Spatiotemporal Dynamics of Central Nervous System Diseases: Advancing Translational Neuropathology via Single-Cell and Spatial Multiomics

Abstract

Central nervous system (CNS) diseases, a leading cause of global disability and mortality, encompass a wide range of brain disorders such as stroke, Alzheimer's disease, Parkinson's disease, and so on. These diseases are characterized by dynamic cellular heterogeneity and disrupted intercellular crosstalk, yet their molecular drivers remain incompletely resolved. Single-cell RNA sequencing (scRNA-seq) dissects transcriptional diversity at cellular resolution, while spatial transcriptomics (ST) maps niche-specific interactions within tissue architecture—complementary approaches that have revealed disease-associated subpopulations, neural–glial communication, and microenvironmental remodeling. However, standalone omics layers inadequately capture the genetic, epigenetic, and functional cascades underlying CNS pathologies. Here, we highlight the transformative potential of integrating scRNA-seq and ST with multiomic profiling to delineate spatially orchestrated molecular networks. Such multiomic convergence enables systematic deconstruction of molecular mechanisms and intercellular communication across disease progression. By correlating these signatures with clinical phenotypes, this strategy accelerates biomarker discovery, patient stratification, and therapeutic target identification. We further discuss challenges in data harmonization, subcellular spatial resolution, and computational scalability that must be addressed to realize personalized CNS medicine. This synthesis advocates for interdisciplinary frameworks to translate multiomic insights into mechanistically grounded diagnostics and therapies, ultimately bridging the gap between molecular discovery and precision clinical intervention.

Keywords

central nervous system disease / multiomics / molecular mechanisms / precise treatment / single-cell RNA sequencing / spatial transcriptomics

References

[1] V. L. Feigin, T. Vos, E. Nichols, et al., “The Global Burden of Neurological Disorders: Translating Evidence Into Policy, ” Lancet Neurology 19, no. 3 (2020): 255-265.

[2] E. Z. Macosko, A. Basu, R. Satija, et al., “Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets, ” Cell 161, no. 5 (2015): 1202-1214.

[3] S. G. Rodriques, L. M. Chen, S. Liu, et al., “RNA Timestamps Identify the Age of Single Molecules in RNA Sequencing, ” Nature Biotechnology 39, no. 3 (2021): 320-325.

[4] P. L. Ståhl, F. Salmén, S. Vickovic, et al., “Visualization and Analysis of Gene Expression in Tissue Sections by Spatial Transcriptomics, ” Science 353, no. 6294 (2016): 78-82.

[5] H. Mathys, C. A. Boix, L. A. Akay, et al., “Single-cell Multiregion Dissection of Alzheimer's Disease, ” Nature 632, no. 8026 (2024): 858-868.

[6] T. Kamath, A. Abdulraouf, S. J. Burris, et al., “Single-cell Genomic Profiling of human Dopamine Neurons Identifies a Population That Selectively Degenerates in Parkinson's Disease, ” Nature Neuroscience 25, no. 5 (2022): 588-595.

[7] S. Ferri-Borgogno, Y. Zhu, J. Sheng, et al., “Spatial Transcriptomics Depict Ligand-Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors, ” Cancer Research 83, no. 9 (2023): 1503-1516.

[8] H. Zeng, J. Huang, H. Zhou, et al., “Integrative in Situ Mapping of Single-cell Transcriptional States and Tissue Histopathology in a Mouse Model of Alzheimer's Disease, ” Nature Neuroscience 26, no. 3 (2023): 430-446.

[9] R. Argelaguet, A. S. E. Cuomo, O. Stegle, J. C. Marioni, “Computational Principles and Challenges in Single-cell Data Integration, ” Nature Biotechnology 39, no. 10 (2021): 1202-1215.

[10] Y. Hasin, M. Seldin, A. Lusis, “Multi-omics Approaches to Disease, ” Genome Biology 18, no. 1 (2017): 83.

[11] S. Dujardin, C. Commins, A. Lathuiliere, et al., “Tau Molecular Diversity Contributes to Clinical Heterogeneity in Alzheimer's Disease, ” Nature Medicine 26, no. 8 (2020): 1256-1263.

[12] D. Lähnemann, J. Köster, E. Szczurek, et al., “Eleven Grand Challenges in Single-cell Data Science, ” Genome Biology 21, no. 1 (2020): 31.

[13] L. Moses, L. Pachter, “Museum of Spatial Transcriptomics, ” Nature Methods 19, no. 5 (2022): 534-546.

[14] T. R. Hammond, C. Dufort, L. Dissing-Olesen, et al., “Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes, ” Immunity 50, no. 1 (2019): 253-271. e6.

[15] P. J. Magistretti, I. Allaman, “Lactate in the Brain: From Metabolic End-product to Signalling Molecule, ” Nature Reviews Neuroscience 19, no. 4 (2018): 235-249.

[16] B. Diaz-Castro, M. R. Gangwani, X. Yu, G. Coppola, B. S. Khakh, “Astrocyte Molecular Signatures in Huntington's disease, ” Science Translational Medicine 11, no. 514 (2019): eaaw8546.

[17] D. Gosselin, D. Skola, N. G. Coufal, et al., “An Environment-dependent Transcriptional Network Specifies human Microglia Identity, ” Science 356, no. 6344 (2017): eaal3222.

[18] Y. Hao, S. Hao, E. Andersen-Nissen, et al., “Integrated Analysis of Multimodal Single-cell Data, ” Cell 184, no. 13 (2021): 3573-3587. e29.

[19] R. W. Yeo, O. Y. Zhou, B. L. Zhong, et al., “Chromatin Accessibility Dynamics of Neurogenic Niche Cells Reveal Defects in Neural Stem Cell Adhesion and Migration During Aging, ” Nat Aging 3, no. 7 (2023): 866-893.

[20] Y. Pan, W. Cao, Y. Mu, Q. Zhu, “Microfluidics Facilitates the Development of Single-Cell RNA Sequencing, ” Biosensors (Basel) 12, no. 7 (2022): 450.

[21] N. Navin, J. Hicks, “Future Medical Applications of Single-cell Sequencing in Cancer, ” Genome Med 3, no. 5 (2011): 31.

[22] A. A. Kolodziejczyk, J. K. Kim, V. Svensson, J. C. Marioni, S. A. Teichmann, “The Technology and Biology of Single-Cell RNA Sequencing, ” Molecular Cell 58, no. 4 (2015): 610-620.

[23] F. W. Townes, R. A. Irizarry, “Quantile Normalization of Single-cell RNA-seq Read Counts Without Unique Molecular Identifiers, ” Genome biology 21 (2020): 160.

[24] L. Liang, Y. Tian, L. Feng, et al., “Single-cell Transcriptomics Reveals the Cell Fate Transitions of human Dopaminergic Progenitors Derived From hESCs, ” Stem Cell Res Ther 13 (2022): 412.

[25] S. Aibar, C. B. González-Blas, T. Moerman, et al., “SCENIC: Single-cell Regulatory Network Inference and Clustering, ” Nature Methods 14, no. 11 (2017): 1083-1086.

[26] J. Baran-Gale, T. Chandra, K. Kirschner, “Experimental Design for Single-cell RNA Sequencing, ” Brief Funct Genomics 17, no. 4 (2017): 233-239.

[27] Fernandes H. J. R., N. Patikas, S. Foskolou, et al., “Single-Cell Transcriptomics of Parkinson's Disease Human in Vitro Models Reveals Dopamine Neuron-Specific Stress Responses, ” Cell Reports 33, no. 2 (2020): 108263.

[28] X. Wang, Y. He, Q. Zhang, X. Ren, Z. Zhang, “Direct Comparative Analyses of 10X Genomics Chromium and Smart-seq2, ” Genomics, Proteomics & Bioinformatics 19, no. 2 (2021): 253-266.

[29] C. Ziegenhain, B. Vieth, S. Parekh, et al., “Comparative Analysis of Single-Cell RNA Sequencing Methods, ” Molecular Cell 65, no. 4 (2017): 631-643. e4.

[30] B. B. Liau, C. Sievers, L. K. Donohue, et al., “Adaptive Chromatin Remodeling Drives Glioblastoma Stem Cell Plasticity and Drug Tolerance, ” Cell Stem Cell 20, no. 2 (2017): 233-246. e7.

[31] R. G. W. Verhaak, K. A. Hoadley, E. Purdom, et al., “An Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR and NF1, ” Cancer Cell 17, no. 1 (2010): 98.

[32] D. B. Mahat, N. D. Tippens, J. D. Martin-Rufino, “Single-cell Nascent RNA Sequencing Unveils Coordinated Global Transcription, ” Nature 631, no. 8019 (2024): 216-223.

[33] Y. Li, Z. Huang, L. Xu, et al., “UDA-seq: Universal Droplet Microfluidics-based Combinatorial Indexing for Massive-scale Multimodal Single-cell Sequencing, ” Nature Methods 22, no. 6 (2025): 1199-1212.

[34] C. K. Mo, J. Liu, S. Chen, et al., “Tumour Evolution and Microenvironment Interactions in 2D and 3D Space, ” Nature 634, no. 8036 (2024): 1178-1186.

[35] J. L. Guo, M. Griffin, J. K. Yoon, et al., “Histological Signatures Map Anti-fibrotic Factors in Mouse and human Lungs, ” Nature 641, no. 8064 (2025): 993-1004.

[36] L. A. Huuki-Myers, A. Spangler, N. J. Eagles, et al., “A Data-driven Single-cell and Spatial Transcriptomic Map of the human Prefrontal Cortex, ” Science 384, no. 6698 (2024): eadh1938.

[37] A. Sampath Kumar, L. Tian, A. Bolondi, et al., “Spatiotemporal Transcriptomic Maps of Whole Mouse Embryos at the Onset of Organogenesis, ” Nature Genetics 55, no. 7 (2023): 1176-1185.

