Effect of Thermal Processing on the Metabolic Components of Black Beans on Ultra-High-Performance Liquid Chromatography Coupled with High-Field Quadrupole-Orbitrap High-Resolution Mass Spectrometry

An ultra-high-performance liquid chromatography coupled with high-field quadrupole-orbitrap mass spectrometry (UHPLC-QE-MS) histological platform was used to analyze the effects of two thermal processing methods (cooking and steaming) on the nutritional metabolic components of black beans. Black beans had the most amino acids, followed by lipids and polyphenols, and more sugars. Multivariate statistical analysis indicated that heat processing significantly affected the metabolic component content in black beans, with effects varying among different components. Polyphenols, especially flavonoids and isoflavones, were highly susceptible. A total of 197 and 210 differential metabolites were identified in both raw black beans and cooked and steamed black beans, respectively. Cooking reduced the cumulative content of amino acids, lipids, polyphenols, sugars, and nucleosides, whereas steaming reduced amino acid and lipid content, slightly increased polyphenol content, and significantly increased sugar and nucleoside content. Our results indicated that metabolic components were better retained during steaming than cooking. Heat treatment had the greatest impact on amino acids, followed by polyphenols, fatty acids, sugars, and vitamins, indicating that cooking promotes the transformation of most substances and the synthesis of a few. The results of this study provide a basis for further research and development of nutritional products using black beans.     

Nano-Structured Ridged Micro-Filaments (≥100 µm Diameter) Produced Using a Single Step Strategy for Improved Bone Cell Adhesion and Proliferation in Textile Scaffolds

Textile scaffolds that are either 2D or 3D with tunable shapes and pore sizes can be made through textile processing (weaving, knitting, braiding, nonwovens) using microfilaments. However, these filaments lack nano-topographical features to improve bone cell adhesion and proliferation. Moreover, the diameter of such filaments should be higher than that used for classical textiles (10–30 µm) to enable adhesion and the efficient spreading of the osteoblast cell (>30 µm diameter). We report, for the first time, the fabrication of biodegradable nanostructured cylindrical PLLA (poly-L-Lactic acid) microfilaments of diameters 100 µm and 230 µm, using a single step melt-spinning process for straightforward integration of nano-scale ridge-like structures oriented in the fiber length direction. Appropriate drawing speed and temperature used during the filament spinning allowed for the creation of instabilities giving rise to nanofibrillar ridges, as observed by AFM (Atomic Force Microscopy). These micro-filaments were hydrophobic, and had reduced crystallinity and mechanical strength, but could still be processed into 2D/3D textile scaffolds of various shapes. Biological tests carried out on the woven scaffolds made from these nano-structured micro filaments showed excellent human bone cell MG 63 adhesion and proliferation, better than on smooth 30 µm- diameter fibers. Elongated filopodia of the osteoblast, intimately anchored to the nano-structured filaments, was observed. The filaments also induced in vitro osteogenic expression, as shown by the expression of osteocalcin and bone sialoprotein after 21 days of culture. This work deals with the fabrication of a new generation of nano-structured micro-filament for use as scaffolds of different shapes suited for bone cell engineering.     

Prisoner’s Dilemma Game with Cooperation-Defection Dominance Strategies on Correlational Multilayer Networks

As multilayer networks are widely applied in modern society, numerous studies have shown the impact of a multilayer network structure and the network nature on the proportion of cooperators in the network. In this paper, we use Barabási–Albert scale-free networks (BA) and Watts and Strogatz networks (WS) to build a multilayer network structure, and we propose a new strategy-updating rule called “cooperation-defection dominance”, which can be likened to dominant and recessive traits in biogenetics. With the newly constructed multilayer network structure and the strategy-updating rules, based on the simulation results, we find that in the BA-BA network, the cooperation dominance strategy can make the networks with different rs show a cooperative trend, while the defection dominance strategy only has an obvious effect on the network cooperation with a larger r. When the BA network is connected to the WS network, we find that the effect of strategy on the proportion of cooperators in the network decreases, and the main influencing factor is the structure of the network. In the three-layer network, the cooperation dominance strategy has a greater impact on the BA network, and the proportion of the cooperators is enhanced more than under the natural evolution strategy, but the promotion effect is still smaller than that of the two-layer BA network because of the WS network. Under the defection dominance strategy, the WS layer appears different from the first two strategies, and we conclude through simulation that when the payoff parameter is at the middle level, its cooperator proportion will be suppressed, and we deduce that the proportion of cooperators and defectors, as well as the payoff, play an important role.     

