Most existing studies provide coarse spatial resolution mappings(typically 1 km or more),which fail to capture local-scale heterogeneity of permafrost distribution in the permafrost boundary region.This study employed...Most existing studies provide coarse spatial resolution mappings(typically 1 km or more),which fail to capture local-scale heterogeneity of permafrost distribution in the permafrost boundary region.This study employed 298 ground-truth samples to evaluate six machine learning(ML)algorithms for simulating permafrost distribution in the Genhe River Basin(GRB)of the Greater Khingan Mountains(GKM)based on our detailed investigation(e.g.,16 boreholes)in this region conducted in 2023-2024,while identifying key environmental drivers through Shapley Additive Explanations(SHAP)analysis.Results show that the random forest(RF)model achieved the best performance,with a classification accuracy of 0.83 and a Kappa coefficient of 0.66.The RF-based permafrost map at a 30 m resolution reveals a total permafrost area of approximately 8248.5 km2,accounting for 52.0%of the GRB.The most influential predictors of permafrost distribution are slope(SLO),topographic wetness index(TWI),and degree of topographic relief(DTR),contributing 13.6%,11.1%,and 9.4%,respectively.Other important factors include normalized difference water index(NDWI,6.8%)and land surface temperature(LST,6.1%).Permafrost is mainly distributed in valley bottoms,toe slopes,and gently sloping areas in the upper and middle reaches of the basin.These zones are closely associated with vegetation types such as wetlands,shrubs,and larch forests.Conversely,permafrost is rarely found in croplands or on steep slopes.These findings improve the understanding of permafrost distribution patterns in the transitional zone of Northeast China,and offer critical data and methodological support for high-resolution permafrost mapping across the region.展开更多
Optical remote sensing allows to efficiently monitor forest ecosystems at regional and global scales.However,most of the widely used optical forward models and backward estimation methods are only suitable for forest ...Optical remote sensing allows to efficiently monitor forest ecosystems at regional and global scales.However,most of the widely used optical forward models and backward estimation methods are only suitable for forest canopies in flat areas.To evaluate the recent progress in forest remote sensing over complex terrain,a satellite-airborne-ground synchronous Fine scale Optical Remote sensing Experiment of mixed Stand over complex Terrain(FOREST)was conducted over a 1 km×1 km key experiment area(KEA)located in the Genhe Reserve Areain 2016.Twenty 30 m×30 m elementary sampling units(ESUs)were established to represent the spatiotemporal variations of the KEA.Structural and spectral parameters were simultaneously measured for each ESU.As a case study,we first built two 3D scenes of the KEA with individual-tree and voxel-based approaches,and then simulated the canopy reflectance using the LargE-Scale remote sensing data and image Simulation framework over heterogeneous 3D scenes(LESS).The correlation coefficient between the LESS-simulated reflectance and the airborne-measured reflectance reaches 0.68-0.73 in the red band and 0.56-0.59 in the near-infrared band,indicating a good quality of the experiment dataset.More validation studies of the related forward models and retrieval methods will be done.展开更多
Objective: To explore the correlation and clinical significance between expression of MDR (multidrug resistance) related gene MRP, MDR1, C-erbB-2 and cell apoptosis in non-small cell lung cancer (NSCLC). Methods: RT-P...Objective: To explore the correlation and clinical significance between expression of MDR (multidrug resistance) related gene MRP, MDR1, C-erbB-2 and cell apoptosis in non-small cell lung cancer (NSCLC). Methods: RT-PCR, Immunohistochemistry were used to examine the expression of mRNA and protein in the MDR and apoptosis related gene. Apoptosis cells were assayed by Terminal deoxynucleotidyl transferase (TdT)- mediated biotin dUTP nick end-labeling (TUNEL). Results: The positive rates of MRP, MDR1, C-erbB-2, bc1-2, C-myc mRNA in 63 cases NSCLC were 81.0% (51/63), 38.1%(24/63), 47.6%(30/63), 65.1%(41/63), 