Background:The accurate estimation of carbon-water flux is critical for understanding the carbon and water cycles of terrestrial ecosystems and further mitigating climate change.Model simulations and observations have...Background:The accurate estimation of carbon-water flux is critical for understanding the carbon and water cycles of terrestrial ecosystems and further mitigating climate change.Model simulations and observations have been widely used to research water and carbon cycles of terrestrial ecosystems.Given the advantages and limitations of each method,combining simulations and observations through a data assimilation technique has been proven to be highly promising for improving carbon-water flux simulation.However,to the best of our knowledge,few studies have accomplished both parameter optimization and the updating of model state variables through data assimilation for carbon-water flux simulation in multiple vegetation types.And little is known about the variation of the performance of data assimilation for carbon-water flux simulation in different vegetation types.Methods:In this study,we assimilated leaf area index(LAI)time-series observations into a biogeochemical model(Biome-BGC)using different assimilation algorithms(ensemble Kalman filter algorithm(EnKF)and unscented Kalman filter(UKF))in different vegetation types(deciduous broad-leaved forest(DBF),evergreen broad-leaved forest(EBF)and grassland(GL))to simulate carbon-water flux.Results:The validation of the results against the eddy covariance measurements indicated that,overall,compared with the original simulation,assimilating the LAI into the Biome-BGC model improved the carbon-water flux simulations(R^(2)increased by 35%,root mean square error decreased by 10%;the sum of the absolute error decreased by 8%)but more significantly,improved the water flux simulations(R^(2)increased by 31%,root mean square error decreased by 18%;the sum of the absolute error decreased by 16%).Among the different forest types,the data assimilation techniques(both EnKF and UKF)achieved the best performance towards carbon-water flux in EBF(R^(2)increased by 44%,root mean square error decreased by 24%;the sum of the absolute error decreased by 28%),and the performances of EnKF and UKF showed slightly different when simulating carbon fluxes.Conclusion:We suggest that to reduce the uncertainty in global carbon-water flux quantification,forthcoming data assimilation treatment should consider the vegetation types where the data assimilation experiments are carried out,the simulated objectives and the assimilation algorithms.展开更多
Breast cancer is one of the most common female malignant tumors in the world. Although many therapeutic methods for HER-2 positive breast cancer have been developed, the drug resistance and distant metastasis still re...Breast cancer is one of the most common female malignant tumors in the world. Although many therapeutic methods for HER-2 positive breast cancer have been developed, the drug resistance and distant metastasis still remain. Tetraarsenic oxide(As_4O_6) has been demonstrated with an anticancer effect on squamous cell carcinoma and cervical cancer. However, there is no report about the relationship between As_4O_6 and HER-2 positive breast cancer. In the present study, we detected the inhibitory efficacy and mechanism of As_4O_6 on the migration and invasion of SKBR3 breast cancer cells using molecular biological methods. The wound-healing assay, matrigel migration assay, transwell invasion assay and cell adhesion assay were used to assess the migration, invasion and adhesion of SKBR3 cells intervened by As_4O_6. Meanwhile, the reverse transcription-PCR and western blotting were performed to investigate the mechanism of As_4O_6 on the migration and invasion of SKBR3 breast cancer cells. The results demonstrated that As_4O_6 could efficiently inhibit the migration and invasion of SKBR3 cells, the HER-2 positive breast cancer cells, and the adhesion of SKBR3 cells was decreased after As_4O_6 treatment. The mechanism revealed that As_4O_6 anticancer efficacy was related to HER-2/EGFR pathways. As_4O_6 exerted its inhibitory effects on migration and invasion in HER-2 positive breast cancer cells by regulating the factors(EGFR, HER-2, Akt, MMP-9) in HER2/ EGFR signaling pathway and other key molecules. In conclusion, the present study indicated that As_4O_6 inhibited the invasion and migration process of HER-2 positive breast cancer SKBR3 cells by negatively regulating the HER-2/EGFR-mediated signaling pathway. These data provided evidence that As_4O_6 might serve as potential anti-metastasis drug for clinical treatment of breast cancer.展开更多
基金supported by the National Natural Science Foundation of China(No.41301451).
