The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cereb...The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.展开更多
Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in c...Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.展开更多
The Northeast China cold vortex(NCCV)is the most important midlatitude synoptic system for weather and climate anomalies in Northeast China in the warm season.Many previous studies have focused on its synoptic and cli...The Northeast China cold vortex(NCCV)is the most important midlatitude synoptic system for weather and climate anomalies in Northeast China in the warm season.Many previous studies have focused on its synoptic and climatic variability.However,little is known about the variability of the NCCV on subseasonal timescales.In this study,we investigate the subseasonal variability of the NCCV in the warm season(May to August)and its impact based on the NCEP–NCAR reanalysis dataset and observational climate data from 1981 to 2020.Results show that the NCCV frequency exhibits a significant quasi-biweekly oscillation(QBWO,10–25 days).In 32 out of 40 years,there is at least one significant period between 10 and 25 days.Our result provides the first direct evidence for a significant QBWO signal in the NCCV frequency.The QBWO circulation on NCCV days features a cold low-pressure anomaly surrounded by warm high-pressure anomalies from northwest to southeast in a clockwise direction,which is related to an upstream wave train propagating southeastward from the Ural Mountains into Northeast China and a downstream blocking high to the northeast.The NCCV QBWO causes more rainfall,with a quadrature phase shift as rainfall leading the NCCV for approximately three days,and synchronized reduced surface air temperature in Northeast China.展开更多
Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation...Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.展开更多
基金supported by the Grant PID2021-126715OB-IOO financed by MCIN/AEI/10.13039/501100011033 and"ERDFA way of making Europe"by the Grant PI22CⅢ/00055 funded by Instituto de Salud CarlosⅢ(ISCⅢ)+6 种基金the UFIECPY 398/19(PEJ2018-004965) grant to RGS funded by AEI(Spain)the UFIECPY-396/19(PEJ2018-004961)grant financed by MCIN (Spain)FI23CⅢ/00003 grant funded by ISCⅢ-PFIS Spain) to PMMthe UFIECPY 328/22 (PEJ-2021-TL/BMD-21001) grant to LM financed by CAM (Spain)the grant by CAPES (Coordination for the Improvement of Higher Education Personnel)through the PDSE program (Programa de Doutorado Sanduiche no Exterior)to VSCG financed by MEC (Brazil)
文摘The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.
基金supported by the National Key R&D Program of China [grant number 2023YFF0805202]the National Natural Science Foun-dation of China [grant number 42175045]the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDB42000000]。
文摘Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.
基金funded by the National Key R&D Program of China(Grant Nos.2023YFC3007700 and 2023YFC3007701)。
文摘The Northeast China cold vortex(NCCV)is the most important midlatitude synoptic system for weather and climate anomalies in Northeast China in the warm season.Many previous studies have focused on its synoptic and climatic variability.However,little is known about the variability of the NCCV on subseasonal timescales.In this study,we investigate the subseasonal variability of the NCCV in the warm season(May to August)and its impact based on the NCEP–NCAR reanalysis dataset and observational climate data from 1981 to 2020.Results show that the NCCV frequency exhibits a significant quasi-biweekly oscillation(QBWO,10–25 days).In 32 out of 40 years,there is at least one significant period between 10 and 25 days.Our result provides the first direct evidence for a significant QBWO signal in the NCCV frequency.The QBWO circulation on NCCV days features a cold low-pressure anomaly surrounded by warm high-pressure anomalies from northwest to southeast in a clockwise direction,which is related to an upstream wave train propagating southeastward from the Ural Mountains into Northeast China and a downstream blocking high to the northeast.The NCCV QBWO causes more rainfall,with a quadrature phase shift as rainfall leading the NCCV for approximately three days,and synchronized reduced surface air temperature in Northeast China.
基金supported by the National Natural Science Foundation of China[grant number 42175132]the National Key R&D Program[grant number 2020YFA0607802]the CAS Information Technology Program[grant number CAS-WX2021SF-0107-02]。
文摘Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.