The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input ...the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 10^{4} data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.
While microbial‐based therapy has been considered as an effective strategy for treating diseases such as colon cancer, its safety remains the biggest challenge. Here, probiotics and prebiotics, which ...possess ideal biocompatibility and are extensively used as additives in food and pharmaceutical products, are combined to construct a safe microbiota‐modulating material. Through the host–guest chemistry between commercial Clostridium butyricum and chemically modified prebiotic dextran, prebiotics‐encapsulated probiotic spores (spores‐dex) are prepared. It is found that spores‐dex can specifically enrich in colon cancers after oral administration. In the lesion, dextran is fermented by C. butyricum, and thereby produces anti‐cancer short‐chain fatty acids (SCFAs). Additionally, spores‐dex regulate the gut microbiota, augment the abundance of SCFA‐producing bacteria (e.g., Eubacterium and Roseburia), and markedly increase the overall richness of microbiota. In subcutaneous and orthotopic tumor models, drug‐loaded spores‐dex inhibit tumor growth up to 89% and 65%, respectively. Importantly, no obvious adverse effect is found. The work sheds light on the possibility of using a highly safe strategy to regulate gut microbiota, and provides a promising avenue for treating various gastrointestinal diseases.
Through host–guest chemistry between Clostridium butyricum and chemically modified prebiotic dextran, prebiotics‐encapsulated probiotic spores (spores‐dex) are prepared to achieve oral bacterial treatment of colon cancer.
Cross-border E-commerce has advanced greatly with the help of big data technology, cross-border payment and logistics maturity and improvement, and backing from the national “One Belt, One Road” ...policy. Firstly, based on the study of enterprise core competitiveness evaluation index system, one is proposed for the core competitiveness of Cross-border E-commerce enterprises, and an evaluation model based on SA-LSTM for the core competitiveness of Cross-border E-commerce enterprises is constructed. Then, with the research objective of refining the core competitiveness of Cross-border E-commerce enterprises, the model was applied to empirically analyze the core attractiveness of major domestically listed Cross-border E-commerce enterprises. The results show that laws and regulations have no significant influence on enterprise competitiveness, the regression coefficient is not significant, and the t-value = 1.793 < 2. Hypothesis A is not verified. And the p-values of the technical environment, development potential, market demand, capital management, process cost, information sharing and service level are all less than 0.05, and the regression coefficients are all significant with t-values greater than 2, indicating that indicators B to H has a significant positive influence on enterprise competitiveness. This study reduces the barriers for SMEs to apply Cross-border E-commerce to participate in foreign trade, reduces the cost of enterprises, and improves their own competitiveness.
Three-dimensional (3D) bioprinting has rapidly developed in the last decade, playing an increasingly important role in applications including pharmacokinetics research, tissue engineering, and organ ...regeneration. As a cutting-edge technology in 3D printing, gel bath-supported 3D bioprinting enables the freeform construction of complex structures with soft and water-containing materials, facilitating the
in vitro
fabrication of live tissue or organ models. To realize
in vivo
-like organs or tissues in terms of biological functions and complex structures by 3D printing, high resolution and fidelity are prerequisites. Although a wide range of gel matrices have recently been developed as supporting materials, the effect of bath properties and printing parameters on the print resolution is still not clearly understood. This review systematically introduces the decisive factors for resolution in both bulk gel bath systems and granular microgel bath systems, providing guidelines for high-resolution 3D bioprinting based on bath properties and printing parameters.
This review introduces the decisive factors for resolution in both bulk gel bath systems and granular microgel bath systems, providing guidelines for high-resolution 3D bioprinting based on the bath properties and printing parameters.
Human serine palmitoyltransferase (SPT) complex catalyzes the initial and rate-limiting step in the de novo biosynthesis of all sphingolipids. ORMDLs regulate SPT function, with human ORMDL3 being ...related to asthma. Here we report three high-resolution cryo-EM structures: the human SPT complex, composed of SPTLC1, SPTLC2 and SPTssa; the SPT-ORMDL3 complex; and the SPT-ORMDL3 complex bound to two substrates, PLP-L-serine (PLS) and a non-reactive palmitoyl-CoA analogue. SPTLC1 and SPTLC2 form a dimer of heterodimers as the catalytic core. SPTssa participates in acyl-CoA coordination, thereby stimulating the SPT activity and regulating the substrate selectivity. ORMDL3 is located in the center of the complex, serving to stabilize the SPT assembly. Our structural and biochemical analyses provide a molecular basis for the assembly and substrate selectivity of the SPT and SPT-ORMDL3 complexes, and lay a foundation for mechanistic understanding of sphingolipid homeostasis and for related therapeutic drug development.
