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In recent years, the health and economic effects of air pollution have attracted considerable attention, and health and insurance services have been closely related to residents’ welfare. However, there are few studies on the influence of pollution on household purchases of insurance. Using data from the 2013 and 2015 China Household Finance Surveys, this study investigates the effect of air pollution on insurance purchases using Logit and Poisson regression models. It is found that air pollution significantly increases the probability of household insurance purchases and the level of premium expenditure, although the impact of air pollution on insurance purchases shows a degree of heterogeneity. Health insurance is more sensitive to air pollution than life insurance and other types of insurance. In areas where NO 2 and O 3 are the main types of pollutants, air pollution has a greater impact on household insurance purchases.

Summary Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.

Extracting balanced geostrophic motions (BM) from sea surface height (SSH) observations obtained by wide‐swath altimetry holds great significance in enhancing our understanding of oceanic dynamic processes at submesoscale wavelength. However, SSH observations derived from wide‐swath altimetry are characterized by high spatial resolution while relatively low temporal resolution, thereby posing challenges to extract the BM from a single SSH snapshot. To address this issue, this paper proposes a deep learning model called the BM‐UBM Network, which takes an instantaneous SSH snapshot as input and outputs the projection corresponding to the BM. Training experiments are conducted both in the Gulf Stream and South China Sea, and three metrics are considered to diagnose model's outputs. The favorable results highlight the potential capability of the BM‐UBM Network to process SSH measurements obtained by wide‐swath altimetry. Plain Language Summary Oceanic dynamic processes can be classified into two categories: balanced geostrophic motions (BM), including large‐scale circulation, mesoscale and submesoscale eddy turbulence, and unbalanced wave motions (UBM), including barotropic tides, and inertia–gravity waves (IGWs). Both types of motions coexist and have respective contributions to the sea surface height (SSH). How to extract the BM from the total SSH observations obtained by satellite altimetry is the crucial problem to be solved in this paper. To tackle this issue, we propose a deep learning model named the BM‐UBM Network to establish the relationship between the total SSH and the BM component. The BM‐UBM Network can generate SSH estimations for the BM when provided with a well‐resolved SSH snapshot. Key Points A Deep learning model is developed to extract balanced motions from sea surface height snapshot based on a realistic simulation Diagnostics of three metrics reveal the effectiveness of the model in extracting balanced motions The model exhibits remarkable advantages over the Gaussian filter (baseline) in capturing the gradient and Laplacian information

Ni-rich oxides, LiNi x Mn y Co z O 2 (NMC), are among leading candidates for cathode materials in Li-ion batteries. However, they are mostly fabricated by coprecipitation approach under complex conditions, which usually produces large secondary particles composed of aggregated primary particles. Undesirable cation mixing and crack propagation upon cycling block ion and electron transport, result in fast capacity fading and poor rate capability. Herein, we present an ultrasound-triggered cation chelation and reassembly route for synthesizing one-dimensional precursor with homogeneous element distribution at the atomic level. This process is accomplished by the synergistic combination of ultrasound and surfactant, which can disperse reactants and remove hydration shells surrounding cations so as to accelerate chelating reaction, and then separate and assemble chelates into one dimensional structure. The whole synthesis time is only 20 min (8.9 min of ultrasonic working time) in an open vessel under natural ambient conditions. One-dimensional LiNi 0.6 Mn 0.2 Co 0.2 O 2 has a high reversible capacity (184 mAh·g −1 at 0.1 C) and long cycling stability (95.1% and 82.4% capacity retention for 100 and 1000 cycles, respectively). The short charging time of 76 s is realized at super high current rate of 20 C, which is very important to improve the competitiveness of electric vehicles relative to fuel vehicles. Our synthetic approach can provide a general strategy for the growth of mixed-metal-EDTA chelate precursors by changing the feeding ratio of Ni 2+ , Mn 2+ and Co 2+ cations in reaction for fabricating NMC cathode materials with other compositions.

