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Abstract The fracture toughness (KIC) of high-entropy oxides (HEOs) is critically important for several applications, but identification and quantification of the toughening mechanisms resulting from lattice-engineering/distortion in HEOs is challenging. Here, based on the classic Griffith criteria, a physics-driven theoretical equation combined with a knowledge-enabled data-driven machine-learning algorithm is proposed to predict the KIC and elucidate the toughening mechanisms of A2Zr2O7-type HEOs. Together with experimental verification, our proposed model is applied to a dataset comprising 41208 (nRE1/n)2Zr2O7 (n = 2~7) HEOs, considering the contributions of the intrinsic brittleness and increased toughness due to the local lattice distortion (LLD), thereby addressing the challenge of accurate estimating KIC in complex HEOs using the rule of mixtures. During crack tip propagation, the interaction mechanism of cations induces stress fields and charge variations of LLD and dissipates crack energy, thus, to yield the crack tip softening and the elastic shielding and to enhance the toughness of HEOs.

Abstract Developing a comprehensive magnetic theory for correlated itinerant magnets poses challenges due to the difficulty in reconciling both local moments and itinerant electrons. In this work, we investigate the microscopic process of magnetic phase transition in ferromagnetic metal Fe3−δ GeTe2. We find that Hund’s coupling is crucial for establishing ferromagnetic order. During the ferromagnetic transition, we observe the formation of quasiparticle flat bands and an opposing tendency in spectral weight transfer, primarily between the lower and upper Hubbard bands, across the two spin channels. Moreover, our results indicate that one of the inequivalent Fe sites exhibits Mott physics, while the other Fe site exhibits Hund’s physics, attributable to their distinct atomic environments. We suggest that ferromagnetic order reduces spin fluctuations and makes flat bands near the Fermi level more distinct. The hybridization between the distinctly flat bands and other itinerant bands offers a possible way to form heavy fermion behavior in ferromagnets. The complex interactions of competing orders drive correlated magnetic metals to a new frontier for discovering outstanding quantum states.

This paper concerns the invasion dynamics of the lattice pioneer-climax competition model with parameter regions in which the system is non-monotone. We estimate the spreading speeds and establish appropriate conditions under which the spreading speeds are linearly selected. Moreover, the existence of travelling waves is determined by constructing suitable upper and lower solutions. It shows that the spreading speed coincides with the minimum wave speed of travelling waves if the diffusion rate of the invasive species is larger or equal to that of the native species. Our results are new to estimate the spreading speed of non-monotone lattice pioneer-climax systems, and the techniques developed in this work can be used to study the invasion dynamics of the pioneer-climax system with interaction delays, which could extend the results in the literature. The analysis replies on the construction of auxiliary systems, upper and lower solutions, and the monotone dynamical system approach.

Abstract Future‐oriented Science & Technology (S&T) Strategies trigger the innovative developments of advanced materials, providing an envision to the significant progress of leading‐/cutting‐edge science, engineering, and technologies for the next few decades. Motivated by Made in China 2025 and New Material Power Strategy by 2035, several key viewpoints about automated research workflows for accelerated discovery and smart manufacturing of advanced materials in terms of AI for Science and main respective of big data, database, standards, and ecosystems are discussed. Referring to classical toolkits at various spatial and temporal scales, AI‐based toolkits and AI‐enabled computations for material design are compared, highlighting the dominant role of the AI agent paradigm. Our recent developed ProME platform together with its functions is introduced briefly. A case study of AI agent assistant welding is presented, which is consisted of the large language model, auto‐coding via AI agent, image processing, image mosaic, and machine learning for welding defect detection. Finally, more duties are called to educate the next generation workforce with creative minds and skills. It is believed that the transformation of knowledge‐enabled data‐driven integrated computational material engineering era to AI+ era promotes the transformation of smart design and manufacturing paradigm from “designing the materials” to “designing with materials.”

Background: The GIMAP family genes play a key role in immune function. Increasing evidence suggests that GIMAP genes were implicated in the tumorigenesis of lung adenocarcinoma (LUAD). This study aimed to investigate the clinical significance of GIMAP family genes in LUAD. Methods: In this study, we explored the expression, mutation, prognostic value of GIMAP family genes and the correlation with immune microenvironment in LUAD. We further investigated the relationship between GIMAP family genes expression and immunotherapy response in GEO LUAD and melanoma cohorts. Results: Among the GIMAP family genes, the expression levels of GIMAP1, GIMAP2, GIMAP4, GIMAP5, GIMAP6, GIMAP7, and GIMAP8 were significantly lower in LUAD tumor tissues than normal tissues. Most GIMAP genes were closely related to age, tumor grade and T stage, but not significantly related to sex, N stage and M stage. In the overall population, patients with high expression of GIMAP family genes had a significant longer overall survival (OS). GO and KEGG enrichment analysis showed that GIMAP family genes were highly enriched in immune-related biological process. The expression of GIMAP family genes was positively correlated with immune cell infiltration and immune checkpoint molecules. Furthermore, high expression of GIMAP family genes were correlated with therapeutic response to immunotherapy in LUAD and melanoma patients. Conclusion: In this study, we identified that GIMAP family genes were significantly associated with immune cell infiltration and immune checkpoint molecules. They potentially play a critical role in anti-tumor immunity and serve as immunotherapy biomarkers.

The scale of tourism has continued to expand in recent years, and many associated activities cause damage to the natural environment. The tourism, economy and natural environment constitute a system: destruction of the natural environment reduces the value of tourism and a lack of tourism affects the development of the economy. To explore the relationship between the tourism, economy and natural environment, and to explore possibilities for sustainable development, this paper takes Hangzhou, a tourist city in China, as a research object. An analysis of time series data is carried out. First, the tourism, economy and natural environment subsystems are constructed by extracting time series data acquired between 2010 and 2020. Second, a tourism evaluation model with coupled economic and natural environment data is constructed and the coupling degree and coupling coordination level in Hangzhou are evaluated. Third, the time series of each subsystem and the coupling coordination level of the whole system are analyzed. Finally, an optimization strategy is proposed for the coupled coordinated development of the tourism, economy and natural environment in Hangzhou. A key result is that the tertiary industry represented by tourism has become the main source of local income. Hangzhou's tourism coupling coordination level has changed from slight disorder in 2010 to good in 2020. It is also found that the COVID-19 pandemic has become a major factor restricting the development of tourism. Before the outbreak of COVID-19, Hangzhou's tourism industry and economy were synchronized. After the outbreak of COVID-19, both the number of tourists and tourism revenue in Hangzhou fell by nearly 15%.

