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Live streaming has emerged as one of the indispensable channels for product information dissemination. Product recommendations from live streamers play an increasingly important role in customers' purchasing decisions. Our study aims to understand the mechanism behind individuals' intention to adopt product recommendations in live streaming. To that end, we implemented a moderated mediation model to test the direct and indirect effects of perceived value on customers' intention to adopt product recommendations from live streamers, the mediating role of perceived credibility in the relationship between perceived value and adoption intention, the moderating role of sense of telepresence in the link between perceived value and perceived credibility, and the moderating role of self-identification in the association between perceived credibility and adoption intention. Results show that perceived credibility plays a partial intermediary role in the link between perceived value and adoption intention, sense of telepresence can positively predict perceived credibility but cannot significantly moderate the relationship between perceived value and adoption intention, and self-identification can positively buffer the association between perceived credibility and adoption intention, but negatively moderate the relationship between perceived value and adoption intention. This study advances theoretical research on product recommendations in the live-streaming context and provides practical inspiration for live streamers and managers of social commerce companies.

Clarifying the spatiotemporal structure and driving mechanism of China’s digital village construction (DVC) is imperative for ameliorating regional disparities and fostering the holistic progression of DVC in China. This study assesses the index of DVC in 30 Chinese provinces from 2011 to 2021 using the Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) and dynamic GRA. It analyzes the spatiotemporal structure of DVC with kernel density, trend surface, and social network analysis techniques. Additionally, it employs Geodetector to elucidate the driving mechanism behind spatial differentiation in China’s digital village development network. The results indicate that: (1) Although the index of DVC in China from 2011 to 2021 has shown progressive enhancement, the average DVC index for all regions throughout the years surveyed stands at 0.457, which means that the DVC in China is still at an early stage. (2) The overall network structure analysis suggests that the number of ties in China’s DVC spatial correlation network grew slowly but still falls significantly short of the ideal number. Additionally, there is an increase in the network density of China’s DVC over the years, providing strong evidence of spatial spillover effects within the network. (3) The block roles of the central and western regions are main inflow and bidirectional spillover while the block roles of the eastern region are agent and main outflow. (4) The main driving factors of DVC in China are investment in information infrastructure and fiscal expenditure on education. Bivariate enhancement effect and nonlinear enhancement were found to exist in all interactions of indicators. These findings offer theoretical insights and practical directives for improving DVC in China and its synergistic effects.

Mesenchymal stem cells (MSCs) have been increasingly tested experimentally and clinically for cardiac repair. However, the underlying mechanisms remain controversial due to the poor viability and considerable death of the engrafted cells in the infracted myocardium. Recent reports have suggested that extracellular vesicles (EVs) released by MSCs have angiogenesis-promoting activity; however, the therapeutic effect of MSC-EVs on an ischemic heart is unclear. In the present study, we reported that MSCs could release a large quantity of EVs around 100 nm in diameter upon hypoxia stimulation though the majority of the cells had not experienced apoptosis. MSC-EVs could be promptly uptaken by human umbilical vein endothelial cells, and the internalization resulted in dose-dependent enhancement of in vitro proliferation, migration, and tube formation of endothelial cells. Using an acute myocardial infarction rat model, we found that intramyocardial injection of MSC-EVs markedly enhanced blood flow recovery, in accordance with reduced infarct size and preserved cardiac systolic and diastolic performance compared to those treated with PBS. These data suggest that like MSCs, MSC-EVs could also protect cardiac tissue from ischemic injury at least by means of promoting blood vessel formation, though further detailed investigations should be performed to define the functionality of MSC-EVs. Key messages MSCs released extracellular vesicles (EVs) upon hypoxia stimulation. MSC-EVs were a mixture of microvesicles and exosomes. MSC-EVs could be promptly uptaken by human umbilical vein endothelial cells. MSC-EVs promoted neoangiogenesis in vitro and in vivo. MSC-EVs preserved cardiac performance in an AMI model.

