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The Beijing-Tianjin-Hebei (BTH) region of above 110 million people, located in North China, is confronted with high risks of precipitation-related disasters during the summer. Efforts to better understand diurnal variation characteristics of summer precipitation and associated physical driving processes are of vital importance to accurate forecast of short-time precipitation. Based on hourly gridded precipitation data at a fine resolution of 0.1° newly developed by China Meteorological Administration (CMA), we investigate diurnal variations of summer precipitation and their linkages with the topographical conditions in the BTH region for the period of 2008–2018. Summer precipitation amounts are shown to nonlinearly change with the topographical height, the largest values occurring at the altitudes of around 350 m in the BTH region. As a whole, diurnal variation of summer mean precipitation in the BTH region exhibits an S-shape structure with the peak appearing around 20:00 LST. While the mountainous precipitation largely triggers the precipitation peak with contribution from coastal and plain areas, the large precipitation in early morning is dominated by the precipitation over coastal and plain areas. Heavy and very heavy precipitation frequencies generally decrease with topographical height while light precipitation frequency increases in a nonlinear manner. The physical processes explaining the tight precipitation-topography linkages are also discussed. Our findings are expected to provide useful information for the improvement of short-time precipitation forecast over the BTH region.

The population movements for the Chinese New Year (CNY) celebrations, known as the world’s largest yearly migration of human beings, have grown rapidly in the past several decades. The massive population outflows from urban areas largely reduce anthropogenic heat release and modify some other processes, and may thus have noticeable impacts on urban climate of large cities in China. Here, we use Beijing as an example to present observational evidence for such impacts over the period of 1990–2014. Our results show a significant cooling trend of up to 0.55 °C per decade, particularly at the nighttime during the CNY holiday relative to the background period. The average nighttime cooling effect during 2005–2014 reaches 0.94 °C relative to the 1990s, significant at the 99% confidence level. The further analysis supports that the cooling during the CNY holiday is attributable primarily to the population outflow of Beijing. These findings illustrate the importance of population movements in influencing urban climate despite certain limitations. As the world is becoming more mobile and increasingly urban, more efforts are called for to understand the role of human mobility at various spatial and temporal scales.

In this study, we investigate the dominant modes of surface air temperature variations of the cold season (from November through to the next March) and the warm season (from May to September) over Central Asia, and their associations with large-scale climate patterns for the period of 1979–2016. The first two modes of the cold season surface air temperature (CSAT) over Central Asia, obtained by empirical orthogonal function (EOF) analysis, feature the monopole structure and the north-south dipole pattern, respectively. For the warm season surface air temperature (WSAT), the leading two EOF modes are characterized by the homogenous structure and the northwest-southeast seesaw pattern, respectively. Further analysis indicates that the large-scale atmospheric circulation anomalies play key roles in the CSAT and WSAT variations over Central Asia. The CSAT variation over Central Asia is closely related to the Scandinavia pattern (SCAND) and the Arctic Oscillation (AO), while the WSAT variation is tightly tied to the East Atlantic/Western Russia pattern (EAWR) and the North Atlantic Oscillation (NAO). These large-scale climate patterns tend to cause the CSAT and WSAT anomalies over Central Asia via their effects on regional geopotential heights, warming advections, and other processes. Positive geopotential height anomalies and increased downward solar radiations generally favor positive SAT anomalies over Central Asia. Moreover, the warm advections are also conducive to the formation of positive SAT anomalies over Central Asia. Our findings are expected to facilitate the improvement of understanding and predicting the CSAT and WSAT variations over Central Asia.

The increase in the occurrence of hot extremes is known to have resulted in serious consequences for human society and ecosystems. However, our ability to seasonally predict hot extremes remains poor, largely due to our limited understanding of slowly evolving earth system components such as soil moisture, and their interactions with climate. In this study, we focus on North China, and investigate the relationship of the spring soil moisture condition to summer hot extremes using soil moisture data from the Global Land Data Assimilation System and observational temperature for the period 1981-2008. It is found that local soil moisture condition in spring is closely linked to summer hot days and heat waves over North China, accounting for 19%-34% of the total variances. Spring soil moisture anomalies can persist to the summer season, and subsequently alter latent and sensible heat fluxes, thus having significant effects on summer hot extremes. Our findings indicate that the spring soil moisture condition can be a useful predictor for summer hot days and heat waves over North China.