ObjectiveTo systematically review and quantitively evaluate the efficacy and safety of mirabegron as a medical expulsive therapy for ureteral stones.MethodsWe performed an extensive search of the EMBASE and PubMed databases for studies examining the use of mirabegron as a medical expulsive therapy for ureteral stones. The primary outcome measure assessed was the stone expulsion rate (SER), while the secondary outcomes evaluated were the stone expulsion interval (SEI) and the occurrence of pain episodes during follow-up. Risk ratios (RRs) and mean differences (MDs) with their respective 95% CIs were calculated.ResultsWe included a total of seven studies involving 728 participants. Our analysis revealed a significant increase in the stone expulsion rate (SER) with mirabegron (RR = 1.40; 95% CI = 1.17–1.67; p

Magnetic resonance (MR) image enhancement technology can reconstruct high-resolution image from a low-resolution image, which is of great significance for clinical application and scientific research. T1 weighting and T2 weighting are the two common magnetic resonance imaging modes, each of which has its own advantages, but the imaging time of T2 is much longer than that of T1. Related studies have shown that they have very similar anatomical structures in brain images, which can be utilized to enhance the resolution of low-resolution T2 images by using the edge information of high-resolution T1 images that can be rapidly imaged, so as to shorten the imaging time needed for T2 images. In order to overcome the inflexibility of traditional methods using fixed weights for interpolation and the inaccuracy of using gradient threshold to determine edge regions, we propose a new model based on previous studies on multi-contrast MR image enhancement. Our model uses framelet decomposition to finely separate the edge structure of the T2 brain image, and uses the local regression weights calculated from T1 image to construct a global interpolation matrix, so that our model can not only guide the edge reconstruction more accurately where the weights are shared, but also carry out collaborative global optimization for the remaining pixels and their interpolated weights. Experimental results on a set of simulated MR data and two sets of real MR images show that the enhanced images obtained by the proposed method are superior to the compared methods in terms of visual sharpness or qualitative indicators.

A pediatric RSV vaccine is an unmet medical need, even after >50 years of effort. Here, the authors show that a chimpanzee adenovirus based RSV vaccine candidate protects calves from disease upon RSV infection, regardless of the time after vaccination (1 or 4 months) or the presence of maternal antibodies.

This paper introduces the concept of equivalence operators based on overlap and grouping functions where the associativity property is not strongly required. Overlap functions and grouping functions are weaker than positive and continuous t-norms and t-conorms, respectively. Therefore, these equivalence operators do not necessarily satisfy certain properties, such as associativity and the neutrality principle. In this paper, two models of fuzzy equivalence operators are obtained by the composition of overlap functions, grouping functions and fuzzy negations. Their main properties are also studied.

Abstract Background Neural stem cells (NSCs)-derived extracellular vesicles (EVs) possess great potential in treating severe neurological and cerebrovascular diseases, as they carry the modulatory and regenerative ingredients of NSCs. Induced pluripotent stem cells (iPSCs)-derived NSCs culture represents a sustainable source of therapeutic EVs. However, there exist two major challenges in obtaining a scalable culture of NSCs for high-efficiency EVs production: (1) the heterogeneity of iPSC-derived NSCs culture impairs the production of high-quality EVs and (2) the intrinsic propensity of neuronal or astroglial differentiation of NSCs during prolonged culturing reduces the number of NSCs for preparing EVs. A NSCs strain that is amenable to stable self-renewal and proliferation is thus greatly needed for scalable and long-term culture. Methods Various constructs of the genes encoding the orphan nuclear receptor NR2E1 (TLX) were stably transfected in iPSCs, which were subsequently cultured in a variety of differentiation media for generation of iNSCsTLX. Transcriptomic and biomarker profile of iNSCsTLX were investigated. In particular, the positivity ratios of Sox2/Nestin and Musashi/Vimentin were used to gauge the homogeneity of the iNSCsTLX culture. The iNSCs expressing a truncated version of TLX (TLX-TP) was expanded for up to 45 passages, after which its neuronal differentiation potential and EV activity were evaluated. Results Stable expression of TLX-TP could confer the iPSCs with rapid and self-driven differentiation into NSCs through stable passaging up to 225 days. The long-term culture of NSCs maintained the highly homogenous expression of NSC-specific biomarkers and potential of neuronal differentiation. EVs harvested from the TLX-expressing NSCs cultures exhibited anti-inflammatory and neuroprotective activities. Conclusions iPSC-derived NSCs stably expressing TLX-TP is a promising cell line for scalable production of EVs, which should be further exploited for therapeutic development in neurological treatment.

Abstract As the world continues to experience the COVID-19 pandemic, seasonal influenza remain a cause of severe morbidity and mortality globally. Worse yet, coinfection with SARS-CoV-2 and influenza A virus (IAV) leads to more severe clinical outcomes. The development of a combined vaccine against both COVID-19 and influenza is thus of high priority. Based on our established lipid nanoparticle (LNP)-encapsulated mRNA vaccine platform, we developed and characterized a novel mRNA vaccine encoding the HA antigen of influenza A (H1N1) virus, termed ARIAV. Then, ARIAV was combined with our COVID-19 mRNA vaccine ARCoV, which encodes the receptor-binding domain (RBD) of the SARS-CoV-2 S protein, to formulate the final combined vaccine, AR-CoV/IAV. Further characterization demonstrated that immunization with two doses of AR-CoV/IAV elicited robust protective antibodies as well as antigen-specific cellular immune responses against SARS-CoV-2 and IAV. More importantly, AR-CoV/IAV immunization protected mice from coinfection with IAV and the SARS-CoV-2 Alpha and Delta variants. Our results highlight the potential of the LNP-mRNA vaccine platform in preventing COVID-19 and influenza, as well as other respiratory diseases.