[38] J. Langlieb, N. S. Sachdev, K. S. Balderrama, et al., “The Molecular Cytoarchitecture of the Adult Mouse Brain, ” Nature 624, no. 7991 (2023): 333-342.

[39] S. G. Rodriques, R. R. Stickels, A. Goeva, et al., “Slide-seq: A Scalable Technology for Measuring Genome-wide Expression at High Spatial Resolution, ” Science 363, no. 6434 (2019): 1463-1467.

[40] S. Vickovic, G. Eraslan, F. Salmén, et al., “High-definition Spatial Transcriptomics for in Situ Tissue Profiling, ” Nature Methods 16, no. 10 (2019): 987-990.

[41] A. Enninful, Z. Zhang, D. Klymyshyn, et al., “Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus, ” Res Sq (2024). Published online November 11, 2024.

[42] Y. Liu, M. Yang, Y. Deng, et al., “High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue, ” Cell 183, no. 6 (2020): 1665-1681.

[43] Y. Lei, X. Liang, Y. Sun, et al., “Region-specific Transcriptomic Responses to Obesity and Diabetes in Macaque Hypothalamus, ” Cell metabolism 36, no. 2 (2024): 438-453. e6.

[44] Y. Zhang, G. Liu, Q. Zeng, et al., “CCL19-producing Fibroblasts Promote Tertiary Lymphoid Structure Formation Enhancing Anti-tumor IgG Response in Colorectal Cancer Liver Metastasis, ” Cancer Cell 42, no. 8 (2024): 1370-1385. e9.

[45] A. Chen, S. Liao, M. Cheng, et al., “Spatiotemporal Transcriptomic Atlas of Mouse Organogenesis Using DNA Nanoball-patterned Arrays, ” Cell 185, no. 10 (2022): 1777-1792. e21.

[46] Y. Fan, Ž. Andrusivová, Y. Wu, et al., “Expansion Spatial Transcriptomics, ” Nature Methods 20, no. 8 (2023): 1179-1182.

[47] M. Schott, D. León-Periñán, E. Splendiani, et al., “Open-ST: High-resolution Spatial Transcriptomics in 3D, ” Cell 187, no. 15 (2024): 3953-3972. e26.

[48] M. Schott, D. León-Periñán, E. Splendiani, et al., “Protocol for High-resolution 3D Spatial Transcriptomics Using Open-ST, ” STAR Protoc 6, no. 1 (2025): 103521.

[49] S. R. Srivatsan, M. C. Regier, E. Barkan, et al., “Embryo-scale, Single Cell Spatial Transcriptomics, ” Science 373, no. 6550 (2021): 111-117.

[50] J. Ding, L. Li, Q. Lu, et al., “SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology, ” Journal of computational biology 31, no. 9 (2024): 871-885.

[51] Y. Lee, D. Bogdanoff, Y. Wang, et al., “XYZeq: Spatially Resolved Single-cell RNA Sequencing Reveals Expression Heterogeneity in the Tumor Microenvironment, ” Science Advances 7, no. 17 (2021): eabg4755.

[52] J. Yang, Z. Zheng, Y. Jiao, et al., “Spotiphy Enables Single-cell Spatial Whole Transcriptomics Across an Entire Section, ” Nature Methods 22, no. 4 (2025): 724-736. Published online March 12, 2025.

[53] S. Mallik, J. Venezian, A. Lobov, et al., “Structural Determinants of co-translational Protein Complex Assembly, ” Cell 188, no. 3 (2025): 764-777. e22.

[54] A. M. Femino, F. S. Fay, K. Fogarty, R. H. Singer, “Visualization of Single RNA Transcripts in Situ, ” Science 280, no. 5363 (1998): 585-590.

[55] T. Lu, M. Wang, W. Zhou, et al., “Decoding Transcriptional Identity in Developing human Sensory Neurons and Organoid Modeling, ” Cell 187, no. 26 (2024): 7374-7393. e28.

[56] E. Lubeck, A. F. Coskun, T. Zhiyentayev, M. Ahmad, L. Cai, “Single-cell in Situ RNA Profiling by Sequential Hybridization, ” Nature Methods 11, no. 4 (2014): 360-361.

[57] A. Sarfatis, Y. Wang, N. Twumasi-Ankrah, J. R. Moffitt, “Highly Multiplexed Spatial Transcriptomics in Bacteria, ” Science 387, no. 6732 (2025): eadr0932.

[58] Z. Yao, C. T. J. van Velthoven, M. Kunst, et al., “A High-resolution Transcriptomic and Spatial Atlas of Cell Types in the Whole Mouse Brain, ” Nature 624, no. 7991 (2023): 317-332.

[59] K. H. Chen, A. N. Boettiger, J. R. Moffitt, S. Wang, X. Zhuang, “RNA Imaging. Spatially Resolved, Highly Multiplexed RNA Profiling in Single Cells, ” Science 348, no. 6233 (2015): aaa6090.

[60] S. Kanatani, J. C. Kreutzmann, Y. Li, et al., “Whole-brain Spatial Transcriptional Analysis at Cellular Resolution, ” Science 386, no. 6724 (2024): 907-915.

[61] P. Kukanja, C. M. Langseth, L. A. Rubio Rodríguez-Kirby, et al., “Cellular Architecture of Evolving Neuroinflammatory Lesions and Multiple Sclerosis Pathology, ” Cell 187, no. 8 (2024): 1990-2009. e19.

[62] R. Ke, M. Mignardi, A. Pacureanu, et al., “In Situ Sequencing for RNA Analysis in Preserved Tissue and Cells, ” Nature Methods 10, no. 9 (2013): 857-860.

[63] H. Q. Nguyen, S. Chattoraj, D. Castillo, et al., “3D mapping and Accelerated Super-resolution Imaging of the human Genome Using in Situ Sequencing, ” Nature Methods 17, no. 8 (2020): 822-832.

[64] J. H. Lee, E. R. Daugharthy, J. Scheiman, et al., “Fluorescent in Situ Sequencing (FISSEQ) of RNA for Gene Expression Profiling in Intact Cells and Tissues, ” Nature Protocols 10, no. 3 (2015): 442-458.

[65] H. Shi, Y. He, Y. Zhou, et al., “Spatial Atlas of the Mouse central Nervous System at Molecular Resolution, ” Nature 622, no. 7983 (2023): 552-561.

[66] X. Wang, W. E. Allen, M. A. Wright, et al., “Three-dimensional Intact-tissue Sequencing of Single-cell Transcriptional States, ” Science 361, no. 6400 (2018): eaat5691.

[67] X. Chen, Y. C. Sun, G. M. Church, J. H. Lee, A. M. Zador, “Efficient in Situ Barcode Sequencing Using Padlock Probe-based BaristaSeq, ” Nucleic Acids Res. 46, no. 4 (2018): e22.

[68] Y. Zhang, J. A. Miller, J. Park, et al., “Reference-based Cell Type Matching of in Situ Image-based Spatial Transcriptomics Data on Primary Visual Cortex of Mouse Brain, ” Scientific Reports 13, no. 1 (2023): 9567.

[69] X. Chen, S. Fischer, M. C. P. Rue, et al., “Whole-cortex in Situ Sequencing Reveals Input-dependent Area Identity, ” Nature (2024). Published online April 24, 2024.

[70] X. Chen, Y. C. Sun, H. Zhan, et al., “High-Throughput Mapping of Long-Range Neuronal Projection Using in Situ Sequencing, ” Cell 179, no. 3 (2019): 772-786. e19.

[71] Y. C. Sun, X. Chen, S. Fischer, et al., “Integrating Barcoded Neuroanatomy With Spatial Transcriptional Profiling Enables Identification of Gene Correlates of Projections, ” Nature Neuroscience 24, no. 6 (2021): 873-885.

[72] X. Wu, W. Xu, L. Deng, et al., “Spatial Multi-omics at Subcellular Resolution via High-throughput in Situ Pairwise Sequencing, ” Nat Biomed Eng 8, no. 7 (2024): 872-889.

[73] Q. Li, X. Zhang, R. Ke, “Spatial Transcriptomics for Tumor Heterogeneity Analysis, ” Frontiers in Genetics 13 (2022): 906158.

[74] J. R. Moffitt, E. Lundberg, H. Heyn, “The Emerging Landscape of Spatial Profiling Technologies, ” Nature Reviews Genetics 23, no. 12 (2022): 741-759.

[75] C. G. Williams, H. J. Lee, T. Asatsuma, R. Vento-Tormo, A. Haque, “An Introduction to Spatial Transcriptomics for Biomedical Research, ” Genome Med 14, no. 1 (2022): 68.

[76] A. Lyubimova, S. Itzkovitz, J. P. Junker, Z. P. Fan, X. Wu, A. van Oudenaarden, “Single-molecule mRNA Detection and Counting in Mammalian Tissue, ” Nature Protocols 8, no. 9 (2013): 1743-1758.

[77] C. H. L. Eng, M. Lawson, Q. Zhu, et al., “Transcriptome-scale Super-resolved Imaging in Tissues by RNA seqFISH, ” Nature 568, no. 7751 (2019): 235-239.

[78] N. Jung, T. K. Kim, “Spatial Transcriptomics in Neuroscience, ” Experimental & Molecular Medicine 55, no. 10 (2023): 2105-2115.

[79] H. S. Kaya-Okur, S. J. Wu, C. A. Codomo, et al., “CUT&Tag for Efficient Epigenomic Profiling of Small Samples and Single Cells, ” Nature Communications 10, no. 1 (2019): 1930.

[80] J. D. Buenrostro, B. Wu, U. M. Litzenburger, et al., “Single-cell Chromatin Accessibility Reveals Principles of Regulatory Variation, ” Nature 523, no. 7561 (2015): 486-490.

[81] T. Lu, C. E. Ang, X. Zhuang, “Spatially Resolved Epigenomic Profiling of Single Cells in Complex Tissues, ” Cell 185, no. 23 (2022): 4448-4464. e17.

