Author: "Geng, Y." / Publisher: elsevier - Searchworks@Jio Institute Digital Library Search Results

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296 results on '"Geng, Y."'

1. Mapping the soil C:N ratio at the European scale by combining multi-year Sentinel radar and optical data via cloud computing

Author: Wang, X., Geng, Y., Zhou, Tao, Li, H., Liu, Y., Ren, R., Zhang, Y., Xu, X., Liu, T., Si, B., Lausch, Angela, Wang, X., Geng, Y., Zhou, Tao, Li, H., Liu, Y., Ren, R., Zhang, Y., Xu, X., Liu, T., Si, B., and Lausch, Angela
Abstract: Spatial information on the soil carbon-to-nitrogen (C:N) ratio is essential for sustainable soil use and management. The unprecedented availability of Sentinel optical and radar data on cloud computing platforms, such as the Google Earth Engine (GEE), has created new possibilities for developing soil prediction models from the local scale to the planetary scale. However, there is a paucity of literature on the effects of Sentinel sensor selection and integration and radar data utilization strategies on mapping the C:N ratio. In this study, we explored the use of multiyear Sentinel-1 radar and Sentinel-2 optical data obtained from the GEE platform combined with the digital soil mapping (DSM) technique to map the soil C:N ratio at the European scale. The performance of soil prediction models, which were constructed using two modeling techniques (random forest and support vector machine), derived under multiple scenarios based on optical, radar and commonly used auxiliary data (climatic and topographic variables) combined with the LUCAS 2018 soil dataset, was evaluated by a cross-validation technique. The results showed that the modeling performance varied with the selection and integration of Sentinel observations, as well as the configuration of the radar data. Models based on single polarization performed the worst across all scenarios related to Sentinel-1, with cross-polarization performing better than copolarization. Models that utilized Sentinel-1 data from ascending orbits outperformed those that utilized data from descending orbits. The application of Sentinel-1 backscatter information derived from different orbits and polarization modes resulted in improved prediction accuracy. Our study also demonstrated the potential of integrating multiyear Sentinel satellite data via the GEE to map the continental-scale C:N ratio. The model based on Sentinel-1 data outperformed the one built on Sentinel-2 data, whereas combining Sentinel-2 optical data with Sentinel-1 rad
Published: 2024

2. Continental-scale mapping of soil pH with SAR-optical fusion based on long-term earth observation data in google earth engine

Author: Geng, Y., Zhou, Tao, Zhang, Z., Cui, B., Sun, J., Zeng, L., Yang, R., Wu, N., Liu, T., Pan, J., Si, B., Lausch, Angela, Geng, Y., Zhou, Tao, Zhang, Z., Cui, B., Sun, J., Zeng, L., Yang, R., Wu, N., Liu, T., Pan, J., Si, B., and Lausch, Angela
Abstract: The advent of cloud computing platforms (e.g., Google Earth Engine (GEE)) and the massive amounts of optical and radar Earth Observation (EO) data hosted by these platforms present new opportunities for mapping soil pH at large scales. However, existing studies generally lack consensus on the effects of satellite and radar sensor parameters on GEE-based soil pH prediction models. In this study, we assessed the suitability of long-term radar (C-band Sentinel-1 and L-band PALSAR-1/2) and optical (Sentinel-2) EO data on GEE for the digital mapping of soil pH on a continental (Europe) scale and determined the most appropriate radar sensor parameters. Thirteen scenarios with different data configurations were simulated and combined with the 2018 LUCAS soil database and two machine learners (boosted regression trees and extreme gradient boosting) to develop soil prediction models. Results showed that the selection of modeling techniques, satellite sensors and radar system parameters largely affected the model output. Models involving a single polarization mode of PALSAR-1/2 data performed the worst (RPD = 1.24). Models based on Sentinel-1 data performed better than those built using PALSAR-1/2 data. The model performance was improved when a model involved more polarization bands, orbital directions, and band frequencies. The multiband model built using the two radar datasets achieved a comparable accuracy to the model based on optical data. Moreover, the model that fused radar-optical data achieved better results, with RPD values of 1.56 and 1.46 for the models with and without radar data, respectively; its performance was comparable to that of models built with commonly used variables (topography and climate). The analysis of importance indicated that long-term optical and radar EO data on GEE were important in our model. The modelling of soil pH at the continental scale largely benefits from GEE. The predicted maps exhibited strong spatial heterogeneit
Published: 2024

3. Effects of optical and radar satellite observations within Google Earth Engine on soil organic carbon prediction models in Spain

Author: Zhou, Tao, Geng, Y., Lv, W., Xiao, S., Zhang, P., Xu, X., Chen, J., Wu, Z., Pan, J., Si, B., Lausch, Angela, Zhou, Tao, Geng, Y., Lv, W., Xiao, S., Zhang, P., Xu, X., Chen, J., Wu, Z., Pan, J., Si, B., and Lausch, Angela
Abstract: The modeling and mapping of soil organic carbon (SOC) has advanced through the rapid growth of Earth observation data (e.g., Sentinel) collection and the advent of appropriate tools such as the Google Earth Engine (GEE). However, the effects of differing optical and radar sensors on SOC prediction models remain uncertain. This research aims to investigate the effects of different optical and radar sensors (Sentinel-1/2/3 and ALOS-2) on SOC prediction models based on long-term satellite observations on the GEE platform. We also evaluate the relative impact of four synthetic aperture radar (SAR) acquisition configurations (polarization mode, band frequency, orbital direction and time window) on SOC mapping with multiband SAR data from Spain. Twelve experiments involving different satellite data configurations, combined with 4027 soil samples, were used for building SOC random forest regression models. The results show that the synthesis mode and choice of satellite images, as well as the SAR acquisition configurations, influenced the model accuracy to varying degrees. Models based on SAR data involving cross-polarization, multiple time periods and “ASCENDING” orbits outperformed those involving copolarization, a single time period and “DESCENDING” orbits. Moreover, combining information from different orbital directions and polarization modes improved the soil prediction models. Among the SOC models based on long-term satellite observations, the Sentinel-3-based models (R2 = 0.40) performed the best, while the ALOS-2-based model performed the worst. In addition, the predictive performance of MSI/Sentinel-2 (R2 = 0.35) was comparable with that of SAR/Sentinel-1 (R2 = 0.35); however, the combination (R2 = 0.39) of the two improved the model performance. All the predicted maps involving Sentinel satellites had similar spatial patterns that were higher in northwest Spain and lower in the south. Overall, this study provides insights into the effects of different optical an
Published: 2023

4. National-scale spatial prediction of soil organic carbon and total nitrogen using long-term optical and microwave satellite observations in Google Earth Engine

Author: Zhou, Tao, Lv, W., Geng, Y., Xiao, S., Chen, J., Xu, X., Pan, J., Si, B., Lausch, Angela, Zhou, Tao, Lv, W., Geng, Y., Xiao, S., Chen, J., Xu, X., Pan, J., Si, B., and Lausch, Angela
Abstract: Modeling accurate and detailed soil spatial information is essential for environmental modeling, precision soil management and decision-making. In this study, we integrated long-term optical (Sentinel-2) and radar (Sentinel-1) satellite observations via the Google Earth Engine (GEE) platform for high-resolution national-scale digital mapping of soil organic carbon (SOC) and total soil nitrogen (TSN) in Austria. Our soil predictive models based on boosted regression tree (BRT) and regression kriging (RK) methods were constructed from 449 soil samples (0–20 cm) covering the study area in the LUCAS soil database and Sentinel observations synthesized with different time intervals. The different input predictors of these soil predictive models resulted in seven modeling scenarios, and their prediction performance was evaluated by a cross-validation technique. Comparative analysis indicated that satellite sensors, modeling techniques, and SAR data acquisition configurations greatly affected the model outputs. Cross-polarization and co-polarization had similar performance in TSN and SOC predictions, and their combination improved the prediction accuracy. Predictive models based on Sentinel-1 with the “ASCENDING” orbits outperformed the models involving the “DESCENDING” orbits; the prediction accuracy of the former was comparable to models involving two orbital data. The models built by Sentinel-1 and Sentinel-2 performed similarly in predicting SOC (R2 = 0.51 vs. R2 = 0.52, respectively) and TSN (their R2 were both 0.42); their synergistic utilization improved the prediction results. Models involving more years of Sentinel observations on the GEE platform provided more accurate modeling results. The best soil predictive models explained 55% and 45% of soil variability for SOC and TSN, respectively, both constructed from long-term Sentinel-1/2 observations using the RK method. The overall trends of the mapping results of the mode
Published: 2023

5. FTransCNN: Fusing Transformer and a CNN based on fuzzy logic for uncertain medical image segmentation

Author: Ding, W, Wang, H, Huang, J, Ju, H, Geng, Y, Lin, CT, Pedrycz, W, Ding, W, Wang, H, Huang, J, Ju, H, Geng, Y, Lin, CT, and Pedrycz, W
Abstract: The accurate segmentation of medical images plays a crucial role in diagnosing and treating diseases. Although many methods now use multimodal joint segmentation, the joint use of segmentation features extracted by multiple models can lead to heterogeneity and uncertainty. Unreasonable fusion methods cannot exploit the advantages of multiple models and still lack good performance in segmentation. Therefore, this study proposes the FTransCNN model, which is composed of a convolutional neural network (CNN) and Transformer and is based on a fuzzy fusion strategy that jointly utilizes the features extracted by a CNN and Transformer through a new fuzzy fusion module. First, the CNN and Transformer act as the backbone network for parallel feature extraction. Second, channel attention is used to promote the global key information of Transformer to improve the feature representation ability, and spatial attention is used to enhance the local details of CNN features and suppress irrelevant regions. Third, the proposed model applies the Hadamard product to model fine-grained interactions between the two branches and uses the Choquet fuzzy integral to suppress heterogeneity and uncertainty in fused features. Fourth, FTransCNN employs fuzzy attention fusion module (FAFM) hierarchical upsampling to effectively capture both low-level spatial features and high-level semantic context. Finally, the new model obtains the final segmentation result by using the deconvolution and results in an improvement in segmentation. The experimental results on Chest X-ray and Kvasir-SEG dataset show that FTransCNN has better performance on segmentation tasks than the-state-of-the-art deep segmentation models.
Published: 2023

6. Magnets: Mechanically Alloyed

Author: Neu, V., primary, Schultz, L., additional, and Geng, Y., additional
Published: 2016
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7. Molecular dynamics simulation of AFM tip-based hot scratching of nanocrystalline GaAs