低温制备≥99.5%多晶氧化铝陶瓷

本文通过引入稀土氧化物Y2O3、Tm2O3为烧结助剂低温制备了氧化铝含量大于99.5;的多晶氧化铝陶瓷.实验表明:稀土氧化物的加入能够明显降低99.5;多晶氧化铝陶瓷的烧结温度,提高致密度.Y2O3、Tm2O3混合烧结助剂与单一稀土氧化物的烧结助剂相比能够明显抑制晶粒的生长,促进晶粒的均匀发育.当Y2O3+Tm2O3的含量为0.3;质量分数时,99.5;多晶氧化铝陶瓷的相对密度可达99.2;理论密度,抗弯强度为533MPa,显微硬度为17.2GPa.陶瓷断裂主要以穿晶断裂为主.     

An unexpected all-metal aromatic tetranuclear silver cluster in human copper chaperone Atox1

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s¹ electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag₄ cluster is Ag₄²⁺, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4n + 2 electron counting rule (n = 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.     

Mesoporous sodium four-coordinate aluminosilicate nanoparticles modulate dendritic cell pyroptosis and activate innate and adaptive immunity

Pyroptosis is a programmed cell death widely studied in cancer cells for tumour inhibition, but rarely in dendritic cell (DC) activation for vaccine development. Here, we report the synthesis of sodium stabilized mesoporous aluminosilicate nanoparticles as DC pyroptosis modulators and antigen carriers. By surface modification of sodium-stabilized four-coordinate aluminium species on dendritic mesoporous silica nanoparticles, the resultant Na-^IVAl-DMSN significantly activated DC through caspase-1 dependent pyroptosis via pH responsive intracellular ion exchange. The released proinflammatory cellular contents further mediated DC hyperactivation with prolonged cytokine release. In vivo studies showed that Na-^IVAl-DMSN induced enhanced cellular immunity mediated by natural killer (NK) cells, cytotoxic T cells, and memory T cells as well as humoral immune response. Our results provide a new principle for the design of next-generation nanoadjuvants for vaccine applications.

Na-^IVAl-DMSN acts as both antigen carriers and modulators to “hyperactivate” dendritic cells (DCs) via potassium (K⁺) efflux dependent pyroptosis, eventually leading to enhanced adaptive and innate immunity.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.     

Cancer-Associated Mutations of the Adenosine A2A Receptor Have Diverse Influences on Ligand Binding and Receptor Functions

The adenosine A_2A receptor (A_2AAR) is a class A G-protein-coupled receptor (GPCR). It is an immune checkpoint in the tumor micro-environment and has become an emerging target for cancer treatment. In this study, we aimed to explore the effects of cancer-patient-derived A_2AAR mutations on ligand binding and receptor functions. The wild-type A_2AAR and 15 mutants identified by Genomic Data Commons (GDC) in human cancers were expressed in HEK293T cells. Firstly, we found that the binding affinity for agonist NECA was decreased in six mutants but increased for the V275A mutant. Mutations A165V and A265V decreased the binding affinity for antagonist ZM241385. Secondly, we found that the potency of NECA (EC₅₀) in an impedance-based cell-morphology assay was mostly correlated with the binding affinity for the different mutants. Moreover, S132L and H278N were found to shift the A_2AAR towards the inactive state. Importantly, we found that ZM241385 could not inhibit the activation of V275A and P285L stimulated by NECA. Taken together, the cancer-associated mutations of A_2AAR modulated ligand binding and receptor functions. This study provides fundamental insights into the structure–activity relationship of the A_2AAR and provides insights for A_2AAR-related personalized treatment in cancer.     

Genetically engineered materials: Proteins and beyond

Information-rich molecules provide opportunities for evolution. Genetically engineered materials are superior in that their properties are coded within genetic sequences and could be fine-tuned. In this review, we elaborate the concept of genetically engineered materials(GEMs) using examples ranging from engineered protein materials to engineered living materials. Proteinbased materials are the materials of choice by nature. Recent progress in protein engineering has led to opportunities to tune...     

Numerical Study on an RBF-FD Tangent Plane Based Method for Convection–Diffusion Equations on Anisotropic Evolving Surfaces

In this paper, we present a fully Lagrangian method based on the radial basis function (RBF) finite difference (FD) method for solving convection–diffusion partial differential equations (PDEs) on evolving surfaces. Surface differential operators are discretized by the tangent plane approach using Gaussian RBFs augmented with two-dimensional (2D) polynomials. The main advantage of our method is the simplicity of calculating differentiation weights. Additionally, we couple the method with anisotropic RBFs (ARBFs) to obtain more accurate numerical solutions for the anisotropic growth of surfaces. In the ARBF interpolation, the Euclidean distance is replaced with a suitable metric that matches the anisotropic surface geometry. Therefore, it will lead to a good result on the aspects of stability and accuracy of the RBF-FD method for this type of problem. The performance of this method is shown for various convection–diffusion equations on evolving surfaces, which include the anisotropic growth of surfaces and growth coupled with the solutions of PDEs.