[82] Y. Deng, M. Bartosovic, P. Kukanja, et al., “Spatial-CUT&Tag: Spatially Resolved Chromatin Modification Profiling at the Cellular Level, ” Science 375, no. 6581 (2022): 681-686.

[83] P. Ma, S. Duan, W. Ma, et al., “Single-cell Chromatin Accessibility Landscape Profiling Reveals the Diversity of Epigenetic Regulation in the Rat Nervous System, ” Scientific Data 12, no. 1 (2025): 140.

[84] M. Stoeckius, C. Hafemeister, W. Stephenson, et al., “Simultaneous Epitope and Transcriptome Measurement in Single Cells, ” Nature Methods 14, no. 9 (2017): 865-868.

[85] V. M. Peterson, K. X. Zhang, N. Kumar, et al., “Multiplexed Quantification of Proteins and Transcripts in Single Cells, ” Nature Biotechnology 35, no. 10 (2017): 936-939.

[86] M. Angelo, S. C. Bendall, R. Finck, et al., “Multiplexed Ion Beam Imaging of human Breast Tumors, ” Nature Medicine 20, no. 4 (2014): 436-442.

[87] Y. Goltsev, N. Samusik, J. Kennedy-Darling, et al., “Deep Profiling of Mouse Splenic Architecture With CODEX Multiplexed Imaging, ” Cell 174, no. 4 (2018): 968-981. e15.

[88] H. S. Bhatia, A. D. Brunner, F. Öztürk, et al., “Spatial Proteomics in Three-dimensional Intact Specimens, ” Cell 185, no. 26 (2022): 5040-5058. e19.

[89] E. M. Unterauer, S. Shetab Boushehri, K. Jevdokimenko, et al., “Spatial Proteomics in Neurons at Single-protein Resolution, ” Cell 187, no. 7 (2024): 1785-1800. e16.

[90] R. Sankowski, P. Süß, A. Benkendorff, et al., “Multiomic Spatial Landscape of Innate Immune Cells at human central Nervous System Borders, ” Nature Medicine 30, no. 1 (2024): 186-198.

[91] R. L. Hansen, Y. J. Lee, “High-Spatial Resolution Mass Spectrometry Imaging: Toward Single Cell Metabolomics in Plant Tissues, ” Chemical Record 18, no. 1 (2018): 65-77.

[92] P. J. Ahl, R. A. Hopkins, W. W. Xiang, et al., “Met-Flow, a Strategy for Single-cell Metabolic Analysis Highlights Dynamic Changes in Immune Subpopulations, ” Communications Biology 3, no. 1 (2020): 305.

[93] Z. Yuan, Q. Zhou, L. Cai, et al., “SEAM Is a Spatial Single Nuclear Metabolomics Method for Dissecting Tissue Microenvironment, ” Nature Methods 18, no. 10 (2021): 1223-1232.

[94] Y. Zhu, Q. Zang, Z. Luo, J. He, R. Zhang, Z. Abliz, “An Organ-Specific Metabolite Annotation Approach for Ambient Mass Spectrometry Imaging Reveals Spatial Metabolic Alterations of a Whole Mouse Body, ” Analytical Chemistry 94, no. 20 (2022): 7286-7294.

[95] R. de Ceglia, A. Ledonne, D. G. Litvin, et al., “Specialized Astrocytes Mediate Glutamatergic Gliotransmission in the CNS, ” Nature 622, no. 7981 (2023): 120-129.

[96] S. Song, H. Oft, S. Metwally, et al., “Deletion of Slc9a1 in Cx3cr1+ Cells Stimulated Microglial Subcluster CREB1 Signaling and Microglia‑Oligodendrocyte Crosstalk, ” J Neuroinflammation 21, no. 1 (2024): 69. Published online 2024.

[97] E. Candelario-Jalil, R. M. Dijkhuizen, T. Magnus, “Neuroinflammation, Stroke, Blood-Brain Barrier Dysfunction, and Imaging Modalities, ” Stroke; A Journal of Cerebral Circulation 53, no. 5 (2022): 1473-1486.

[98] Y. Zhang, J. Li, Y. Zhao, et al., “Arresting the Bad Seed: HDAC3 Regulates Proliferation of Different Microglia After Ischemic Stroke, ” Science Advances 10, no. 10 (2024): eade6900.

[99] H. Li, P. Liu, B. Zhang, et al., “Acute Ischemia Induces Spatially and Transcriptionally Distinct Microglial Subclusters, ” Genome Med 15 (2023): 109.

[100] X. Li, J. Lyu, R. Li, et al., “Single-cell Transcriptomic Analysis of the Immune Cell Landscape in the Aged Mouse Brain After Ischemic Stroke, ” J Neuroinflammation 19 (2022): 83.

[101] G. S. Kim, E. Harmon, M. C. Gutierrez, et al., “Single-cell Analysis Identifies Ifi27l2a as a Gene Regulator of Microglial Inflammation in the Context of Aging and Stroke in Mice, ” Nature Communications 16, no. 1 (2025): 1639.

[102] P. Zong, J. Feng, C. X. Li, et al., “Activation of Endothelial TRPM2 Exacerbates Blood-brain Barrier Degradation in Ischemic Stroke, ” Cardiovascular Research 120, no. 2 (2023): 188-202.

[103] X. Jiang, A. V. Andjelkovic, L. Zhu, et al., “Blood-brain Barrier Dysfunction and Recovery After Ischemic Stroke, ” Progress in Neurobiology 163-164 (2018): 144-171.

[104] Y. Li, B. Liu, T. Zhao, et al., “Comparative Study of Extracellular Vesicles Derived From Mesenchymal Stem Cells and Brain Endothelial Cells Attenuating Blood-brain Barrier Permeability via Regulating Caveolin-1-dependent ZO-1 and Claudin-5 Endocytosis in Acute Ischemic Stroke, ” J Nanobiotechnology 21, no. 1 (2023): 70.

[105] Y. Zou, Y. Xu, X. Chen, Y. Wu, L. Fu, Y. Lv, “Research Progress on Leucine-Rich Alpha-2 Glycoprotein 1: A Review, ” Frontiers in Pharmacology 12 (2022): 809225.

[106] Z. Ruan, G. Cao, Y. Qian, et al., “Single-cell RNA Sequencing Unveils Lrg1's Role in Cerebral Ischemia‒Reperfusion Injury by Modulating Various Cells, ” J Neuroinflammation 20, no. 1 (2023): 285.

[107] S. Muhammad, W. Barakat, S. Stoyanov, et al., “The HMGB1 Receptor RAGE Mediates Ischemic Brain Damage, ” Journal of Neuroscience 28, no. 46 (2008): 12023-12031.

[108] Y. Xh, W. Y, G. Pp, “Lipoxin A4 Analogue Protects Brain and Reduces Inflammation in a Rat Model of Focal Cerebral Ischemia Reperfusion, ” Brain Research 1323 (2010): 174-83.

[109] Y. Liu, X. Li, C. Cao, et al., “Critical Role of Slc22a8 in Maintaining Blood-brain Barrier Integrity After Experimental Cerebral Ischemia-reperfusion, ” Journal of Cerebral Blood Flow and Metabolism 45, no. 1 (2025): 85-101. Published online July 28, 2024:271678×241264401.

[110] A. Patir, J. Barrington, S. Szymkowiak, et al., “Phenotypic and Spatial Heterogeneity of Brain Myeloid Cells After Stroke Is Associated With Cell Ontogeny, Tissue Damage, and Brain Connectivity, ” Cell Reports 43, no. 5 (2024): 114250.

[111] S. Bardehle, M. Krüger, F. Buggenthin, et al., “Live Imaging of Astrocyte Responses to Acute Injury Reveals Selective Juxtavascular Proliferation, ” Nature Neuroscience 16, no. 5 (2013): 580-586.

[112] I. B. Wanner, M. A. Anderson, B. Song, et al., “Glial Scar Borders Are Formed by Newly Proliferated, Elongated Astrocytes That Interact to Corral Inflammatory and Fibrotic Cells via STAT3-Dependent Mechanisms After Spinal Cord Injury, ” Journal of Neuroscience 33, no. 31 (2013): 12870-12886.

[113] R. D. Kim, A. E. Marchildon, P. W. Frazel, P. Hasel, A. X. Guo, S. A. Liddelow, “Temporal and Spatial Analysis of Astrocytes Following Stroke Identifies Novel Drivers of Reactivity,” BioRxiv (2023). Published online November 20, 2023:2023.11.12.566710.

[114] E. Y. Scott, N. Safarian, D. L. Casasbuenas, et al., “Integrating Single-cell and Spatially Resolved Transcriptomic Strategies to Survey the Astrocyte Response to Stroke in Male Mice, ” Nature Communications 15, no. 1 (2024): 1584.

[115] D. Bormann, M. Knoflach, E. Poreba, et al., “Single-nucleus RNA Sequencing Reveals Glial Cell Type-specific Responses to Ischemic Stroke in Male Rodents, ” Nature Communications 15, no. 1 (2024): 6232.

[116] Y. Jin, S. E. Dougherty, K. Wood, et al., “Regrowth of Serotonin Axons in the Adult Mouse Brain Following Injury, ” Neuron 91, no. 4 (2016): 748-762.

[117] P. Langhorne, J. Bernhardt, G. Kwakkel, “Stroke Rehabilitation, ” Lancet 377, no. 9778 (2011): 1693-1702.

[118] H. Abe, S. Jitsuki, W. Nakajima, et al., “CRMP2-binding Compound, Edonerpic Maleate, Accelerates Motor Function Recovery From Brain Damage, ” Science 360, no. 6384 (2018): 50-57.

[119] M. T. Joy, E. Ben Assayag, D. Shabashov-Stone, et al., “CCR5 Is a Therapeutic Target for Recovery After Stroke and Traumatic Brain Injury, ” Cell 176, no. 5 (2019): 1143-1157. e13.