Author: Fan, P., Goel, S., Luo, X., Yan, Y., Geng, Y., He, Y., and Wang, Y.
Subjects: AFM Tip-based hot machining, Molecular dynamic (MD) simulation, Single crystal gallium arsenide, Dislocation nucleation
Abstract: GaAs is a hard, brittle material and its cutting at room-temperature is rather difficult, so the work explored whether hot conditions improve its cutting performance or not. Atomic force microscope (AFM) tip-based hot machining of the (0 1 0) oriented single crystal GaAs was simulated using molecular dynamics (MD). Three representative temperatures 600 K, 900 K and 1200 K (below the melting temperature of ~1511 K) were used to cut GaAs to benchmark against the cutting performance at 300 K using indicators such as the cutting forces, kinetic coefficient of friction, cutting temperature, shear plane angle, sub-surface damage depth, shear strain in the cutting zone, and stress on the diamond tip. Hotter conditions resulted in the reduction of cutting forces by 25% however, the kinetic coefficient of friction went up by about 8%. While material removal rate was found to increase with the increase of the substrate temperature, it was accompanied by an increase of the sub-surface damage in the substrate. Simulations at 300 K showed four major types of dislocations with Burgers vector 1/2, 1/6, and 1/2 underneath the cutting zone and these were found to cause ductile response in zinc-blende GaAs. Lastly, a phenomenon of chip densification was found to occur during hot cutting which referred to the fact that the amorphous cutting chips obtained from cutting at low temperature will have lower density than the chips obtained from cutting at higher temperatures.
Published: 2021

8. Quantitative identification of yellow rust in winter wheat with a new spectral index: Development and validation using simulated and experimental data

Author: Ren, Y, Huang, W, Ye, H, Zhou, X, Ma, H, Dong, Y, Shi, Y, Geng, Y, Huang, Y, Jiao, Q, Xie, Q, Ren, Y, Huang, W, Ye, H, Zhou, X, Ma, H, Dong, Y, Shi, Y, Geng, Y, Huang, Y, Jiao, Q, and Xie, Q
Abstract: Yellow rust, caused by Puccinia striiformis f. sp. Tritici, is a serious disease attacking wheat (Triticum aestivum L.) across the globe. The occurrence of yellow rust can result in severe yield reduction and economic loss. Hyperspectral remote sensing has demonstrated potential in detecting yellow rust, with the majority of studies distinguishing qualitatively between diseased and healthy individuals or performing simple grading of disease severity. However, research on the quantification of the severity of yellow rust is limited. To fill this gap in the literature, in the current study, we constructed a new spectral index, the yellow rust optimal index (YROI), using the hyperspectral data obtained by ASD field spectrometer to quantitatively estimate yellow rust severity. The index is based on the spectral response of spores, and vegetation biophysical and biochemical parameters (VPCPs); and integrated with the PROSPECT-D model. We evaluated the new index and compared it with 11 commonly used yellow rust detection indices using experimental leaf- and canopy-scale spectral datasets. Results demonstrated the superior accuracy of YROI for both the leaf (R2 = 0.822, RMSE = 0.070) and canopy (R2 = 0.542, RMSE = 0.085) scales. In this research, we quantitatively analyzed the spectral response mechanism of wheat yellow rust, which provided a new idea for the quantitative identification of crop diseases. Moreover, our results can be employed as a reference and theoretical basis for the accurate and timely quantitative identification of crop diseases over the large areas in the future.
Published: 2021

9. High-resolution digital mapping of soil organic carbon and soil total nitrogen using DEM derivatives, Sentinel-1 and Sentinel-2 data based on machine learning algorithms

Author: Zhou, Tao, Geng, Y., Chen, J., Pan, J., Haase, Dagmar, Lausch, Angela, Zhou, Tao, Geng, Y., Chen, J., Pan, J., Haase, Dagmar, and Lausch, Angela
Abstract: Soil organic carbon (SOC) and soil total nitrogen (STN) are important indicators of soil health and play a key role in the global carbon and nitrogen cycles. High-resolution radar Sentinel-1 and multispectral Sentinel-2 images have the potential to investigate soil spatial distribution information over a large area, although Sentinel-1 and Sentinel-2 data have rarely been combined to map either SOC or STN content. In this study, we applied machine learning techniques to map both SOC and STN content in the southern part of Central Europe using digital elevation model (DEM) derivatives, multi-temporal Sentinel-1 and Sentinel-2 data, and evaluated the potential of different remote sensing sensors (Sentinel-1 and Sentinel-2) to predict SOC and STN content. Four machine-learners including random forest (RF), boosted regression trees (BRT), support vector machine (SVM) and Bagged CART were used to construct predictive models of SOC and STN contents based on 179 soil samples and different combinations of environmental covariates. The performance of these models was evaluated based on a 10-fold cross-validation method by three statistical indicators. Overall, the BRT model performed better than RF, SVM and Bagged CART, and these models yielded similar spatial distribution patterns of SOC and STN. Our results showed that multi-source sensor methods provided more accurate predictions of SOC and STN contents than individual sensors. The application of radar Sentinel-1 and multispectral Sentinel-2 images proved useful for predicting SOC and STN. A combination of Sentinel-1/2-derived predictors and DEM derivatives yielded the highest prediction accuracy. The prediction accuracy changed with and without the Sentinel-1/2-derived predictors, with the R2 for estimating both SOC and STN content using the BRT model increasing by 12.8% and 18.8%, respectively. Topographic variables were the main explanatory variables for SOC and STN predictions, where elevation was assigned as the vari
Published: 2020

10. Mapping of soil organic carbon content using multi-source remote sensing variables in the Heihe River Basin in China

Author: Zhou, Tao, Geng, Y., Haase, Dagmar, Lausch, Angela, Zhou, Tao, Geng, Y., Haase, Dagmar, and Lausch, Angela
Abstract: Soil organic carbon (SOC) has a large impact on soil quality and global climate change. It is therefore important to be able to predict SOC accurately to promote sustainable soil management. Although the synthetic aperture radar (SAR) has many advantages and has been widely used in soil science research, it has rarely been used in previous SOC mapping studies based on remote sensing images. The purpose of this study was to investigate the ability of multi-temporal Sentinel-1A data in SOC prediction, by comparing the predictive performance of random forest (RF) and boosted regression tree (BRT) models in the Heihe River Basin in northwestern China. A set of 162 topsoil (0–20 cm) samples were taken and 15 environmental variables were obtained including land use, topography, climate, and remote sensing images (optical and SAR data). Using a cross-validation procedure to evaluate the performance of the models, three statistical indices were calculated. Overall, both RF and BRT models effectively predicted SOC content, exhibiting similar performance and producing similar spatial distribution patterns of SOC. The results showed that the addition of multi-temporal Sentinel-1A images improved prediction accuracy, with the root mean squared error (RMSE), the mean absolute error (MAE) and the coefficient of determination (R2) improving by 9.0%, 8.3% and 13.5%, respectively. Furthermore, the combination of all environmental variables had the best prediction performance explaining 75% of SOC variation. The most important environmental variables explaining SOC variation were precipitation, elevation, and temperature. The multi-temporal Sentinel-1A data in RF and BRT models explained 9% and 7%, respectively. The results from our case study highlight the usefulness of multi-temporal Sentinel-1 data in SOC mapping.
Published: 2020

11. Prediction of soil organic carbon and the C:N ratio on a national scale using machine learning and satellite data: A comparison between Sentinel-2, Sentinel-3 and Landsat-8 images

Author: Zhou, Tao, Geng, Y., Ji, C., Xu, X., Wang, H., Pan, J., Bumberger, Jan, Haase, Dagmar, Lausch, Angela, Zhou, Tao, Geng, Y., Ji, C., Xu, X., Wang, H., Pan, J., Bumberger, Jan, Haase, Dagmar, and Lausch, Angela
Abstract: Soil organic carbon (SOC) and soil carbon-to-nitrogen ratio (C:N) are the main indicators of soil quality and health and play an important role in maintaining soil quality. Together with Landsat, the improved spatial and temporal resolution Sentinel sensors provide the potential to investigate soil information on various scales. We analyzed and compared the potential of satellite sensors (Landsat-8, Sentinel-2 and Sentinel-3) with various spatial and temporal resolutions to predict SOC content and C:N ratio in Switzerland. Modeling was carried out at four spatial resolutions (800 m, 400 m, 100 m and 20 m) using three machine learning techniques: support vector machine (SVM), boosted regression tree (BRT) and random forest (RF). Soil prediction models were generated in these three machine learners in which 150 soil samples and different combinations of environmental data (topography, climate and satellite imagery) were used as inputs. The prediction results were evaluated by cross-validation. Our results revealed that the model type, modeling resolution and sensor selection greatly influenced outputs. By comparing satellite-based SOC models, the models built by Landsat-8 and Sentinel-2 performed the best and the worst, respectively. C:N ratio prediction models based on Landsat-8 and Sentinel-2 showed better results than Sentinel-3. However, the prediction models built by Sentinel-3 had competitive or better accuracy at coarse resolutions. The BRT models constructed by all available predictors at a resolution of 100 m obtained the best prediction accuracy of SOC content and C:N ratio; their relative improvements (in terms of R2) compared to models without remote sensing data input were 29.1% and 58.4%, respectively. The results of variable importance revealed that remote sensing variables were the best predictors for our soil prediction models. The predicted maps indicated that the higher SOC content was mainly distributed
Published: 2020

12. Synthesis and electrical conducting behavior of graphite nanoplatelet/polymer nanocomposites

Author: Geng, Y., primary, Li, J., additional, and Kim, J.K., additional
Published: 2010
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13. Contributor contact details

Author: Tjong, S.C., primary, Mai, Yiu-Wing, additional, Cheng, Xinjian, additional, Tjong, S.C., additional, Li, Robert K.Y., additional, Psarras, G.C., additional, Smith, R.C., additional, Nelson, J.K., additional, Schadler, L.S., additional, Li, Ai-Dong, additional, Liu, Wen-Chao, additional, Fu, Shao-Yun, additional, Lee, Kwang-Pill, additional, Gopalan, A., additional, Komathi, S., additional, Raghupathy, D., additional, Pissis, P., additional, Kripotou, S., additional, Kyritsis, A., additional, Bao, S.P., additional, Tang, C.Y., additional, Geng, Y., additional, Li, J., additional, Kim, J.K., additional, Dasari, A., additional, Cai, G.-P., additional, Yu, Z.-Z., additional, Chen, Pei, additional, Wong, Shing-Chung, additional, Lu, Chunsheng, additional, Yang, Mingshu, additional, Zhang, Shimin, additional, Qin, Huanli, additional, Liu, T.X., additional, Huang, S., additional, Thomassin, Jean-Michel, additional, Jérôme, Robert, additional, Detrembleur, Christophe, additional, Molenberg, Isabel, additional, Huynen, Isabelle, additional, Ma, Chen-Chi M., additional, Hsiao, Min-Chien, additional, Liao, Shu-Hang, additional, Yen, Ming-Yu, additional, Teng, Chih-Chun, additional, Hsiao, Min-Hsuan, additional, Teo, W.E., additional, Kaur, S., additional, Seeram, Ramakrishna, additional, Lu, Yang, additional, Yu, Shu-Hong, additional, Zeng, Wei, additional, Guo Chen, Shi, additional, Zhao, Bin, additional, Rong, Min Zhi, additional, Zhang, Ming Qiu, additional, Gao, Wei, additional, Li, Zhengwei, additional, Marouf, B.T., additional, Bagheri, R., additional, Pearson, R.A., additional, Liang, Y.L., additional, Lu, Yong-Lai, additional, Zhang, Li-Qun, additional, Xie, Xiao-Lin, additional, Du, Fei-Peng, additional, Li, Yu Chao, additional, and Tjong, Sie Chin, additional
Published: 2010
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14. Toward the 2-degree target: Evaluating co-benefits of road transportation in China