The processing-transportation composite robots, with their dual functions of processing and transportation, as well as comprehensive robot-machine interactions, have been widely and efficiently applied in the manufacturing industry, leading to a continuous increase in energy consumption. Hence, this work focuses on investigating robot-machine integrated energy-efficient scheduling in flexible job shop environments. To address the new problem, an innovative mixed-integer linear programming model and a novel dual-self-learning co-evolutionary algorithm are proposed, aimed at minimizing the total energy consumption and makespan. In the proposed algorithm, a three-dimensional vector is first used to comprehensively express the solution, and then a greedy decoding strategy is designed to reduce the idle time and energy consumption simultaneously. A hybrid initialization method with adaptive random selection and chaos mapping is developed to ensure the diversity and high quality of the initial solutions. A dual-self-learning mechanism, including a self-learning evolutionary mechanism and a self-learning cooperation mechanism, is designed to select suitable evolutionary operators and enhance interactions between populations, respectively. Finally, multiple sets of experiments are conducted to demonstrate the effectiveness of the proposed mathematical model, improved components and algorithm through numerical, statistical, and differential analyses.

With the continuous growth of global energy demand and the late stage of conventional oilfield exploitation, the demand for developing and utilizing low-permeability heavy oil reservoirs is becoming increasingly urgent. However, the exploitation of low-permeability heavy oil reservoirs faces many challenges due to their high viscosity, low permeability, and complex geological conditions. To overcome these challenges, researchers have gradually introduced SC-CO2 as an oil displacement agent in the exploitation of heavy oil reservoirs. However, the oil displacement mechanism of SC-CO2 in low-permeability heavy oil reservoirs and its improvement mechanism are still not completely understood. The article provides a detailed study and understanding of the oil displacement mechanism of SC-CO2, which involves the expansion of heavy oil volume through SC-CO2 dissolution. This mechanism reduces the capillary resistance and flow resistance during the oil flow process. The permeation of CO2 disrupts the internal structure and arrangement of heavy oil, reducing its viscosity. CO2 extracts both light and heavy components from the heavy oil, reducing the residual oil saturation. In addition, the mechanism of improving the effect of oil displacement agents such as nanoparticles, polymers, and surfactants on SC-CO2 displacement was also explored. By further exploring the mechanisms and improvement mechanisms of SC-CO2 displacement for heavy oil, it can guide the selection and optimization of oil displacement agents. Furthermore, understanding the mechanism can also provide a theoretical basis for engineering practice and technical innovation. While the research on CO2 flooding is analyzed and evaluated, the obstacles and challenges that still exist at this stage are indicated, and future research work on CO2 in low-permeability heavy oil reservoirs is proposed.

WRKY transcription factors are key players in the plant immune response, but less is known about their involvement in antiviral defense than about their roles in defense against bacterial or fungi pathogens. Here, we report that Arabidopsis thaliana WRKY DNA-binding protein 8 (WRKY8) has a role in mediating the long-distance movement of crucifer-infecting tobacco mosaic virus (TMV-cg). The expression of WRKY8 was inhibited by TMV-cg infection, and mutation of WRKY8 accelerated the accumulation of TMV-cg in systemically infected leaves. Quantitative RT-PCR analysis showed that the expression of ABA insensitive 4 (ABI4) was reduced and the expression of 1-aminocyclopropane-1-carboxylic acid synthase 6 (ACS6) and ethylene response factor 104 (ERF104) was enhanced in the systemically infected leaves of wrky8 . Immunoprecipitation assays demonstrated that WRKY8 could bind selectively to putative W-boxes of the ABI4 , ACS6 , and ERF104 promoters. Furthermore, TMV-cg infection enhanced WRKY8 binding to the ABI4 promoter but reduced the binding of WRKY8 to the ACS6 and ERF104 promoters, indicating that regulation of ABI4 , ACS6 , and ERF104 by WRKY8 is at least partially dependent on TMV-cg. Exogenous applications of abscisic acid (ABA) reduced the systemic accumulation of TMV-cg. Mutations in ABA deficient 1, ABA deficient 2, ABA deficient 3, or abi4 accelerated systemic TMV-cg accumulation. In contrast, exogenous application of aminocyclopropane-1-carboxylic acid enhanced the systemic accumulation of TMV-cg, but mutations in acs6, erf104, or an octuple acs mutant inhibited systemic TMV-cg accumulation. Our results demonstrate that WRKY8 is involved in the defense response against TMV-cg through the direct regulation of the expression of ABI4 , ACS6 , and ERF104 and may mediate the crosstalk between ABA and ethylene signaling during the TMV-cg– Arabidopsis interaction.