Introduction: Daily maximum (Tmax) and minimum (Tmin) temperatures and Diurnal temperature range (DTR) profoundly affect the ecological environment and socioeconomic systems. In this study, we project future changes in Tmax, Tmin and DTR for RCP4.5 and RCP8.5 using fine-resolution downscaled data from the 18global coupled models over the main regions of the Belt and Road Initiative (BRI). Outcomes: The Multi-Model Ensemble (MME) mean projections show that future warming is stronger in Tmax than in Tmin, leading to the increased DTR over central and southern Europe, many areas surrounding the Black Sea and the Caspian Sea, and southeastern China. By contrast, the DTR is projected to decline over the regions north of 55°N and other some areas due to the more rapid increase in Tmin than in Tmax. As a whole, the diurnal asymmetry of projected future temperature changes is found to mainly occur from November to March. Conclusions: Our findings contribute to the knowledgebase on climate change over the main BRI regions. Regarding uneven spatiotemporal changes in Tmax, Tmin and DTR, appropriate climate change adaptation strategies, and options should be adopted to reduce or avoid disadvantaged consequences to the natural system and human society over specific regions.

The gill and gastrointestinal tract are primary entry routes for pathogens. The symbiotic microbiota are essential to the health, nutrition and disease of fish. Though the intestinal microbiota of Nile tilapia (Oreochromis niloticus) has been extensively studied, information on the mucosa-associated microbiota of this species, especially the gill and gastrointestinal mucosa-associated microbiota, is lacking. This study aimed to characterize the gill and gastrointestinal mucosa- and digesta-associated microbiota, as well as the intestinal metabolite profiles in the New Genetically Improved Farmed Tilapia (NEW GIFT) strain of farmed adult Nile tilapia by high-throughput sequencing and gas chromatography/mass spectrometry metabolomics. The diversity, structure, composition, and predicted function of gastrointestinal microbiota were significantly different across gastrointestinal regions and sample types (Welch t-test; p < 0.05). By comparing the mucosa- and digesta-associated microbiota, linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that Pelomonas, Ralstoniapickettii, Comamonadaceae, and Staphylococcus were significantly enriched in the mucosa-associated microbiota, whereas many bacterial taxa were significantly enriched in the digesta-associated microbiota, including Chitinophagaceae, Cetobacterium, CandidatusCompetibacter, Methyloparacoccus, and chloroplast (LDA score > 3.5). Furthermore, Undibacterium, Escherichia-Shigella, Paeniclostridium, and Cetobacterium were dominant in the intestinal contents and mucosae, whereas Sphingomonasaquatilis and Roseomonasgilardii were commonly found in the gill and stomach mucosae. The Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) analysis revealed that the predictive function of digesta-associated microbiota significantly differed from that of mucosa-associated microbiota (R = 0.8152, p = 0.0001). In addition, our results showed a significant interdependence between specific intestinal microbes and metabolites. Notably, the relative abundance values of several potentially beneficial microbes, including Undibacterium, Crenothrix, and Cetobacterium, were positively correlated with most intestinal metabolites, whereas the relative abundance values of some potential opportunistic pathogens, including Acinetobacter, Mycobacterium, Escherichia-Shigella, Paeniclostridium, Aeromonas, and Clostridiumsensustricto 1, were negatively correlated with most intestinal metabolites. This study revealed the characteristics of gill and gastrointestinal mucosa-associated and digesta-associated microbiota of farmed Nile tilapia and identified a close correlation between intestinal microbes and metabolites. The results serve as a basis for the effective application of targeted probiotics or prebiotics in the diet to regulate the nutrition and health of farmed tilapia.

Abdominal aortic aneurysm (AAA) is a serious life-threatening vascular disease, and its ferroptosis/cuproptosis markers have not yet been characterized. This study was aiming to identify markers associated with ferroptosis/cuproptosis in AAA by bioinformatics analysis combined with machine learning models and to perform experimental validation. This study used three scRNA-seq datasets from different mouse models and a human PBMC bulk RNA-seq dataset. Candidate genes were identified by integrated analysis of scRNA-seq, cell communication analysis, monocle pseudo-time analysis, and hdWGCNA analysis. Four machine learning algorithms, LASSO, REF, RF and SVM, were used to construct a prediction model for the PBMC dataset, the above results were comprehensively analyzed, and the targets were confirmed by RT-qPCR. scRNA-seq analysis showed Mo/MF as the most sensitive cell type to AAA, and 34 cuproptosis associated ferroptosis genes were obtained. Pseudo-time series analysis, hdWGCNA and machine learning prediction model construction were performed on these genes. Subsequent comparison of the above results showed that only PIM1 appeared in all algorithms. RT-qPCR and western blot results were consistent with sequencing results, showing that PIM1 was significantly upregulated in AAA. In a conclusion, PIM1 as a novel biomarker associated with cuproptosis/ferroptosis in AAA was highlighted.