[120] J. Mt, C. St, “Encouraging an Excitable Brain state: Mechanisms of Brain Repair in Stroke, ” Nature Reviews Neuroscience 22, no. 1 (2021): 38-53.

[121] G. H. D. Poplawski, R. Kawaguchi, E. Van Niekerk, et al., “Injured Adult Neurons Regress to an Embryonic Transcriptional Growth state, ” Nature 581, no. 7806 (2020): 77-82.

[122] B. Han, S. Zhou, Y. Zhang, et al., “Integrating Spatial and Single-cell Transcriptomics to Characterize the Molecular and Cellular Architecture of the Ischemic Mouse Brain, ” Science Translational Medicine 16, no. 733 (2024): eadg1323.

[123] S. Song, L. Yu, M. N. Hasan, et al., “Elevated Microglial Oxidative Phosphorylation and Phagocytosis Stimulate Post-stroke Brain Remodeling and Cognitive Function Recovery in Mice, ” Communications Biology 5, no. 1 (2022): 35.

[124] S. Jin, C. F. Guerrero-Juarez, L. Zhang, et al., “Inference and Analysis of Cell-cell Communication Using CellChat, ” Nature Communications 12, no. 1 (2021): 1088.

[125] C. Jin, Y. Shi, L. Shi, et al., “Leveraging Single-cell RNA Sequencing to Unravel the Impact of Aging on Stroke Recovery Mechanisms in Mice, ” PNAS 120, no. 25 (2023): e2300012120.

[126] J. Magid-Bernstein, R. Girard, S. Polster, et al., “Cerebral Hemorrhage: Pathophysiology, Treatment, and Future Directions, ” Circulation Research 130, no. 8 (2022): 1204-1229.

[127] L. Gu, H. Chen, M. Sun, et al., “Unraveling Dynamic Immunological Landscapes in Intracerebral Hemorrhage: Insights From Single-cell and Spatial Transcriptomic Profiling, ” MedComm 5, no. 7 (2024): e635.

[128] L. Ye, X. Tang, J. Zhong, et al., “Unraveling the Complex Pathophysiology of White Matter Hemorrhage in Intracerebral Stroke: A Single-cell RNA Sequencing Approach, ” CNS neuroscience & therapeutics 30, no. 3 (2024): e14652.

[129] P. Zhang, C. Gao, Q. Guo, et al., “Single-cell RNA Sequencing Reveals the Evolution of the Immune Landscape During Perihematomal Edema Progression After Intracerebral Hemorrhage, ” J Neuroinflammation 21, no. 1 (2024): 140.

[130] Y. Huang, R. W. Mahley, “Apolipoprotein E: Structure and Function in Lipid Metabolism, Neurobiology, and Alzheimer's Diseases, ” Neurobiology of Disease 72, no. Pt A (2014): 3-12.

[131] Y. Huang, L. Mucke, “Alzheimer Mechanisms and Therapeutic Strategies, ” Cell 148, no. 6 (2012): 1204-1222.

[132] N. Koutsodendris, M. R. Nelson, A. Rao, Y. Huang, “Apolipoprotein E and Alzheimer's Disease: Findings, Hypotheses, and Potential Mechanisms, ” Annu Rev Pathol 17 (2022): 73-99.

[133] Y. Shi, M. Manis, J. Long, et al., “Microglia Drive APOE-dependent Neurodegeneration in a Tauopathy Mouse Model, ” Journal of Experimental Medicine 216, no. 11 (2019): 2546-2561.

[134] J. Therriault, A. L. Benedet, T. A. Pascoal, et al., “APOEε4 potentiates the Relationship Between Amyloid-β and Tau Pathologies, ” Molecular Psychiatry 26, no. 10 (2021): 5977-5988.

[135] C. Wang, R. Najm, Q. Xu, et al., “Gain of Toxic Apolipoprotein E4 Effects in human iPSC-derived Neurons Is Ameliorated by a Small-molecule Structure Corrector, ” Nature Medicine 24, no. 5 (2018): 647-657.

[136] J. Zhao, Y. Fu, Y. Yamazaki, et al., “APOE4 exacerbates Synapse Loss and Neurodegeneration in Alzheimer's disease Patient iPSC-derived Cerebral Organoids, ” Nature Communications 11, no. 1 (2020): 5540.

[137] J. W. Blanchard, L. A. Akay, J. Davila-Velderrain, et al., “APOE4 impairs Myelination via Cholesterol Dysregulation in Oligodendrocytes, ” Nature 611, no. 7937 (2022): 769-779.

[138] G. Barisano, K. Kisler, B. Wilkinson, et al., “A “Multi-omics” Analysis of Blood-brain Barrier and Synaptic Dysfunction in APOE4 Mice, ” Journal of Experimental Medicine 219, no. 11 (2022): e20221137.

[139] L. Brase, S. F. You, R. D'Oliveira Albanus, et al., “Single-nucleus RNA-sequencing of Autosomal Dominant Alzheimer Disease and Risk Variant Carriers, ” Nature Communications 14, no. 1 (2023): 2314.

[140] M. S. Haney, R. Pálovics, C. N. Munson, et al., “APOE4/4 is Linked to Damaging Lipid Droplets in Alzheimer's Disease Microglia, ” Nature 628, no. 8006 (2024): 154-161.

[141] Z. S. Ji, R. E. Pitas, R. W. Mahley, “Differential Cellular Accumulation/Retention of Apolipoprotein E Mediated by Cell Surface Heparan Sulfate Proteoglycans. Apolipoproteins E3 and E2 Greater Than e4, ” Journal of Biological Chemistry 273, no. 22 (1998): 13452-13460.

[142] Y. Yamauchi, N. Deguchi, C. Takagi, et al., “Role of the N- and C-terminal Domains in Binding of Apolipoprotein E Isoforms to Heparan Sulfate and Dermatan Sulfate: A Surface Plasmon Resonance Study, ” Biochemistry 47, no. 25 (2008): 6702-6710.

[143] J. F. Arboleda-Velasquez, F. Lopera, M. O'Hare, “Resistance to Autosomal Dominant Alzheimer's Disease in an APOE3 Christchurch Homozygote: A Case Report, ” Nature Medicine 25, no. 11 (2019): 1680-1683.

[144] C. C. Liu, M. E. Murray, X. Li, et al., “APOE3-Jacksonville (V236E) Variant Reduces Self-aggregation and Risk of Dementia, ” Science Translational Medicine 13, no. 613 (2021): eabc9375.

[145] M. C. Almeida, S. J. Eger, C. He, et al., “Single-nucleus RNA Sequencing Demonstrates an Autosomal Dominant Alzheimer's Disease Profile and Possible Mechanisms of Disease Protection, ” Neuron 112, no. 11 (2024): 1778-1794. e7.

[146] B. Chambraud, E. Sardin, J. Giustiniani, et al., “A Role for FKBP52 in Tau Protein Function, ” PNAS 107, no. 6 (2010): 2658-2663.

[147] J. N. Rauch, G. Luna, E. Guzman, et al., “LRP1 is a Master Regulator of Tau Uptake and Spread, ” Nature 580, no. 7803 (2020): 381-385.

[148] M. R. Nelson, “The APOE-R136S Mutation Protects Against APOE4-driven Tau Pathology, Neurodegeneration and Neuroinflammation, ” Nature Neuroscience 26 (2023): 2104-2121.

[149] S. Alford, D. Patel, N. Perakakis, C. S. Mantzoros, “Obesity as a Risk Factor for Alzheimer's Disease: Weighing the Evidence, ” Obesity Reviews 19, no. 2 (2018): 269-280.

[150] A. Singh-Manoux, A. Dugravot, M. Shipley, et al., “Obesity Trajectories and Risk of Dementia: 28 Years of Follow-up in the Whitehall II Study, ” Alzheimers Dement 14, no. 2 (2018): 178-186.

[151] S. Suzzi, T. Croese, A. Ravid, et al., “N-acetylneuraminic Acid Links Immune Exhaustion and Accelerated Memory Deficit in Diet-induced Obese Alzheimer's disease Mouse Model, ” Nature Communications 14, no. 1 (2023): 1293.

[152] B. M. Bettcher, M. G. Tansey, G. Dorothée, M. T. Heneka, “Peripheral and central Immune System Crosstalk in Alzheimer Disease — a Research Prospectus, ” Nature reviews Neurology 17, no. 11 (2021): 689-701.

[153] Y. Lu, C. Saibro-Girardi, N. F. Fitz, et al., “Multi-transcriptomics Reveals Brain Cellular Responses to Peripheral Infection in Alzheimer's disease Model Mice, ” Cell reports 42, no. 7 (2023): 112785.

[154] Y. Zhang, H. Chen, R. Li, K. Sterling, W. Song, “Amyloid β-based Therapy for Alzheimer's Disease: Challenges, Successes and Future, ” Signal Transduct Target Ther 8, no. 1 (2023): 248.

[155] V. Gazestani, T. Kamath, N. M. Nadaf, et al., “Early Alzheimer's Disease Pathology in human Cortex Involves Transient Cell States, ” Cell 186, no. 20 (2023): 4438-4453. e23.

[156] A. Ishii, J. A. Pathoulas, O. MoustafaFathy Omar, et al., “Contribution of Amyloid Deposition From Oligodendrocytes in a Mouse Model of Alzheimer's Disease, ” Mol Neurodegeneration 19, no. 1 (2024): 83.

[157] N. Habib, C. McCabe, S. Medina, et al., “Disease-associated Astrocytes in Alzheimer's Disease and Aging, ” Nature Neuroscience 23, no. 6 (2020): 701-706.

[158] J. Xie, Y. Lan, C. Zou, et al., “Single-nucleus Analysis Reveals Microenvironment-specific Neuron and Glial Cell Enrichment in Alzheimer's Disease, ” BMC Genomics [Electronic Resource] 25, no. 1 (2024): 526.