76.2%(48/63) respectively. Their levels were higher than those of corresponding proteins (74.6%, 34.9%, 46.0%, 61.9%, 71.4%, respectively). The significant association was found between the mRNA level and the protein expression (r =+0.764, P<0.02). The C-myc expression in 2 cases adjacent and benign lung tissue were light positive, and another 3 cases were negative. The positive correlation were demonstrated between C-myc and C-erbB-2 (r=+0.547, p=0.001) as well as bcl-2 and C-erbB-2 (r =+0.486, p=0.023) in NSCLC. There is no any correlation among bcl-2, C-myc and MRP or MDR1. There exists inverse correlation between apoptotic index and bcl-2 (r = -0.587, p = 0.017), and no any correlation among apoptotic index and MRP or MDR1 or C-erbB-2 or C-myc. The average apoptotic index were higher in the effective chemotherapy group (27.2( 2.1, 30.5(1.8) than that in the non-effective chemotherapy group (9.4( 1.3, 12.6( 2.4) with adenocarcinoma and squamous cell carcinoma (p =0.01, p=0.004). The positive rates of bcl-2, MRP, C-erbB-2 expression in the effective chemotherapy group (31.8%, 40.9%, 22.7%, respectively) were lower than those in the non-effective chemotherapy group (77.4%, 90.3%, 67.7%, respectively) (p=0.036, p=0.012, p=0.01), but MDR1 and C-myc expression have no any significant difference (p=0.067, p=0.282). The median survival time in the patients with coexpression of more than three MDR and/or apoptosis related genes are shorter (8.6 months) than that in those patients with coexpression of less than three MDR and/or apoptosis related genes (15.5 months)(p=0.01). Conclusion: The multidrug resistance in NSCLC is not only related to many drug resistance genes, but also involved in cell apoptosis and apoptosis related gene expression. The coexpression of MDR and apoptosis related gene is related to the survival time.展开更多
基金financially supported by the Science and Technology Fundamental Resources Investigation Program of China(2022FY100704)the National Natural Science Foundation of China(42376254,42322608)+1 种基金the program of the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,CAS(CSFSE-ZZ-2408)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(2022430).
文摘Most existing studies provide coarse spatial resolution mappings(typically 1 km or more),which fail to capture local-scale heterogeneity of permafrost distribution in the permafrost boundary region.This study employed 298 ground-truth samples to evaluate six machine learning(ML)algorithms for simulating permafrost distribution in the Genhe River Basin(GRB)of the Greater Khingan Mountains(GKM)based on our detailed investigation(e.g.,16 boreholes)in this region conducted in 2023-2024,while identifying key environmental drivers through Shapley Additive Explanations(SHAP)analysis.Results show that the random forest(RF)model achieved the best performance,with a classification accuracy of 0.83 and a Kappa coefficient of 0.66.The RF-based permafrost map at a 30 m resolution reveals a total permafrost area of approximately 8248.5 km2,accounting for 52.0%of the GRB.The most influential predictors of permafrost distribution are slope(SLO),topographic wetness index(TWI),and degree of topographic relief(DTR),contributing 13.6%,11.1%,and 9.4%,respectively.Other important factors include normalized difference water index(NDWI,6.8%)and land surface temperature(LST,6.1%).Permafrost is mainly distributed in valley bottoms,toe slopes,and gently sloping areas in the upper and middle reaches of the basin.These zones are closely associated with vegetation types such as wetlands,shrubs,and larch forests.Conversely,permafrost is rarely found in croplands or on steep slopes.These findings improve the understanding of permafrost distribution patterns in the transitional zone of Northeast China,and offer critical data and methodological support for high-resolution permafrost mapping across the region.
基金supported in part by the National Basic Research Program of China(2013CB733400)in part by the Natural Science Foundation of China(41930111 and 41871258)+1 种基金in part by the Youth Innovation Promotion Association CAS under Grant 2020127in part by the‘Future Star’Talent Plan of the Aerospace Information Research Institute of Chinese Academy of Sciences under Grant Y920570Z1F.