Author: Tian, X., Dai, H., Geng, Y., Zhang, S., Xie, Y., Liu, X., Lu, P., Bleischwitz, R., Tian, X., Dai, H., Geng, Y., Zhang, S., Xie, Y., Liu, X., Lu, P., and Bleischwitz, R.
Abstract: Background Co-benefit assessments on health and economic impacts of climate change mitigation towards the 2-degree target are still largely insufficient in literature, especially from a sectoral perspective. Objectives This study aims to (1) evaluate PM2.5 pollution-related health impacts on China's road transport sector at both national and provincial levels towards the 2-degree target by 2050; (2) uncover the contribution from the road transport sector compared with that of all sectors; (3) distinguish the contribution from climate change mitigation actions compared with air pollution control oriented actions in road transport sector; and (4) identify the heterogeneous influences at the provincial level. Methods Health and economic impacts are estimated using an integrated approach that combines the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) model, the IMED/CGE (Integrated Model of Energy, Environment and Economy for Sustainable Development/computable general equilibrium) model and IMED/HEL (Health) model. Five scenarios are proposed based on climate change mitigation and stringency of air pollution control policy. Results It is found that China's road transport sector could contribute to around 10.6% of total PM2.5 concentration reduction resulting from all sectors' participation in achieving the 2-degree target, equivalent to 10.8% of the monetized health benefits obtained from achieving the 2-degree target by all sectors. Populous provinces dependent on secondary industries would benefit more under the 2-degree target. Meanwhile, compared with the potential maximum benefits from air pollution control oriented measures in the road transport sector, such climate actions could bring noticeable synergies as well. Approximately climate change mitigation action alone can lead to 70% reduction of health impacts by applying air pollution control measures. Conclusions This research has implications for other emerging economies and those reluctan
Published: 2019

15. DETECTION OF APOPTOTIC DNA FRAGMENTATION IN INDIVIDUAL X-IRRADIATED THYMOCYTES

Author: OHYAMA, H., primary, TAMAMOTO, H., additional, GENG, Y., additional, and YAMADA, T., additional
Published: 1991
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16. Pursuing air pollutant co-benefits of CO2 mitigation in China: a provincial leveled analysis

Author: Dong, H., Dai, H., Dong, L., Fujita, T., Geng, Y., Klimont, Z., Inoue, T., Bunya, S., Fujii, M., Masui, T., Dong, H., Dai, H., Dong, L., Fujita, T., Geng, Y., Klimont, Z., Inoue, T., Bunya, S., Fujii, M., and Masui, T.
Published: 2015

17. Rescue of cyclin D1 deficiency by knockin cyclin E

Author: Geng, Y., Whoriskey, W., Park, M.Y., Bronson, R.T., Medema, R.H., Li, T., Weinberg, R.A., Sicinski, P., Geng, Y., Whoriskey, W., Park, M.Y., Bronson, R.T., Medema, R.H., Li, T., Weinberg, R.A., and Sicinski, P.
Published: 1999

18. The impact of COVID-19 on the cascade of care of HCV in the US and China

Author: Yee Hui Yeo, Xu Gao, Jian Wang, Qingyu Li, Xingyang Su, Yu Geng, Rui Huang, Chao Wu, Fanpu Ji, Vinay Sundaram, Mazen Noureddin, Maria Buti, Walid S. Ayoub, Institut Català de la Salut, [Yeo YH] Division of General Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. [Gao X, Su X] Department of Infectious Diseases, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China. [Wang J, Geng Y] Department of Infectious Diseases, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China. [Li Q] School of Medicine, University of California, Los Angeles, CA, USA. [Buti M] Unitat del Fetge, Vall d'Hebron Hospital Universitari, Barcelona, Spain. CIBEREHD del Instituto Carlos III, Barcelona, Spain, and Vall d'Hebron Barcelona Hospital Campus
Subjects: virosis::hepatitis viral humana::hepatitis C::hepatitis C crónica [ENFERMEDADES], Hepatology, COVID-19, Otros calificadores::Otros calificadores::/farmacoterapia [Otros calificadores], General Medicine, Hepacivirus, Hepatitis C, Chronic, Virus Diseases::Hepatitis, Viral, Human::Hepatitis C::Hepatitis C, Chronic [DISEASES], Other subheadings::Other subheadings::/drug therapy [Other subheadings], Antiviral Agents, COVID-19 (Malaltia), Humans, RNA, Medicaments antivírics - Ús terapèutic, Pandemics, Hepatitis C - Tractament
Abstract: COVID-19 pandemic; Direct-acting antivirals; Telemedicine Pandemia de COVID-19; Antivirales de acción directa; Telemedicina Pandèmia del Covid-19; Antivirals d'acció directa; Telemedicina Abstract Background and objectives: The COVID-19 pandemic imperiled the global health system. We aimed to determine the impact of COVID-19 on the care continuum of HCV-infected patients. Material and Methods: Two hundred and fifty-six patients who were prescribed a course of DAA therapy at three tertiary medical centers in the US and China between January 1, 2019 to June 30, 2020 were included. We assessed the proportions of patients who completed DAA therapy and had HCV RNA testing during and after the end of therapy. We also assessed the impact of utilization of telemedicine. Results: The proportion of patients undergoing HCV RNA testing during DAA treatment decreased from >81.7% before pandemic to 67.8% during the pandemic (P=0.006), with a more prominent decrease in the US. There were significant decreases in HCV RNA testing >12 (P20 weeks (P
Published: 2022

19. Revealing the distribution characteristics and key driving factors of dissolved organic matter in Baiyangdian Lake inflow rivers from different seasons and sources.

Author: Shi K, Zhao Y, Wu C, Geng Y, Zhou S, and Chai B
Abstract: The river course is a transitional area connecting the source and receiving water bodies. The dissolved organic matter (DOM) in the river course is an important factor affecting the aquatic environment and ecological health. However, there are shortcomings in studying the differences and quantitative contributions of river DOM in different seasons and sources. In this study, ultraviolet-visible (UV-vis) and three-dimensional fluorescence spectra were used to characterize the optical properties, analyze the spatiotemporal changes, and establish the quantitative relationship between environmental factors and DOM in the inflow rivers of Baiyangdian Lake. The results showed that the relative DOM concentrations in summer and autumn were significantly higher than those in the other seasons (P < 0.001) and that the DOM source (S R < 1) was mainly exogenous. The fluorescence abundance of protein-like substances (C1 + C2 + C3) was the highest in spring, whereas that of humus C4 was the highest in autumn. Moreover, the inflow rivers exhibited strong autogenetic characteristics (BIX > 1) throughout the year. Self-organizing maps (SOM) indicated that the main driving factors of water quality were NO 3 - -N in spring, autumn, and winter and DO, pH, and chemical oxygen demand (COD) in summer. Random forest analysis showed that the fluorescent components (C1-C4) were closely related to the migration and transformation of nitrogen, and pH and nitrogen were the main predictors of each component. The Mantel test and structural equation model (SEM) showed that temperature and NO 3 - -N significantly influenced the DOM concentration, components, and molecular properties in different seasons. Moreover, the river source also affected the distribution mechanism of DOM in the water body. Our study comprehensively analyzed the response of DOM in inflow rivers in different seasons and water sources, providing a basis for further understanding the driving mechanisms of water quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could influence the work described herein., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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20. 1,25-dihydroxyvitamin D 3 enhances the expression of phosphorus transporters via vitamin D receptor in ligated duodenal loops of Arbor Acres male broilers.

Author: Zhang W, Geng Y, Yang K, Hu Y, Xue M, Cui X, Zhang L, Wang S, Li T, Luo X, and Hu Y
Abstract: 1,25-dihydroxyvitamin D 3 [1,25-(OH) 2 D 3 ] could promote phosphorus (P) absorption in the duodenum of broilers. The vitamin D receptor (VDR) mediates the action of 1,25-(OH) 2 D 3 . However, it remains unknown whether and how VDR is involved in promoting P absorption in the duodenum of broilers by 1,25-(OH) 2 D 3 . The objective of the current study was to investigate the effect of added 1,25-(OH) 2 D 3 levels on P absorption, mRNA or protein expression levels of VDR, retinoid X receptor (RXR), type IIb sodium-phosphate cotransporter (NaPi-IIb), inorganic phosphate transporter (PiT) 1 and PiT-2, and the enrichments of VDR bound to DNA promoters of the above P transporters in the ligated duodenal loops of Arbor Acres male broilers. The duodenal loops were perfused with solutions (pH = 6.0) containing 0 (control), 12.5, or 25.0 ng/L of 1,25-(OH) 2 D 3 for up to 40 min. The results indicated that the addition of either 12.5 or 25.0 ng/L 1,25-(OH) 2 D 3 to the perfusates increased (P < 0.04) P absorption percentage and rate, as well as the mRNA expression levels of VDR, RXR, NaPi-IIb, and PiT-2, alongside protein expression levels of VDR, NaPi-IIb, and PiT-2, whereas it did not affect (P > 0.10) PiT-1 mRNA and protein expression levels. Moreover, 1,25-(OH) 2 D 3 administration increased (P < 0.01) the enrichments of VDR bound to NaPi-IIb and PiT-2 DNA promoter regions in the ligated duodenal loops of broilers, which were in line with their mRNA expression levels. These findings suggest that 1,25-(OH) 2 D 3 increased P absorption possibly through VDR-mediated transactivation of NaPi-IIb and PiT-2 genes in the duodenum of Arbor Acres male broilers., Competing Interests: Conflict of interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the content of this paper., (Copyright © 2024. Published by Elsevier Inc.)
Published: 2024
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21. A new microalgal negative carbon technology for landfill leachate treatment: Simultaneous removal of nitrogen and phosphorus.

Author: Lian X, Wang Z, Liu Z, Xiong Z, Dai H, Yang L, Liu Y, Yang J, Geng Y, Hu M, Shao P, and Luo X
Subjects: Biodegradation, Environmental, Chlorella, Microalgae, Water Pollutants, Chemical analysis, Phosphorus analysis, Nitrogen, Carbon, Waste Disposal, Fluid methods
Abstract: Replete with ammonia nitrogen and organic pollutants, landfill leachate typically undergoes treatment employing expensive and carbon-intensive integrated techniques. We propose a novel microalgae technology for efficient, low-carbon simultaneous treatment of carbon, nitrogen, and phosphorus in landfill leachate (LL). The microbial composition comprises a mixed microalgae culture with Chlorella accounting for 82.58%. After seven days, the process with an N/P ratio of approximately 14:1 removed 98.81% of NH 4 + -N, 88.62 % of TN, and 99.55% of TP. Notably, the concentrations of NH 4 + -N and TP met the discharge standards, while the removal rate of NH 4 + -N was nearly three times higher than previously reported in relevant studies. The microalgae achieved a removal efficiency of 64.27% for Total Organic Carbon (TOC) and 99.26% for Inorganic Carbon (IC) under mixotrophic cultivation, yielding a biomass of 1.18 g/L. The treatment process employed in this study results in a carbon emissions equivalent of -8.25 kgCO 2 /kgN removed , representing a reduction of 33.56 kgCO 2 compared to the 2AO + MBR process. In addition, shake flask experiments were conducted to evaluate the biodegradability of leachate after microalgae treatment. After microalgae treatment, the TOC B (Biodegradable Total Organic Carbon)/TOC ratio decreased from 56.54% to 27.71%, with no significant improvement in biodegradability. It establishes a fundamental foundation for further applied research in microalgae treatment of leachate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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22. Non-classical event-related potentials reveal attention network alteration in patients with temporal lobe epilepsy.