文摘Background:The accurate estimation of carbon-water flux is critical for understanding the carbon and water cycles of terrestrial ecosystems and further mitigating climate change.Model simulations and observations have been widely used to research water and carbon cycles of terrestrial ecosystems.Given the advantages and limitations of each method,combining simulations and observations through a data assimilation technique has been proven to be highly promising for improving carbon-water flux simulation.However,to the best of our knowledge,few studies have accomplished both parameter optimization and the updating of model state variables through data assimilation for carbon-water flux simulation in multiple vegetation types.And little is known about the variation of the performance of data assimilation for carbon-water flux simulation in different vegetation types.Methods:In this study,we assimilated leaf area index(LAI)time-series observations into a biogeochemical model(Biome-BGC)using different assimilation algorithms(ensemble Kalman filter algorithm(EnKF)and unscented Kalman filter(UKF))in different vegetation types(deciduous broad-leaved forest(DBF),evergreen broad-leaved forest(EBF)and grassland(GL))to simulate carbon-water flux.Results:The validation of the results against the eddy covariance measurements indicated that,overall,compared with the original simulation,assimilating the LAI into the Biome-BGC model improved the carbon-water flux simulations(R^(2)increased by 35%,root mean square error decreased by 10%;the sum of the absolute error decreased by 8%)but more significantly,improved the water flux simulations(R^(2)increased by 31%,root mean square error decreased by 18%;the sum of the absolute error decreased by 16%).Among the different forest types,the data assimilation techniques(both EnKF and UKF)achieved the best performance towards carbon-water flux in EBF(R^(2)increased by 44%,root mean square error decreased by 24%;the sum of the absolute error decreased by 28%),and the performances of EnKF and UKF showed slightly different when simulating carbon fluxes.Conclusion:We suggest that to reduce the uncertainty in global carbon-water flux quantification,forthcoming data assimilation treatment should consider the vegetation types where the data assimilation experiments are carried out,the simulated objectives and the assimilation algorithms.
文摘Breast cancer is one of the most common female malignant tumors in the world. Although many therapeutic methods for HER-2 positive breast cancer have been developed, the drug resistance and distant metastasis still remain. Tetraarsenic oxide(As_4O_6) has been demonstrated with an anticancer effect on squamous cell carcinoma and cervical cancer. However, there is no report about the relationship between As_4O_6 and HER-2 positive breast cancer. In the present study, we detected the inhibitory efficacy and mechanism of As_4O_6 on the migration and invasion of SKBR3 breast cancer cells using molecular biological methods. The wound-healing assay, matrigel migration assay, transwell invasion assay and cell adhesion assay were used to assess the migration, invasion and adhesion of SKBR3 cells intervened by As_4O_6. Meanwhile, the reverse transcription-PCR and western blotting were performed to investigate the mechanism of As_4O_6 on the migration and invasion of SKBR3 breast cancer cells. The results demonstrated that As_4O_6 could efficiently inhibit the migration and invasion of SKBR3 cells, the HER-2 positive breast cancer cells, and the adhesion of SKBR3 cells was decreased after As_4O_6 treatment. The mechanism revealed that As_4O_6 anticancer efficacy was related to HER-2/EGFR pathways. As_4O_6 exerted its inhibitory effects on migration and invasion in HER-2 positive breast cancer cells by regulating the factors(EGFR, HER-2, Akt, MMP-9) in HER2/ EGFR signaling pathway and other key molecules. In conclusion, the present study indicated that As_4O_6 inhibited the invasion and migration process of HER-2 positive breast cancer SKBR3 cells by negatively regulating the HER-2/EGFR-mediated signaling pathway. These data provided evidence that As_4O_6 might serve as potential anti-metastasis drug for clinical treatment of breast cancer.