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Advancement and depiction involving prototypes pertaining to inside vitro plus vivo mouse styles of ibrutinib-resistant CLL.
Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 °C target could avoid ~118,000 and ~614,000 PM2.5 attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 °C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393-$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries.The precise precursor supply is a precondition for controllable growth of two-dimensional (2D) transition metal dichalcogenides (TMDs). Although great efforts have been devoted to modulating the transition metal supply, few effective methods of chalcogen feeding control were developed. Here we report a strategy of using active chalcogen monomer supply to grow high-quality TMDs in a robust and controllable manner, e.g., MoS2 monolayers perform representative photoluminescent circular helicity of ~92% and electronic mobility of ~42 cm2V-1s-1. Meanwhile, a uniform quaternary TMD alloy with three different anions, i.e., MoS2(1-x-y)Se2xTe2y, was accomplished. Our mechanism study revealed that the active chalcogen monomers can bind and diffuse freely on a TMD surface, which enables the effective nucleation, reaction, vacancy healing and alloy formation during the growth. Our work offers a degree of freedom for the controllable synthesis of 2D compounds and their alloys, benefiting the development of high-end devices with desired 2D materials.Bone defects combined with tumors, infections, or other bone diseases are challenging in clinical practice. Autologous and allogeneic grafts are two main traditional remedies, but they can cause a series of complications. To address this problem, researchers have constructed various implantable biomaterials. However, the original pathological microenvironment of bone defects, such as residual tumors, severe infection, or other bone diseases, could further affect bone regeneration. Thus, the rational design of versatile biomaterials with integrated bone therapy and regeneration functions is in great demand. Many strategies have been applied to fabricate smart stimuli-responsive materials for bone therapy and regeneration, with stimuli related to external physical triggers or endogenous disease microenvironments or involving multiple integrated strategies. Typical external physical triggers include light irradiation, electric and magnetic fields, ultrasound, and mechanical stimuli. These stimuli can transform the internal atomic packing arrangements of materials and affect cell fate, thus enhancing bone tissue therapy and regeneration. In addition to the external stimuli-responsive strategy, some specific pathological microenvironments, such as excess reactive oxygen species and mild acidity in tumors, specific pH reduction and enzymes secreted by bacteria in severe infection, and electronegative potential in bone defect sites, could be used as biochemical triggers to activate bone disease therapy and bone regeneration. Herein, we summarize and discuss the rational construction of versatile biomaterials with bone therapeutic and regenerative functions. The specific mechanisms, clinical applications, and existing limitations of the newly designed biomaterials are also clarified.The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.Nonalcoholic fatty liver disease (NAFLD) affects a large population with incompletely defined mechanism(s). Here we report that Kindlin-2 is dramatically up-regulated in livers in obese mice and patients with NAFLD. Kindlin-2 haploinsufficiency in hepatocytes ameliorates high-fat diet (HFD)-induced NAFLD and glucose intolerance without affecting energy metabolism in mice. BMS-986020 In contrast, Kindlin-2 overexpression in liver exacerbates NAFLD and promotes lipid metabolism disorder and inflammation in hepatocytes. A C-terminal region (aa 570-680) of Kindlin-2 binds to and stabilizes Foxo1 by inhibiting its ubiquitination and degradation through the Skp2 E3 ligase. Kindlin-2 deficiency increases Foxo1 phosphorylation at Ser256, which favors its ubiquitination by Skp2. Thus, Kindllin-2 loss down-regulates Foxo1 protein in hepatocytes. Foxo1 overexpression in liver abrogates the ameliorating effect of Kindlin-2 haploinsufficiency on NAFLD in mice. Finally, AAV8-mediated shRNA knockdown of Kindlin-2 in liver alleviates NAFLD in obese mice. Collectively, we demonstrate that Kindlin-2 insufficiency protects against fatty liver by promoting Foxo1 degradation.A Disintegrin and Metalloproteinase with ThromboSpondin motif (ADAMTS) 5 functions as an anti-angiogenic and anti-cancer protein independent of its metalloproteinase activity. Both full-length ADAMTS5 and TS5-p45, the autocatalytically cleaved C-terminal 45 kDa truncate of ADAMTS5, inhibits angiogenesis, and induces endothelial cell (EC) apoptosis. However, how ADAMTS5 triggers EC apoptosis remains unclear. This work shows that caspase-8 (Cas-8) and caspase-9 (Cas-9) are involved in TS5-p45-induced EC apoptosis. We identify cell surface nucleolin (NCL) as a novel high-affinity receptor for TS5-p45 in ECs, mediating TS5-p45's cell surface binding and pro-apoptotic function. We show that the central RNA-binding domain (RBD) of NCL is essential and sufficient for its binding to TS5-p45. Upon interacting with EC surface NCL, TS5-p45 is internalized through clathrin- and caveolin-dependent endocytosis and trafficked to the nucleus via late endosomes (LEs). We demonstrate that the nuclear trafficking of TS5-p45 is reted metalloproteinase ADAMTS5 in angiogenesis inhibition.Attention-deficit/hyperactivity disorder (ADHD) is a common childhood mental disorder with undetermined pathophysiological mechanisms. The gut microbiota and immunological dysfunction may influence brain functions and social behaviours. In the current study, we aimed to explore the correlation of gut microbiome imbalance and inflammation in the pathophysiology of ADHD. Forty-one children with ADHD and thirty-nine healthy-control (HC) individuals were recruited. Faecal samples from all participants were collected and submitted for 16 S rRNA V3-V4 amplicon microbiome sequencing analysis. The plasma levels of 10 cytokines, including TNF-α, IL-6, IL-1β, IL-2, IL-10, IL-13, IL-17A, IFN-α2, IFN-γ, and MCP-1, were determined using a custom-made sandwich enzyme-linked immunosorbent assay (ELISA) developed by Luminex Flowmetrix. There was no significant difference between the ADHD and HC groups in species diversity in the faeces, as determined with α-diversity and β-diversity analysis. In the ADHD group, three differentially abundant taxonomic clades at the genus level were observed, namely Agathobacter, Anaerostipes, and Lachnospiraceae. Top differentially abundant bacteria and representative biological pathways were identified in children with ADHD using linear discriminant analysis (LDA) effect size (LEfSe), and the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) analysis, respectively. The plasma levels of TNF-α were significantly lower in children with ADHD than in HCs. Within the ADHD group, the levels of TNF-α were negatively correlated with ADHD symptoms and diversity of the gut microbiome. Our study provides new insights into the association between gut microbiome dysbiosis and immune dysregulation, which may contribute to the pathophysiology of ADHD.With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, nondestructive testing, experimental mechanics, and biomedicine. In recent years, deep learning, a subfield of machine learning, is emerging as a powerful tool to address problems by learning from data, largely driven by the availability of massive datasets, enhanced computational power, fast data storage, and novel training algorithms for the deep neural network. It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology. Unlike the traditional "physics-based" approach, deep-learning-enabled optical metrology is a kind of "data-driven" approach, which has already provided numerous alternative solutions to many challenging problems in this field with better performances. In this review, we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology. We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning, followed by a comprehensive review of its applications in various optical metrology tasks, such as fringe denoising, phase retrieval, phase unwrapping, subset correlation, and error compensation. The open challenges faced by the current deep-learning approach in optical metrology are then discussed. Finally, the directions for future research are outlined.Personality traits, especially neuroticism, strongly predict psychopathology. The domestic dog (Canis lupus familiaris Linnaeus, 1758) is used as a natural model for psychiatric disorders, but the similarity between dog and human personality and the association between dog personality and unwanted behavioral traits, such as fearfulness, aggressiveness, and impulsivity/inattention, remain unknown. This study utilized structural equation modeling (SEM) with survey data of 11,360 dogs to examine the associations and correlations between seven personality and ten unwanted behavioral traits. Personality traits included insecurity, energy, training focus, aggressiveness/dominance, human sociability, dog sociability, and perseverance. Unwanted behavioral traits included fearfulness, noise sensitivity, fear of surfaces/heights, separation anxiety, barking, stranger-directed aggression, owner-directed aggression, dog-directed aggression, hyperactivity/impulsivity, and inattention. We first fitted confirmatory factor models for the unwanted behavioral traits and the best model grouped unwanted behaviors into four latent traits fear-related behavior, fear-aggression, aggression, and impulsivity/inattention and used this structure in the subsequent SEM model.
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