Non-alcoholic fatty liver disease (NAFLD) has now become the leading chronic liver disease worldwide with lifestyle changes. This may lead to NAFLD becoming the leading cause of end-stage liver disease in the future. To date, there are still no effective therapeutic drugs for NAFLD. An in-depth exploration of the pathogenesis of NAFLD can help to provide a basis for new therapeutic agents or strategies. As the most important immune cells of the liver, macrophages play an important role in the occurrence and development of liver inflammation and are expected to become effective targets for NAFLD treatment. Programmed cell death (PCD) of macrophages plays a regulatory role in phenotypic transformation, and there is also a certain connection between different types of PCD. However, how PCD regulates macrophage polarization has still not been systematically elucidated. Based on the role of lipid metabolic reprogramming in macrophage polarization, PCD may alter the phenotype by regulating lipid metabolism. We reviewed the effects of macrophages on inflammation in NAFLD and changes in their lipid metabolism, as well as the relationship between different types of PCD and lipid metabolism in macrophages. Furthermore, interactions between different types of PCD and potential therapeutic agents targeting of macrophages PCD are also explored.

Background Hylurgus ligniperda , a major international forestry quarantine pest, was recently found to have invaded and posed a serious threat to the Pinus forests of the Jiaodong Peninsula in China. Continuous monitoring and vigilance of the early population is imperative, and rapid molecular detection technology is urgently needed. We focused on developing a single-gene-based species-specific PCR (SS-PCR) method. Results We sequenced and assembled the mitochondrial genome of H. ligniperda to identify suitable target genes. We identified three closely related species for detecting the specificity of SS-PCR through phylogenetic analysis based on 13 protein-coding genes (PCGs). Subsequently, we analyzed the evolution of 13 PCGs and selected four mitochondrial genes to represent slow-evolving gene ( COI ) and faster-evolving genes (e.g. ND2 , ND4 , and ND5 ), respectively. We developed four species-specific primers targeting COI , ND2 , ND4 , and ND5 to rapidly identify H. ligniperd a. The results showed that the four species-specific primers exhibited excellent specificity and sensitivity in the PCR assays, with consistent performance across a broader range of species. This method demonstrates the ability to identify beetles promptly, even during their larval stage. The entire detection process can be completed within 2–3 h. Conclusions This method is suitable for large-scale species detection in laboratory settings. Moreover, the selection of target genes in the SS-PCR method is not affected by the evolutionary rate. SS-PCR can be widely implemented at port and forestry workstations, significantly enhancing early management strategies and quarantine measures against H. ligniperda . This approach will help prevent the spread of the pest and effectively preserve the resources of Chinese pine forests.

A population of 178 recombinant inbred lines (RILs) was developed using a single seed descendant from a cross between G. hirsutum. acc DH962 and G. hirsutum. cv Jimian5, was used to construct a genetic map and to map QTL for fiber and yield traits. A total of 644 polymorphic loci were used to construct a final genetic map, containing 616 loci and spanning 2016.44 cM, with an average of 3.27 cM between adjacent markers. Statistical analysis revealed that segregation distortion in the intraspecific population was more serious than that in the interspecific population. The RIL population and the two parents were phenotyped under 8 environments (two locations, six years), revealing a total of 134 QTL, including 64 for fiber qualities and 70 for yield components, independently detected in seven environments, explaining 4.40-15.28% of phenotypic variation (PV). Among the 134 QTL, 9 common QTL were detected in more than one environment, and 22 QTL and 19 new QTL were detected in combined analysis (E9). A total of 26 QTL hotspot regions were observed on 13 chromosomes and 2 larger linkage groups, and some QTL clusters related to fiber qualities or yield components were also observed. The results obtained in the present study suggested that to map accurate QTL in crops with larger plant types, such as cotton, phenotyping under multiple environments is necessary to effectively apply the obtained results in molecular marker-assisted selection breeding and QTL cloning.