Author: Xie Y, Zhang W, Wu Z, Huang K, Geng Y, Yang H, and Feng L
Abstract: Objective: To explore the characteristic changes of multiple ERP components associated with attention impairments in patients with temporal lobe epilepsy (TLE)., Methods: A total of 92 patients diagnosed with TLE at Xiangya Hospital during May 2022 and January 2023 and 85 healthy controls were included in this study. Participants were asked to complete attention network test with recording of electroencephalogram., Results: Compared with healthy controls, significant lower amplitudes (cue-related N1, N2 and CNV) and longer latencies (target-related N2) were found in TLE patients. Besides classical components, other components could also reveal the impairments of attention function. Cue-related N1 (p ≤ 0.007) and N2 (p ≤ 0.01) components indicated impaired alerting and orienting network in TLE. And cue-related CNV-E component (p = 0.003) promoted the alerting network was damaged and target-related N2 component (p = 0.008) indicated the executive control network was impaired., Conclusion: These findings consummate the non-classical ERP features of attention impairments in TLE patients., Significance: The above findings have strong clinical guiding significance for early identification and intervention., Competing Interests: Conflicts of interest All authors declare that there are no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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23. Anti-inflammatory activity and underlying mechanism against sepsis-induced acute lung injury of a low-molecular-weight polysaccharide from the root of Stemona tuberosa Lour.

Author: Qiu X, Geng Y, Cai X, Ou Y, Li M, Zhang Y, He D, Qian X, Wu Y, Ma H, Yan JK, Yao H, and Chen WH
Abstract: The root of Stemona tuberosa Lour has been used to treat tuberculosis, scabies, and eczema. Polysaccharides are among its main bioactive ingredients. A low-molecular-weight (1819 Da) polysaccharide (SPS2-A) was obtained from the root of S. tuberosa Lour by optimizing three-phase partitioning, purified using an ion chromatography column, and its effects and mechanisms were investigated. Structural analysis revealed that SPS2-A contained arabinose, galactose (Gal), glucose (Glc), xylose, and mannose. The SPS2-A backbone structure comprised sugar residues →4)-α-D-Glcp-(1→, →4)-α-D-Galp-(1→, and →4,6)-β-D-Galp-(1→, while the side chain primarily comprised α-D-Glcp-(1 → connected to the O-6 position of the residue →4,6)-β-D-Galp-(1→. In vitro, SPS2-A downregulated the expression of interleukin-6 in lipopolysaccharide-induced RAW264.7 macrophages. In vivo, SPS2-A significantly downregulated the expression of myeloperoxidase, interleukin-6, interleukin-1β, and tumor necrosis factor-α in bronchoalveolar lavage fluid and lung tissue. Western blotting analysis indicated that SPS2-A reduced lung inflammation in mice with sepsis-induced acute lung injury by activating the nuclear factor κB pathway. These results suggest that SPS2-A is a potential anti-inflammatory candidate for the treatment of sepsis-induced acute lung injury., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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24. Pretreated polystyrene is degraded by a microbial consortium enriched from wetland plastic waste.

Author: Zhang J, Shao Y, Shao Y, Yang W, Xuan N, Geng Y, Bian F, Zhang Y, and Chen G
Abstract: The biodegradation of polystyrene (PS), a type of plastic with aromatic rings in its polymer chain, is a critical environmental goal worldwide. Microbial degradation of PS has been reported, but the underlying mechanisms are poorly understood. Here, we constructed a microcosm wetland containing PS plastic. We isolated six highly efficient PS plastic-degrading bacterial strains and created a microbial consortium (MCs) consisting of these strains. After a 30-day incubation period, MCs-treated PS exhibited hallmarks of degradation, including -CO- formation, reduced hydrophobicity, surface porosity, and 20 % weight loss. The efficiency of PS degradation was enhanced by using a combination of physical-chemical pretreatment and biological methods, increasing the microbial degradation rate by 20 %. Antioxidant 2246 (C 23 H 32 O 2 ) was detected in the culture supernatant via GC-MS. Metatranscriptomic sequencing analysis provided insight into the possible metabolic pathway of PS degradation by the composite bacteria. We identified 31 highly expressed genes encoding proteins that function in carbon metabolism pathways and 34 unique proteases which catalyze the cleavage of long polymer chains. The resulting small molecules are absorbed and further degraded intracellularly by enzymes such as coenzyme synthase, hydratase, transferase, carboxylase, and dehydrogenase. These findings lay the foundation for the efficient and sustainable degradation of PS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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25. Effects of cortisone in zebrafish (Danio rerio): Insights into gut microbiota interactions and molecular mechanisms underlying DNA damage and apoptosis.

Author: Tan J, Yang L, Ye M, Geng Y, Guo Y, Zou H, and Hou L
Subjects: Animals, Water Pollutants, Chemical toxicity, Molecular Docking Simulation, Caspase 3 metabolism, Oxidative Stress drug effects, Caspase 8 metabolism, Zebrafish, Gastrointestinal Microbiome drug effects, Apoptosis drug effects, DNA Damage drug effects, Cortisone metabolism
Abstract: Cortisone can enter aquatic ecosystems and pose a risk to organisms therein. However, few studies have explored the effects of cortisone on the gut microbiota of aquatic organisms. Here, we exposed zebrafish (Danio rerio) to cortisone at environmentally relevant concentrations (5.0, 50.0, or 500.0 ng L -1 ) for 60 days to explore its toxicological effects and their association with gut microbiota changes. The terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick-end labeling assay revealed that exposure to 50 ng L -1 cortisone significantly increased the intestinal cell apoptosis rate, 8-hydroxydeoxyguanosine contents, and caspase-3 and caspase-8 activities. Moreover, the transcriptome analysis results demonstrated a notable downregulation in the expression of most differentially expressed genes associated with apoptosis pathways, as well as changes in DNA replication, oxidative stress, and drug metabolism pathways; these results indicated the occurrence of cortisone-induced stress response in zebrafish. Molecular docking analysis revealed that cortisone can bind to caspase-3 through hydrogen bonds and hydrophobic interactions but that no such interactions occur between cortisone and caspase-8. Thus, cortisone may induce oxidative DNA damage and apoptosis by activating caspase-3. Finally, the 16S rRNA sequencing results demonstrated that cortisone significantly affected microbial community structures and functions in the intestinal ecosystem. These changes may indicate gut microbiota response to cortisone-induced intestinal damage and inflammation. In conclusion, the current results clarify the mechanisms underlying intestinal response to cortisone exposure and provide a basis for evaluating the health risks of cortisone in animals., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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26. Integrating automated machine learning and metabolic reprogramming for the identification of microplastic in soil: A case study on soybean.

Author: Liu Z, Wang W, Geng Y, Zhang Y, Gao X, Xu J, and Liu X
Subjects: Herbicides analysis, Environmental Monitoring methods, Polyethylene, Soil chemistry, Metabolic Reprogramming, Glycine max metabolism, Glycine max drug effects, Soil Pollutants analysis, Soil Pollutants metabolism, Machine Learning, Microplastics toxicity, Microplastics analysis
Abstract: The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant quality and yield, as well as affect human health and food chain cycles. Therefore, developing rapid and effective detection methods is crucial. In this study, traditional machine learning (ML) and H2O automated machine learning (H2O AutoML) were utilized to offer a powerful framework for detecting PE-MPs (0.1 %, 1 %, and 2 % by dry soil weight) and the co-contamination of PE-MPs and fomesafen (a common herbicide) in soil. The development of the framework was based on the results of the metabolic reprogramming of soybean plants. Our study stated that traditional ML exhibits lower accuracy due to the challenges associated with optimizing complex parameters. H2O AutoML can accurately distinguish between clean soil and contaminated soil. Notably, H2O AutoML can detect PE-MPs as low as 0.1 % (with 100 % accuracy) and co-contamination of PE-MPs and fomesafen (with 90 % accuracy) in soil. The VIP and SHAP analyses of the H2O AutoML showed that PE-MPs and the co-contamination of PE-MPs and fomesafen significantly interfered with the antioxidant system and energy regulation of soybean. We hope this study can provide a reliable scientific basis for sustainable development of the environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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27. Size and isotope analysis of individual nanoparticles by multi-collector ICP-MS using "event-triggered signal capture" with a high-speed oscilloscope.

Author: Xing P, Belshaw NS, Dong J, Li L, Geng Y, Zheng H, Liu X, and Zhu Z
Abstract: Accurate quantitative elemental and isotope analysis of nanoparticles at the single-particle level is crucial for better understanding their origin, properties and behaviors. Single particle inductively coupled plasma-mass spectrometry (spICP-MS) has emerged as a promising technique for nanoparticle analysis. However, challenges persist in obtaining accurate and consistent element profiles and ratios for small-sized nanoparticles by conventional quadrupole (QMS) or time-of-flight mass analyzers (TOF-MS) due to their low level and transient nature. In this paper, we present a novel analytical method for single nanoparticle analysis using multiple collector ICP-MS (MC-ICP-MS) combined with a modern high-speed digital oscilloscope. The single particle events are acquired using an "event-triggered signal capture" (ETSC) technique, which enables the simultaneously capture and visualization of multiple isotopes of transient individual particle profiles with nanosecond time resolution. This greatly facilitates precise and efficient analysis of nanoparticles. The minimum detectable particle size is calculated to be as small as 8 nm (∼1 ag 109 Ag) for AgNPs. Based on the 109/107 Ag ratios obtained from 2000 particles, the precisions of 109/107 Ag ratio measurements on 20 nm, 40 nm, 60 nm, 80 nm and 100 nm were approximately 0.086 (SD), 0.063 (SD), 0.051 (SD), 0.040 (SD), and 0.029 (SD), which is limited by counting statistics of the isotopic signals. Furthermore, the achieved standard error of 109/107 Ag can be reduced to sub-permil level (0.7 ‰) even for the measurement of 20 nm AgNPs (N = 17,000). These results demonstrate that the ETSC provides a unique method for isotope analysis of single particles, holding great potential for enhancing our understanding of nanoparticles., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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28. Effects of potassium diformate on growth performance, apparent digestibility of nutrients, serum biochemical indices, and intestinal microflora in Cherry Valley ducks.

