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In order to solve the problem of concrete shaft support in deep topsoil layer, ANSYS finite element software was used to compare and analyze the deformation and stress of hybrid fiber high-strength concrete shaft and ordinary high-strength concrete shaft when the thickness of topsoil layer varied from 200 m to 600 m. The calculation results show that: the strain of mixed fiber concrete shaft is greater than that of ordinary concrete shaft under the same stress, and the fiber can improve the brittleness of shaft; the maximum circumferential stress on shaft increases with the increase of topsoil layer thickness, and increases gradually from outside to inside along the shaft radial direction, and the circumferential strain is always compressive strain and the inner surface is greater than the outer surface. As the burial depth increases, the deformation of shaft changes from mainly axial deformation to mainly radial deformation; finally, the regression equation of the relationship between stress-strain and thickness of topsoil layer is given, which can guide the engineering practice.

Acute pancreatitis (AP) is an inflammatory disease with high morbidity and mortality. The regulation mechanism of miRNA is involved in the production and development of various diseases, but the regulation mechanism of miRNA in AP is still not fully elucidated. The expression of miR-339-3p was detected using quantitative real-time PCR. The levels of TNF-α, IL-1β, and IL-6 were detected using enzyme-linked immunosorbent assay. Cell apoptosis was measured using flow cytometry. The protein expressions of TNF receptor-associated factor 3 (TRAF3), Bcl-2, C-caspase 3, Bax, p-p38, and p38 were measured using western blot. Luciferase reporter assay and RNA immunoprecipitation assay were applied to ensure that miR-399-3p targeted TRAF3. Caerulein promoted the expression of TNF-α, IL-1β, and IL-6, enhanced the expression of C-caspase 3 and Bax while inhibited Bcl-2 protein expression. Meanwhile, caerulein also reduced the expression of miR-339-3p and induced the expression of TRAF3 in rat pancreatic acinar cells. miR-399-3p transfection inhibited the levels of TNF-α, IL-1β, and IL-6 and C-caspase 3 and Bax protein expression as well as suppressed cell apoptosis, while increased Bcl-2 protein expression in caerulein-induced AP. TRAF3 has been verified as a target of miR-339-3p. Interestingly, the reduction of miR-399-3p inhibited the p38 pathway, which was impaired by the upregulation of TRAF3. In addition, the suppression effects of miR-339-3p on cell inflammation and apoptosis in caerulein-induced AP were reversed by enhancing TRAF3 expression. In this study, in vitro model of AP was characterized by strong inflammation and cell apoptosis. We have first demonstrated the regulatory network of miR-339-3p and TRAF3. Overexpression of miR-339-3p inhibited cell inflammation and cell apoptosis in caerulein-induced AP through modulating TRAF3 expression via the p38 pathway, providing a new therapeutic target in the treatment of AP.

Recent advances in the research of late transition metal (Ni) salicylaldimine bimetallic catalysts in ethylene polymerization and copolymerization of ethylene with comonomers have been introduced. The effect of positioning two polymerization-active metal centers in close proximity on catalytic activity, molecular weight, molecular weight distribution, and levels of branching are thoroughly documented. The synergistic effect of these binuclear catalysts compared to their mononuclear analogs is the subject of this review.

In the Cyber-Physical system(CPS), equipment generates a large amount of communication information and equipment data during the operation of the system, which are at risk of being modified and stolen. Block chain technology with distributed storage as the core is conducive to ensuring the data security of CPS system, but the existing consensus algorithms have the problem that data recording rights are concentrated in a few nodes and are easy to be hijacked by malicious nodes. By introducing node validity, the dynamic change of node behavior can be reflected. The experimental results show that the consensus mechanism based on the validity of nodes makes the distribution of nodes with access to data records more decentralized, better reflects the de-centralization characteristics of the system, and improves the security of data.

