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Partitioning of evapotranspiration (ET) into soil evaporation (E) and plant transpiration (T) poses a significant challenge. This study proposed a novel approach that combines eddy covariance, micro-lysimeter, and high-resolution unmanned aerial vehicle (UAV) images within the flux footprint to optimize the canopy and soil resistances of the Shuttleworth-Wallace model (S-W) using a multi-objective optimization scheme. A two-year experiment was conducted at the Yucheng and Luancheng sites to investigate the effectiveness of the proposed method for the summer maize-wheat winter system in the North China Plain. Our results showed that the S-W model with multi-objective optimization by using high-resolution UAV images within the flux footprint significantly improved the estimation accuracy of ET components compared with the traditional one- and two-objective optimization schemes. The estimation of ET, T, and E of our method had an average root mean square error of 0.67 mm day−1, 0.66 mm day−1, and 0.28 mm day−1, respectively. The optimized S-W model using high-resolution UAV data within the flux footprint produced better ET partitioning than that optimized using Moderate Resolution Imaging Spectroradiometer (MODIS) data. We then applied the proposed method to estimate ET and ET components in the North China Plain. This study highlighted the importance of utilizing multi-source data (especially high-resolution UAV images) and multi-objective optimization for accurate ET partitioning.

Background: Oral cancer is one of the most prevalent malignant neoplasms globally, with its microenvironment being extremely complicated and heterogeneous with regard to distribution of different types of cells, which creates a barrier against treatment. We integrated single-cell RNA sequencing, pseudotime analysis, and intercellular communication to identify subtypes, state transitions, and interactions in the development of oral cancer and their roles in tumor progression and immune response. Methods: Principal component analysis (PCA) followed by dimensionality reduction techniques (UMAP and t-SNE) revealed multiple populations in the single-cell data from oral cancer. Analysis of gene expression patterns associated individual genes with distinct principal components that described features of cell subtypes or states in the oral cancer microenvironment. We also conducted gene set enrichment analysis (GSEA) and cell–cell communication network analysis to investigate the important signaling pathways as well as potential cell–cell communications. Results: Gene expression patterns linked to oral cancer cell subtypes and states in this study included cell membrane, signal transduction and immune response in different biological processes. Pseudotime analysis showed differentiation trajectories and expression of essential differentiation genes were also altered. Cell–cell communication network analysis revealed that myeloid cells interacted heavily with myeloid cells and they also had strong interactions with endothelial cells. Analysis of the MIF signaling pathway network showed participation of various cell types in MIF signaling, suggesting its potential significance in the oral cancer microenvironment. Conclusion: The intercellular communication complexity of TME in oral cancer is reported here with the first-ever single cell analysis and data providing new perspective regarding the heterogeneity of oral cancer. [ABSTRACT FROM AUTHOR]

Despite the high sepsis-associated mortality, effective and specific treatments remain limited. Using conventional antibiotics as TIENAM (imipenem and cilastatin sodium for injection, TIE) is challenging due to increasing bacterial resistance, diminishing their efficacy and leading to adverse effects. We previously found that aloe-emodin (AE) exerts therapeutic effects on sepsis by reducing systemic inflammation and regulating the gut microbiota. Here, we investigated whether administering AE and TIE post-sepsis onset, using a cecal ligation and puncture (CLP)-induced sepsis model, extends survival and improves physiological functions. Survival rates, inflammatory cytokines, tissue damage, immune cell populations, ascitic fluid microbiota, and key signaling pathways were assessed. Combining AE and TIE significantly enhanced survival rates, and reduced inflammation and bacterial load in septic mice, indicating potent antimicrobial properties. Moreover, substantial improvements in survival rates of AE + TIE-treated mice (10% to 60%) within 168 h were observed relative to the CLP group. This combination therapy also effectively modulated inflammatory marker (interleukin [IL]-6, IL-1β, and tumor necrosis factor [TNF]-α) levels and immune cell counts by decreasing those of B, NK, and TNFR2+ Treg cells, while increasing that of CD8+ T cells; alleviated tissue damage; reduced bacterial load in the peritoneal cavity; and suppressed the NF-κB signaling pathway. We also observed a significantly altered peritoneal cavity microbiota composition post-treatment, characterized by reduced pathogenic bacteria (Bacteroides) abundance. Our findings underscore the potential of AE + TIE in treating sepsis, and encourage further research and possible clinical implementations to surmount the limitations of TIE and amplify the therapeutic potential of AE. [ABSTRACT FROM AUTHOR]

Human-related factors are a crucial inducement of traffic accidents. Understanding the influence of freeway environments on the driving behavior and workload experienced by drivers has been demonstrated to be of primary importance for improving traffic safety. To study the effect of alignment, traffic flow, and sign information on drivers' mental workload and behavior, 16 scenarios were constructed using the orthogonal design method, and simulated driving experiments were carried out with 45 participants. During driving, indicators such as the mean and standard deviation of vehicle speed and lane departure were collected, and the NASA-TLX questionnaire was adopted to measure workload. Analysis of variance results indicated that the radius of the horizontal curve, gradient, flow, and sign information level have a significant influence on drivers' workload and speed keeping ability. In addition, the horizontal curve radius has a significant effect on lane keeping ability. The importance of safety influencing factors on driving workload and performance was quantitatively ranked by integrating the trend of Deng's correlation degree, comprehensive correlation degree, and similar correlation degree, whose weight was calculated using the entropy method. Traffic sign information was found to have the greatest impact on workload. In terms of driving performance, traffic volume has the greatest influence on the mean and standard deviation of vehicle speed, followed by the amount of sign information. Lane departure is most affected by the radius of the horizontal curve. These findings provide guidance for freeway traffic safety regulation, including workload control and road facility optimization., Author(s): Lian Xie [1,2]; Chaozhong Wu [1,3]; Min Duan [4]; Nengchao Lyu (corresponding author) [1,3] 1. Introduction Statistics of road traffic accidents show that 80% of accidents and 65% of [...]