Non-alcoholic fatty liver disease (NAFLD) is a progressive metabolic disease characterized by hepatic steatosis, inflammation, and fibrosis that seriously endangers global public health. Epidemiological studies have shown that the incidence of non-alcoholic fatty liver disease in postmenopausal women has significantly increased. Studies have shown that estrogen deficiency is the main reason for this situation, and supplementing estrogen has become a new direction for preventing the occurrence of postmenopausal fatty liver. However, although classical estrogen replacement therapy can reduce the incidence of postmenopausal NAFLD, it has the risk of increasing stroke and cardiovascular diseases, so it is not suitable for the treatment of postmenopausal NAFLD. More and more recent studies have provided evidence that phytoestrogens are a promising method for the treatment of postmenopausal NAFLD. However, the mechanism of phytoestrogens in preventing and treating postmenopausal NAFLD is still unclear. This paper summarizes the clinical and basic research evidence of phytoestrogens and reviews the potential therapeutic effects of phytoestrogens in postmenopausal NAFLD from six angles: enhancing lipid metabolism in liver and adipose tissue, enhancing glucose metabolism, reducing oxidative stress, reducing the inflammatory response, regulating intestinal flora, and blocking liver fibrosis (Graphical Abstract).

Background Ubiquitination is a basic post-translational modification of intracellular proteins and can be reversed enzymatically by DUBs (deubiquitinating enzymes). More than 90 DUBs have been identified. Among them, the deubiquitinating enzyme YOD1, a member of the ovarian tumor domain protease (OTUs) subfamily, is involved in the regulation of endoplasmic reticulum (ER)-related degradation pathways. In fact, it is reported that YOD1 is an important proliferation and metastasis-inducing gene, which can stimulate the characteristics of cancer stem cells and maintain circulating tumor cells (CTC). However, the expression level, prognostic effect and biological functional mechanism of YOD1 in pancreatic cancer are still unclear. Results In the GEO and TCGA databases, YOD1 mRNA expression is significantly up regulated in a variety of human pancreatic cancer tissues. Survival analysis showed that the up regulation of YOD1 can predict poor prognosis of pancreatic cancer. Cox analysis showed that high YOD1 expression is an independent prognostic factor of pancreatic cancer. ROC analysis shows that YOD1 has significant diagnostic value. The immunohistochemistry (IHC) results showed that the protein expression level of YOD1 in pancreatic cancer tissue was higher than that in neighboring non-pancreatic cancer tissues ( P  < 0.001). In addition, we found that YOD1 expression is negatively correlated with the infiltration level of CD8 + T cells, macrophages, neutrophils and dendritic cells (DC) in pancreatic cancer. The expression of YOD1 has a strong correlation with the different immune marker sets in PAAD. Co-expression network and functional enrichment analysis indicate that YOD1 may participate in the development of pancreatic cancer through cell adhesion molecules, p53, Hippo, TGF-β and other pathways. The experimental results of EDU, Transwell, Immunohistochemistry (IHC), Western blot and Flow Cytometry indicate that YOD1 is highly expressed in pancreatic cancer cells and pancreatic cancer tissues, and its overexpression can promote the proliferation and metastasis of pancreatic cancer cells and affect the immune microenvironment. Conclusion Our results indicate that YOD1 may be a useful biomarker for the prognosis of human pancreatic cancer, and it may also be a potential molecular target for the diagnosis and treatment of pancreatic cancer.

In December 2022, China classified COVID‐19 as a category B infectious disease. This ended 2 years of close epidemiological surveillance of COVID‐19. The objective of this questionnaire was to assess the infection status in the COVID‐19 pandemic since December in Henan Province, China, and the prevalence of infection in people who were taking ursodeoxycholic acid (UDCA) during this period. We distributed questionnaires to patients attending the gastroenterology clinic at the First Affiliated Hospital of Henan University of Chinese Medicine. The questionnaire lasted for 3 weeks and a total of 660 were collected, of which the number of people taking UDCA was 70. This is the first investigation into the rate of infection among those taking UDCA during the time of the COVID‐19 pandemic. Our results showed that the overall infection rate among those taking UDCA was 71.43% ( n  = 50), with a 10% ( n  = 7) rate of asymptomatic infections, which was significantly lower than the 85.42% ( n  = 504) and 6.27% ( n  = 37) rates among respondents who did not take. The administration of UDCA showed a trend toward reducing the rate of COVID‐19 infection, but the difference was not statistically significant when compared to patients with shorter durations of medication use. While less than 30% of participants remained uninfected during the study period, indicating a potential protective effect, it is important to note that complete prevention of SARS‐CoV‐2 infection by UDCA was not observed.