How does the motor relearning program improve neurological function of brain ischemia monkeys?

The motor relearning program can significantly improve various functional disturbance induced by ischemic cerebrovascular diseases. However, its mechanism of action remains poorly understood. In injured brain tissues, glial fibrillary acidic protein and neurofilament protein changes can reflect the condition of injured neurons and astrocytes, while vascular endothelial growth factor and basic fibroblast growth factor changes can indicate angiogenesis. In the present study, we induced ischemic brain injury in the rhesus macaque by electrocoagulation of the M1 segment of the right middle cerebral artery. The motor relearning program was conducted for 60 days from the third day after model establishment. Immunohistochemistry and single-photon emission CT showed that the numbers of glial fibrillary acidic protein-, neurofilament protein-, vascular endothelial growth factor- and basic fibroblast growth factor-positive cells were significantly increased in the infarcted side compared with the contralateral hemisphere following the motor relearning program. Moreover, cerebral blood flow in the infarcted side was significantly improved. The clinical rating scale for stroke was used to assess neurological function changes in the rhesus macaque following the motor relearning program. Results showed that motor function was improved, and problems with consciousness, self-care ability and balance function were significantly ameliorated. These findings indicate that the motor relearning program significantly promoted neuronal regeneration, repair and angiogenesis in the surroundings of the infarcted hemisphere, and improve neurological function in the rhesus macaque following brain ischemia.

Co-editing PINK1 and DJ-1 Genes Via Adeno-Associated Virus-Delivered CRISPR/Cas9 System in Adult Monkey Brain Elicits Classical Parkinsonian Phenotype

Whether direct manipulation of Parkinson’s disease(PD)risk genes in the adult monkey brain can elicit a Parkinsonian phenotype remains an unsolved issue.Here,we used an adeno-associated virus serotype 9(AAV9)-delivered CRISPR/Cas9 system to directly co-edit PINK1 and DJ-1 genes in the substantia nigras(SNs)of two monkey groups:an old group and a middle-aged group.After the operation,the old group exhibited all the classic PD symptoms,including bradykinesia,tremor,and postural instability,accompanied by key pathological hallmarks of PD,such as severe nigral dopaminergic neuron loss(>64%)and evidentα-synuclein pathology in the gene-edited SN.In contrast,the phenotype of their middle-aged counterparts,which also showed clear PD symptoms and pathological hallmarks,were less severe.In addition to the higher final total PD scores and more severe pathological changes,the old group were also more susceptible to gene editing by showing a faster process of PD progression.These results suggested that both genetic and aging factors played important roles in the development of PD in the monkeys.Taken together,this system can effectively develop a large number of genetically-edited PD monkeys in a short time(6–10 months),and thus provides a practical transgenic monkey model for future PD studies.

完整猕猴脑连续亚微米分辨的三维成像

解剖整个脑回路结构对于揭示神经系统的组织结构逻辑至关重要.然而,在庞大而复杂的灵长类大脑中绘制亚微米分辨率的神经元投影仍然具有挑战性.本文开发了高效的技术方案,以亚微米分辨率绘制整个猕猴大脑的神经元投射.该方案包括一种可长期保存组织结构和荧光信号的新型包埋方法,高分辨率快速全脑光学成像方法和图像后处理方法.利用该方案获取完整猕猴脑的0.32μm×0.32μm×10.00μm体素分辨率数据集展示了单细胞定位、密度、形状等解剖构筑信息.结合病毒标记,追踪了猕猴半脑从前额皮质到丘脑的长距离投射神经纤维,结果显示,额叶皮层的轴突可投射到视皮层、纹状体、丘脑和中脑等多个脑区.该方案为整个猕猴大脑的亚微米级三维细胞构筑和神经元环路研究提供了有效的方法,有助于揭示大脑功能和疾病基础.

原位敲除猕猴视网膜RHO基因构建非人灵长类视网膜色素变性模型

遗传视网膜退行性疾病是全球范围内最主要的致盲疾病.该疾病主要的特征是视网膜感光细胞退化导致了不可逆的视觉能力丧失.视网膜色素变性(Retinitis pigmentosa,RP)便是其中的一大亚类,目前临床上尚无有效的治疗手段.本研究首次利用腺相关病毒(Adeno Associated Virus,AAV)介导的CRISPR/SaCa9技术,成功实现原位敲除目的基因RHO,建立了非人灵长类RP模型.研究结果发现,RHO敲除的猕猴视网膜表现出典型的RP感光细胞变性,视杆和视锥细胞渐行性死亡.在分子水平上,RHO基因成功地被敲除.RHO蛋白表达量也大幅度下降.免疫组化和电镜结果揭示了突变视杆细胞外段缺失或者变短,再现了RP最典型的特征.生理功能检测发现,RHO敲除视网膜的视网膜电流图(Electroretinogram,ERG)反应大幅度下降,证明了其视觉能力的受损.该动物模型为研究人类RP的发病机理以及制定相应治疗策略提供了重要的类人模型.

Feature-reduction and semi-simulated data in functional connectivity-based cortical parcellation

Recently, restingstate functional magnetic resonance imaging has been used to parcellate the brain into functionally distinct regions based on the information available in functional connectivity maps. However, brain voxels are not independent units and adjacent voxels are always highly correlated, so functional connectivity maps contain redundant information, which not only impairs the computational efficiency during clustering, but also reduces the accuracy of clustering results. The aim of this study was to propose featurereduction approaches to reduce the redundancy and to develop semisimulated data with defined ground truth to evaluate these approaches. We proposed a featurereduction approach based on the Affinity Propagation Algorithm （APA） and compared it with the classic feature reduction approach based on Principal Component Analysis （PCA）. We tested the two approaches to the parcellation of both semisimulated and real seed regions using the Kmeans algorithm and designed two experiments to evaluate their noise resistance. We found that all functional connectivitymaps （with/without feature reduction） provided correct information for the parcellation of the semi simulated seed region and the computational efficiency was greatly improved by both feature reduction approaches. Meanwhile, the APAbased featurereduction approach outperformed the PCA based approach in noiseresistance. The results suggested that functional connectivity maps can provide correct information for cortical parcellation, and featurereduction does not significantly change the information. Considering the improvement in computational efficiency and the noiseresistance, featurereduction of functional connectivity maps before cortical parcellation is both feasible and necessary.