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The oxygen vacancies and surface oxygen species play pivotal roles in CO catalytic oxidation. In this study, Co3O4−CeO2 supported on resin based spherical activated carbon was fabricated and the effect of CeO2 on surface oxygen species was demonstrated through controlling various Ce contents. When Ce content was optimal (nCo : nCe=9), the maximum surface adsorbed oxygen content (60.3 %) is displayed and the catalyst achieved good CO conversion (T100=110 °C), water resistance and robust stability. DFT simulation calculation confirmed that the energy barriers of two transition states significantly decreased to 0.60 eV and 0.37 eV, respectively, with the addition of CeO2. The results indicate that the presence of CeO2 is conducive to the increasement of surface adsorbed oxygen content and optimal Co/Ce ratio is the most favorable for the CO oxidation. It is attributed to the visible decline of the energy barrier between oxygen vacancies and gas–phase oxygen at the Co3O4−CeO2 interface, and the process of oxygen vacancies replenishment could be more prone to occur at the interface. This study may provide a protocol for further improving surface species on supporting catalysts. [ABSTRACT FROM AUTHOR]

The prediction of surrounding agent trajectories in heterogeneous traffic environments remains a challenging task for autonomous driving due to several critical issues, such as understanding social interactions among agents and the environment, handling multiclass traffic movements, and generating feasible trajectories in accordance with real‐world rules, all of which hinder prediction accuracy. To address these issues, a new multimodal trajectory prediction framework based on the transformer network is presented in this study. A hierarchical‐structured context‐aware module, inspired by human perceptual logic, is proposed to capture contextual information within the scene. An efficient linear global attention mechanism is also proposed to reduce the computation and memory load of the transformer framework. Additionally, this study introduces a novel auxiliary loss to penalize infeasible off‐road predictions. Empirical results on the Lyft l5kit data set demonstrate the state‐of‐the‐art performance of the proposed model, which substantially enhances the accuracy and feasibility of prediction outcomes. The proposed model also possesses a unique feature, effectively dealing with missing input observations. This study underscores the importance of comprehending social interactions among agents and the environment, handling multiclass traffic movements, and generating feasible trajectories adhering to real‐world rules in autonomous driving. [ABSTRACT FROM AUTHOR]

Background: Our study aims to delineate the miRSNP–microRNA–gene–pathway interactions in the context of hypertrophic scars (HS) and keloids. Materials and Methods: We performed a computational biology study involving differential expression analysis to identify genes and their mRNAs in HS and keloid tissues compared to normal skin, identifying key hub genes and enriching their functional roles, comprehensively analyzing microRNA‐target genes and related signaling pathways through bioinformatics, identifying MiRSNPs, and constructing a pathway‐based network to illustrate miRSNP‐miRNA‐gene‐signaling pathway interactions. Results: Our results revealed a total of 429 hub genes, with a strong enrichment in signaling pathways related to proteoglycans in cancer, focal adhesion, TGF‐β, PI3K/Akt, and EGFR tyrosine kinase inhibitor resistance. Particularly noteworthy was the substantial crosstalk between the focal adhesion and PI3K/Akt signaling pathways, making them more susceptible to regulation by microRNAs. We also identified specific miRNAs, including miRNA‐1279, miRNA‐429, and miRNA‐302e, which harbored multiple SNP loci, with miRSNPs rs188493331 and rs78979933 exerting control over a significant number of miRNA target genes. Furthermore, we observed that miRSNP rs188493331 shared a location with microRNA302e, microRNA202a‐3p, and microRNA20b‐5p, and these three microRNAs collectively targeted the gene LAMA3, which is integral to the focal adhesion signaling pathway. Conclusions: The study successfully unveils the complex interactions between miRSNPs, miRNAs, genes, and signaling pathways, shedding light on the genetic factors contributing to HS and keloid formation. [ABSTRACT FROM AUTHOR]