[159] E. Giraldo, A. Lloret, T. Fuchsberger, J. Viña, “Aβ and Tau Toxicities in Alzheimer's Are Linked via Oxidative Stress-induced p38 Activation: Protective Role of Vitamin E, ” Redox Biology 2 (2014): 873-877.

[160] S. Tsartsalis, H. Sleven, N. Fancy, et al., “A Single Nuclear Transcriptomic Characterisation of Mechanisms Responsible for Impaired Angiogenesis and Blood-brain Barrier Function in Alzheimer's Disease, ” Nature Communications 15, no. 1 (2024): 2243.

[161] N. N. Fancy, A. M. Smith, A. Caramello, et al., “Characterisation of Premature Cell Senescence in Alzheimer's Disease Using Single Nuclear Transcriptomics, ” Acta Neuropathologica 147, no. 1 (2024): 78.

[162] Y. Chen, Y. Yu, “Tau and Neuroinflammation in Alzheimer's Disease: Interplay Mechanisms and Clinical Translation, ” J Neuroinflammation 20, no. 1 (2023): 165.

[163] A. Wachter, M. E. Woodbury, S. Lombardo, et al., “Landscape of Brain Myeloid Cell Transcriptome Along the Spatiotemporal Progression of Alzheimer's Disease Reveals Distinct Sequential Responses to Aβ and Tau, ” Acta Neuropathologica 147, no. 1 (2024): 65.

[164] R. Duan, A. Liu, Y. Sun, et al., “Loss of Smek1 Induces Tauopathy and Triggers Neurodegeneration by Regulating Microtubule Stability, ” Advanced Science 11, no. 40 (2024): 2400584.

[165] H. Fu, J. Hardy, K. E. Duff, “Selective Vulnerability in Neurodegenerative Diseases, ” Nature Neuroscience 21, no. 10 (2018): 1350-1358.

[166] R. Praschberger, S. Kuenen, N. Schoovaerts, et al., “Neuronal Identity Defines α-synuclein and Tau Toxicity, ” Neuron 111, no. 10 (2023): 1577-1590. e11.

[167] J. Aguila, S. Cheng, N. Kee, et al., “Spatial RNA Sequencing Identifies Robust Markers of Vulnerable and Resistant Human Midbrain Dopamine Neurons and Their Expression in Parkinson's Disease, ” Front Mol Neurosci 14 (2021): 699562.

[168] L. Lin, O. Isacson, “Axonal Growth Regulation of Fetal and Embryonic Stem Cell-derived Dopaminergic Neurons by Netrin-1 and Slits, ” Stem Cells 24, no. 11 (2006): 2504-2513.

[169] I. Bezprozvanny, “Calcium Signaling and Neurodegenerative Diseases, ” Trends in Molecular Medicine 15, no. 3 (2009): 89-100.

[170] M. Maor-Nof, Z. Shipony, R. Lopez-Gonzalez, et al., “53 is a central Regulator Driving Neurodegeneration Caused by C9orf72 Poly(PR), ” Cell 184, no. 3 (2021): 689.

[171] C. Y. Kao, M. Xu, L. Wang, et al., “Elevated COUP-TFII Expression in Dopaminergic Neurons Accelerates the Progression of Parkinson's Disease Through Mitochondrial Dysfunction, ” PLos Genet 16, no. 6 (2020): e1008868.

[172] S. Smajić, C. A. Prada-Medina, Z. Landoulsi, et al., “Single-cell Sequencing of human Midbrain Reveals Glial Activation and a Parkinson-specific Neuronal state, ” Brain 145, no. 3 (2022): 964-978.

[173] I. Brunk, C. Blex, D. Speidel, N. Brose, G. Ahnert-Hilger, “Ca2+-dependent Activator Proteins of Secretion Promote Vesicular Monoamine Uptake, ” Journal of Biological Chemistry 284, no. 2 (2009): 1050-1056.

[174] P. Reinhardt, B. Schmid, L. F. Burbulla, et al., “Genetic Correction of a LRRK2 Mutation in human iPSCs Links Parkinsonian Neurodegeneration to ERK-dependent Changes in Gene Expression, ” Cell Stem Cell 12, no. 3 (2013): 354-367.

[175] K. Tiklová, Å. K. Björklund, L. Lahti, et al., “Single-cell RNA Sequencing Reveals Midbrain Dopamine Neuron Diversity Emerging During Mouse Brain Development, ” Nature Communications 10, no. 1 (2019): 581.

[176] H. Braak, U. Rüb, K. Del Tredici, “Cognitive Decline Correlates With Neuropathological Stage in Parkinson's Disease, ” Journal of the Neurological Sciences 248, no. 1 (2006): 255-258.

[177] D. J. Irwin, M. Grossman, D. Weintraub, et al., “Neuropathological and Genetic Correlates of Survival and Dementia Onset in Synucleinopathies: A Retrospective Analysis, ” Lancet Neurology 16, no. 1 (2017): 55-65.

[178] C. Smith, N. Malek, K. Grosset, B. Cullen, S. Gentleman, D. G. Grosset, “Neuropathology of Dementia in Patients With Parkinson's Disease: A Systematic Review of Autopsy Studies, ” Journal of Neurology, Neurosurgery, and Psychiatry 90, no. 11 (2019): 1234-1243.

[179] L. Yu, T. Wang, R. S. Wilson, et al., “Common Age-related Neuropathologies and Yearly Variability in Cognition, ” Ann Clin Transl Neurol 6, no. 11 (2019): 2140-2149.

[180] T. M. Goralski, L. Meyerdirk, L. Breton, et al., “Spatial Transcriptomics Reveals Molecular Dysfunction Associated With Cortical Lewy Pathology, ” Nature Communications 15 (2024): 2642.

[181] L. Horan-Portelance, M. Iba, D. J. Acri, J. R. Gibbs, M. R. Cookson, “Imaging Spatial Transcriptomics Reveals Molecular Patterns of Vulnerability to Pathology in a Transgenic α-synucleinopathy Model,” BioRxiv (2024). Published online December 14, 2024.

[182] L. Rojanathammanee, E. J. Murphy, C. K. Combs, “Expression of Mutant Alpha-synuclein Modulates Microglial Phenotype in Vitro, ” J Neuroinflammation 8 (2011): 44.

[183] A. S. Harms, C. J. Barnum, K. A. Ruhn, et al., “Delayed Dominant-Negative TNF Gene Therapy Halts Progressive Loss of Nigral Dopaminergic Neurons in a Rat Model of Parkinson's Disease, ” Molecular Therapy 19, no. 1 (2011): 46-52.

[184] Q. Liu, Z. Liu, W. Xie, et al., “Single-cell Sequencing of the substantia nigra Reveals Microglial Activation in a Model of MPTP, ” Frontiers in aging neuroscience 16 (2024): 1390310.

[185] H. L. Smith, O. J. Freeman, A. J. Butcher, et al., “Astrocyte Unfolded Protein Response Induces a Specific Reactivity State That Causes Non-Cell-Autonomous Neuronal Degeneration, ” Neuron 105, no. 5 (2020): 855.

[186] J. G. Sheng, K. Ito, R. D. Skinner, “In Vivo and In Vitro Evidence Supporting a Role for the Inflammatory Cytokine Interleukin-1 as a Driving Force in Alzheimer Pathogenesis, ” Neurobiology of Aging 17, no. 5 (1996): 761-766, Accessed January 25, 2024 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886636/.

[187] K. Sathe, W. Maetzler, J. D. Lang, et al., “S100B is Increased in Parkinson's Disease and Ablation Protects Against MPTP-induced Toxicity Through the RAGE and TNF-α Pathway, ” Brain 135, no. Pt 11 (2012): 3336-3347.

[188] D. Agarwal, C. Sandor, V. Volpato, et al., “A Single-cell Atlas of the human Substantia nigra Reveals Cell-specific Pathways Associated With Neurological Disorders, ” Nature Communications 11 (2020): 4183.

[189] P. Wang, L. Yao, M. Luo, et al., “Single-cell Transcriptome and TCR Profiling Reveal Activated and Expanded T Cell Populations in Parkinson's Disease, ” Cell Discovery 7, no. 1 (2021): 52.

[190] P. Wang, M. Luo, W. Zhou, et al., “Global Characterization of Peripheral B Cells in Parkinson's Disease by Single-Cell RNA and BCR Sequencing, ” Frontiers in Immunology 13 (2022), Accessed January 30, 2024 https://www.frontiersin.org/articles/10.3389/fimmu.2022.814239.

[191] A. M. Schonhoff, D. A. Figge, G. P. Williams, et al., “Border-associated Macrophages Mediate the Neuroinflammatory Response in an Alpha-synuclein Model of Parkinson disease, ” Nature Communications 14, no. 1 (2023): 3754.

[192] G. P. Williams, A. M. Schonhoff, A. Jurkuvenaite, N. J. Gallups, D. G. Standaert, A. S. Harms, “CD4 T Cells Mediate Brain Inflammation and Neurodegeneration in a Mouse Model of Parkinson's Disease, ” Brain 144, no. 7 (2021): 2047-2059.

[193] R. Stupp, W. P. Mason, M. J. van den Bent, et al., “Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma, ” New England Journal of Medicine 352, no. 10 (2005): 987-996.

[194] C. Neftel, J. Laffy, M. G. Filbin, et al., “An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma, ” Cell 178, no. 4 (2019): 835-849. e21.

[195] Y. Ren, Z. Huang, L. Zhou, et al., “Spatial Transcriptomics Reveals Niche-specific Enrichment and Vulnerabilities of Radial Glial Stem-Like Cells in Malignant Gliomas, ” Nature Communications 14 (2023): 1028.

[196] R. Lm, W. Okn, M. G, et al., “Gradient of Developmental and Injury Response Transcriptional States Defines Functional Vulnerabilities Underpinning Glioblastoma Heterogeneity, ” Nature Cancer 2, no. 2 (2021): 157-173.