Carcinogen exposure has been associated with enhanced cancer immunogenicity that is often attributed to neoantigen generation. However, the broader, neoantigen-independent impact of carcinogens on immune responses to cancer cells remains underexplored. In this issue of the JCI, Huang et al. uncover a mechanism wherein carcinogen-treated cancer cells exhibit an inability to establish an immunosuppressive tumor microenvironment (TME) due to reduced M-CSF expression. Intriguingly, the so-called carcinogen-induced tumor-associated macrophages (TAMs) within this TME exhibited anti-tumor properties instead of the conventional immunosuppressive phenotype. This phenomenon extended to human lung cancers, as evidenced by TAM reprogramming in smokers versus nonsmokers. This study substantially advances our understanding of carcinogen-mediated effects on cancer immunogenicity, potentially redirecting approaches to cancer immunotherapy., Carcinogen treatment augments cancer immunogenicity beyond neoantigens Carcinogens are substances with the ability to cause cancer mainly by generating mutations in cellular DNA. Carcinogens responsible for a substantial number of [...]

Background: Peri‐implantitis and periodontitis have similar immunological bioprocesses and inflammatory phenotypes. In the inflammatory process, the adaptive immune cells can drive the development of disease. This research investigated the differences and diagnostic significance of peri‐implantitis and periodontitis in adaptive immune responses. Methods: We acquired four GEO datasets of gene expressions in surrounding tissues in healthy person, healthy implant, periodontitis, and peri‐implantitis patients. The structural characteristics and enrichment analyses of differential expression genes were examined. The adaptive immune landscapes in peri‐implantitis and periodontitis were then evaluated using single sample gene set enrichment analysis. The STRING database and Cytoscape were used to identify adaptive hub genes, and the ROC curve was used to verify them. Finally, qRT‐PCR method was used to verify the expression level of Hub gene in activated T cells on the titanium‐containing or titanium‐free culture plates. Results: At the transcriptome level, the data of healthy implant, peri‐implantitis and periodontitis were highly dissimilar. The peri‐implantitis and periodontitis both exhibited adaptive immune response. Except for the activated CD4+T cells, there was no significant difference in other adaptive immune cells between peri‐implantitis and periodontitis. In addition, correlation analysis showed that CD53, CYBB, and PLEK were significantly positively linked with activated CD4+T cells in the immune microenvironment of peri‐implantitis, making them effective biomarkers to differentiate it from periodontitis. Conclusions: Peri‐implantitis has a uniquely immunogenomic landscape that differs from periodontitis. This study provides new insights and ideas into the activated CD4+T cells and hub genes that underpin the immunological bioprocess of peri‐implantitis. [ABSTRACT FROM AUTHOR]