Background Malignant transformation and progression of cancer are driven by the co-evolution of cancer cells and their dysregulated tumor microenvironment (TME). Recent studies on immunotherapy demonstrate the efficacy in reverting the anti-tumoral function of T cells, highlighting the therapeutic potential in targeting certain cell types in TME. However, the functions of other immune cell types remain largely unexplored. Results We conduct a single-cell RNA-seq analysis of cells isolated from tumor tissue samples of non-small cell lung cancer (NSCLC) patients, and identify subtypes of tumor-infiltrated B cells and their diverse functions in the progression of NSCLC. Flow cytometry and immunohistochemistry experiments on two independent cohorts confirm the co-existence of the two major subtypes of B cells, namely the naïve-like and plasma-like B cells. The naïve-like B cells are decreased in advanced NSCLC, and their lower level is associated with poor prognosis. Co-culture of isolated naïve-like B cells from NSCLC patients with two lung cancer cell lines demonstrate that the naïve-like B cells suppress the growth of lung cancer cells by secreting four factors negatively regulating the cell growth. We also demonstrate that the plasma-like B cells inhibit cancer cell growth in the early stage of NSCLC, but promote cell growth in the advanced stage of NSCLC. The roles of the plasma-like B cell produced immunoglobulins, and their interacting proteins in the progression of NSCLC are further validated by proteomics data. Conclusion Our analysis reveals versatile functions of tumor-infiltrating B cells and their potential clinical implications in NSCLC.

The use of models for the prediction of future climate conditions is commonplace. This study investigates regional sea surface temperature biases across 22 climate models and finds that they are linked to the large circulation system in the Atlantic Ocean. Improvements to climate models will need to consider the impact of remote biases on regional processes. The Intergovernmental Panel on Climate Change’s Fifth Assessment Report largely depends on simulations, predictions and projections by climate models 1 . Most models, however, have deficiencies and biases that raise large uncertainties in their products. Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of special regions and aspects of the climate system 2 , 3 , 4 . Here we show that biases or errors in special regions can be linked with others at far away locations. We find in 22 climate models that regional sea surface temperature (SST) biases are commonly linked with the Atlantic meridional overturning circulation (AMOC), which is characterized by the northward flow in the upper ocean and returning southward flow in the deep ocean. A simulated weak AMOC is associated with cold biases in the entire Northern Hemisphere with an atmospheric pattern that resembles the Northern Hemisphere annular mode. The AMOC weakening is also associated with a strengthening of Antarctic Bottom Water formation and warm SST biases in the Southern Ocean. It is also shown that cold biases in the tropical North Atlantic and West African/Indian monsoon regions during the warm season in the Northern Hemisphere have interhemispheric links with warm SST biases in the tropical southeastern Pacific and Atlantic, respectively. The results suggest that improving the simulation of regional processes may not suffice for overall better model performance, as the effects of remote biases may override them.

Hepatocellular carcinoma (HCC) is the most commonmalignancy. Exsome plays a significant role in the elucidation of signal transduction pathways between hepatoma cells, angiogenesis and early diagnosis of HCC. Exosomes are small vesicular structures that mediate interaction between different types of cells, and contain a variety of components (including DNA, RNA, and proteins). Numerous studies have shown that these substances in exosomes are involved in growth, metastasis and angiogenesis in liver cancer, and then inhibited the growth of liver cancer by blocking the signaling pathway of liver cancer cells. In addition, the exosomal substances could also be used as markers for screening early liver cancer. In this review, we summarized to reveal the significance of exosomes in the occurrence, development, diagnosis and treatment of HCC, which in turn might help us to further elucidate the mechanism of exosomes in HCC, and promote the use of exosomes in the clinical diagnosis and treatment of HCC.

Observed Southern Ocean surface cooling and sea-ice expansion over the past several decades are inconsistent with many historical simulations from climate models. Here we show that natural multidecadal variability involving Southern Ocean convection may have contributed strongly to the observed temperature and sea-ice trends. These observed trends are consistent with a particular phase of natural variability of the Southern Ocean as derived from climate model simulations. Ensembles of simulations are conducted starting from differing phases of this variability. The observed spatial pattern of trends is reproduced in simulations that start from an active phase of Southern Ocean convection. Simulations starting from a neutral phase do not reproduce the observed changes, similarly to the multimodel mean results of CMIP5 models. The long timescales associated with this natural variability show potential for skilful decadal prediction.