The arrival interval at high-speed railway stations is one of the key factors that restrict the improvement of the train following intervals. In the process of practical railway operation, sudden conflicts occur sometimes. Especially when the conflict arises at the station, because the home signal cannot be opened in time, the emergency may affect the adjustment of the train operation under the scheduled timetable, resulting in a longer train following interval or even delay. With the development of artificial intelligence and the deep integration of big data, the architecture of train operation control and dispatch integration is gradually improving from the theoretical point. Based on this and inspired by the Green Wave policy, we propose an integrated operation method that reduces the arrival interval by avoiding unnecessary stops in front of the home signal and increasing the running speed of trains through the throat area. It is a two-step optimization method combining both intelligent optimization and mathematical–theoretical analysis algorithms. In the first step, the recommended approaching speed and position are obtained by analytical calculation. In the second step, the speed profile from the current position to the position corresponding to the recommended approaching speed is optimized by intelligent optimization algorithms. Finally, the integrated method is verified through the analysis of two distinct case studies. The first case study utilizes data from the Beijing–Shanghai high-speed railway line, while the second one is based on the field test. The numerical result shows that the proposed method could save the entry running time effectively, compared with the normal strategy given by the train driver. The method can mitigate controllable conflict events occurring at the station and provides theoretical support for practical operation.

Chikungunya fever (CHIKF) has spread to more than 100 countries worldwide, with frequent outbreaks in Europe and the Americas in recent years. Despite the relatively low lethality of infection, patients can suffer from long-term sequelae. Until now, no available vaccines have been approved for use; however, increasing attention is being paid to the development of vaccines against chikungunya virus (CHIKV), and the World Health Organization has included vaccine development in the initial blueprint deliverables. Here, we developed an mRNA vaccine using the nucleotide sequence encoding structural proteins of CHIKV. And immunogenicity was evaluated by neutralization assay, Enzyme-linked immunospot assay and Intracellular cytokine staining. The results showed that the encoded proteins elicited high levels of neutralizing antibody titers and T cell-mediated cellular immune responses in mice. Moreover, compared with the wild-type vaccine, the codon-optimized vaccine elicited robust CD8+ T-cell responses and mild neutralizing antibody titers. In addition, higher levels of neutralizing antibody titers and T-cell immune responses were obtained using a homologous booster mRNA vaccine regimen of three different homologous or heterologous booster immunization strategies. Thus, this study provides assessment data to develop vaccine candidates and explore the effectiveness of the prime-boost approach.

Long-lived tree species need to cope with changing environments and pathogens during their lifetime. Fungal diseases cause damage to trees growth and forest nurseries. As model system for woody plants, poplars are also hosts of a large variety of fungus. The defense strategies to fungus are generally associated with the type of fungus, therefore, the defense strategies of poplar against necrotrophic and biotrophic fungus are different. Poplars initiate constitutive defenses and induced defenses based on recognition of the fungus, hormone signaling network cascades, activation of defense-related genes and transcription factors and production of phytochemicals. The means of sensing fungus invasion in poplars are similar with herbs, both of which are mediated by receptor proteins and resistance (R) proteins, leading to pattern-triggered immunity (PTI) and effector-triggered immunity (ETI), but poplars have evolved some unique defense mechanisms compared with Arabidopsis due to their longevity. In this paper, current researches on poplar defensive responses to necrotrophic and biotrophic fungus, which mainly include the physiological and genetic aspects, and the role of noncoding RNA (ncRNA) in fungal resistance are reviewed. This review also provides strategies to enhance poplar disease resistance and some new insights into future research directions.

Abstract In this study, an energy‐efficient speed trajectory planner is proposed for high‐speed trains traveling on tracks with steep gradients and speed limits, especially for situations in which the speed limit has been reached, which causes adjoint variable discontinuity during calculation. New optimal switching rules at points where the speed limit is reached on steep tracks are derived by analysing the jump condition of state‐constrained Pontryagin's maximum principle. Accordingly, a novel two‐step algorithm for high‐speed trains, including an optimal‐cruise minimum‐time algorithm and search‐substitution algorithm, is designed to solve dynamic train models considering time‐energy and space‐energy conversions, respectively. Practical case studies demonstrates that the proposed method can save energy by approximately 3% and 10% in comparison to the approximate‐optimal time‐satisfied and minimum running time strategies, respectively. Moreover, the proposed method approximately consumes 0.98% and 1.62% of the computation time taken by discrete dynamic programming and reinforcement learning, respectively.

The precipitation of zirconium hydride blisters on the surface of zirconium alloy cladding destroys the integrity of the material and leads to material failure, which has serious potential safety hazards. To study the corrosion kinetics of zirconium hydride blisters, we established a phase-field model coupled with anisotropic elastic, which can reflect the microstructure evolution process of zirconium hydride blisters. The model studies the natural growth of hydride blister and the structural evolution process after applying radial stress and discusses the corrosion characteristics, stress distribution, and displacement changes. Zirconium hydride blisters tend to be semi-ellipsoidal in natural growth. Applying radial outward stress will promote the growth of blisters and aggravate the harm of corrosion. The stress state changes with applying stress, which affects the elastic driving force, resulting in the change of blister morphology. This work is helpful to understand the corrosion kinetic mechanism of hydride blisters.

Background: This study was conducted to explore the safety, tolerance, pharmacokinetics, pharmacodynamics, and immunogenicity of LY06006, a recombinant humanized monoclonal antibody to RANKL, when administrated subcutaneously in Chinese healthy adults.Research design and methods: This was a randomized, double-blinded, placebo-controlled, single ascending dose study performed in 32 healthy Chinese adults, who were randomly assigned to receive a single injection dose of 18, 60, 120 mg study drug or placebo with a follow-up of 140–252 days.Results: No deaths or drug-related serious adverse events occurred. LY06006 was rapidly absorbed in the 60 mg group with a Tmax range of 120–480 h and serum LY06006 concentrations decreased slowly 11–13 days after dosing with a long mean (SD) half-life of 389.58 (63.44) h. The most frequent AEs were elevated serum parathyroid hormone (PTH) level (83.3%), hypocalcemia (54.2%), and hypophosphatemia (45.8%). None of the 32 subjects tested positive for anti-drug antibody during the trial.Conclusion: Single-dose subcutaneous administration of LY06006 was safe and well-tolerated in healthy Chinese adults. Cmax showed linear pharmacokinetic characteristics in the dose range of 18–120 mg based on dose-exposure proportionality analysis.

