ABSTRACT
The Qinghai-Tibet Plateau (QTP) holds significance for investigating Earth's surface processes. However, due to rugged terrain, forest canopy, and snow accumulation, open-access Digital Elevation Models (DEMs) exhibit considerable noise, resulting in low accuracy and pronounced data inconsistency. Furthermore, the glacier regions within the QTP undergo substantial changes, necessitating updates. This study employs a fusion of open-access DEMs and high-accuracy photons from the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2). Additionally, snow cover and canopy heights are considered, and an ensemble learning fusion model is presented to harness the complementary information in the multi-sensor elevation observations. This innovative approach results in the creation of HQTP30, the most accurate representation of the 2021 QTP terrain. Comparative analysis with high-resolution imagery, UAV-derived DEMs, control points, and ICESat-2 highlights the advantages of HQTP30. Notably, in non-glacier regions, HQTP30 achieved a Mean Absolute Error (MAE) of 0.71 m, while in glacier regions, it reduced the MAE by 4.35 m compared to the state-of-the-art Copernicus DEM (COPDEM), demonstrating its versatile applicability.
ABSTRACT
Zinc finger MIZ-type containing 1 (ZMIZ1) is a transcriptional coactivator related to the protein inhibitors of activated STATs (PIAS) family. Mounting evidence suggests that ZMIZ1 plays a crucial role in the occurrence and development of cancers. The function of ZMIZ1 in tongue squamous cell carcinoma (TSCC) and the mechanisms underpinning its role in this disease have not been fully clarified. We performed qualitative ZMIZ1 protein expression analyses using immunohistochemistry in 20 patient-derived, paraffin-embedded TSCC tissue sections. We used RNAi to knock down ZMIZ1 expression in the CAL-27 TSCC cell line and quantified the impact of ZMIZ1 knock down on proliferation, migration and apoptosis via CCK-8, scratch assay and flow cytometry, respectively. We used qRT-PCR and western blotting to investigate the role of ZMIZ1 in this cell line. Finally, we established a model of lung metastasis in nude mice to replicate the in vitro results. ZMIZ1 protein was significantly more abundant in TSCC case tissue samples. ZMIZ1 knockdown reduced the invasion and metastases of TSCC tumor cells and promoted apoptosis. ZMIZ1 knockdown was associated with the down-regulation of Notch signaling pathway related factors Jagged1 and Notch1, and invasion and metastasis related factors MKP-1, SSBP2 and MMP7 in vitro and in vivo, at the mRNA level. In vitro and in vivo data suggest that knock down of ZMIZ1 may inhibit TSCC invasion and metastasis by modulating Notch signaling. ZMIZ1 inhibition may therefore represent a new therapeutic target for TSCC.
Subject(s)
Apoptosis , Carcinoma, Squamous Cell , Cell Proliferation , Receptor, Notch1 , Signal Transduction , Tongue Neoplasms , Animals , Female , Humans , Male , Mice , Middle Aged , Carcinoma, Squamous Cell/metabolism , Carcinoma, Squamous Cell/pathology , Carcinoma, Squamous Cell/genetics , Cell Line, Tumor , Cell Movement , Gene Expression Regulation, Neoplastic , Jagged-1 Protein/metabolism , Jagged-1 Protein/genetics , Lung Neoplasms/metabolism , Lung Neoplasms/genetics , Lung Neoplasms/pathology , Lung Neoplasms/secondary , Mice, Nude , Receptor, Notch1/metabolism , Receptor, Notch1/genetics , Tongue Neoplasms/metabolism , Tongue Neoplasms/pathology , Tongue Neoplasms/genetics , Transcription Factors/metabolism , Transcription Factors/genetics , Xenograft Model Antitumor AssaysABSTRACT
Solar energy is considered one of the key solutions to the growing demand for energy and to reducing greenhouse gas emissions. Thanks to the relatively low cost of land use for solar energy and high power generation potential, a large number of photovoltaic (PV) power stations have been established in desert areas around the world. Despite the contribution to easing the energy crisis and combating climate change, large-scale construction and operation of PV power stations can change the land cover and affect the environment. However, few studies have focused on these special land cover changes, especially vegetation cover changes, which hinders understanding the effects of the extensive development of solar energy. Here, we used Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA) based on Landsat images to monitor changes in vegetation abundance before and after the PV power stations deployment. To reduce the interference of PV shading on vegetation abundance estimation, we improved the vegetation (VG) fraction from SMA and developed the Photovoltaics-Adjusted Vegetation (PAVG) fraction for vegetation abundance measurements in PV power stations. Results show that PV power stations in China's 12 biggest deserts expanded from 0 to 102.56 km2 from 2011 to 2018, mainly distributed in the central part of north China. The desert vegetation in the deployment area of PV power stations presented a significant greening trend. Compared to 2010, the greening area reached 30.80 km2, accounting for 30% of the total area of PV power stations. Overall, the large-scale deployment of PV power stations has promoted desert greening, primarily due to government-led Photovoltaic Desert Control Projects and favorable climatic change. This study shows the great benefits of PV power stations in combating desertification and improving people's welfare, which bring sustainable economic, ecological and social prosperity in sandy ecosystems.
