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22q11.2 deletion syndrome (22q11DS) is a highly penetrant and common genetic cause of neuropsychiatric disease. Here we generated induced pluripotent stem cells from 15 individuals with 22q11DS and 15 control individuals and differentiated them into three-dimensional (3D) cerebral cortical organoids. Transcriptional profiling across 100 days showed high reliability of differentiation and revealed changes in neuronal excitability-related genes. Using electrophysiology and live imaging, we identified defects in spontaneous neuronal activity and calcium signaling in both organoid- and 2D-derived cortical neurons. The calcium deficit was related to resting membrane potential changes that led to abnormal inactivation of voltage-gated calcium channels. Heterozygous loss of DGCR8 recapitulated the excitability and calcium phenotypes and its overexpression rescued these defects. Moreover, the 22q11DS calcium abnormality could also be restored by application of antipsychotics. Taken together, our study illustrates how stem cell derived models can be used to uncover and rescue cellular phenotypes associated with genetic forms of neuropsychiatric disease.

Vegetation net primary productivity (NPP) is critical to maintaining and enhancing the carbon sink of vegetation. Shaoguan is a characteristic forest city in the subtropical region of South China and an ecological barrier in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA), playing an instrumental role in protecting water resources, purifying air, and maintaining ecological balance. However, studies that quantify subtropical vegetation NPP dynamics in Shaoguan under the influence of climate and human drivers are still incomplete. In this research, vegetation NPP at 30 m resolution was estimated from 2001 to 2020 using the enhanced CASA model based on the GF-SG algorithm in Shaoguan. The RESTREND method was then utilized to quantify climatic and human effects on NPP. The results indicated that the vegetation NPP in Shaoguan increased rapidly (4.09 g C/m2/yr, p < 0.001) over the past 20 years. Climate and human drivers contributed 0.948 g C/m2/yr and 3.137 g C/m2/yr to vegetation NPP, respectively. Human activity plays a major role in vegetation restoration through ecological projects, whereas vegetation deterioration is primarily attributable to the combined action of climate change and human activity, such as urban expansion, deforestation, and meteorological disasters. The results emphasize the importance of ecological projects for the restoration of vegetated ecosystems and ecological construction in Shaoguan. [ABSTRACT FROM AUTHOR]

Lodging is one of the typical abiotic adversities during paddy rice growth. In addition to affecting photosynthesis, it can seriously damage crop growth and development, such as reducing rice quality and hindering automated harvesting. It is, therefore, imperative to accurately and in good time acquire crop-lodging areas for yield prediction, agricultural insurance claims, and disaster-management decisions. However, the accuracy requirements for crop-lodging monitoring remain challenging due to complicated impact factors. Aiming at identifying paddy rice lodging on Shazai Island, Guangdong, China, caused by heavy rainfall and strong wind, a decision-tree model was constructed using multiple-parameter information from Sentinel-1 SAR images and the in situ lodging samples. The model innovatively combined the five backscattering coefficients with five polarization decomposition parameters and quantified the importance of each parameter feature. It was found that the decision-tree method coupled with polarization decomposition can be used to obtain an accurate distribution of paddy rice-lodging areas. The results showed that: (1) Radar parameters can capture the changes in lodged paddy rice. The radar parameters that best distinguish paddy rice lodging are VV, VV+VH, VH/VV, and Span. (2) Span is the parameter with the strongest feature importance, which shows the necessity of adding polarization parameters to the classification model. (3) The dual-polarized Sentinel-1 database classification model can effectively extract the area of lodging paddy rice with an overall accuracy of 84.38%, and a total area precision of 93.18%. These observations can guide the future use of SAR-based information for crop-lodging assessment and post-disaster management. [ABSTRACT FROM AUTHOR]

Massive progress and fruitful results have been achieved since the implementation of the Belt and Road Initiative (B&R). However, the risk of exchange rate between countries along the Belt and Road cannot be ignored. In this paper, we propose a B&R exchange rate index to evaluate the currency risk of countries along the B&R, along with a research on the multiscale features of the B&R exchange rate index and the effective RMB exchange rate index using the EMD algorithm. Then, we propose an integrated forecasting approach. We adopt the EMD algorithm and the Grey Relational Analysis to decompose and reconstruct the B&R exchange rate index and the effective RMB exchange rate index into three subsections with different volatility characteristics. The prediction outcome of the integrated model for the original series equals a sum of the Auto‐regressive Integrated Moving Average model for trend term and the Long Short‐Term Memory model for market fluctuation term as well as noise term. The results of our prediction demonstrate a much better performance of our proposed integrated forecasting model than pure methods. Lastly, several suggestions are put forward to help relevant enterprises effectively avoid and manage the exchange risks. [ABSTRACT FROM AUTHOR]