Remote sensing image classification exploiting multiple sensors is a very challenging problem: The traditional methods based on the medium- or low-resolution remote sensing images always provide low accuracy and poor automation level because the potential of multi-source remote sensing data are not fully utilized and the low-level features are not effectively organized. The recent method based on deep learning can efficiently improve the classification accuracy, but as the depth of deep neural network increases, the network is prone to be overfitting. In order to address these problems, a novel Two-channel Densely Connected Convolutional Networks (TDCC) is proposed to automatically classify the ground surfaces based on deep learning and multi-source remote sensing data. The main contributions of this paper includes the following aspects: First, the multi-source remote sensing data consisting of hyperspectral image (HSI) and Light Detection and Ranging (LiDAR) are pre-processed and re-sampled, and then the hyperspectral data and LiDAR data are input into the feature extraction channel, respectively. Secondly, two-channel densely connected convolutional networks for feature extraction were proposed to automatically extract the spatial-spectral feature of HSI and LiDAR. Thirdly, a feature fusion network is designed to fuse the hyperspectral image features and LiDAR features. The fused features were classified and the output result is the category of the corresponding pixel. The experiments were conducted on popular dataset, the results demonstrate that the competitive performance of the TDCC with respect to classification performance compared with other state-of-the-art classification methods in terms of the OA, AA and Kappa, and it is more suitable for the classification of complex ground surfaces.

A data identifier (DID) is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering (ICME), inheritable integrated intelligent manufacturing (I3M), and the Industrial Internet of Things. With the guidance and quick acceleration of the development of advanced materials, as envisioned by official documents worldwide, more investigations are required to construct relative numerical standards for material informatics. This work proposes a universal DID format consisting of a set of build chains, which aligns with the classical form of identifier in both international and national standards, such as ISO/IEC 29168-1:2000, GB/T 27766–2011, GA/T 543.2–2011, GM/T 0006–2012, GJB 7365–2011, SL 325–2014, SL 607–2018, WS 363.2–2011, and QX/T 39–2005. Each build chain is made up of capital letters and numbers, with no symbols. Moreover, the total length of each build chain is not restricted, which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC 10646. Based on these rules, the proposed DID is flexible and convenient for extending and sharing in and between various cloud-based platforms. Accordingly, classical two-dimensional (2D) codes, including the Hanxin Code, Lots Perception Matrix (LP) Code, Quick Response (QR) code, Grid Matrix (GM) code, and Data Matrix (DM) Code, can be constructed and precisely recognized and/or decoded by either smart phones or specific machines. By utilizing these 2D codes as the fingerprints of a set of data linked with its cloud-based platforms, progress and updates in the composition–processing–structure–property–performance workflow process can be tracked spontaneously, paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity, performance, and collaboration.

In the field of remote sensing image processing, the classification of hyperspectral image (HSI) is a hot topic. There are two main problems lead to the classification accuracy unsatisfactory. One problem is that the recent research on HSI classification is based on spectral features, the relationship between different pixels has been ignored; the other is that the HSI data does not contain or only contain a small amount of labeled data, so it is impossible to build a well classification model. To solve these problems, a dual-channel CNN model has been proposed to boost its discriminative capability for HSI classification. The proposed dual-channel CNN model has several distinct advantages. Firstly, the model consists of spectral feature extraction channel and spatial feature extraction channel; the 1-D CNN and 3-D CNN are used to extract the spectral and spatial features, respectively. Secondly, the dual-channel CNN have been used for fusing the spatial-spectral features, the fusion feature is input into the classifier, which effectively improves the classification accuracy. Finally, due to considering the spatial and spectral features, the model can effectively solve the problem of lack of training samples. The experiments on benchmark data sets have demonstrated that the proposed dual-channel CNN model considerably outperforms other state-of-the-art method.

Complex fuzzy sets (CFSs), as an important extension of fuzzy sets, have been investigated in the literature. Operators of CFSs are of high importance. In addition, α−migrativity for various fuzzy operations on [0, 1] has been well discussed, where α is a real number and α∈0,1. Thus, this paper studies α−migrativity for binary functions on the unit circle of the complex plane O, where α is a complex number and α∈O. In particular, we show that a binary function is α−migrativity for all α∈O if and only if it is α−migrativity for all α∈0,1∪O¯, where O¯ is the boundary point subset of O. Finally, we discuss the relationship between migrativity and rotational invariance of binary operators on O.

With global climate change, for evaluating warming effect on subalpine forest distribution, the substantial effects of long-term warming on tree growth and soil nutrients need to be explored. In this study, we focused on different responses in the boundaries of trees and soils to warming. Using the open-top chamber (OTC), a 10-year artificial warming experiment was conducted to evaluate the impacts of warming on Abies faxoniana at three different altitudes. We determined metabolites and nutrient concentrations in needles of A. faxoniana and characterized the soil chemistries. Many kinds of sugars, amino acids, and organic acids showed higher contents at high altitude (3,500 m) compared with low altitude (2,600 m), which could have been due to the temperature differences. Warming significantly decreased needle sugar and amino acid concentrations at high altitude but increased them at low altitude. These results indicated contrasting physiological and metabolic responses of A. faxoniana to long-term warming at different altitudes. Furthermore, we found that OTC warming significantly increased the concentrations of soil extractable sodium, aluminum (Al), and manganese (Mn), while decreased potassium (K) and phosphorus (P) concentrations and pH values at low altitude rather than at middle (3,000 m) or high altitude. The soil carbon and nitrogen contents were increased only at the middle altitude. In A. faxoniana at low altitudes, more mineral nutrients iron, K, and P were demand, and a mass of Al, Mn, and zinc was accumulated under warming. Soil P limitation and heavy metals accumulation are disadvantageous for trees at low altitudes with warming. Therefore, compared with high altitudes, A. faxoniana growing at low boundary in alpine regions is expected to be more susceptible to warming.