[197] M. L. Suvà, I. Tirosh, “The Glioma Stem Cell Model in the Era of Single-Cell Genomics, ” Cancer Cell 37, no. 5 (2020): 630-636.

[198] A. Bhaduri, E. Di Lullo, D. Jung, et al., “Outer Radial Glia-Like Cancer Stem Cells Contribute to Heterogeneity of Glioblastoma, ” Cell Stem Cell 26, no. 1 (2020): 48-63. e6.

[199] A. A. Pollen, T. J. Nowakowski, J. Chen, et al., “Molecular Identity of Human Outer Radial Glia during Cortical Development, ” Cell 163, no. 1 (2015): 55-67.

[200] A. A. Hamed, D. J. Kunz, I. El-Hamamy, et al., “A Brain Precursor Atlas Reveals the Acquisition of Developmental-Like States in Adult Cerebral Tumours, ” Nature Communications 13 (2022): 4178.

[201] M. Castellan, A. Guarnieri, A. Fujimura, et al., “Single-cell Analyses Reveal YAP/TAZ as Regulators of Stemness and Cell Plasticity in Glioblastoma, ” Nat Cancer 2, no. 2 (2021): 174-188.

[202] C. Guetta-Terrier, D. Karambizi, B. Akosman, et al., “Chi3l1 Is a Modulator of Glioma Stem Cell States and a Therapeutic Target in Glioblastoma, ” Cancer Research 83, no. 12 (2023): 1984-1999.

[203] L. Wang, J. Jung, H. Babikir, et al., “A Single-cell Atlas of Glioblastoma Evolution Under Therapy Reveals Cell-intrinsic and Cell-extrinsic Therapeutic Targets, ” Nat Cancer 3, no. 12 (2022): 1534-1552.

[204] D. R. Grimes, M. Jansen, R. J. Macauley, J. G. Scott, D. Basanta, “Evidence for Hypoxia Increasing the Tempo of Evolution in Glioblastoma, ” British Journal of Cancer 123, no. 10 (2020): 1562-1569.

[205] V. Bhandari, C. Hoey, L. Y. Liu, et al., “Molecular Landmarks of Tumor Hypoxia Across Cancer Types, ” Nature Genetics 51, no. 2 (2019): 308-318.

[206] D. H. Heiland, A. Gaebelein, M. Börries, et al., “Microenvironment-Derived Regulation of HIF Signaling Drives Transcriptional Heterogeneity in Glioblastoma Multiforme, ” Molecular Cancer Research 16, no. 4 (2018): 655-668.

[207] K. R. Luoto, R. Kumareswaran, R. G. Bristow, “Tumor Hypoxia as a Driving Force in Genetic Instability, ” Genome Integrity 4, no. 1 (2013): 5.

[208] K. C. Johnson, K. J. Anderson, E. T. Courtois, et al., “Single-cell Multimodal Glioma Analyses Identify Epigenetic Regulators of Cellular Plasticity and Environmental Stress Response, ” Nature Genetics 53, no. 10 (2021): 1456-1468.

[209] A. Kathagen, A. Schulte, G. Balcke, et al., “Hypoxia and Oxygenation Induce a Metabolic Switch Between Pentose Phosphate Pathway and Glycolysis in Glioma Stem-Like Cells, ” Acta Neuropathologica 126, no. 5 (2013): 763-780.

[210] V. M. Ravi, P. Will, J. Kueckelhaus, et al., “Spatially Resolved Multi-omics Deciphers Bidirectional Tumor-host Interdependence in Glioblastoma, ” Cancer Cell 40, no. 6 (2022): 639-655. e13.

[211] E. F. Simonds, E. D. Lu, O. Badillo, et al., “Deep Immune Profiling Reveals Targetable Mechanisms of Immune Evasion in Immune Checkpoint Inhibitor-refractory Glioblastoma, ” Journal for ImmunoTherapy of Cancer 9, no. 6 (2021): e002181.

[212] A. Xiong, J. Zhang, Y. Chen, Y. Zhang, F. Yang, “Integrated Single-cell Transcriptomic Analyses Reveal That GPNMB-high Macrophages Promote PN-MES Transition and Impede T Cell Activation in GBM, ” EBioMedicine 83 (2022): 104239.

[213] Q. W. Wang, L. H. Sun, Y. Zhang, et al., “MET Overexpression Contributes to STAT4-PD-L1 Signaling Activation Associated With Tumor-associated, Macrophages-mediated Immunosuppression in Primary Glioblastomas, ” Journal for ImmunoTherapy of Cancer 9, no. 10 (2021): e002451.

[214] A. H. Lee, L. Sun, A. Y. Mochizuki, et al., “Neoadjuvant PD-1 Blockade Induces T Cell and cDC1 Activation but Fails to Overcome the Immunosuppressive Tumor Associated Macrophages in Recurrent Glioblastoma, ” Nature Communications 12 (2021): 6938.

[215] X. Jin, L. J. Y. Kim, Q. Wu, et al., “Targeting Glioma Stem Cells Through Combined BMI1 and EZH2 Inhibition, ” Nature Medicine 23, no. 11 (2017): 1352-1361.

[216] T. Hara, R. Chanoch-Myers, N. D. Mathewson, et al., “Interactions Between Cancer Cells and Immune Cells Drive Transitions to Mesenchymal-Like States in Glioblastoma, ” Cancer Cell 39, no. 6 (2021): 779-792. e11.

[217] C. E. Eyler, H. Matsunaga, V. Hovestadt, S. J. Vantine, P. van Galen, B. E. Bernstein, “Single-cell Lineage Analysis Reveals Genetic and Epigenetic Interplay in Glioblastoma Drug Resistance, ” Genome biology 21 (2020): 174.

[218] Z. Chen, N. Soni, G. Pinero, et al., “Monocyte Depletion Enhances Neutrophil Influx and Proneural to Mesenchymal Transition in Glioblastoma, ” Nature Communications 14, no. 1 (2023): 1839.

[219] H. J. Kim, J. H. Park, H. C. Kim, C. W. Kim, I. Kang, H. K. Lee, “Blood Monocyte-derived CD169+ Macrophages Contribute to Antitumor Immunity Against Glioblastoma, ” Nature Communications 13 (2022): 6211.

[220] Z. Chen, C. J. Herting, J. L. Ross, et al., “Genetic Driver Mutations Introduced in Identical Cell-of-origin in Murine Glioblastoma Reveal Distinct Immune Landscapes but Similar Response to Checkpoint Blockade, ” Glia 68, no. 10 (2020): 2148.

[221] D. Douillet, C. C. Sze, C. Ryan, et al., “Uncoupling Histone H3K4 Trimethylation From Developmental Gene Expression via an Equilibrium of COMPASS, Polycomb and DNA Methylation, ” Nature Genetics 52, no. 6 (2020): 615-625.

[222] R. Chaligne, F. Gaiti, D. Silverbush, et al., “Epigenetic Encoding, Heritability and Plasticity of Glioma Transcriptional Cell States, ” Nature Genetics 53, no. 10 (2021): 1469-1479.

[223] C. M. Pretzsch, M. Arenella, J. P. Lerch, et al., “Patterns of Brain Maturation in Autism and Their Molecular Associations, ” JAMA Psychiatry 81, no. 12 (2024): 1253-1264.

[224] O. Peñagarikano, B. S. Abrahams, E. I. Herman, et al., “Absence of CNTNAP2 Leads to Epilepsy, Neuronal Migration Abnormalities, and Core Autism-related Deficits, ” Cell 147, no. 1 (2011): 235-246.

[225] M. T. Lazaro, J. Taxidis, T. Shuman, et al., “Reduced Prefrontal Synaptic Connectivity and Disturbed Oscillatory Population Dynamics in the CNTNAP2 Model of Autism, ” Cell reports 27, no. 9 (2019): 2567-2578. e6.

[226] W. E. Jang, J. H. Park, G. Park, et al., “Cntnap2-dependent Molecular Networks in Autism Spectrum Disorder Revealed Through an Integrative Multi-omics Analysis, ” Molecular Psychiatry 28, no. 2 (2023): 810-821.

[227] F. Şimşek, Ü. Işık, E. Aktepe, F. Kılıç, F. B. Şirin, M. Bozkurt, “Comparison of Serum VEGF, IGF-1, and HIF-1α Levels in Children With Autism Spectrum Disorder and Healthy Controls, ” Journal of Autism and Developmental Disorders 51, no. 10 (2021): 3564-3574.

[228] J. Cui, H. Li, C. Hu, et al., “Unraveling Pathogenesis and Potential Biomarkers for Autism Spectrum Disorder Associated With HIF1A Pathway Based on Machine Learning and Experiment Validation, ” Neurobiology of Disease 204 (2025): 106763.

[229] D. Majerczyk, E. G. Ayad, K. L. Brewton, P. Saing, P. C. Hart, “Systemic Maternal Inflammation Promotes ASD via IL-6 and IFN-γ, ” Bioscience Reports 42, no. 11 (2022): BSR20220713.

[230] B. Wamsley, L. Bicks, Y. Cheng, et al., “Molecular Cascades and Cell Type-specific Signatures in ASD Revealed by Single-cell Genomics, ” Science 384, no. 6698 (2024): eadh2602.

[231] T. T. Logan, S. Villapol, A. J. Symes, “TGF-β Superfamily Gene Expression and Induction of the Runx1 Transcription Factor in Adult Neurogenic Regions After Brain Injury, ” PLoS ONE 8, no. 3 (2013): e59250.

[232] K. M. Dhandapani, M. Hadman, L. De Sevilla, M. F. Wade, V. B. Mahesh, D. W. Brann, “Astrocyte Protection of Neurons: Role of Transforming Growth Factor-beta Signaling via a c-Jun-AP-1 Protective Pathway, ” Journal of Biological Chemistry 278, no. 44 (2003): 43329-43339.