Mitogen‐activated protein kinase (MAPK) signalling cascades are functionally important signalling modules in eukaryotes. Transcriptome reprogramming of immune‐related genes is a key process in plant immunity. Emerging evidence shows that plant MAPK cascade is associated with processing (P)‐body components and contributes to transcriptome reprogramming of immune‐related genes. However, it remains largely unknown how this process is regulated. Here, we show that OsMPK12, which is induced by Magnaporthe oryzae infection, positively regulates rice blast resistance. Further analysis revealed that OsMPK12 directly interacts with enhancer of mRNA decapping protein 4 (OsEDC4), a P‐body‐located protein, and recruits OsEDC4 to where OsMPK12 is enriched. Importantly, OsEDC4 directly interacts with two decapping complex members OsDCP1 and OsDCP2, indicating that OsEDC4 is a subunit of the mRNA decapping complex. Additionally, we found that OsEDC4 positively regulates rice blast resistance by regulating expression of immune‐related genes and maintaining proper mRNA levels of some negatively‐regulated genes. And OsMPK12 and OsEDC4 are also involved in rice growth and development regulation. Taken together, our data demonstrate that OsMPK12 positively regulates rice blast resistance via OsEDC4‐mediated mRNA decay of immune‐related genes, providing new insight into not only the new role of the MAPK signalling cascade, but also posttranscriptional regulation of immune‐related genes. [ABSTRACT FROM AUTHOR]

Background & Aims: Following the classification of metabolic dysfunction‐associated fatty liver disease (MAFLD), non‐alcoholic fatty liver disease (NAFLD) has recently been redefined again as metabolic dysfunction‐associated steatotic liver disease (MASLD). However, the distinctions in characteristics and mortality outcomes between NAFLD, MAFLD and MASLD remain unclear. Methods: We analysed data from 7519 participants in the third National Health and Nutrition Examination Surveys of United States (US) and their linked mortality until 2019. Survey weight‐adjusted multivariable Cox proportional model was used to study the mortality over three terms. Results: The prevalence of NAFLD, MAFLD and MASLD was 18.5%, 19.3% and 20.8%, respectively. Most individuals with NAFLD (94.5%) or MAFLD (100%) can be classified as MASLD, while a relatively low percentage of those with MASLD were also diagnosed with either NAFLD (84.1%) or MAFLD (92.7%). During a median follow‐up of 26.9 years, both MAFLD and MASLD were associated with increased risk of all‐cause mortality (adjusted hazard ratio [aHR] 1.18, 95% CI 1.04–1.33 and 1.19, 1.06–1.34, respectively), this association was mainly observed in NAFLD−/MASLD+ subgroups. NAFLD was not associated with all‐cause mortality. However, all three terms were associated with an increased risk of all‐cause mortality in individuals with advanced fibrosis (aHR: 1.71–1.81). Subgroup analyses showed that higher risk of all‐cause mortality for both MAFLD and MASLD were observed among older adults (≥65 year), non‐Hispanic whites and those without diabetes. Conclusions: Both MASLD and MALFD were linked to higher all‐cause mortality risk, but MASLD identified a greater number of individuals compared to MAFLD. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a chronic joint disease characterized by synovitis and joint cartilage destruction. The severity of OA is highly associated with the imbalance between M1 and M2 synovial macrophages. In this study, a novel strategy is designed to modulate macrophage polarization by reducing intracellular reactive oxygen species (ROS) levels and regulating mitochondrial function. A ROS‐responsive polymer is synthesized to self‐assemble with astaxanthin and autophagy activator rapamycin to form nanoparticles (NP@PolyRHAPM). In vitro experiments show that NP@PolyRHAPM significantly reduced intracellular ROS levels. Furthermore, NP@PolyRHAPM restored mitochondrial membrane potential, increased glutathione (GSH) levels, and promoted intracellular autophagy, hence successfully repolarizing M1 macrophages into the M2 phenotype. This repolarization enhanced chondrocyte proliferation and vitality while inhibiting apoptosis. In vivo experiments utilizing an anterior cruciate ligament transection (ACLT)‐induced OA mouse model revealed the anti‐inflammatory and cartilage‐protective effects of NP@PolyRHAPM, effectively mitigating OA progression. Consequently, the findings suggest that intra‐articular delivery of ROS‐responsive nanocarrier systems holds significant promise as a potential and effective therapeutic strategy for OA treatment. [ABSTRACT FROM AUTHOR]

Knowledge graph (KG) has been fully considered in natural language generation (NLG) tasks. A KG can help models generate controllable text and achieve better performance. However, most existing related approaches still lack explainability and scalability in large‐scale knowledge reasoning. In this work, we propose a novel CogNLG framework for KG‐to‐text generation tasks. Our CogNLG is implemented based on the dual‐process theory in cognitive science. It consists of two systems: one system acts as the analytic system for knowledge extraction, and another is the perceptual system for text generation by using existing knowledge. During text generation, CogNLG provides a visible and explainable reasoning path. Our framework shows excellent performance on all datasets and achieves a BLEU score of 36.7, which increases by 6.7 compared to the best competitor. [ABSTRACT FROM AUTHOR]