We report significant differences in high-pressure properties of vanadium at zero temperature and finite temperature when different projector augmented wave (PAW) potentials are used in simulations based on density functional theory. When a PAW potential with only five electrons taken as valence electrons is used, the cold pressures in the high-pressure region are seriously underestimated, and an abnormality occurs in the melting curve of vanadium at about 400 GPa. We show that the reason for these discrepancies lies in the differences in the descriptions of the interatomic force, electron dispersion, and anisotropy of electron bonding obtained from different PAW potentials at high pressure, which lead to striking differences in the mechanical stability of the system. We propose a procedure for selecting PAW potentials suitable for simulations at high temperature and high pressure. Our results provide valuable guidance for future simulations of thermodynamic properties under extreme conditions.

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid the literature, making it difficult to formulate new hypotheses to be tested in clinical settings and ultimately improve this technology platform. Here, we propose a systems biology approach, based on the combination of literature mining and mechanistic graphical modeling, to consolidate existing knowledge around mRNA vaccines mode of action and enhance the translatability of preclinical hypotheses into clinical evidence. A Natural Language Processing (NLP) pipeline for automated knowledge extraction retrieved key biological evidences that were joined into an interactive mechanistic graphical model representing the chain of immune events induced by mRNA vaccines administration. The achieved mechanistic graphical model will help the design of future experiments, foster the generation of new hypotheses and set the basis for the development of mathematical models capable of simulating and predicting the immune response to mRNA vaccines.

Alternative oxidase (AOX) and plastid terminal oxidase (PTOX) are terminal oxidases of electron transfer in mitochondria and chloroplasts, respectively. Here, taking advantage of the variegation phenotype of the Arabidopsis PTOX deficient mutant (im), we examined the functional relationship between PTOX and its five distantly related homologs (AOX1a, 1b, 1c, 1d, and AOX2). When engineered into chloroplasts, AOX1b, 1c, 1d, and AOX2 rescued the im defect, while AOX1a partially suppressed the mutant phenotype, indicating that AOXs could function as PQH2 oxidases. When the full length AOXs were overexpressed in im, only AOX1b and AOX2 rescued its variegation phenotype. In vivo fluorescence analysis of GFP-tagged AOXs and subcellular fractionation assays showed that AOX1b and AOX2 could partially enter chloroplasts while AOX1c and AOX1d were exclusively present in mitochondria. Surprisingly, the subcellular fractionation, but not the fluorescence analysis of GFP-tagged AOX1a, revealed that a small portion of AOX1a could sort into chloroplasts. We further fused and expressed the targeting peptides of AOXs with the mature form of PTOX in im individually; and found that targeting peptides of AOX1a, AOX1b, and AOX2, but not that of AOX1c or AOX1d, could direct PTOX into chloroplasts. It demonstrated that chloroplast-localized AOXs, but not mitochondria-localized AOXs, can functionally compensate for the PTOX deficiency in chloroplasts, providing a direct evidence for the functional relevance of AOX and PTOX, shedding light on the interaction between mitochondria and chloroplasts and the complex mechanisms of protein dual targeting in plant cells.

In this work, we consider a diffusive SIR-B epidemic model with multiple transmission pathways and saturating incidence rates. We first present the explicit formula of the basic reproduction number $\mathcal{R}_0$. Then we show that if $\mathcal{R}_0>1$, there exists a constant $c^*>0$ such that the system admits traveling wave solutions connecting the disease-free equilibrium and endemic equilibrium with speed $c$ if and only if $c\geq c^*$. Since the system does not admit the comparison principle, we appeal to the standard Schauder's fixed point theorem to prove the existence of traveling waves. Moreover, a suitable Lyapunov function is constructed to prove the upward convergence of traveling waves.

This article concerns the bifurcation of limit cycles from a quartic integrable and non-Hamiltonian system. By using the first order averaging method and some mathematical technique on estimating the number of the zeros, we show that under a class of piecewise smooth quartic perturbations, seven is a lower and twelve an upper bound for the maximum number of limit cycles bifurcating from the unperturbed quartic isochronous center.

Abstract Salicaceae plants are dioecious woody plants. Previous studies have shown that male individuals are more tolerant to water deficiency than females for male‐biased poplars. However, Salix paraplesia is a female‐biased species in nature. It is still unknown whether female willows are more tolerant to drought stress than males. To better understand the sexually different tolerance to water deficiency in willows, a greenhouse experiment combined with a field investigation was conducted, and physiological traits were tested in male and female S. paraplesia under a drought‐stressed condition (50% of soil water capacity). Our field investigation showed that S. paraplesia was a species with female‐biased sex ratio along altitude gradients (2,400 m, 2,600 m and 2,800 m) in their natural habitats. Our results showed that the height growth, biomass accumulation, total chlorophyll pigment content (TChl), and the net photosynthetic rate were higher in female willows than in males at the low and middle altitudes (2,400 m and 2,600 m) rather than at a high altitude (2,800 m) under well‐watered conditions. Under drought‐stressed conditions, the growth, biomass, and photosynthesis were greatly inhibited in both sexes, while females showed higher biomass and TChl content and suffered less negative effects than did males. Particularly, females that originated from a high altitude showed lower leaf relative electrolyte leakage, malondialdehyde content, and less disorder of chloroplast ultrastructures but a higher peroxidase activity (POD) than that of males. Therefore, S. paraplesia females exhibited a better drought tolerance and self‐protective ability than males from high altitude. There is a reason to speculate that the population structure of S. paraplesia at a high altitude would be likely to further female biases with the increased drought intensity in the alpine regions.

