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This study retains the basic structure of DRASTIC model and obtains more specific evaluation results by adding land-use type and groundwater resource yield parameters, modifying the rating scale and weight of nine parameters. Comparison of the modified DRASTIC-LY vulnerability map with the map of the original DRASTIC-LY method revealed differences in 40.49% of the study area. The risk map shows that the very high vulnerability area decreased from 2.79 to 1.67%, while the high vulnerability area increased from 18.70 to 28.86%. Areas with low vulnerability increased by 10.15%, while areas with medium vulnerability decreased by 15.01%. The areas with very high groundwater vulnerability are mainly distributed in the Hanbin area on the north bank of the Han River, the areas with high are mainly concentrated on both sides of the Fujia River, while the areas with low are distributed in most areas in the west of the basin. The Pearson's correlation factor was 0.0583 in the original DRASTIC model, 0.1113 in the DRASTIC-LY method and 0.8291 in the modified DRASTIC-LY model, which indicated that the revised DRASTIC-LY model was more appropriate than the original model. The results can help the government with the protection of water resources. HIGHLIGHTS Improve the DRASTIC model.; Determine the weight, grade and category of each parameter.; Based on the sensitivity analysis and model validation results, construct the best model suitable for groundwater vulnerability assessment.; The results of this study will help government managers improve the composition of water use and strengthen the protection of vulnerable aquifers.;

In recent years, rapid urbanization in the Southern Jiangsu urban area has significantly altered land use patterns, impacting local ecosystem service value (ESV). This study examines land use changes (LUCs) from 2000 to 2020 and assesses ESV changes with the equivalent factor method. The PLUS model is also used to project future LUCs in line with the "Land and Space Planning of Jiangsu Province (2021–2035)". The simulation considers scenarios for natural development (NDS), ecological protection (EPS), farmland protection (FPS), and comprehensive development (CDS) for the year 2035. The research findings show that over the past two decades, urbanized areas have persistently grown, whereas there has been a steady decline in the extents of farmland, forested areas, and grasslands. The total ESV has shown a decreasing trend, with the spatial distribution of ESV exhibiting higher values in the eastern regions and lower values in the west. The relationship between land use and ESV is negative, as evidenced by both the comprehensive land use (LA) and the Moran's I index. Scenario predictions reveal that farmland, forest land, and grassland show a decreasing trend under the NDS, while it is the opposite under the EPS. The FPS is predominant in farmland area, and all land types in the CDS comply with national land planning requirements. Overall, the research findings reveal and predict the influence of LUCs on ESV in the study area under four scenarios, which is beneficial optimizing regional resource planning schemes and formulating ecological compensation policies. [ABSTRACT FROM AUTHOR]

The Rapid expansion of the Lanzhou–Xining (Lanxi) urban cluster in China during recent decades poses a threat to the fragile arid environment. Quantitatively assessing the impact of urban expansion on vegetation in the Lanxi urban cluster has profound implications for future sustainable urban planning. This study investigated the urban expansion dynamics of the Lanxi urban cluster and its impacts on regional vegetation between 2001 and 2021 based on time series land cover data and auxiliary remote sensing data, such as digital elevation model (DEM) data, nighttime light data, and administrative boundary data. Thereinto, urban expansion dynamics were evaluated using the annual China Land Cover Dataset (CLCD, 2001–2021). Urban expansion impacts on regional vegetation were assessed via the Vegetation Disturbance Index (VDI), an index capable of quantitatively assessing the positive and negative impacts of urban expansion at the pixel level, which can be obtained by overlaying the Enhanced Vegetation Index (EVI) and rainfall data. The major findings indicate that: (1) Over the past two decades, the Lanxi region has experienced rapid urban expansion, with the built-up area expanding from 183.50 km2 to 294.30 km2, which is an average annual expansion rate of 2.39%. Notably, Lanzhou, Baiyin, and Xining dominated the expansion. (2) Urban expansion negatively affected approximately 53.50 km2 of vegetation, while about 39.56 km2 saw positive impacts. The negative effects were mainly due to the loss of cropland and grassland. Therefore, cities in drylands should balance urban development and vegetation conservation by strictly controlling cropland and grassland occupancy and promoting intelligent urban growth. [ABSTRACT FROM AUTHOR]

