Xiaoming Zhang

Remote sensing has more advantages than the traditional methods of land surface water (LSW) mapping because it is a low-cost, reliable information source that is capable of making high-frequency and repeatable observations. The normalized difference water indexes (NDWIs), calculated from various band combinations (green, near-infrared (NIR), or shortwave-infrared (SWIR)), have been successfully applied to LSW mapping. In fact, new NDWIs will become available when Advanced Land Imager (ALI) data are used as the ALI sensor provides one green band (Band 4), two NIR bands (Bands 6 and 7), and three SWIR bands (Bands 8, 9, and 10). Thus, selecting the optimal band or combination of bands is critical when ALI data are employed to map LSW using NDWI. The purpose of this paper is to find the best performing NDWI model of the ALI data in LSW map. In this study, eleven NDWI models based on ALI, Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data were compared to assess the performance of ALI data in LSW mapping, at three different study sites in the Yangtze River Basin, China. The contrast method, Otsu method, and confusion matrix were calculated to evaluate the accuracies of the LSW maps. The accuracies of LSW maps derived from eleven NDWI models showed that five NDWI models of the ALI sensor have more than an overall accuracy of 91% with a Kappa coefficient of 0.78 of LSW maps at three test sites. In addition, the NDWI model, calculated from the green (Band 4: 0.525–0.605 μm) and SWIR (Band 9: 1.550–1.750 μm) bands of the ALI sensor, namely NDWIA4,9, was shown to have the highest LSW mapping accuracy, more than the other NDWI models. Therefore, the NDWIA4,9 is the best indicator for LSW mapping of the ALI sensor. It can be used for mapping LSW with high accuracy.

<h3>Background</h3> CD8⁺ T cells differentiate into exhausted status within tumors, including hepatocellular carcinoma (HCC), which constitutes a solid barrier to effective anti-tumor immunity. A detailed characterization of exhausted T cells and their prognostic value in HCC is lacking. <h3>Methods</h3> We collected fresh tumor tissues with adjacent non-tumor liver tissues and blood specimens of 56 HCC patients, as well as archived samples from two independent cohorts of HCC patients (<i>n</i> = 358 and <i>n</i> = 254), who underwent surgical resection. Flow cytometry and multiplex immunostaining were used to characterize CD8⁺ T cells. Patient prognosis was evaluated by Kaplan-Meier analysis and Cox regression analysis. <h3>Results</h3> CD8⁺ T cells were classified into three distinct subpopulations: PD1^Hi, PD1^Int and PD1⁻. PD1^Hi CD8⁺ T cells were significantly enriched in tumor compared to adjacent non-tumor liver tissues. PD1^Hi CD8⁺ T cells highly expressed exhaustion-related inhibitory receptors (TIM3, CTLA-4, etc.) and transcription factors (Eomes, BATF, etc.). In addition, PD1^Hi CD8⁺ T cells expressed low levels of cytotoxic molecules and displayed a compromised capacity to produce pro-inflammatory cytokines while the expression of anti-inflammatory IL-10 was up-regulated following mitotic stimulation. Furthermore, PD1^Hi CD8⁺ T cells shared features with tissue resident memory T cells and were also characterized in an aberrantly activated status with an apoptosis-prone potential. In two independent cohorts of HCC patients (<i>n</i> = 358 and <i>n</i> = 254), we demonstrated that PD1^Hi or TIM3⁺PD1^Hi CD8⁺ T cells were significantly correlated with poor prognosis, and the latter was positioned in close proximity to PD-L1⁺ tumor associated macrophages. <h3>Conclusion</h3> The current study unveils the unique features of PD1^Hi CD8⁺ exhausted T cells in HCC, and also suggests that exhausted T cells could act as a biomarker to select the most care-demanding patients for tailored therapies.

The tumor ecosystem of papillary thyroid carcinoma (PTC) is poorly characterized. Using single-cell RNA sequencing, we profile transcriptomes of 158,577 cells from 11 patients' paratumors, localized/advanced tumors, initially-treated/recurrent lymph nodes and radioactive iodine (RAI)-refractory distant metastases, covering comprehensive clinical courses of PTC. Our data identifies a "cancer-primed" premalignant thyrocyte population with normal morphology but altered transcriptomes. Along the developmental trajectory, we also discover three phenotypes of malignant thyrocytes (follicular-like, partial-epithelial-mesenchymal-transition-like, dedifferentiation-like), whose composition shapes bulk molecular subtypes, tumor characteristics and RAI responses. Furthermore, we uncover a distinct BRAF-like-B subtype with predominant dedifferentiation-like thyrocytes, enriched cancer-associated fibroblasts, worse prognosis and promising prospect of immunotherapy. Moreover, potential vascular-immune crosstalk in PTC provides theoretical basis for combined anti-angiogenic and immunotherapy. Together, our findings provide insight into the PTC ecosystem that suggests potential prognostic and therapeutic implications.