Abstract:The accurate estimation of crop biomass during the growing season is very important for crop growth monitoring and yield estimation. The objective of this paper was to explore the potential of hyperspectral and light detection and ranging (LiDAR) data for better estimation of the biomass of maize. First, we investigated the relationship between field-observed biomass with each metric, including vegetation indices (VIs) derived from hyperspectral data and LiDAR-derived metrics. Second, the partial least squares (PLS) regression was used to estimate the biomass of maize using VIs (only) and LiDAR-derived metrics (only), respectively. Third, the fusion of hyperspectral and LiDAR data was evaluated in estimating the biomass of maize. Finally, the biomass estimates were validated by a leave-one-out cross-validation (LOOCV) method. Results indicated that all VIs showed weak correlation with field-observed biomass and the highest correlation occurred when using the red edge-modified simple ratio index (ReMSR). Among all LiDAR-derived metrics, the strongest relationship was observed between coefficient of variation (H CV ) of digital terrain model (DTM) normalized point elevations with field-observed biomass. The combination of VIs through PLS regression could not improve the biomass estimation accuracy of maize due to the high correlation between VIs. In contrast, the H CV combined with H mean performed better than one LiDAR-derived metric alone in biomass estimation (R 2 = 0.835, RMSE = 374.655 g/m 2 , RMSE CV = 393.573 g/m 2 ). Additionally, our findings indicated that the fusion of hyperspectral and LiDAR data can provide better biomass estimates of maize (R 2 = 0.883, RMSE = 321.092 g/m 2 , RMSE CV = 337.653 g/m 2 ) compared with LiDAR or hyperspectral data alone.

The tumor microenvironment (TME) in gastric cancer (GC) has been shown to be important for tumor control but the specific characteristics for GC are not fully appreciated. We generated an atlas of 166,533 cells from 10 GC patients with matched paratumor tissues and blood. Our results show tumor-associated stromal cells (TASCs) have upregulated activity of Wnt signaling and angiogenesis, and are negatively correlated with survival. Tumor-associated macrophages and LAMP3+ DCs are involved in mediating T cell activity and form intercellular interaction hubs with TASCs. Clonotype and trajectory analysis demonstrates that Tc17 (IL-17+CD8+ T cells) originate from tissue-resident memory T cells and can subsequently differentiate into exhausted T cells, suggesting an alternative pathway for T cell exhaustion. Our results indicate that IL17+ cells may promote tumor progression through IL17, IL22, and IL26 signaling, highlighting the possibility of targeting IL17+ cells and associated signaling pathways as a therapeutic strategy to treat GC.

BackgroundPrevious studies supported that dietary factor was associated with constipation, but the relationship between dietary energy intake and constipation has not been well-studied. Therefore, we aimed to evaluate the prevalence and correlation between energy intake and constipation among men and women.MethodsThese observational analyses included 12,587 adults (≥20 years) from the 2005–2010 cycles of the National Health and Nutrition Examination Surveys (NHANES). Constipation was defined as Bristol Stool Scale Type 1 (separate hard lumps, like nuts) or Type 2 (sausage-like but lumpy). Total energy intake was obtained from the two 24-h dietary recalls and averaged. We used the logistic regression model in Generalized Linear Model (GLM) function, controlling demographic, lifestyle, and dietary factors, to estimate the association between energy intake and constipation among men and women.ResultsThe overall weighted incidence of constipation in this research was 7.4%, the incidence in women and men was 10.4 and 4.3%, respectively. After multivariable adjustment, middle energy consumption correlated with decreased risk of constipation in men (OR:0.5, 95% CI:0.29–0.84), and lower-middle energy intake increased the constipation risk in women (OR: 1.56, 95% CI: 1.15–2.13). High energy consumption was not associated with increased or decreased constipation risk.ConclusionsTo our knowledge, this is the first research to investigate the association between energy intake and constipation; the study demonstrates that appropriate energy consumption can help reduce the risk of constipation in men, and relatively low energy intake is associated with increased constipation risk in women.

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