文摘Optical remote sensing allows to efficiently monitor forest ecosystems at regional and global scales.However,most of the widely used optical forward models and backward estimation methods are only suitable for forest canopies in flat areas.To evaluate the recent progress in forest remote sensing over complex terrain,a satellite-airborne-ground synchronous Fine scale Optical Remote sensing Experiment of mixed Stand over complex Terrain(FOREST)was conducted over a 1 km×1 km key experiment area(KEA)located in the Genhe Reserve Areain 2016.Twenty 30 m×30 m elementary sampling units(ESUs)were established to represent the spatiotemporal variations of the KEA.Structural and spectral parameters were simultaneously measured for each ESU.As a case study,we first built two 3D scenes of the KEA with individual-tree and voxel-based approaches,and then simulated the canopy reflectance using the LargE-Scale remote sensing data and image Simulation framework over heterogeneous 3D scenes(LESS).The correlation coefficient between the LESS-simulated reflectance and the airborne-measured reflectance reaches 0.68-0.73 in the red band and 0.56-0.59 in the near-infrared band,indicating a good quality of the experiment dataset.More validation studies of the related forward models and retrieval methods will be done.
基金the Grant from Beijing Natural Science Foundation(No.7992005), and a Grant from Postdoctoral Foundation of National Committee of
文摘Objective: To explore the correlation and clinical significance between expression of MDR (multidrug resistance) related gene MRP, MDR1, C-erbB-2 and cell apoptosis in non-small cell lung cancer (NSCLC). Methods: RT-PCR, Immunohistochemistry were used to examine the expression of mRNA and protein in the MDR and apoptosis related gene. Apoptosis cells were assayed by Terminal deoxynucleotidyl transferase (TdT)- mediated biotin dUTP nick end-labeling (TUNEL). Results: The positive rates of MRP, MDR1, C-erbB-2, bc1-2, C-myc mRNA in 63 cases NSCLC were 81.0% (51/63), 38.1%(24/63), 47.6%(30/63), 65.1%(41/63), 76.2%(48/63) respectively. Their levels were higher than those of corresponding proteins (74.6%, 34.9%, 46.0%, 61.9%, 71.4%, respectively). The significant association was found between the mRNA level and the protein expression (r =+0.764, P<0.02). The C-myc expression in 2 cases adjacent and benign lung tissue were light positive, and another 3 cases were negative. The positive correlation were demonstrated between C-myc and C-erbB-2 (r=+0.547, p=0.001) as well as bcl-2 and C-erbB-2 (r =+0.486, p=0.023) in NSCLC. There is no any correlation among bcl-2, C-myc and MRP or MDR1. There exists inverse correlation between apoptotic index and bcl-2 (r = -0.587, p = 0.017), and no any correlation among apoptotic index and MRP or MDR1 or C-erbB-2 or C-myc. The average apoptotic index were higher in the effective chemotherapy group (27.2( 2.1, 30.5(1.8) than that in the non-effective chemotherapy group (9.4( 1.3, 12.6( 2.4) with adenocarcinoma and squamous cell carcinoma (p =0.01, p=0.004). The positive rates of bcl-2, MRP, C-erbB-2 expression in the effective chemotherapy group (31.8%, 40.9%, 22.7%, respectively) were lower than those in the non-effective chemotherapy group (77.4%, 90.3%, 67.7%, respectively) (p=0.036, p=0.012, p=0.01), but MDR1 and C-myc expression have no any significant difference (p=0.067, p=0.282). The median survival time in the patients with coexpression of more than three MDR and/or apoptosis related genes are shorter (8.6 months) than that in those patients with coexpression of less than three MDR and/or apoptosis related genes (15.5 months)(p=0.01). Conclusion: The multidrug resistance in NSCLC is not only related to many drug resistance genes, but also involved in cell apoptosis and apoptosis related gene expression. The coexpression of MDR and apoptosis related gene is related to the survival time.
