Publications by authors named "X F Guang"
Strong human activities greatly challenge the high-accuracy spatial prediction of soil pollutants and their speciation. This study first determined three auxiliary variables of soil total arsenic (TA) in a typical strong human-affected area, namely in-situ portable X-ray fluorescence (PXRF) TA calibrated by robust geographically weighted regression (RGWR), atmospheric deposition information simulated by atmospheric diffusion model (AERMOD), and land-use types. Then, robust residual cokriging with the above three auxiliary variables (RRCoK-RCPXRF/AD/LUT) was proposed to spatially predict soil TA.
View Article and Find Full Text PDFMaximum Entropy model (MaxEnt), as a machine learning algorithm, is widely used to identify potential risk areas for emerging infectious diseases. However, MaxEnt usually overlooks the influence of the optimal selection of spatial grid scale and the optimal combination of factor information on identification accuracy. Furthermore, the internal level information of factors is closely related to the potential risk of disease occurrence but is rarely applied to enhance MaxEnt's accuracy.
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- Compound extreme weather events, linked to climate change, are becoming more frequent and are expected to lead to an increase in emergency ambulance calls (EACs), but their impact has not been thoroughly studied.
- The researchers analyzed over 242,000 EAC records from Shenzhen between January 2020 and June 2023, focusing on days with at least two extreme weather events using a specialized statistical model.
- Findings indicate that various combinations of extreme weather (like cold monsoons or heat waves) have significant links to increased EACs related to diseases like cardiovascular and endocrine diseases, highlighting a growing public health concern.
Article Synopsis
- The successful elimination of leftover tumor cells is crucial to prevent cancer spread and recurrence, and an advanced nanoplatform could enhance cancer treatment effectiveness.* -
- The study introduces a novel nanoplatform called DSF-CuS@TA, which is designed to release therapeutic agents in response to specific triggers like pH changes and near-infrared light, enabling a "triple attack" strategy against tumors.* -
- Results indicate that combining DSF-based chemotherapy with NIR-II phototherapy using this intelligent nanoplatform can significantly improve tumor destruction, offering a promising new approach to cancer treatment.*
Purpose: Necroptosis, a monitored form of inflammatory cell death, contributes to coronary heart disease (CHD) progression. This study examined the potential of using necroptosis genes as diagnostic markers for CHD and sought to elucidate the underlying roles.
Methods: Through bioinformatic analysis of GSE20680 and GSE20681, we first identified the differentially expressed genes (DEGs) related to necroptosis in CHD.