Introduction Hypoxia, a hallmark of solid tumors, is an important aspect of the tumor microenvironment (Ji 2014). Hypoxia is associated with tumorigenesis, spoor prognosis, increased angiogenesis, and tumor growth. Hypoxia [...], The early metastasis of cervical cancer is a multistep process requiring the cancer cells to adapt to the signal input from different tissue environments, including hypoxia. Hypoxia-induced epithelial-to-mesenchymal transition (EMT) plays a critical role in the ability to invade surrounding tissues. However, the molecular mechanisms underlying EMT in cervical cancer remain to be elucidated. Herein, we show that hypoxia-inducible factor-1alpha (HIF-1[alpha]) and aryl hydrocarbon receptor nuclear translocator (ARNT) are recruited to the human coilin-interacting nuclear ATPase protein (hCINAP) promoter and initiate hCINAP expression in hypoxia. Ablation of hCINAP decreased the migratory capacity and EMT of cervical cancer cells under hypoxic conditions. Furthermore, hCINAP regulated EMT through the Akt--mTOR signaling pathway, and inhibits hypoxia-induced p53-dependent apoptosis. Our data collectively show that hCINAP may have essential roles in the metastasis of cervical cancer and could be a potential target for curing cervical cancer. Key words: hCINAP, hypoxia, Akt--mTOR, HIF-1[alpha]--ARNT, p53. La metastase precoce du cancer du col de l'uterus est un processus en plusieurs etapes qui exige que les cellules cancereuses s'adaptent aux signaux emis par differents environnements tissulaires, y compris l'hypoxie. La transition epithelio-mesenchymateuse (TEM) induite par l'hypoxie joue un role essentiel dans l'acquisition de la capacite a envahir les tissus environnants. Cependant, le mecanisme moleculaire sous-jacent a la TEM dans le cancer du col de l'uterus reste a elucider. Les auteurs ont montre ici que HIF-1[alpha] et ARNT sont recrutes sur le promoteur de hCINAP et qu'ils initient l'expression de hCINAP en hypoxie. L'ablation de l'hCINAP diminuait la capacite migratoire et la TEM des cellules cancereuses du col de l'uterus en hypoxie. Par ailleurs, hCINAP regule la TEM par la signalisation Akt--mTOR et inhibe l'apoptose dependante de p53 induite par l'hypoxie. Ces donnees ont collectivement montre que hCINAP pourrait jouer un role essentiel dans la metastase du cancer du col de l'uterus et pourrait etre une cible potentielle pour la guerison de ce cancer. [Traduit par la Redaction] Mots-cles : hCINAP, hypoxie, Akt--mTOR, HIF-1[alpha]--ARNT, p53.

Bare soil will cause soil erosion and contribute to air pollution through the generation of dust, making the timely and effective monitoring of bare soil an urgent requirement for environmental management. Although there have been some researches on bare soil extraction using high-resolution remote sensing images, great challenges still need to be solved, such as complex background interference and small-scale problems. In this regard, the Hybrid Attention Network (HA-Net) is proposed for automatic extraction of bare soil from high-resolution remote sensing images, which includes the encoder and the decoder. In the encoder, HA-Net initially utilizes BoTNet for primary feature extraction, producing four-level features. The extracted highest-level features are then input into the constructed Spatial Information Perception Module (SIPM) and the Channel Information Enhancement Module (CIEM) to emphasize the spatial and channel dimensions of bare soil information adequately. To improve the detection rate of small-scale bare soil areas, during the decoding stage, the Semantic Restructuring-based Upsampling Module (SRUM) is proposed, which utilizes the semantic information from input features and compensate for the loss of detailed information during downsampling in the encoder. An experiment is performed based on high-resolution remote sensing images from the China–Brazil Resources Satellite 04A. The results show that HA-Net obviously outperforms several excellent semantic segmentation networks in bare soil extraction. The average precision and IoU of HA-Net in two scenes can reach 90.9% and 80.9%, respectively, which demonstrates the excellent performance of HA-Net. It embodies the powerful ability of HA-Net for suppressing the interference from complex backgrounds and solving multiscale issues. Furthermore, it may also be used to perform excellent segmentation tasks for other targets from remote sensing images. [ABSTRACT FROM AUTHOR]