, we show that our proposed method achieves strongly better classification than both the classification method based on global volume alone and the s-rep-based classification method without proper Euclideanization of non-Euclidean GOPs. We show classification using Euclideanized s-reps is also superior to classification using PDMs, whether the PDMs are first Euclideanized or not. We also show improved performance with Euclideanized boundary PDMs over non-linear boundary PDMs. This demonstrates the benefit that proper Euclideanization of non-Euclidean GOPs brings not only to s-rep-based classification but also to PDM-based classification.