[233] L. Wang, C. Wang, J. A. Moriano, et al., “Molecular and Cellular Dynamics of the Developing human Neocortex, ” Nature (2025). Published online January 8, 2025.

[234] M. Neumann, D. M. Sampathu, L. K. Kwong, et al., “Ubiquitinated TDP-43 in Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis, ” Science 314, no. 5796 (2006): 130-133.

[235] F. Limone, D. A. Mordes, A. Couto, et al., “Single-nucleus Sequencing Reveals Enriched Expression of Genetic Risk Factors in Extratelencephalic Neurons Sensitive to Degeneration in ALS, ” Nat Aging 4, no. 7 (2024): 984-997.

[236] S. S. Pineda, H. Lee, M. J. Ulloa-Navas, et al., “Single-cell Dissection of the human Motor and Prefrontal Cortices in ALS and FTLD, ” Cell 187, no. 8 (2024): 1971-1989. e16.

[237] S. Coupel, A. Moreau, M. Hamidou, V. Horejsi, J. P. Soulillou, B. Charreau, “Expression and Release of Soluble HLA-E Is an Immunoregulatory Feature of Endothelial Cell Activation, ” Blood 109, no. 7 (2007): 2806-2814.

[238] Y. Shi, L. Huang, H. Dong, et al., “Decoding the Spatiotemporal Regulation of Transcription Factors During human Spinal Cord Development, ” Cell Research 34, no. 3 (2024): 193-213.

[239] T. Itou, K. Fujita, Y. Okuzono, et al., “Th17 and Effector CD8 T Cells Relate to Disease Progression in Amyotrophic Lateral Sclerosis: A Case Control Study, ” J Neuroinflammation 21, no. 1 (2024): 331.

[240] E. Álvarez-Sánchez, Á. Carbayo, N. Valle-Tamayo, et al., “Single-cell RNA Sequencing Highlights the Role of Distinct Natural Killer Subsets in Sporadic Amyotrophic Lateral sclerosis, ” J Neuroinflammation 22, no. 1 (2025): 15.

[241] I. Blumcke, R. Spreafico, G. Haaker, et al., “Histopathological Findings in Brain Tissue Obtained During Epilepsy Surgery, ” New England Journal of Medicine 377, no. 17 (2017): 1648-1656.

[242] I. Blumcke, F. Cendes, H. Miyata, M. Thom, E. Aronica, I. Najm, “Toward a Refined Genotype-phenotype Classification Scheme for the International Consensus Classification of Focal Cortical Dysplasia, ” Brain Pathology 31, no. 4 (2021): e12956.

[243] C. Chung, X. Yang, T. Bae, et al., “Comprehensive Multi-omic Profiling of Somatic Mutations in Malformations of Cortical Development, ” Nature Genetics 55, no. 2 (2023): 209-220.

[244] Y. Wang, Y. Wang, L. Guo, et al., “Spatial Transcriptomics in Focal Cortical Dysplasia Type IIb, ” Acta Neuropathol Commun 12, no. 1 (2024): 185.

[245] S. Baldassari, E. Klingler, L. G. Teijeiro, et al., “Single-cell Genotyping and Transcriptomic Profiling of Mosaic Focal Cortical Dysplasia, ” Nature Neuroscience 28, no. 5 (2025): 964-972.

[246] B. Puhahn-Schmeiser, K. Leicht, F. Gessler, T. M. Freiman, “Aberrant Hippocampal Mossy Fibers in Temporal Lobe Epilepsy Target Excitatory and Inhibitory Neurons, ” Epilepsia 62, no. 10 (2021): 2539-2550.

[247] Q. Liu, C. Shen, Y. Dai, et al., “Single-cell, Single-nucleus and Xenium-based Spatial Transcriptomics Analyses Reveal Inflammatory Activation and Altered Cell Interactions in the Hippocampus in Mice With Temporal Lobe Epilepsy, ” Biomarker Research 12, no. 1 (2024): 103.

[248] Q. Ge, J. Yang, F. Huang, et al., “Multimodal Single-cell Analyses Reveal Molecular Markers of Neuronal Senescence in human Drug-resistant Epilepsy, ” Journal of Clinical Investigation 135, no. 5 (2025): e188942.

[249] Y. Wang, M. Eddison, G. Fleishman, et al., “EASI-FISH for Thick Tissue Defines Lateral Hypothalamus Spatio-molecular Organization, ” Cell 184, no. 26 (2021): 6361-6377. e24.

[250] Y. Ma, K. Zheng, C. Zhao, et al., “Microglia LILRB4 Upregulation Reduces Brain Damage After Acute Ischemic Stroke by Limiting CD8+ T Cell Recruitment, ” J Neuroinflammation 21, no. 1 (2024): 214.

[251] N. Yu, Y. Zhao, P. Wang, F. Zhang, C. Wen, S. Wang, “Changes in Border-associated Macrophages After Stroke: Single-cell Sequencing Analysis, ” Neural Regeneration Research 21, no. 1 (2025): 346-356. Published online January 29, 2025.

[252] T. Liu, M. Bai, M. Liu, et al., “Novel Synergistic Mechanism of 11-keto-β-boswellic Acid and Z-Guggulsterone on Ischemic Stroke Revealed by Single-cell Transcriptomics, ” Pharmacological Research 193 (2023): 106803.

[253] Y. Zhao, Q. Li, J. Niu, et al., “Neutrophil Membrane-Camouflaged Polyprodrug Nanomedicine for Inflammation Suppression in Ischemic Stroke Therapy, ” Advanced Materials 36, no. 21 (2024): e2311803.

[254] W. Cai, M. Hu, C. Li, et al., “FOXP3+ macrophage Represses Acute Ischemic Stroke-induced Neural Inflammation, ” Autophagy 19, no. 4 (2023): 1144-1163.

[255] C. Liu, H. Sui, Z. Li, et al., “THBS1 in Macrophage-derived Exosomes Exacerbates Cerebral Ischemia-reperfusion Injury by Inducing Ferroptosis in Endothelial Cells, ” J Neuroinflammation 22, no. 1 (2025): 48.

[256] J. E. Kim, R. P. Lee, E. Yazigi, et al., “Soluble PD-L1 Reprograms Blood Monocytes to Prevent Cerebral Edema and Facilitate Recovery After Ischemic Stroke, ” Brain, Behavior, and Immunity 116 (2024): 160-174.

[257] A. Nakamura, S. Sakai, Y. Taketomi, et al., “PLA2G2E-mediated Lipid Metabolism Triggers Brain-autonomous Neural Repair After Ischemic Stroke, ” Neuron 111, no. 19 (2023): 2995-3010. e9.

[258] Z. Chen, X. Wang, H. Wu, et al., “X-box Binding Protein 1 as a Key Modulator in “Healing Endothelial Cells”, a Novel EC Phenotype Promoting Angiogenesis After MCAO, ” Cellular & Molecular Biology Letters 27, no. 1 (2022): 97.

[259] A. Loan, N. Awaja, M. Lui, et al., “Single-cell Profiling of Brain Pericyte Heterogeneity Following Ischemic Stroke Unveils Distinct Pericyte Subtype-targeted Neural Reprogramming Potential and Its Underlying Mechanisms, ” Theranostics 14, no. 16 (2024): 6110-6137.

[260] X. Wang, A. Zhang, Q. Yu, et al., “Single-Cell RNA Sequencing and Spatial Transcriptomics Reveal Pathogenesis of Meningeal Lymphatic Dysfunction After Experimental Subarachnoid Hemorrhage, ” Adv Sci (Weinh) 10, no. 21 (2023): e2301428.

[261] J. Zheng, H. Wu, X. Wang, et al., “Temporal Dynamics of Microglia-astrocyte Interaction in Neuroprotective Glial Scar Formation After Intracerebral Hemorrhage, ” Journal of Pharmaceutical Analysis 13, no. 8 (2023): 862-879.

[262] X. S. Li, W. Liu, G. Jiang, et al., “Celastrol Ameliorates Neuronal Mitochondrial Dysfunction Induced by Intracerebral Hemorrhage via Targeting cAMP-Activated Exchange Protein-1, ” Adv Sci (Weinh) 11, no. 19 (2024): e2307556.

[263] Y. Niu, X. Chen, Y. Zhang, Y. Ge, J. Gao, T. Huang, “Decoding Neuronal Genes in Stroke-induced Pain: Insights From Single-nucleus Sequencing in Mice, ” BMC Neurology [Electronic Resource] 24, no. 1 (2024): 459.

[264] C. Wang, M. Xiong, M. Gratuze, et al., “Selective Removal of Astrocytic APOE4 Strongly Protects Against Tau-mediated Neurodegeneration and Decreases Synaptic Phagocytosis by Microglia, ” Neuron 109, no. 10 (2021): 1657-1674. e7.

[265] N. Koutsodendris, J. Blumenfeld, A. Agrawal, et al., “Neuronal APOE4 Removal Protects Against Tau-mediated Gliosis, Neurodegeneration and Myelin Deficits, ” Nat Aging 3, no. 3 (2023): 275-296.

[266] A. Rao, N. Chen, M. J. Kim, et al., “Microglia Depletion Reduces human Neuronal APOE4-related Pathologies in a Chimeric Alzheimer's Disease Model, ” Cell Stem Cell 32, no. 1 (2025): 86-104. e7.

[267] C. S. McAlpine, J. Park, A. Griciuc, et al., “Astrocytic Interleukin-3 Programs Microglia and Limits Alzheimer's Disease, ” Nature 595, no. 7869 (2021): 701-706.

[268] B. van Lengerich, L. Zhan, D. Xia, et al., “A TREM2-activating Antibody With a Blood-brain Barrier Transport Vehicle Enhances Microglial Metabolism in Alzheimer's disease Models, ” Nature Neuroscience 26, no. 3 (2023): 416-429.