Retinal pigment epithelium (RPE) cell damage is implicated in the pathogenesis of age‐related macular degeneration (AMD). An increase of interferon‐γ (IFN‐γ) levels was observed in patients with AMD, ...but whether inflammatory factors are causally related to AMD progression is unclear. Here, we demonstrate a direct causal relationship between IFN‐γ and RPE cell death. IFN‐γ induced human retinal pigment epithelial cell (ARPE‐19) death accompanied by increases in Fe2+, reactive oxygen species, lipid peroxidation, and glutathione (GSH) depletion, which are main characteristics of ferroptosis. Mechanistically, IFN‐γ upregulates the level of intracellular Fe2+ through inhibiting Fe2+ efflux protein SLC40A1 and induces GSH depletion by blocking cystine/glutamate antiporter, System xc‐. At the same time, treatment with IFN‐γ decreases the level of glutathione peroxidase 4 (GPx4), rendering the cells more sensitive to ferroptosis. JAK1/2 and STAT1 inhibitors could reverse the reduction of SLC7A11, GPx4 and GSH expression induced by IFN‐γ, indicating IFN‐γ induces ARPE‐19 cell ferroptosis via activation of the JAK1‐2/STAT1/SLC7A11 signaling pathway. The above results were largely confirmed in IFN‐γ‐treated mice in vivo. Finally, we used sodium iodate (NaIO3)‐induced retinal degeneration to further explore the role of ferroptosis in AMD in vivo. Consistent with the role of IFN‐γ, treatment with NaIO3 decreased SLC7A11, GPx4 and SLC40A1 expressions. NaIO3‐induced RPE damage was accompanied by increased iron, lipid peroxidation products (4‐hydroxynonenal, malondialdehyde), and GSH depletion, and ferroptosis inhibitors could reverse the above phenomenon. Taken together, our findings suggest that inhibiting ferroptosis or reducing IFN‐γ may serve as a promising target for AMD.
IFN‐γ downregulates the expression of SLC7A11 via JAK1‐2/STAT1 signaling pathway, which results in decreases in cysteine transport and, subsequently, decreased GSH synthesis. Simultaneously, IFN‐γ increases intracellular Fe2+ levels through the inhibition of SLC40A1. GSH depletion and Fe2+ accumulation cause retinal pigment epithelial cells ferroptosis and accelerate the progression of AMD.
Abstract
Optical networks that distribute entanglement among various quantum systems will form a powerful framework for quantum science but are yet to interface with leading quantum hardware such as ...superconducting qubits. Consequently, these systems remain isolated because microwave links at room temperature are noisy and lossy. Building long distance connectivity requires interfaces that map quantum information between microwave and optical fields. While preliminary microwave-to-optical transducers have been realized, developing efficient, low-noise devices that match superconducting qubit frequencies (gigahertz) and bandwidths (10 kilohertz – 1 megahertz) remains a challenge. Here we demonstrate a proof-of-concept on-chip transducer using trivalent ytterbium-171 ions in yttrium orthovanadate coupled to a nanophotonic waveguide and a microwave transmission line. The device′s miniaturization, material, and zero-magnetic-field operation are important advances for rare-earth ion magneto-optical devices. Further integration with high quality factor microwave and optical resonators will enable efficient transduction and create opportunities toward multi-platform quantum networks.
Frequentist model averaging has been demonstrated as an efficient tool to deal with model uncertainty in big data analysis. In contrast with a conventional data set, the number of regressors in a big ...data set is usually quite large, which leads to a exponential number of potential candidate models. In this paper, we propose a heteroscedasticity-robust model screening (HRMS) method that constructs a candidate model set through an iterative procedure. Our simulation results and empirical exercise with big data analytics demonstrate the superiority of our HRMS method over existing methods.
•Propose a new heteroscedasticity-robust model screening (HRMS) method.•Show that HRMS has good performance in simulation.•Demonstrate that HRMS is computationally efficient.•Show that HRMS can lead to large gains in box office prediction accuracy.
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