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Background: Traditional Chinese Medicine (TCM) has been used in the treatment of anthracycline (ANTs)-induced cardiotoxicity. This meta-analysis aims to evaluate systematically the efficacy and safety of TCM combined with dexrazoxane (DRZ) on cardiotoxicity caused by ANTs. Materials and Methods: Retrieval of the China National Knowledge Infrastructure (CNKI), WAN FANG DATA, Chinese Biomedical Database (CBM), Cochrane Library, and PubMed was conducted through various methods. The meta-analysis was registered on PROSPERO (Registration ID: CRD42023435324). A randomized controlled trial (RCT) of TCM in combination with DRZ to avert cardiotoxicity caused by ANTs was compiled. The efficacy and safety of TCM Combined with DRZ, the cardiotoxicity induced by ANTs was synthesized and discussed, along with the outcomes of cardiac troponin T (cTnT), cardiac troponin I (cTnI), brain natriuretic peptide (BNP), creatine kinase isoenzymes (CK-MB), creatine kinase (CK), left ventricular ejection fraction (LVEF), electrocardiogram (ECG) abnormalities, and the incidence of adverse reactions. RevMan 5.3 was used for meta-analysis. Results: A total of 10 RCTs with 746 patients were included. The pooled results showed that TCM combined with DRZ treatment decreased significantly the incidence of ECG abnormalities (RR = 0.47, 95% CI [0.32,0.70], p = 0.0001), the level of cTnT (MD = −7.16, 95% CI [−8.31, −6.02], p< 0.001), CK (MD = −14.94, 95% CI [−22.91, −6.97], p< 0.001), cTnI (MD = −0.10, 95% CI [−0.14, −0.06], p< 0.001), BNP (MD = −33.66, 95% CI [−36.95, −30.37], p< 0.001), CK-MB (MD = −5.93, 95% CI [−8.16, −3.70], p< 0.001). However, there was no significant change in LVEF in the experimental group compared with the control group (MD = 4.81, 95% CI [−02.99, 12.21], p = 0.23). Moreover, adverse events have no significant difference between the two groups as well (RR = 0.60, 95% CI [0.31, 1.15], p = 0.13). Conclusion: This meta-analysis revealed TCM combined with DRZ appears to be able to improve the efficacy of cardiotoxicity caused by ANTs, but the included studies were of poor quality, and high-quality RCTs would be preferred for future studies. [ABSTRACT FROM AUTHOR]

The Jiaolai Basin, situated in the northern Sulu orogenic belt along East Aisa continental margin, preserves evidence of the extensional events in East Asia and the post‐orogenic evolution of the Sulu orogenic belt during the Cretaceous period. In this study, multiple provenance analyses were employed to reconstruct the source‐to‐sink system of the Laiyang Group within the Jiaolai Basin. These studies reveal a history of northward expansion dictated by two significant rift events. During the early Early Cretaceous period (ca. 135–121 Ma), the Zhucheng and Gaomi sags in southern region developed initially. Subsequently, in the late Early Cretaceous period (ca. 120–113 Ma), the Laiyang sag in northern region emerged. Furthermore, these sags were fed by independent source‐to‐sink systems in their early stages but eventually shared a similar source‐to‐sink system towards the end of the Laiyang Group deposition (ca. 113 Ma). The provenance analysis results indicate that ca. 121 Ma, ultrahigh‐pressure rocks in the northern segment of the Sulu orogenic belt experienced rapid exhumation, while those in the southern segment might have remained concealed until ca. 113 Ma. The two rift events in East Asia, coupled with the alteration in the direction and magnitude of extension documented in the Jiaolai Basin, suggests that trench retreat and the change in subduction direction from E–W to NW–SE of the Izanagi plate played a principal role in driving the extensional events in East Asia during the Early Cretaceous. Our findings imply that the change in Izanagi subduction direction may have occurred ca. 121 Ma.Model depicting the northward expansion evolution of the Jiaolai Basin in East Asia during the Early Cretaceous period. The left column illustrates the new stratigraphic framework as presented in this study. The grey arrows in the diagram indicate the primary provenance directions, with the size of the arrows representing the relative contribution of each source. [ABSTRACT FROM AUTHOR]

Supply chain risk management (SCRM) literature is heterogeneous. While much attention has been given to the economic and environmental dimensions, the social dimension has so far received less focus. Thus, this study analyzes the social risks involved in the agri-food supply chains (AFSCs) of Argentina and China by employing an integrated approach. Semi-structured interviews were used to collect data, followed by using a combination of three complementary data analysis methods: thematic analysis to identify social risks, total interpretive structural modeling (TISM) to build interrelationships among the identified social risks, and fuzzy MICMAC (cross-impact matrix multiplication applied to classification analysis) to cluster social risks into four categories. Next, we conducted a comparative analysis between the two countries. Theoretical contributions are mainly threefold. First, we identified various social risks involved in the AFSCs of Argentina and China, including those just touched on by scholars, such as cultural issues, government’s weak monitoring system, the power differential between managers and subordinates, inappropriate disposal of agrichemical containers, and the lack of basic literacy skills. Second, we believe that our study is the first to establish connections among the identified AFSC social risks, which represents the originality of this work. Third, we discover that cultural issues is the key risk that has the highest capability to elicit other social risks involved in the AFSCs. Our work extends scholarship’s knowledge to understand AFSC social risks from the cultural perspective. This study also generates contributions to policymakers, migrant associations, and the government tax departments of Argentina and China. [ABSTRACT FROM AUTHOR]

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]

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]

• The CCGlu-enhancing HS-SPME Arrow combined with GC-Orbitrap-MS was developed to determine 34 SACs in tobacco. • This method possessed satisfactory sensitivity with the LOQ values ranging from 0.07 to 5.97 ng/g and 11 analytes identified for the first time in this study. • PCA results of 45 practical samples showed SACs as potential indicators of three aroma types and geographical origins of Virginia tobacco in China. The identification and measurement of sulfur aroma compounds (SACs) to precisely describe tobacco quality and style have remained as significant topics in tobacco research for many years. However, the ultra-trace quantification of SACs in complex tobacco matrices poses a considerable challenge in analytical area. In this study, an accurate and sensitive analysis of SACs in tobacco through a natural deep eutectic solvent (NADES) enhancing headspace-solid-phase microextraction (HS-SPME) Arrow combined with GC-Orbitrap was developed. The NADES system composed of choline chloride and D-glucose (CCGlu) in the pretreatment possessed excellent enhancement of HS-SPME Arrow extraction efficiency for natural tobacco targets. To improve selectivity, GC-Orbitrap was applied that prominently reduced chemical interferences from the tobacco matrix, improving confidence in the determination and identification of SACs in tobacco. During method validation, the limit of quantification (LOQ) ranged from 0.07 to 5.97 ng/g, apparently lower than those reported previously. And acceptable accuracies were attained with relative recoveries ranging from 85.4 % to 111 %. Finally, the developed method was applied to 45 Virginia tobacco samples, and 23 SACs were identified, among which 11 analytes were detected for the first time in this study. The results were preliminarily analyzed using principal component analysis, demonstrating that SACs could be employed as useful variables to characterize the aroma types and geographical origins of tobacco in China, which might be suitable for monitoring tobacco quality. [ABSTRACT FROM AUTHOR]