Land surface models (LSMs) should have reliable forcing, validation, and surface attribute data as the foundation for effective model development and improvement. Eddy covariance flux tower data are considered the benchmarking data for LSMs. However, currently available flux tower datasets often require multiple aspects of processing to ensure data quality before application to LSMs. More importantly, these datasets lack site-observed attribute data, limiting their use as benchmarking data. Here, we conducted a comprehensive quality screening of the existing reprocessed flux tower dataset, including the proportion of gap-filled data, external disturbances, and energy balance closure (EBC), leading to 90 high-quality sites. For these sites, we collected vegetation, soil, topography information, and wind speed measurement height from literature, regional networks, and Biological, Ancillary, Disturbance, and Metadata (BADM) files. Then we obtained the final flux tower attribute dataset by global data product complement and plant functional types (PFTs) classification. This dataset is provided in NetCDF format complete with necessary descriptions and reference sources. Model simulations revealed substantial disparities in output between the attribute data observed at the site and the defaults of the model, underscoring the critical role of site-observed attribute data and increasing the emphasis on flux tower attribute data in the LSM community. The dataset addresses the lack of site attribute data to some extent, reduces uncertainty in LSMs data source, and aids in diagnosing parameter as well as process deficiencies. The dataset is available at https://doi.org/10.5281/zenodo.10939725 (Shi et al., 2024). [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is the most prominent grain‐producing region in China. However, it is currently facing significant impacts from climate change. Since the climate‐related impacts on crop yield in this region are a major concern for society in the future, quantifying climate change impacts on crop yields in NEC is essential to ensure future food security. This study aimed to quantify the effects of future climate change on crop yields in NEC and explore adaptation strategies using the Crop Growth Model (PCSE) driven by downscaled CMIP6 climate projections under four Shared Socioeconomic Pathways (SSPs) scenarios during 2015–2100. Results showed that there could be average reductions in crop yields of 21.4% for maize and 4.2% for soybean by the year 2100 under SSP585 compared to the 2015 baseline. The increasing temperature was the dominant factor in reducing yields, although elevated CO2 and precipitation offered partial compensation. The optimized planting date brought noticeable benefits for rice and soybean but had limited effects on maize due to heat stress. Relocating rice expansion eastward and implementing earlier planting increased yields by up to 50% but adversely decreased soybean and maize due to competition. This study enriches our comprehension of climate change impacts on NEC agriculture, while also quantifying potential benefits and constraints of evaluated adaptations. The proposed adaptations may help mitigate projected yield declines in other key agricultural regions across the globe. Adjusting crop management practices to capitalize on changing climate factors shows promise as a strategy for sustaining production globally. Plain Language Summary: Northeast China (NEC) is essential for achieving food accessibility and food security in China, but its agricultural production is seriously threatened by climate change. This study investigated how climate change could impact maize, rice, and soybean crop yields in this region from 2015 to 2100, using the PCSE crop model and forcing from the international Coupled Model Intercomparison Project 6 (CMIP6) climate projections. Simulation results suggested rising temperatures would negatively affect crop yields, especially for maize. Increased carbon dioxide and rainfall partially offset these losses. By 2100, average declines were projected for maize (−21%) and soybeans (−4%), respectively. Altering planting dates to match crop needs was an effective adaptation to boost yields, with rice benefiting the most. Relocating rice production eastward and expanding its area substantially increased simulated rice yields (+62%) but decreased other crops due to competition (−32% maize, −28% soybeans). Even with adaptations, some areas still showed yield declines, indicating extra measures may be needed to maintain production. Overall, this study suggests significant risks to crop yields from climate change in Northeast China, with adaptations like optimized planting and strategic crop relocation able to mitigate some but not all of the projected impacts. Key Points: Rising temperatures negatively impacted simulated future crop yields, especially for maizeAdjusting planting dates boosted yields for rice and soybeans but had limited benefits for maizeRelocating and expanding the rice area increased yields substantially [ABSTRACT FROM AUTHOR]

This study develops an unstructured mesh generation tool for land surface modeling using a multi‐scale hexagon discrete mesh. The tool can automatically determine the required mesh resolution for different regions based on multi‐objective criteria such as elevation, slope, land cover, and land use. The refined unstructured meshes demonstrate significant enhancement in the representation of spatial heterogeneity. The tool is coupled with the Common Land Model (CoLM) to enable land surface simulations using unstructured meshes. Evaluations focused on runoff, river discharge, and inundation indicate improved model performance compared to traditional structured mesh‐based CoLM simulations under the same computational cost constraints. This tool provides new capabilities for more efficiently capturing localized land surface processes and extreme events. Plain Language Summary: The traditional square mesh cells used in land surface models (LSMs) have limitations in capturing the hydrological processes in regions with spatial solid heterogeneity, for example, mountains and forest‐grass transition zones. This study develops a new tool to generate unstructured mesh with flexible cell shapes and sizes. The tool can automatically adjust the mesh resolution based on the various land surface features. Thus, it can represent better spatial differences in elevation, vegetation, soil, etc. For example, it can use finer meshes for mountains and coarser meshes for desert areas. The new unstructured meshes are coupled with an existing LSM called Common Land Model. Model testing shows improved runoff, river discharge, and flooding simulation compared to traditional square mesh models under the same computation cost. Overall, the new unstructured mesh modeling approach enables more efficient and accurate simulation of localized land processes and extreme events, for example, droughts and floods. It has significance for disaster prevention and environmental studies. Key Points: An unstructured mesh generation tool for land surface models can automatically refine resolution based on multi‐objective landscape criteriaCoupling refined unstructured meshes with the Common Land Model (CoLM) model improves local hydrological simulation compared to traditional mesh‐based CoLMThe tool enables more efficient and accurate modeling of localized land surface processes and extreme events such as droughts and floods [ABSTRACT FROM AUTHOR]