Abstract Background JS001, a humanized IgG4 monoclonal antibody against the programmed death-1 (PD-1) receptor, blocks the interaction of PD-1 with its ligands and promotes T cell activation in preclinical studies. This phase I study is designed to evaluate the safety, tolerability, and clinical activity of JS001 in advanced melanoma or urologic cancer patients who are refractory to standard systemic therapy. Patients and methods In the dose escalation cohorts, subjects initially received a single-dose, intravenous infusion of JS001, and were followed for 28 days followed by multi-dose infusions every 2 weeks. In the dose expansion cohorts, subjects received multi-dose infusions every 2 weeks. Clinical response was evaluated after each 8-week treatment cycle according to RECIST v1.1 criteria. Results Thirty-six subjects diagnosed with advanced melanoma (n = 22), urothelial cancer (UC) (n = 8), or renal cell cancer (RCC) (n = 6) were enrolled. Melanoma subjects included 14 acral and 4 mucosal subtypes. JS001 was well tolerated, and no dose-limiting toxicity was observed. By the safety data cutoff date, 100% of subjects had treatment-related adverse events (TRAE) with most adverse events being grade 1 or 2, and ≥ grade 3 TRAEs occurred in 36%. Among all 36 subjects, 1 confirmed complete response (acral melanoma), 7 confirmed partial responses (2 acral melanoma, 1 mucosal melanoma, 2 UC, and 2 RCC), and 10 stable disease were observed, for an objective response rate of 22.2% (95% CI, 10.1 to 39.2), and a disease control rate of 50.0% (95% CI, 32.9 to 67.1). Clinical responses were correlated with PD-L1 expression on tumor cells, the presence of tumor infiltrating lymphocytes (TIL), baseline tumor volume, ECOG performance status, serum LDH levels, high percentage of activated CD8+ T cells and CD3− CD16+ CD54+ NK cells in the peripheral blood as well as tumor mutational burden (TMB). Conclusion JS001 was well tolerated and demonstrated promising anti-tumor activity in UC and RCC as well as in previously underexplored acral and mucosal melanoma subtypes. Subjects with an immune-active profile in the tumor microenvironment or in peripheral blood responded favorably to JS001 treatment. The completion of the current phase I study has led to the initiation of the first prospective anti-PD-1 registration trial in Asia focusing on acral and mucosal melanoma subtypes, representative of the regional disease epidemiology. Trial registration Clinical Trial ID: NCT02836795, registered July 19, 2016, retrospectively registered.

C-terminal peptidase (Ctp) cleaves the C-terminal extension of the D1 precursor (pD1) to form mature D1. Among the three homologs CtpA, CtpB, and CtpC in photosynthetic organisms only the first is capable of processing pD1 while the roles of CtpB and CtpC remain elusive. Phylogenetic analysis of Ctps from photosynthetic organisms revealed that CtpA has diverged early from CtpB and CtpC during evolution implying distinct roles for the Ctps. Analysis of Arabidopsis Ctp-deficient mutants revealed that pD1 processing was not affected in atctpb, atctpc, or atctpbatctpc mutants, demonstrating that AtCtpA, not AtCtpB or AtCtpC, is responsible for cleaving the pD1 C-terminal extension. Ectopic expression of CtpAs from Synechococcus elongatus, Chlamydomonas reinhardtii, and Physcomitrella patens in atctpa rescued the lethal phenotype of the mutant indicating that SeCtpA, CrCtpA, and PpCtpA could process pD1 in Arabidopsis. Enzyme activity assays showed that PpCtpA and CrCtpA could convert pD1 into mature D1 in vitro. In contrast, expressing CtpB or CtpC from Arabidopsis, C. reinhardtii, or P. patens in atctpa did not rescue its D1 maturation deficiency, and enzyme activity assays also showed that neither CtpB nor CtpC could process pD1 in vitro. Taken together, we conclude that the function of pD1 processing by CtpA is conserved in photosynthetic organisms. It is possible that among other factors CtpA developed this function to initiate the formation of the oxygenic D1/D2 type PSII complex during evolution whereas CtpB or CtpC have other roles that are still unclear.

To investigate the underlying molecular mechanism of tripartite motif-containing 58 (TRIM58) in the development of clear cell renal cell carcinoma (ccRCC), we explored TRIM58 expression and methylation in tumor tissues and the association with clinicopathological features and prognosis of tissue samples; Moreover, we examined the direct gene transcription of TRIM58-specific DNA demethyltransferase (TRIM58-TET1) by the CRISPR-dCas9 fused with the catalytic domain of TET1 and the biological functions in RCC cells. In this study, we demonstrate that TRIM58 is frequently downregulated by promoter methylation in ccRCC tissues, associated significantly with tumor nuclear grade and poor patient survival. TRIM58-TET1 directly induces demethylation of TRIM58 CpG islands, and activates TRIM58 transcription in RCC cell lines. Besides, DNA demethylation of TRIM58 by TRIM58-TET1 significantly inhibits cell proliferation and migration Overall, our results demonstrate that TRIM58 is inactivated by promoter methylation, associates with tumor nuclear grade and poor survival, and TRIM58 DNA demethylation could directly activate TRIM58 transcription and inhibit cell proliferation and migration in RCC cell lines.

As an extension of hesitant fuzzy set, the probabilistic hesitant fuzzy set (PHFS) can more accurately express the initial decision information given by experts, thus the decision method based on PHFS is more true and reliable. In this paper, multi-attribute decision-making (MADM) method is proposed under probabilistic hesitant fuzzy environment, which is based the new distance measures of probabilistic hesitant fuzzy elements (PHFEs) and the COmplex PRoportional ASsessment (COPRAS) method. Firstly, the existing problems of some distances are analyzed and we propose some new distance measures including new Hamming distance, new Euclidean distance and new generalized distance under probabilistic hesitant fuzzy environment. Secondly, a maximizing deviation method based on the new Hamming distance measure is proposed to obtain the attribute weights in probabilistic hesitant fuzzy information. Then, the COPRAS method is extended to solve MADM problems under probabilistic hesitant fuzzy environment. Finally, compared other methods, an example is given to demonstrate the effectiveness of the proposed method.

The shear viscosity of matter and efficient simulating methods in a wide range of temperatures and densities are desirable. In this study, we present the deep-learning many-body potential (the deep potential) method to reduce the computational cost of simulations for the viscosity of liquid aluminum at high temperature and high pressure with accurate results. Viscosities for densities of 2.35 g/cm3, 2.7 g/cm3, 3.5 g/cm3, and 4.27 g/cm3 and temperatures from melting points to about 50 000 K are calculated. The results agree well with the experiment data at a pressure near 1 bar and are consistent with the simulation of first-principles at high pressure and high temperature. We reveal the behavior of the shear viscosity of liquid Al at a range where the current experimental results do not exist. Based on the available experimental data and newly generated simulation data, we propose a modified Enskog–Dymond theory, which can analytically calculate the viscosity of Al at this range. This research is helpful for numerous potential applications.