Author: Li M, Yuan X, Li L, Geng Y, Hong L, Pu L, Yang H, Li L, and Zhang J
Subjects: Animals, Female, Random Allocation, Nutrients metabolism, Dose-Response Relationship, Drug, Blood Chemical Analysis veterinary, Ducks growth & development, Ducks physiology, Animal Feed analysis, Diet veterinary, Digestion drug effects, Gastrointestinal Microbiome drug effects, Dietary Supplements analysis, Animal Nutritional Physiological Phenomena drug effects
Abstract: This study was performed to investigate the effects of potassium diformate (KDF) on growth performance, apparent digestibility of nutrients, serum biochemical indices, and intestinal microflora of Cherry Valley ducks. In total, 144 female healthy 1-day-old Cherry Valley ducks were divided into 3 groups with 6 replicates per group and 8 ducks per replicate according to the principle of similar body weight. The control group was fed a basic diet. In the 2 experimental groups, 0.8% and 1.2% KDF was added to the basic diet, respectively. The trial period was 6 wk and the pretrial period was 3 wk. The final weight and ADG were significantly higher in the 0.8% KDF group than in the control group (P < 0.05). The feed-to-gain ratio was significantly lower in both KDF groups than in the control group (P < 0.05). The apparent digestibility of CP was significantly higher in both KDF groups than in the control group (P < 0.05). The apparent digestibility of calcium was also significantly higher in the 0.8% KDF group (P < 0.05). The serum levels of alkaline phosphatase, cholesterol, and total protein were significantly lower in the 0.8% KDF group than in the control group (P < 0.05), the IgM content was significantly higher (P < 0.05), the low-density lipoprotein cholesterol, triglyceride, and urea levels were significantly lower (P < 0.01), and the glucose level was significantly higher (P < 0.01). The serum total protein level was significantly higher in the 1.2% KDF group than in the control group (P < 0.05). The relative abundance of Firmicutes and Patescibacteria in the gut of ducks was significantly higher in the 0.8% KDF group than in the control group (P < 0.05), the relative abundance of unclassified Erysipelotrichaceae and Lactobacillus was significantly higher (P < 0.01), and the relative abundance of Fusobacteriota was significantly lower (P < 0.05). However, the relative abundance of Firmicutes in the gut of ducks was significantly higher in the 1.2% KDF group than in the control group (P < 0.05). The relative abundance of unclassified Erysipelotrichaceae and Clostridium sensu stricto 1 was significantly higher (P < 0.01), as was the relative abundance of Fusobacteriota and Proteobacteria (P < 0.05). These findings indicate that the addition of 0.8% KDF to the diet can improve the growth performance of Cherry Valley ducks, promote the absorption of nutrients, change the structure of the microflora in the cecum, and increase the relative abundance of dominant bacteria. It was also shown that there was a significant difference between the 0.8% and 1.2% KDF levels which suggest that the safety margin for overdosing is quite low., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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29. Accelerated Hypofractionated Radiotherapy for Locally Advanced NSCLC: A Systematic Review From the International Association for the Study of Lung Cancer Advanced Radiation Technology Subcommittee.

Author: Said BI, Geng Y, Badiyan SN, Bang A, Bezjak A, Chua KLM, Faivre-Finn C, Kong FM, Przybysz D, Putora PM, Munoz-Schuffenegger P, Siva S, Xu-Welliver M, McDonald F, Louie A, and Chun SG
Abstract: Introduction: Accelerated hypofractionated radiotherapy has gained increasing interest for locally advanced NSCLC, as it can potentially increase radiobiologically effective dose and reduce health care resource utilization. Nevertheless, there is sparse prospective evidence supporting routine use of accelerated hypofractionation with or without concurrent chemotherapy. For this reason, the International Association for the Study of Lung Cancer Advanced Radiation Technology Subcommittee conducted a systematic review of prospective studies of accelerated hypofractionation for locally advanced NSCLC., Methods: A systematic search was conducted on Ovid MEDLINE, Ovid EMBASE, Wiley Cochrane Library, and ClinicalTrials.gov for English publications from 2010 to 2024 for prospective clinical trials and registries investigating accelerated hypofractionated radiotherapy defined as more than 2 Gy delivered in 10 to 25 fractions for nonmetastatic locally advanced (stage III) NSCLC., Results: There were 33 prospective studies identified that met the criteria for inclusion. Of 14 prospective studies evaluating definitive accelerated hypofractionation (without concurrent chemotherapy), there were six prospective registries, seven phase 1 to 2 trials, and one phase 3 randomized clinical trial, with a median dose of 60 Gy delivered in a median of 16 fractions, median progression-free survival of 6.4 to 25 months, median survival of 6 to 34 months, and 0% to 8% severe grade ≥3 esophagitis. There were 19 studies evaluating accelerated hypofractionated chemoradiation with platinum doublet-based chemotherapy as the most common concurrent regimen. Of these accelerated hypofractionated chemoradiation studies, there were 18 phase 1 to 2 trials and one prospective registry with a median radiation dose of 61.6 Gy delivered in a median of 23 fractions, median progression-free survival of 10 to 25 months, median survival of 13 to 38 months, grade ≥3 esophagitis of 0% to 23.5%, and grade ≥3 pneumonitis of 0% to 11.8%., Conclusions: Despite the increasing use of accelerated hypofractionation for locally advanced NSCLC, the supporting randomized evidence remains sparse. Only one randomized clinical trial comparing 60 Gy in 15 fractions with 60 Gy in 30 fractions without concurrent chemotherapy did not reveal the superiority of accelerated hypofractionation. Therefore, the use of accelerated hypofractionated radiotherapy should be approached with caution, using advanced radiation techniques, especially with concurrent chemotherapy or targeted agents. Accelerated hypofractionated radiotherapy should be carefully considered alongside other multidisciplinary options and be further investigated through prospective clinical trials., Competing Interests: Disclosure Dr. Chun is supported by grant R50CA275822 from the National Institutes of Health (content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health) and reports having financial relationships with AstraZeneca, Curio Science, Nektar Therapeutics, Elsevier, and the Binaytara Foundation. Dr. Bang reports receiving grant support from BC Cancer Foundation and having financial relationships with AstraZeneca and the International Association for the Study of Lung Cancer. Dr. Przybysz reports receiving grant funding from AstraZeneca and Astellas and having financial relationships with AstraZeneca, Astellas, UpToDate, and Guidepoint. Dr. Faivre-Finn reports receiving grant support from AstraZeneca, Merck, and Elekta. Dr. Badiyan reports receiving grant funding from AstraZeneca and having financial relationships with the RTOG Foundation, Elekta, and Reflexion. Dr. Bezjak reports having financial relationships with AstraZeneca and the Canadian Radiation Oncology Foundation. Dr. McDonald reports having financial relationships with AstraZeneca. Dr. Chua reports receiving grant support from the National Medical Research Council of Singapore and having financial relationships with Varian Medical Systems, AstraZeneca, Regeneron, Roche, Seagen, Merck Sharp & Dohme, and Takeda. Dr. Kong reports receiving grant support from Varian Medical and the Shenzhen Science and Technology Program and having financial relationships with AstraZeneca and Merck. Dr. Putora reports receiving grants from AstraZeneca, Takeda, and Bayer. Dr. Siva reports receiving grant support from the Cancer Council Victoria, Varian, Bayer, and Merck and having financial relationships with AstraZeneca, Roche, and Telix. Dr. Welliver reports receiving grant support from the United States Department of Defense and having financial relationships with Onclive and Eli Lilly. The remaining authors declare no conflict of interest., (Copyright © 2024 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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30. Exploring a traditional Chinese-medicine nursing method for preventing bladder spasm after transurethral resection of the prostate.

Author: Yu J, Geng Y, Tang J, and Qiao X
Subjects: Humans, Male, Medicine, Chinese Traditional methods, Spasm prevention & control, Spasm etiology, Postoperative Complications prevention & control, Postoperative Complications etiology, Transurethral Resection of Prostate methods
Abstract: Competing Interests: Declaration of competing interest All auyhors disclosed no ralevent relationships.
Published: 2024
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31. Delving into nitrogen and phosphorus dynamics in shallow eutrophic lakes: Multi-interface response to freeze-thaw cycles.

Author: Geng Y, Cao Z, Yu R, Li X, Sun H, and Wang X
Abstract: Assessing the impact of freeze-thaw cycles on nutrient transfer in lakes is crucial for addressing the global eutrophication of freshwater ecosystems in cold and arid regions. However, available information about the dynamics of nitrogen (N) and phosphorus (P) release during intact freeze-thaw cycles, especially in the sediment-porewater-water column continuum of lakes, is limited. This study collected the samples during ice-covered (January) and non-ice-covered (April, July, and October) periods. The changes in total nitrogen (TN) and total phosphorus (TP) were analyzed to estimate their release fluxes from the sediment-water interface. Both redundancy analysis (RDA) and variance partitioning analysis (VPA) were used to explore the effects of environmental variables on N and P. The results indicated that during the ice-covered period (ICP), the surface water content of different forms of N and P was lower than that of the overlying water, whereas the opposite was true during the non-ice-covered period (NICP). The overall trend for the different forms of N was TN > DIN > NH 4 -N > NO 3 -N > NO 2 -N, and for P, it was TP > PP > DTP > DOP>DIP. The vertical profiles of the porewater TN and TP generally demonstrated an increase followed by a decrease from the surface to the bottom, with an inflection point at 15 cm. Sediment TN and TP trends over time matched porewater trends, with both being spatially highest at the lake inlet. ICP sediments acted as sinks for TN and TP, and NICP sediments acted as sources. N and P in the water column were significantly correlated mainly with physicochemical indicators, whereas sediment contributed positively to TN and TP in the porewater. VPA indicated that environmental factors explained 46.45 % of the variation in TN and TP in the porewater. These findings emphasize the importance of freeze-thaw cycling processes in driving N and P nutrient enrichment, source-sink effects, and multi-media coupling in shallow lakes in arid plateau regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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32. Artificial Intelligence and Machine Learning in Cancer Pain: A Systematic Review.

Author: Salama V, Godinich B, Geng Y, Humbert-Vidan L, Maule L, Wahid KA, Naser MA, He R, Mohamed ASR, Fuller CD, and Moreno AC
Subjects: Humans, Artificial Intelligence, Cancer Pain classification, Cancer Pain diagnosis, Cancer Pain therapy, Machine Learning, Pain Management methods
Abstract: Background/objectives: Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain management in cancer., Methods: A comprehensive search of Ovid MEDLINE, EMBASE and Web of Science databases was conducted using terms: "Cancer," "Pain," "Pain Management," "Analgesics," "Artificial Intelligence," "Machine Learning," and "Neural Networks" published up to September 7, 2023. AI/ML models, their validation and performance were summarized. Quality assessment was conducted using PROBAST risk-of-bias andadherence to TRIPOD guidelines., Results: Forty four studies from 2006 to 2023 were included. Nineteen studies used AI/ML for classifying pain after cancer therapy [median AUC 0.80 (range 0.76-0.94)]. Eighteen studies focused on cancer pain research [median AUC 0.86 (range 0.50-0.99)], and 7 focused on applying AI/ML for cancer pain management, [median AUC 0.71 (range 0.47-0.89)]. Median AUC (0.77) of models across all studies. Random forest models demonstrated the highest performance (median AUC 0.81), lasso models had the highest median sensitivity (1), while Support Vector Machine had the highest median specificity (0.74). Overall adherence to TRIPOD guidelines was 70.7%. Overall, high risk-of-bias (77.3%), lack of external validation (14%) and clinical application (23%) was detected. Reporting of model calibration was also missing (5%)., Conclusion: Implementation of AI/ML tools promises significant advances in the classification, risk stratification, and management decisions for cancer pain. Further research focusing on quality improvement, model calibration, rigorous external clinical validation in real healthcare settings is imperative for ensuring its practical and reliable application in clinical practice., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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33. HD-Former: A hierarchical dependency Transformer for medical image segmentation.

