The incidence of central nervous system (CNS) disease has persistently increased over the last several years. There is an urgent need for effective methods to improve the cure rates of CNS disease. However, the precise molecular basis underlying the development and progression of major CNS diseases remains elusive. A complete molecular map will contribute to research on CNS disease treatment strategies. Emerging technologies such as single-cell RNA sequencing (scRNA-seq) and Spatial Transcriptomics (ST) are potent tools for exploring the molecular complexity, cell heterogeneity, and functional specificity of CNS disease. scRNA-seq and ST can provide insights into the disease at cellular and spatial transcription levels. This review presents a survey of scRNA-seq and ST studies on CNS diseases, such as chronic neurodegenerative diseases, acute CNS injuries, and others. These studies offer novel perspectives in treating and diagnosing CNS diseases by discovering new cell types or subtypes associated with the disease, proposing new pathophysiological mechanisms, uncovering novel therapeutic targets, and identifying putative biomarkers. Graphical Abstract Implications of scRNA-seq and ST for CNS diseases. A comprehensive understanding of cellular information and spatial context using scRNA-seq and ST, helping to elucidate the biological functions, the intricate connection between crucial regulatory pathways, and cell communication after CNS diseases.

Urban scene classifications with very-high-resolution (VHR) satellite images play an important role in urban functional-zone investigation and landscape analysis. Most scene classification techniques utilize visual features which however are weak in identifying scenes, as scenes are usually composed of diverse objects with variant visual cues. To resolve this issue, we use spatial object relations to characterize urban scenes and recognize their categories. Accordingly, two questions are considered in this study: how to measure spatial object relations and how to use these relations to classify urban scenes? First, we propose a novel scene feature, semantic and spatial co-occurrence probability (SSCP), to measure spatial relations between objects with considering their directions, distances, and semantics, which can hopefully resolve the three key issues in measuring spatial object relations, i.e., anisotropy, scale- and semantic-dependencies. Then, a semilatent Dirichlet allocation is employed to classify scenes based on the proposed SSCP. In experiments, our method is first verified based on the UC Merced data set, and then used to generate an urban functional-zone map for Beijing, China. Both experiments indicate high accuracies and state-of-the-art performances of our method. In addition, we give a deep insight into SSCP's characteristics including convergence, high efficiency, and invariance to affine transformation, which can make our method more applicable.

Background and Objective: Ischemic stroke is a complex neurological disease with poor prognosis, resulting in significant economic burdens for patients, their families, and society at large. Traditional Chinese Medicine (TCM) offers unique advantages and has been utilized for thousands of years in the prevention and treatment of ischemic stroke. However, there is currently a lack of bibliometric analysis and knowledge mapping regarding TCM treatments for this condition. To identify the key areas and future directions of TCM treatment for Ischemic Stroke. Methods: We extracted articles on TCM treatments for ischemic stroke from the Web of Science Core Collection (WoSCC) database, spanning from January 1, 1990, to March 20, 2025, and conducted a bibliometric analysis. Data processing was performed using CiteSpace, VOSviewer, and Origin2024b. Results: We collected 506 published papers, with China accounting for the majority of these publications (97.0 %, 418 articles). The Journal of Ethnopharmacology and Frontiers in Pharmacology were the two most frequently published journals. The leading institutions contributing to this research included the Chinese Academy of Medical Sciences, Beijing University of Chinese Medicine, and Peking Union Medical College (now known as Capital Medical University). The primary research hotspots in TCM treatment for ischemic stroke focused on protective effects, brain injury, and neural regeneration. Notably, network pharmacology, molecular docking, and metabolomics were identified as the commonly used research methods. Among them, network pharmacology was the most frequently used research method. Additionally, we summarized the TCM remedies that have been extensively researched and cited in the context of ischemic stroke, including catalpol, angong niuhuang wan, buyang huanwu decoction, jeo-dang-tang, yiqifumai powder injection, and gualou guizhi decoction. Conclusion: The work highlights the key topics and recent research frontiers, providing valuable resources for scholars interested in the role of TCM in treating ischemic stroke.

The optimal design of high-speed 650nm plastic optical fiber (POF) communication system with independent design silicon-based 650nm optical transceiver chips is implemented in this paper. Firstly, the parameters of optical path are obtained in theory by analyzing and calculating of system optical path based on the hemispherical and spherical lens system model. Then, the system optical path is designed and simulated in the software TracePro with the help of the control variables method. Finally, the system experiments of optical power, transient response and transmission characteristic are completed. The test results indicate that the output optical power is increased by 30µW using the lens and polished POF. The system has good transient. And the bandwidth of 180MHz is obtained to satisfy the demand of 100Mbps POF communication system.