We investigate a reduced scaling full-potential DFT method based on the multiple scattering theory (MST) code MuST, which is released online (https://github.com/mstsuite/MuST) very recently. First, we test the accuracy by calculating structural properties of typical body-centered cubic (BCC) metals (V, Nb, and Mo). It is shown that the calculated lattice parameters, bulk moduli, and elastic constants agree with those obtained from the VASP, WIEN2k, EMTO, and Elk codes. Second, we test the locally self-consistent multiple scattering (LSMS) mode, which achieves reduced scaling by neglecting the multiple scattering processes beyond a cut-off radius. In the case of Nb, the accuracy of 0.5 mRy/atom can be achieved with a cut-off radius of 20 Bohr, even when small deformations are imposed on the lattice. Despite that the calculation of valence states based on MST exhibits linear scaling, the whole computational procedure has an overall scaling of about O(N1.6), due to the fact that the updating of Coulomb potential scales almost as O(N2). Nevertheless, it can be still expected that MuST would provide a reliable and accessible way to large-scale first-principles simulations of metals and alloys.

During the past two decades, the high-entropy alloy AlCoCrFeNi has attracted much attention due to its outstanding thermal and mechanical properties under ambient conditions. However, the exploration on the thermodynamic properties of this alloy under high temperatures and high pressures is relatively insufficient. Combining structural modeling with the similar atomic environment (SAE) method and first-principles simulations with the modified mean-field potential (MMFP) approach, we studied the lattice and magnetic structure as well as the thermodynamic properties of the body-centered-cubic AlCoCrFeNi, through supercell simulations. AlCoCrFeNi was found to display a strong local lattice distortion compared with typical 3d high-entropy alloys; the ferromagnetic structure stable at 0 K was predicted to transform to the paramagnetic structure at the Curie temperature TC = 279.75 K, in good agreement with previous calculations; the calculated equilibrium volumes, bulk modulus, and shock Hugoniot all agree well with available experimental data and other theoretical values. These results demonstrate the validity and reliability of our methods used to study the dynamic properties of AlCoCrFeNi, providing a promising scheme for accessing the dynamic properties of sophisticated high-entropy alloys.

Alzheimer disease (AD) has an insidious onset and heterogeneous clinical symptoms. The well-accepted biomarkers for clinical diagnosis of AD include β-amyloid (Aβ) deposition and pathologic tau level within cerebral spinal fluid (CSF) and imaging AD pathology such as positive emission tomography (PET) imaging of the amyloid-binding agent Pittsburgh compound B (PET-PiB). However, the high expense and invasive nature of these methods highly limit their wide usage in clinic practice. Therefore, it is imperious to develop less expensive and invasive methods, and plasma biomarkers are the premium targets. In the current study, we utilized a single-blind comparison method; all the probable AD cases met the core clinical National Institute on Aging and Alzheimer’s Association (NIA-AA) criteria and validated by PET-PiB. We used ultrasensitive immunomagnetic reduction (IMR) assays to measure plasma Aβ42 and total-tau (t-tau) levels, in combination with different variables including Aβ42 × t-tau value, Montreal Cognitive Assessment (MoCA), and Mini Mental State Examination (MMSE). We used logistic regression to analyze the effect of all these variables in the algorism. Our results showed that (1) plasma Aβ42 and t-tau are efficient biomarkers for AD diagnosis using IMR platform, whereas Aβ42 × t-tau value is more efficient for discriminating control and AD; (2) in the control group, Aβ42 level and age demonstrated strong negative correlation; Aβ42 × t-tau value and age demonstrated significant negative correlation; (3) in the AD group, t-tau level and MMSE score demonstrated strong negative correlation; (4) using the model that Aβ42, Aβ42 × t-tau, and MoCA as the variable to generate receiver operating characteristic (ROC) curve, cutoff value = 0.48, sensitivity = 0.973, specificity = 0.982, area under the curve (AUC) = 0.986, offered better categorical efficacy, sensitivity, specificity, and AUC. The multifactor model of plasma Aβ42 and t-tau in combination with MoCA can be a viable model separate health and AD subjects in clinical practice.

With the widespread propagation of Internet of Things through wireless sensor networks, massive amounts of sensor data are being generated at an unprecedented rate, resulting in very large quantities of explicit or implicit information. When analyzing such sensor data, it is of particular importance to detect accurately and efficiently not only individual anomalous behaviors but also anomalous events (i.e. patterns of behaviors). However, most previous work has focused only on detecting anomalies while generally ignoring the correlations between them. Even in approaches that take into account correlations between anomalies, most disregard the fact that the anomaly status of sensor data changes over time. In this article, we propose an unsupervised contextual anomaly detection method in Internet of Things through wireless sensor networks. This method accounts for both a dynamic anomaly status and correlations between anomalies based contextually on their spatial and temporal neighbors. We then demonstrate the effectiveness of the proposed method in an anomaly detection model. The experimental results show that this method can accurately and efficiently detect not only individual anomalies but also anomalous events.

Obtaining overlap/grouping functions from a given pair of overlap/grouping functions is an important method of generating overlap/grouping functions, which can be viewed as a binary operation on the set of overlap/grouping functions. In this paper, firstly, we studied closures of overlap/grouping functions w.r.t. ⊛-composition. In addition, then, we show that these compositions are order preserving. Finally, we investigate the preservation of properties like idempotency, migrativity, homogeneity, k-Lipschitz, and power stable.

Abstract Background The primary aim of this study was to evaluate the safety of a novel dendritic cell (DC) vaccine pulsed with survivin and MUC1, silenced with suppressor of cytokine signaling 1 (SOCS1), and immune stimulated with flagellin for patients with stage I to IIIA non-small cell lung cancer (NSCLC) in a phase I open-label, uncontrolled, and dose-escalation trial. Moreover, we evaluate the potential efficacy of this modified DC vaccine as secondary aim. Methods The patients were treated with the vaccine at 1 × 106, 1 × 107and the maximum dose 8 × 107 at day 7, 14, and 21 after characterization of the vaccine phenotype by flow cytometry. The safety of the vaccine was assessed by adverse events, and the efficacy by the levels of several specific tumor markers and the patient quality of life. Results The vaccine was well tolerated without dose-limiting toxicity even at higher doses. The most common adverse event reported was just grade 1 flu-like symptoms without unanticipated or serious adverse event. A significant decrease in CD3 + CD4 + CD25 + Foxp3+ T regulatory (Treg) cell number and increase in TNF-α and IL-6 were observed in two patients. Two patients showed 15% and 64% decrease in carcino-embryonic antigen and CYFRA21, respectively. The vaccination with the maximum dose significantly improved the patients’quality of life when administered at the highest dose. More importantly, in the long-term follow-up until February 17, 2017, 1 patient had no recurrence, 1 patients had a progressive disease (PD), and 1 patient was died in the low dose group. In the middle dose group, all 3 patients had no recurrence. In the high dose group, 1 patient was died, 1 patient had a PD, and the other 7 patients had no recurrence. Conclusions We provide preliminary data on the safety and efficacy profile of a novel vaccine against non-small cell lung cancer, which was reasonably well tolerated, induced modest antitumor activity without dose-limiting toxicity, and improved patients’ quality of life. Further more, the vaccine maybe a very efficacious treatment for patients with resected NSCLC to prevent recurrence. Our findings on the safety and efficacy of the vaccine in this phase I trial warrant future phase II/III clinical trial.