Author: Wu H, Min W, Gai D, Huang Z, Geng Y, Wang Q, and Chen R
Subjects: Humans, Image Processing, Computer-Assisted methods, Algorithms, Neural Networks, Computer
Abstract: Medical image segmentation is a compelling fundamental problem and an important auxiliary tool for clinical applications. Recently, the Transformer model has emerged as a valuable tool for addressing the limitations of convolutional neural networks by effectively capturing global relationships and numerous hybrid architectures combining convolutional neural networks (CNNs) and Transformer have been devised to enhance segmentation performance. However, they suffer from multilevel semantic feature gaps and fail to account for multilevel dependencies between space and channel. In this paper, we propose a hierarchical dependency Transformer for medical image segmentation, named HD-Former. First, we utilize a Compressed Bottleneck (CB) module to enrich shallow features and localize the target region. We then introduce the Dual Cross Attention Transformer (DCAT) module to fuse multilevel features and bridge the feature gap. In addition, we design the broad exploration network (BEN) that cascades convolution and self-attention from different percepts to capture hierarchical dense contextual semantic features locally and globally. Finally, we exploit uncertain multitask edge loss to adaptively map predictions to a consistent feature space, which can optimize segmentation edges. The extensive experiments conducted on medical image segmentation from ISIC, LiTS, Kvasir-SEG, and CVC-ClinicDB datasets demonstrate that our HD-Former surpasses the state-of-the-art methods in terms of both subjective visual performance and objective evaluation. Code: https://github.com/barcelonacontrol/HD-Former., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
Published: 2024
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34. Efficient and harmless removal of insecticide diazinon via the stepwise combination of biodegradation and photodegradation.

Author: Geng Y, Zha W, Lv J, Jiao W, Zhang Y, Ma X, Wu X, Hua R, and Fang L
Subjects: Water Pollutants, Chemical metabolism, Water Pollutants, Chemical chemistry, Animals, Diazinon metabolism, Diazinon toxicity, Diazinon chemistry, Biodegradation, Environmental, Insecticides metabolism, Insecticides toxicity, Insecticides chemistry, Photolysis
Abstract: Diazinon, an organophosphorus insecticide, is predominantly removed through photodegradation and biodegradation in the environment. However, photodegradation can generate diazoxon, a highly toxic oxidation byproduct, while biodegradation is hard to complete mineralize diazinon, showing limitations in both methods. In this study, we provided an efficient strategy for the complete and harmless removal of diazinon by synergistically employing biodegradation and photodegradation. The diazinon-degrading strain X1 was capable of completely degrading 200 μM of diazinon into 2-isopropyl-6-methyl-4-pyrimidinol (IMP) within 6 h without producing the highly toxic diazoxon. IMP was the only intermediate metabolite in biodegradation process, which cannot be further degraded by strain X1. Through RT-qPCR and prokaryotic expression analyses, the hydrolase OpdB was pinpointed as the key enzyme for diazinon degradation in strain X1. Photodegradation was further used to degrade IMP and a pyridazine ring-opening product of IMP was identified via high resolution mass spectrometry. The acute toxicity of this product to aquatic organisms were 123 times and 6630 times lower than that of diazinon and IMP, respectively. The stepwise application of biodegradation and photodegradation was proved to be a successful approach for the remediation of diazinon and its metabolite IMP. This integrated method ensures the harmless and complete elimination of diazinon and IMP within only 6 h. The research provides a theoretical basis for the efficient and harmless remediation of organophosphorus insecticide residuals in the environment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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35. The roles of rare and abundant microbial species in the primary succession of biological soil crusts are differentiated in metal tailings ponds with different states.

Author: Geng Y, Zhou P, Wang Z, Peng C, Li G, and Li D
Subjects: Ponds microbiology, Metals, Heavy analysis, Soil Pollutants analysis, Bacteria classification, Soil chemistry, Industrial Waste, Microbiota, Soil Microbiology
Abstract: Tailings ponds formed by long-term accumulation of mineral processing waste have become a global environmental problem. Even worse, tailings ponds are often simply abandoned or landfilled after they cease to be used. This allows pollution to persist and continue to spread in the environment. The significance of primary succession mediated by biological soil crusts for tailings pond remediation has been illustrated by previous studies. However, the process of primary succession may not be the same at different stages during the lifetime of tailings ponds. Therefore, we investigated the environmental differences and the successional characteristics of microbial communities in the primary successional stage of tailings ponds at three different states. The results showed that the primary succession process positively changed the environment of tailings ponds in any state of tailings ponds. The primary successional stage determined the environmental quality more than the state of the tailings pond. In the recently abandoned tailings ponds, abundant species were more subjected to heavy metal stress, while rare species were mainly limited by nutrient content. We found that as the succession progressed, rare species gradually acquired their own community space and became more responsive to environmental stresses. Rare species played an important role in microbial keystone species groups., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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36. Preparation and evaluation of microencapsulated delivery system of recombinant interferon alpha protein from rainbow trout.

Author: Ouyang P, Li Y, Wei W, Li Q, Liu J, MaYang, Li S, Zhou Y, Chen D, Geng Y, and Huang X
Subjects: Animals, Capsules, Antiviral Agents pharmacology, Antiviral Agents chemistry, Drug Compounding, Chitosan chemistry, Chitosan analogs & derivatives, Infectious hematopoietic necrosis virus drug effects, Drug Delivery Systems, Fish Diseases virology, Fish Diseases drug therapy, Oncorhynchus mykiss virology, Interferon-alpha pharmacology, Recombinant Proteins pharmacology
Abstract: Diseases caused by viruses pose a significant risk to the health of aquatic animals, for which there are presently no efficacious remedies. Interferon (IFN) serving as an antiviral agent, is frequently employed in clinical settings. Due to the unique living conditions of aquatic animals, traditional injection of interferon is cumbersome, time-consuming and labor-intensive. This study aimed to prepare IFN microcapsules through emulsion technique by using resistant starch (RS) and carboxymethyl chitosan (CMCS). Optimization was achieved using the Box-Behnken design (BBD) response surface technique, followed by the creation of microcapsules through emulsification. With RS at a concentration of 1.27 %, a water‑oxygen ratio of 3.3:7.4, CaCl 2 at 13.67 %, CMCS at 1.04 %, the rate of encapsulation can escalate to 80.92 %. Rainbow trout infected with Infectious hematopoietic necrosis virus (IHNV) and common carp infected with Spring vireemia (SVCV) exhibited a relative survival rate (RPS) of 65 % and 60 % after treated with IFN microcapsules, respectively. Moreover, the microcapsules effectively reduced the serum AST levels and enhanced the expression of IFNα, IRF3, ISG15, MX1, PKR and Viperin in IHNV-infected rainbow trout and SVCV-infected carp. In conclusion, this integrated IFN microcapsule showed potential as an antiviral agent for treatment of viral diseases in aquaculture., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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37. Resourceful application and mechanism of oyster shell-microalgae synergistic system：Sustainable treatment of harsh low carbon nitrogen ratio actual wastewater.

Author: Geng Y, Yang L, Lian CA, Pavlostathis SG, Qiu Z, Xiong Z, Liu Y, Li B, Hu J, Fan W, Luo X, and Yu K
Subjects: Animals, Water Pollutants, Chemical analysis, Nitrogen analysis, Nitrogen metabolism, Microalgae growth & development, Wastewater chemistry, Ostreidae, Carbon, Animal Shells chemistry, Waste Disposal, Fluid methods
Abstract: Microalgal technology holds great promise for both low C/N wastewater treatment and resource recovery simultaneously. Nevertheless, the advancement of microalgal technology is hindered by its reduced nitrogen removal efficiency in low C/N ratio wastewater. In this work, microalgae and waste oyster shells were combined to achieve a total inorganic nitrogen removal efficiency of 93.85% at a rate of 2.05 mg L -1 h -1 in low C/N wastewater. Notably, over four cycles of oyster shell reuse, the reactor achieved an average 85% ammonia nitrogen removal extent, with a wastewater treatment cost of only $0.092/ton. Moreover, microbial community analysis during the reuse of oyster shells revealed the critical importance of timely replacement in inhibiting the growth of non-functional bacteria (Poterioochromonas_malhamensi). The work demonstrated that the oyster shell - microalgae system provides a time- and cost-saving, environmental approach for the resourceful treatment of harsh low C/N wastewater., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)
Published: 2024
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38. Different microbial functional traits drive bulk and rhizosphere soil phosphorus mobilization in an alpine meadow after nitrogen input.

Author: Han B, He Y, Chen J, Wang Y, Shi L, Lin Z, Yu L, Wei X, Zhang W, Geng Y, Shao X, and Jia S
Subjects: Microbiota, Phosphorus analysis, Soil Microbiology, Rhizosphere, Nitrogen metabolism, Nitrogen analysis, Grassland, Soil chemistry
Abstract: Enhanced nitrogen (N) input is expected to influence the soil phosphorus (P) cycling through biotic and abiotic factors. Among these factors, soil microorganisms play a vital role in regulating soil P availability. However, the divergent contribution of functional microorganisms to soil P availability in the rhizosphere and bulk soil under N addition remains unclear. We conducted an N addition experiment with four N input rates (0, 5, 10, and 15 g N m -2 year -1 ) in an alpine meadow over three years. Metagenomics was employed to investigate the functional microbial traits in the rhizosphere and bulk soil. We showed that N addition had positive effects on microbial functional traits related to P-cycling in the bulk and rhizosphere soil. Specifically, high N addition significantly increased the abundance of most microbial genes in the bulk soil but only enhanced the abundance of five genes in the rhizosphere soil. The soil compartment, rather than the N addition treatment, was the dominant factor explaining the changes in the diversity and network of functional microorganisms. Furthermore, the abundance of functional microbial genes had a profound effect on soil available P, particularly in bulk soil P availability driven by the ppa and ppx genes, as well as rhizosphere soil P availability driven by the ugpE gene. Our results highlight that N addition stimulates the microbial potential for soil P mobilization in alpine meadows. Distinct microbial genes play vital roles in soil P availability in bulk and rhizosphere soil respectively. This indicates the necessity for models to further our knowledge of P mobilization processes from the bulk soil to the rhizosphere soil, allowing for more precise predictions of the effects of N enrichment on soil P cycling., Competing Interests: Declaration of competing interest We would like to submit the enclosed manuscript entitled “Different microbial functional traits drive bulk and rhizosphere soil phosphorus mobilization in an alpine meadow after nitrogen input” to Science of the Total Environment. This manuscript, or any part of it, has not been published and will not be submitted elsewhere for publication while being considered by Science of the Total Environment. The authors declare that there are no competing financial interests. All authors of this paper have directly participated in this manuscript and approved the final version submitted., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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39. A novel ESIPT fluorescent probe for early detection and assessment of ferroptosis-mediated acute kidney injury via peroxynitrite fluctuation.