The ongoing climate change has posed severe threat to the natural system and human society. However, how soil temperature feedbacks matter for climate change projections is not yet well explored. In this study, we assess the role of soil temperature feedbacks for summer air temperature variability over East Asia under global warming. Regional climate model simulations with and without soil temperature‐atmosphere interactions were performed to isolate the role of soil temperature feedbacks under historical (1976–2005) and future (2071–2100) warming conditions. Results indicate that soil temperature feedbacks can largely enhance interannual variability of summer daily mean and minimum surface air temperatures over East Asia, with strongest impacts over Mongolia and many areas of northern Tibetan Plateau and northern China, in the historical period. The soil temperature feedback strength below 925‐hPa mainly depends on changes in longwave radiation, surface heat flux partitioning, and temperature advections, while it is largely determined by the diabatic heating processes in the lower troposphere. The spatial distribution of soil temperature feedbacks is projected to change notably over East Asia under future warming condition. In particular, the impacts of soil temperature feedbacks on summer temperature are shown to be stronger in the lower troposphere under future condition. These results imply the important role of soil temperature feedbacks on air temperature variability for regional climate modeling especially in the context of climate change. Plain Language Summary The global warming poses serious threat to natural ecosystem and human society. Soil temperature plays a significant role in land‐atmosphere interactions, however, its feedbacks on climate change have not yet well addressed. This study investigates the role of soil temperature feedbacks for summer air temperature variability over East Asia under the global warming by long‐term regional climate model simulations. Results show that soil temperature feedbacks can make a large contribution to enhancing interannual variability of summer daily mean and minimum surface air temperatures over East Asia in both historical and future warming period. Soil temperature feedbacks are projected to have substantially stronger impacts on summer air temperature at the land surface and the lower troposphere under future warming condition. The strong soil temperature feedbacks on summer air temperature variability mainly results from the modification of soil temperature to surface energy balance components, atmospheric temperature advection and diabatic heating. Our results highlight the substantial role of soil temperature feedbacks for summer air temperature variability in the lower atmosphere over East Asia under the global warming, and is helpful to improve the ability of climate change simulations and projections of models. Key Points Soil temperature feedbacks have the significant potential to enhance interannual variability of summer air temperature over East Asia The soil temperature feedback strength is mainly dependent on the diabatic heating processes in the lower troposphere Soil temperature feedbacks on summer temperature are projected to change notably in terms of spatial distribution in the future period

The plant-specific PLATZ transcription factors play crucial roles in plant growth, development, and responses to abiotic stresses. However, despite their functional significance, PLATZ genes remain poorly characterized in soybeans. In this study, we conducted a genome-wide analysis of the GmPLATZ gene family and investigated their expression profiles under salt stress. We identified a total of 29 GmPLATZ genes in the soybean genome and systematically analyzed their physicochemical properties, conserved domains, evolutionary relationships, cis-acting elements, and expression regulation patterns. Subcellular localization predictions indicated nuclear localization for most GmPLATZs, except for GmPLATZ5 and GmPLATZ14, which showed dual chloroplast–nuclear localization. A gene family expansion analysis indicated that 21 segmental duplication events were the primary driver of GmPLATZ diversification. A phylogenetic analysis classified the GmPLATZ genes into four subgroups, while gene structure and motif analyses revealed conserved zinc-binding domains and identified multiple cis-acting elements associated with light responsiveness, hormone signaling, and stress responses. Expression profiling showed tissue-specific expression patterns, with 13 GmPLATZ genes differentially expressed under salt stress, including root-preferential members (e.g., GmPLATZ1, GmPLATZ10) and leaf-preferential members (e.g., GmPLATZ8, GmPLATZ9). This study provides a theoretical basis for further investigation of GmPLATZ gene functions in soybean development and stress tolerance.

Single-cell RNA sequencing (scRNA-seq) is a high-tech method for characterizing the expression patterns of heterogeneous cells in the same tissue and has changed our evaluation of biological systems by increasing the number of individual cells analyzed. However, the full potential of scRNA-seq, particularly in plant science, has not yet been elucidated. To explore the utilization of scRNA-seq technology in plants, we firstly conducted a comprehensive review of significant scRNA-seq findings in the past few years. Secondly, we introduced the research and applications of scRNA-seq technology to plant tissues in recent years, primarily focusing on model plants, crops, and wood. We then offered five databases that could facilitate the identification of distinct expression marker genes for various cell types. Finally, we analyzed the potential problems, challenges, and directions for applying scRNA-seq in plants, with the aim of providing a theoretical foundation for the better use of this technique in future plant research.