Abstract Background Recently, increasing innovations improved the accuracy of next generation sequencing (NGS) data. However, the validation of all NGS variants increased the cost and turn‐around time of clinical diagnosis, and therefore limited the further development of clinical applications. We aimed to comprehensively assess the necessity of validating NGS variants. Methods Validation data of 7,601 NGS variants involving 1,045 genes were collected from 5,190 clinical samples and sequenced by one of five targeted capture panels and two NGS chemistries, respectively. These genes and variants were widely distributed in 24 human chromosomes and mitochondrial genome. Variants validation was firstly processed by Sanger sequencing. If validation results were unavailable or inconsistent with NGS calls, another validation test would be performed by mass spectrometry genotyping. Results A total of 6,939 high quality NGS variants with ≥35 × depth coverage and ≥35% heterozygous ratio were 100% confirmed by a secondary methodology. 5,775 heterozygous variants were separated from 760 homozygous variants and 404 hemizygous variants by 80% heterozygous ratio. A total of 1.5% (98/6,939) of NGS variants were validated by mass spectrometry genotyping. Conclusion Considering of the above comprehensive assessment, a new variant with high quality from a well‐validated capture‐based NGS workflow can be reported directly without validation.

The hydride growth on metallic surface can cause material failure, which is a significant form of pitting corrosion. A new multiphase-field model is constructed to study the hydride corrosion kinetics, in which three order parameters are introduced to represent the passive film, hydride and metal phase, respectively. Coupling with hydrogen concentration field and elastic strain field, this model not only presents the growth of hydride and the rupture of passive film, but also reveals the hydrogen diffusion mechanism and the effect of strain energy on pitting corrosion process. The simulation shows the semi-ellipsoidal cerium hydride forms and grows near the passive film/cerium interface. During this process, the passive film on the upper side of the hydride is also hydrogenated or peeled off, resulting in faster hydrogen transport, which in turn promotes the growth of hydride. The formation of cerium hydride causes volume expansion, and the strain energy is mainly distributed around the hydride, which inhibits its growth. The present study contributes to understanding the formation mechanism of hydride corrosion at mesoscale, especially the pitting corrosion kinetics of rare earth metals.

In this paper we introduce the wide regime equation of state (WEOS) developed in Institute of Applied Physics and Computational Mathematics (IAPCM). A semi-empirical model of the WEOS is given by a thermodynamically complete potential of the Helmholtz free energy which combines several theoretical models and has some adjustable parameters calibrated via some experimental and theoretical data. The validation methods of the equation of state in wide regime are presented using copper as a prototype. The results of the WEOS are well consistent with the available theoretical and experimental data, including ab initio cold curve under compression, isotherm, Hugoniot, off-Hugoniot and sound velocity data. It enhances our confidence in the accuracy of the WEOS, which is very important for the validation and verification of equation of state in high temperature and pressure technology.

Human GLP-1 (glucagon-like peptide-1) can produce a remarkable improvement in glycemic control in patients with type 2 diabetes. However, its clinical benefits are limited by its short half-life, which is less than 2 min because of its small size and rapid enzymatic inactivation by dipeptidyl peptidase IV. We engineered GLP-1-IgG2σ-Fc, a 68-kDa fusion protein linking a variant human GLP-1 (A8G/G26E/R36G) to a human IgG2σ constant heavy-chain. A stably transfected Chinese hamster ovary cell line was obtained using electroporation. Western blotting showed that the expressed protein was immunoreactive to both GLP-1 and IgG antibodies. GLP-1-IgG2σ-Fc stimulated insulin secretion from INS-1 cells in a dose- and glucose-dependent manner and increased insulin mRNA expression. The half-life of GLP-1-IgG2σ-Fc in cynomolgus monkeys was approximately 57.1 ± 4.5 h. In the KKAy mouse model of diabetes, one intraperitoneal injection of GLP-1-IgG2σ-Fc (1 mg/kg) reduced blood glucose levels for 5 days. A 4-week repeat-administration study identified sustained effects on blood glucose levels. Oral glucose tolerance tests conducted at the beginning and end of this 4-week period showed that GLP-1-IgG2σ-Fc produced a stable glucose lowering effect. In addition, KKAy mice treated with GLP-1-IgG2σ-Fc showed statistically significant weight loss from day 23. In conclusion, these properties of GLP-1-IgG2σ-Fc demonstrated that it represented a potential long-acting GLP-1 receptor agonist for the treatment of type 2 diabetes.

FHL1 is an important tumor-suppressor that is downregulated in multiple tumors by unknown mechanisms. We demonstrated that miR-410 specifically targets the 3'UTR of FHL1. Furthermore, using DNA bisulfite modification and sequencing experiments, we demonstrated that the FHL1 promoter is hypermethylated in cancer cells. FHL1 methylation is increased upon miR-410 expression, suggesting that the regulation of FHL1 by miR-410 occurs by a dual mechanism. Using chromatin immunoprecipitation assays, we observed that miR-410 overexpression results in the increased binding of DNMT3A at the FHL1 promoter, which could explain how miR-410 regulates FHL1 methylation. Importantly, in vitro and in vivo results suggest that miR-410 may have oncogenic properties. Furthermore, both miR-410 and DNMT3A are upregulated in clinical human liver and colorectal tumors cancers. Our results suggest that miR-410 may function as an oncomiR and are consistent with its key function in regulating FHL1 in certain digestive system cancers.