Author: Chen M, Lin S, Tang B, Tian T, Leng Y, Liu D, Wang K, Geng Y, Luo Z, Shen L, and Chen T
Subjects: Animals, Mice, Humans, Optical Imaging, Molecular Structure, Early Diagnosis, Ferroptosis drug effects, Fluorescent Dyes chemistry, Fluorescent Dyes chemical synthesis, Peroxynitrous Acid metabolism, Acute Kidney Injury chemically induced, Zebrafish
Abstract: Background: Acute kidney injury (AKI) poses a severe risk to public health, mostly manifested by damage and death of renal tubular epithelial cells. However, routine blood examination, a conventional approach for clinical detection of AKI, is not available for identifying early-stage AKI. Plenty of reported methods were lack of early biomarkers and real time evaluation tools, which resulted in a vital challenge for early diagnosis of AKI. Therefore, developing novel probes for early detection and assessment of AKI is exceedingly crucial., Results: Based on ESIPT mechanism, a new fluorescent probe (MEO-NO) with 2-(2'-hydroxyphenyl) benzothiazole (HBT) derivatives as fluorophore has been synthesized for dynamic imaging peroxynitrite (ONOO - ) levels in ferroptosis-mediated AKI. Upon the addition of ONOO - , MEO-NO exhibited obvious fluorescence changes, a significant Stokes shift (130 nm) and rapid response (approximately 45 s), and featured exceptional sensitivity (LOD = 7.28 nM) as well as high selectivity from the competitive species at physiological pH. In addition, MEO-NO was conducive to the biological depth imaging ONOO - in cells, zebrafish, and mice. Importantly, MEO-NO could monitor ONOO - levels during sorafenib-induced ferroptosis and CP-induced AKI. With the assistance of MEO-NO, we successfully visualized and tracked ONOO - variations for early detection and assessment of ferroptosis-mediated AKI in cells, zebrafish and mice models., Significance and Novelty: Benefiting from the superior performance of MEO-NO, experimental results further demonstrated that the levels of ONOO - was overexpressed during ferroptosis-mediated AKI in cells, zebrafish, and mice models. The developed novel probe MEO-NO provided a strong visualization tool for imagining ONOO - , which might be a potential method for the prevention, diagnosis, and treatment of ferroptosis-mediated AKI., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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40. Association between the proportion of HDL-Cholesterol subclasses and the severity of coronary artery stenosis in patients with Acute Myocardial Infarction.

Author: Geng Y, Wang B, Liu L, Lv C, Qian H, Lv T, and Zhang P
Abstract: Background: Past research has shown an inverse correlation between high-density lipoprotein (HDL) and coronary heart disease (CHD), while recent studies have shown that extremely high or low HDL levels increase the risk of cardiovascular death., Objective: To explore the relationships between HDL subtypes and the degree of coronary artery stenosis in patients with acute myocardial infarction (AMI)., Methods: This was a single-center cross-sectional study. Ultimately, we included 1,200 adult participants with AMI hospitalized from 2017 to 2023. Patients were classified into mild and moderate-severe groups according to their Gensini score. Restricted cubic spline and multivariate logistic regression models were used to explore the associations between HDL subclasses and the severity of coronary stenosis., Results: The adjusted odds ratios (ORs), 95 % confidence intervals (CIs), and p values for HDL subclasses in the multivariate logistic model (adjusted for age, gender, hypertension status, diabetes status, stroke status, and kidney disease status) were as follows: HDL-2b: 0.97 (0.95-1.00, p= 0.018) and HDL-3: 0.98 (0.97-0.99, p= 0.008). Subgroup analysis revealed that HDL-3 exhibited a statistically significant impact on the severity of coronary stenosis among individuals aged <75 years of age and among men, and the influence of HDL-2b on the severity of coronary stenosis was statistically significant only in individuals aged ≥75 years., Conclusion: The relationship between reduced levels of HDL-2b and HDL-3 and the risk of coronary stenosis exhibited a linear pattern and was significantly modified by age. Subgroup analysis identified specific populations that warrant attention regarding HDL-2b and HDL-3., Competing Interests: Declaration of competing interest All authors declare no potential conflicts of interest in this work., (Copyright © 2024. Published by Elsevier Inc.)
Published: 2024
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41. Infantile fibrosarcoma in the mediastinum: A rare case report.

Author: Xie M, Geng Y, Zhang J, and Gan L
Subjects: Humans, Infant, Male, Female, Tomography, X-Ray Computed, Fibrosarcoma surgery, Fibrosarcoma pathology, Fibrosarcoma diagnostic imaging, Fibrosarcoma diagnosis, Mediastinal Neoplasms pathology, Mediastinal Neoplasms surgery, Mediastinal Neoplasms diagnostic imaging, Mediastinal Neoplasms diagnosis
Abstract: Competing Interests: Declaration of competing interest The authors declare that they have no competing interests.
Published: 2024
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42. Construction of a pectin/sodium alginate composite hydrogel delivery system for improving the bioaccessibility of phycocyanin.

Author: Li Z, Geng Y, Bu K, Chen Z, Xu K, and Zhu C
Subjects: Drug Delivery Systems, Drug Liberation, Biological Availability, Animals, Alginates chemistry, Pectins chemistry, Phycocyanin chemistry, Hydrogels chemistry, Drug Carriers chemistry
Abstract: In this study, different concentrations of sodium alginate were compounded with pectin and phycocyanin to co-prepare composite hydrogel spheres (HP-PC-SA 0.2 %, 0.6 %, 1.0 %, 1.4 %) to evaluate the potential of the composite hydrogel spheres for the application as phycocyanin delivery carriers. The hydrogel spheres' physicochemical properties and bioaccessibility were assessed through scanning electron microscopy, textural analysis, drug-carrying properties evaluation, and in vitro and in vivo controlled release analysis in the gastrointestinal environment. Results indicated that higher sodium alginate concentrations led to smaller pore sizes and denser networks on the surface of hydrogel spheres. The textural properties of hydrogel spheres improved, and their water-holding capacity increased from 93.01 % to 97.97 %. The HP-PC-SA (1.0 %) formulation achieved the highest encapsulation rate and drug loading capacity, at 96.87 % and 6.22 %, respectively. Within the gastrointestinal tract, the composite hydrogel's structure significantly enhanced and protected the phycocyanin's digestibility, achieving a bioaccessibility of up to 88.03 %. In conclusion, our findings offer new insights into improving functionality and the effective use of phycocyanin via pectin-based hydrogel spheres., Competing Interests: Declaration of competing interest The authors declare no conflict of interest related to the publication of this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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43. Binding patterns of inhibitors to different pockets of kinesin Eg5.

Author: Jia N, Zhang B, Huo Z, Qin J, Ji Q, and Geng Y
Subjects: Binding Sites, Humans, Adenosine Diphosphate metabolism, Adenosine Diphosphate chemistry, Hydrogen Bonding, Kinesins antagonists & inhibitors, Kinesins chemistry, Kinesins metabolism, Molecular Dynamics Simulation, Protein Binding
Abstract: The kinesin-5 family member, Eg5, plays very important role in the mitosis. As a mitotic protein, Eg5 is the target of various mitotic inhibitors. There are two targeting pockets in the motor domain of Eg5, which locates in the α2/L5/α3 region and the α4/α6 region respectively. We investigated the interactions between the different inhibitors and the two binding pockets of Eg5 by using all-atom molecular dynamics method. Combined the conformational analysis with the free-energy calculation, the binding patterns of inhibitors to the two binding pockets are shown. The α2/L5/α3 pocket can be divided into 4 regions. The structures and binding conformations of inhibitors in region 1 and 2 are highly conserved. The shape of α4/α6 pocket is alterable. The space of this pocket in ADP-binding state of Eg5 is larger than that in ADP·Pi-binding state due to the limitation of a hydrogen bond formed in the ADP·Pi-binding state. The results of this investigation provide the structural basis of the inhibitor-Eg5 interaction and offer a reference for the Eg5-targeted drug design., (Copyright © 2024 Elsevier Inc. All rights reserved.)
Published: 2024
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44. The influence of microtopography to road inundation caused by extreme flood.

Author: Geng Y, Zhong Y, Huang X, Liu P, and Wang Z
Abstract: Microtopography plays a critical role in road inundation during urban flood events. The microtopography in this paper was defined as terrain-scale features that encompass surface roughness, slope, road network and urban building layout. This paper aims to explore the mechanism of depression storage and road inundation under different microtopography. Simulations under 4 rainfall intensities (144.0- 182.88 mm/h) and 14 slope combinations (four transverse slope and five longitudinal slope) were implemented in an 800 by 70 cm local model. The correlation heat map directly reflected that longitudinal slope had higher influence on drainage than other factors. Then real topographical and hydrological data was applied to predict road inundation with five different extreme rainfall events in Jiangning District (Nanjing City, China). The microtopography characteristics of frequent inundation road were extracted, which further verified the conclusions of the local model. Results show that: the microtopography depressions drainage process could be divided into six main stages: filling stage, interaction stage, unstable drainage stage, stable flow stage, drainage stage and stage of drainage end. Water was stored on depressions of road, and the storage volume and discharge efficiency were affected by the surface relief and slope. The emergence of slope provided an altered path and power for water drainage. Only 0.3 % slope could contribute a 28.4 % to discharge efficiency. Upon comparation, the best combination for drainage was 2.0 % transverse slope with 3.0 % longitudinal slope. These findings provided meaningful insights and perspectives for urban flood hazard mitigation and were a more detailed reference for road design., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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45. Characterizing the regional distribution, interaction with microorganisms, and sources of dissolved organic matter for summer rainfall: Insights from spectroscopy, community structure, and back-trajectory analyses.

Author: Wu C, Zhao Y, Geng Y, Shi K, and Zhou S
Subjects: Spectrometry, Fluorescence, Water Quality, Organic Chemicals analysis, Humic Substances analysis, Dissolved Organic Matter, Rivers chemistry
Abstract: Dissolved organic matter (DOM) in rainfall participates in many biogeochemical cycles in aquatic environments and affects biological activities in water bodies. Revealing the characteristics of rainfall DOM could broaden our understanding of the carbon cycle. Therefore, the distribution characteristics and response mechanisms of DOM to microorganisms were investigated in different regions of Hebei. The results indicated that the water quality of the northern region was worse than that of the middle and southern regions. The two protein like components (C1, C2) and one humic like component (C3) were obtained; at high molecular weight (MW), the fluorescence intensity is high in the northern region (0.03 ± 0.02 R.U.), while at low MW, the fluorescence intensity is highest in the southern region (0.50 ± 0.18 R.U.). Furthermore, C2 is significantly positively correlated with C1 (P < 0.01), while C2 is significantly negatively correlated with C3 (P < 0.05) was observed. The spectral index results indicated that rainfall DOM exhibited low humification and highly autochthonous characteristics. The southern region obtained higher richness and diversity of microbial species than northern region (P < 0.05). The community exhibits significant spatiotemporal differences, and the Acinetobacter, Enterobacter, and Massilia, were dominant genus. Redundancy and network analyses showed that the effects of C1, C2, and nitrate on microorganisms increased with decreasing MW, while low MW exhibited a more complex network between DOM and microorganisms than high MW. Meanwhile, C1, C2 had a large total effect on β-diversity and function through structural equation modeling. The backward trajectory model indicates that the sources of air masses are from the northwest, local area, and sea in the northern, middle, and southern regions, respectively. This study broadened the understanding of the composition of summer rainfall DOM and its interactions with microorganisms during rainfall., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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46. Late gestational exposure to fenvalerate impacts ovarian reserve in neonatal mice via YTHDF2-mediated P-body assembly.

Author: He F, Mu X, Zhang Y, Wang Y, Geng J, Geng Y, Ma Y, Yin X, Gao R, Chen X, and He J
Subjects: Humans, Pregnancy, Animals, Female, Mice, Adult, Animals, Newborn, Processing Bodies, Oocytes metabolism, Mammals metabolism, Methyltransferases, RNA-Binding Proteins, Ovarian Reserve, Pyrethrins toxicity, Pyrethrins metabolism, Nitriles
Abstract: Fenvalerate (FEN), a type II pyrethroid pesticide, finds extensive application in agriculture, graziery and public spaces for pest control, resulting in severe environmental pollution. As an environmental endocrine disruptor with estrogen-like activity, exposure to FEN exhibited adverse effects on ovarian functions. Additionally, the presence of the metabolite of FEN in women's urine shows a positive association with the risk of primary ovarian insufficiency (POI). In mammals, the primordial follicle pool established during the early life serves as a reservoir for storing all available oocytes throughout the female reproductive life. The initial size of the primordial follicle pool and the rate of its depletion affect the occurrence of POI. Nevertheless, there is very limited research about the impact of FEN exposure on primordial folliculogenesis. In this study, pregnant mice were orally administrated with 0.2, 2.0 and 20.0 mg/kg FEN from 16.5 to 18.5 days post-coitus (dpc). Ovaries exposed to FEN exhibited the presence of large germ-cell cysts that persist on 1 days post-parturition (1 dpp), followed by a significant reduction in the total number of oocytes in pups on 5 dpp. Moreover, the levels of m6A-RNA and its associated proteins METTL3 and YTHDF2 were significantly increased in the ovaries exposed to FEN. The increased YTHDF2 promoted the assembly of the cytoplasmic processing bodies (P-body) in the oocytes, accompanied with altered expression of transcripts. Additionally, when YTHDF2 was knocked-down in fetal ovary cultures, the primordial folliculogenesis disrupted by FEN exposure was effectively restored. Further, the female offspring exposed to FEN displayed ovarian dysfunctions reminiscent of POI in early adulthood, characterized by decreases in ovarian coefficient and female hormone levels. Therefore, the present study revealed that exposure to FEN during late pregnancy disrupted primordial folliculogenesis by YTHDF2-mediated P-body assembly, causing enduring adverse effects on female fertility., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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47. SDMI-Net: Spatially Dependent Mutual Information Network for semi-supervised medical image segmentation.

Author: Gai D, Huang Z, Min W, Geng Y, Wu H, Zhu M, and Wang Q
Subjects: Humans, Neural Networks, Computer, Algorithms, Databases, Factual, Image Processing, Computer-Assisted methods
Abstract: Semi-supervised medical image segmentation strives to polish deep models with a small amount of labeled data and a large amount of unlabeled data. The efficiency of most semi-supervised medical image segmentation methods based on voxel-level consistency learning is affected by low-confidence voxels. In addition, voxel-level consistency learning fails to consider the spatial correlation between neighboring voxels. To encourage reliable voxel-level consistent learning, we propose a dual-teacher affine consistent uncertainty estimation method to filter out some voxels with high uncertainty. Moreover, we design the spatially dependent mutual information module, which enhances the spatial dependence between neighboring voxels by maximizing the mutual information between the local voxel blocks predicted from the dual-teacher models and the student model, enabling consistent learning at the block level. On two benchmark medical image segmentation datasets, including the Left Atrial Segmentation Challenge dataset and the BraTS-2019 dataset, our method achieves state-of-the-art performance in both quantitative and qualitative aspects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
Published: 2024
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48. Maternal exposure to beta-Cypermethrin disrupts placental development by dysfunction of trophoblast cells from oxidative stress.

Author: Tang X, Geng Y, Gao R, Chen Z, Mu X, Zhang Y, Yin X, Ma Y, Chen X, Li F, and He J
Subjects: Female, Pregnancy, Animals, Mice, Humans, Maternal Exposure adverse effects, Placentation drug effects, Cell Line, Placenta drug effects, Placenta pathology, Placenta metabolism, Apoptosis drug effects, Pyrethrins toxicity, Trophoblasts drug effects, Trophoblasts pathology, Trophoblasts metabolism, Oxidative Stress drug effects, Insecticides toxicity
Abstract: As a broad-spectrum and efficient insecticide, beta-Cypermethrin (β-CYP) poses a health risk to pregnancy. It matters the mechanisms of maternal exposure to β-CYP for impacting reproductive health. The placenta, a transient organ pivotal for maternal-fetal communication during pregnancy, plays a crucial role in embryonic development. The effect of β-CYP exposure on the placenta and its underlying molecular mechanisms remain obscure. The objective of this study was to investigate the effect of β-CYP exposure on placental development and the function of trophoblast, as well as the underlying mechanisms through CD-1 mouse model (1, 10, 20 mg/kg.bw) and in vitro HTR-8/SVneo cell model (12.5, 25, 50, 100 μM). We found slower weight gain and reduced uterine wet weight in pregnant mice with maternal exposure to β-CYP during pregnancy, as well as adverse pregnancy outcomes such as uterine bleeding and embryo resorption. The abnormal placental development in response to β-CYP was noticed, including imbalanced placental structure and disrupted labyrinthine vascular development. Trophoblasts, pivotal in placental development and vascular remodeling, displayed abnormal differentiation under β-CYP exposure. This aberration was characterized by thickened trophoblast layers in the labyrinthine zone, accompanied by mitochondrial and endoplasmic reticulum swelling within trophoblasts. Further researches on human chorionic trophoblast cell lines revealed that β-CYP exposure induced apoptosis in HTR-8/SVneo cells. This induction resulted in a notable decrease in migration and invasion abilities, coupled with oxidative stress and the inhibition of the Notch signaling pathway. N-acetylcysteine (an antioxidant) partially restored the impaired Notch signaling pathway in HTR-8/SVneo cells, and mitigated cellular functional damage attributed to β-CYP exposure. Collectively, exposure to β-CYP induced oxidative stress and then led to inhibition of the Notch signaling pathway and dysfunction of trophoblast cells, ultimately resulted in abnormal placenta and pregnancy. These findings indicate Reactive Oxygen Species as potential intervention targets to mitigate β-CYP toxicity. The comprehensive elucidation contributes to our understanding of β-CYP biosafety and offers an experimental basis for preventing and managing its reproductive toxicity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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49. Removal of dyes from wastewater using Eucalyptus wood fiber loaded nanoscale zero-valent iron: Characterization and removal mechanism.

Author: Qiu D, Geng Y, Geng J, Du H, and Chang J
Subjects: Adsorption, Kinetics, Metal Nanoparticles chemistry, Hydrogen-Ion Concentration, Congo Red chemistry, Congo Red isolation & purification, Rhodamines chemistry, Eucalyptus chemistry, Wastewater chemistry, Wood chemistry, Coloring Agents chemistry, Coloring Agents isolation & purification, Iron chemistry, Water Pollutants, Chemical chemistry, Water Pollutants, Chemical isolation & purification, Water Purification methods
Abstract: Wood fiber as a natural and renewable material has low cost and plenty of functional groups, which owns the ability to adsorb dyes. In order to improve the application performance of wood fiber in dye-pollution wastewater, Eucalyptus wood fiber loaded nanoscale zero-valent iron (EWF-nZVI) was developed to give EWF magnetism and the ability to degrade dyes. EWF-nZVI was characterized via FTIR, XRD, zeta potential, VSM, SEM-EDS and XPS. Results showed that EWF-nZVI owned a strong magnetism of 96.51 emu/g. The dye removal process of EWF-nZVI was more in line with the pseudo-second-order kinetics model. In addition, the Langmuir isotherm model fitting results showed that the maximum removal capacities of Congo red and Rhodamine B by EWF-nZVI were 714.29 mg/g and 68.49 mg/g at 328 K, respectively. After five adsorption-desorption cycles, the regeneration efficiencies of Congo red and Rhodamine B were 74 % and 42 % in turn. The dye removal mechanisms of EWF-nZVI included redox degradation (Congo red and Rhodamine B) and electrostatic adsorption (Congo red). In summary, EWF-nZVI is a promising biomass-based material with high dye removal capacities. This work is beneficial to promote the large-scale application of wood fiber in water treatment., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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50. Quantifying chemical correlations between fruits and processed fruit products: A non-targeted analysis approach.

Author: Wang RQ, Geng Y, Zhou NJ, Song JN, Yu HD, Liu YR, Yue ZG, Li RQ, Chang Q, Xu XJ, Yang CQ, Wang JK, and Tang ZS
Subjects: Flavonoids analysis, Fruit and Vegetable Juices analysis, Fruit chemistry, Beverages analysis
Abstract: Juices and beverages are produced by industry for long-distance distribution and shelf-stability, providing valuable nutrients. However, their nutritional value is often underestimated due to insufficient analytical methods. We have employed non-targeted analysis through a standardized analytical protocol, taking advantage of Data Independent Acquisition (DIA) technique and a novel Chromatographic Retention Behavior (CRB) data deconvolution algorithm. After analyzing 9 fruits and their products, correlations between fruits and their juices are accurately digitalized by similarities of their LC-MS fingerprints. We also specify non-targeted molecules primarily associate with nutrient loss in these analyzed juice products, including nitrogenous nutrients, flavonoids, glycosides, and vitamins. Moreover, we unveiled previously unreported fruit-characteristic metabolites, of which reconstituted-from-concentrate (RFC) juices contain over 40% of the content found in their fresh counterparts. Conclusively, our method establishes a quantitative benchmark for rational selection of RFC juices to substitute natural fruits., Competing Interests: Declaration of competing interest Except Huai-Dong Yu is an advisor and cofounder to Gezhu Bio. Co., Ltd. Beijing, Peoples R. China, the remaining authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)
Published: 2024
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