[269] L. Van Olst, B. Simonton, A. J. Edwards, et al., “Microglial Mechanisms Drive Amyloid-β Clearance in Immunized Patients With Alzheimer's Disease, ” Nature Medicine 31, no. 5 (2025): 1604-1616. Published online March 6, 2025.

[270] F. A. Sayed, L. Kodama, L. Fan, et al., “AD-linked R47H-TREM2 Mutation Induces Disease-enhancing Microglial States via AKT Hyperactivation, ” Science Translational Medicine 13, no. 622 (2021): eabe3947.

[271] Ö. İş, X. Wang, J. S. Reddy, et al., “Gliovascular Transcriptional Perturbations in Alzheimer's Disease Reveal Molecular Mechanisms of Blood Brain Barrier Dysfunction, ” Nature Communications 15, no. 1 (2024): 4758.

[272] S. De Schepper, J. Z. Ge, G. Crowley, et al., “Perivascular Cells Induce Microglial Phagocytic States and Synaptic Engulfment via SPP1 in Mouse Models of Alzheimer's Disease, ” Nature Neuroscience 26, no. 3 (2023): 406-415.

[273] W. Qu, M. Lam, J. J. McInvale, et al., “Xenografted human iPSC-derived Neurons With the Familial Alzheimer's disease APPV717I Mutation Reveal Dysregulated Transcriptome Signatures Linked to Synaptic Function and Implicate LINGO2 as a Disease Signaling Mediator, ” Acta Neuropathologica 147, no. 1 (2024): 107.

[274] M. Jorfi, J. Park, C. K. Hall, et al., “Infiltrating CD8+ T Cells Exacerbate Alzheimer's Disease Pathology in a 3D human Neuroimmune Axis Model, ” Nature Neuroscience 26, no. 9 (2023): 1489-1504.

[275] P. Xu, H. He, Q. Gao, et al., “Human Midbrain Dopaminergic Neuronal Differentiation Markers Predict Cell Therapy Outcomes in a Parkinson's disease Model, ” Journal of Clinical Investigation 132, no. 14 (2022): e156768.

[276] K. Nishimura, S. Yang, K. W. Lee, et al., “Single-cell Transcriptomics Reveals Correct Developmental Dynamics and High-quality Midbrain Cell Types by Improved hESC Differentiation, ” Stem Cell Reports 18, no. 1 (2022): 337-353.

[277] J. Giehrl-Schwab, F. Giesert, B. Rauser, et al., “Parkinson's Disease Motor Symptoms Rescue by CRISPRa-reprogramming Astrocytes Into GABAergic Neurons, ” EMBO Molecular Medicine 14, no. 5 (2022): e14797.

[278] Y. Zhuo, W. S. Li, W. Lu, et al., “TGF-β1 Mediates Hypoxia-preconditioned Olfactory Mucosa Mesenchymal Stem Cells Improved Neural Functional Recovery in Parkinson's disease Models and Patients, ” Mil Med Res 11 (2024): 48.

[279] W. Kong, Y. Liu, P. Ai, et al., “Genetically Modified E. Coli Secreting Melanin (E.melanin) Activates the Astrocytic PSAP-GPR37L1 Pathway and Mitigates the Pathogenesis of Parkinson's Disease, ” J Nanobiotechnology 22 (2024): 690.

[280] R. X. Zhu, Y. H. Chen, X. Xia, et al., “Formation of CSE-YAP Complex Drives FOXD3-mediated Transition of Neurotoxic Astrocytes in Parkinson's Disease, ” Pharmacological Research 210 (2024): 107507.

[281] H. Hong, Y. Wang, M. Menard, et al., “Suppression of the JAK/STAT Pathway Inhibits Neuroinflammation in the Line 61-PFF Mouse Model of Parkinson's Disease, ” J Neuroinflammation 21 (2024): 216.

[282] L. H. Geraldo, Y. Xu, L. Jacob, et al., “SLIT2/ROBO Signaling in Tumor-associated Microglia and Macrophages Drives Glioblastoma Immunosuppression and Vascular Dysmorphia, ” The Journal of Clinical Investigation 131, no. 16 (2021): e141083.

[283] J. Li, M. M. Kaneda, J. Ma, et al., “PI3Kγ inhibition Suppresses Microglia/TAM Accumulation in Glioblastoma Microenvironment to Promote Exceptional Temozolomide Response, ” Proceedings of the National Academy of Sciences of the United States of America 118, no. 16 (2021): e2009290118.

[284] P. Chen, W. H. Hsu, A. Chang, et al., “Circadian Regulator CLOCK Recruits Immune Suppressive Microglia Into the GBM Tumor Microenvironment, ” Cancer Discovery 10, no. 3 (2020): 371.

[285] W. Xuan, W. H. Hsu, F. Khan, et al., “Circadian Regulator CLOCK Drives Immunosuppression in Glioblastoma, ” Cancer immunology research 10, no. 6 (2022): 770-784.

[286] S. Goswami, T. Walle, A. E. Cornish, et al., “Immune Profiling of human Tumors Identifies CD73 as a Combinatorial Target in Glioblastoma, ” Nature Medicine 26, no. 1 (2020): 39-46.

[287] V. M. Ravi, N. Neidert, P. Will, et al., “T-cell Dysfunction in the Glioblastoma Microenvironment Is Mediated by Myeloid Cells Releasing Interleukin-10, ” Nature Communications 13 (2022): 925.

[288] E. A. Winkler, C. N. Kim, J. M. Ross, et al., “A Single-cell Atlas of the Normal and Malformed human Brain Vasculature, ” Science 375, no. 6584 (2022): eabi7377.

[289] X. Hong, Y. Jian, S. Ding, et al., “Kir4.1 channel Activation in NG2 Glia Contributes to Remyelination in Ischemic Stroke, ” Ebiomedicine 87 (2023): 104406.

[290] Y. Liao, J. Wang, C. Guo, et al., “Combination of Systems Pharmacology and Experimental Evaluation to Explore the Mechanism of Synergistic Action of Frankincense-Myrrh in the Treatment of Cerebrovascular Diseases, ” Frontiers in Pharmacology 12 (2022): 796224.

[291] Z. Zhu, Y. Fu, D. Tian, et al., “Combination of the Immune Modulator Fingolimod with Alteplase in Acute Ischemic Stroke: A Pilot Trial, ” Circulation 132, no. 12 (2015): 1104-1112.

[292] W. Cai, X. Dai, J. Chen, et al., “STAT6/Arg1 promotes Microglia/Macrophage Efferocytosis and Inflammation Resolution in Stroke Mice, ” JCI Insight 4, no. 20 (2019): e131355.

[293] R. Liu, P. Song, X. Gu, et al., “Comprehensive Landscape of Immune Infiltration and Aberrant Pathway Activation in Ischemic Stroke, ” Frontiers in immunology 12 (2021): 766724.

[294] H. Sato, Y. Taketomi, A. Ushida, et al., “The Adipocyte-inducible Secreted Phospholipases PLA2G5 and PLA2G2E Play Distinct Roles in Obesity, ” Cell metabolism 20, no. 1 (2014): 119-132.

[295] C. Ma, G. CB, H. S. Rp, et al., “Citrullination Regulates Pluripotency and Histone H1 Binding to Chromatin, ” Nature 507, no. 7490 (2014): 104-108.

[296] S. C. Stadler, C. T. Vincent, V. D. Fedorov, et al., “Dysregulation of PAD4-mediated Citrullination of Nuclear GSK3β Activates TGF-β Signaling and Induces Epithelial-to-mesenchymal Transition in Breast Cancer Cells, ” PNAS 110, no. 29 (2013): 11851-11856.

[297] L. Shi, Z. Sun, W. Su, et al., “Treg Cell-derived Osteopontin Promotes Microglia-mediated White Matter Repair After Ischemic Stroke, ” Immunity 54, no. 7 (2021): 1527-1542. e8.

[298] Q. Duan, L. Ni, P. Wang, et al., “Deregulation of XBP1 Expression Contributes to Myocardial Vascular Endothelial Growth Factor-A Expression and Angiogenesis During Cardiac Hypertrophy in Vivo, ” Aging Cell 15, no. 4 (2016): 625-633.

[299] J. H. Ahn, H. Cho, J. H. Kim, et al., “Meningeal Lymphatic Vessels at the Skull Base Drain Cerebrospinal Fluid, ” Nature 572, no. 7767 (2019): 62-66.

[300] A. Louveau, I. Smirnov, T. J. Keyes, et al., “Structural and Functional Features of central Nervous System Lymphatic Vessels, ” Nature 523, no. 7560 (2015): 337-341.

[301] J. Chen, L. Wang, H. Xu, et al., “Meningeal Lymphatics Clear Erythrocytes That Arise From Subarachnoid Hemorrhage, ” Nature Communications 11, no. 1 (2020): 3159.

[302] G. Oliver, J. Kipnis, G. J. Randolph, N. L. Harvey, “The Lymphatic Vasculature in the 21st Century: Novel Functional Roles in Homeostasis and Disease, ” Cell 182, no. 2 (2020): 270-296.

[303] D. Pham, X. Tan, B. Balderson, et al., “Robust Mapping of Spatiotemporal Trajectories and Cell-cell Interactions in Healthy and Diseased Tissues, ” Nature Communications 14, no. 1 (2023): 7739.

[304] Z. Hong, J. Cao, D. Liu, et al., “Celastrol Targeting Nedd4 Reduces Nrf2-mediated Oxidative Stress in Astrocytes After Ischemic Stroke, ” Journal of Pharmaceutical Analysis 13, no. 2 (2023): 156-169.

[305] H. Xu, H. Zhao, C. Ding, et al., “Celastrol Suppresses Colorectal Cancer via Covalent Targeting Peroxiredoxin 1, ” Signal Transduct Target Ther 8, no. 1 (2023): 51.

[306] C. Y. Yan, S. H. Ouyang, X. Wang, et al., “Celastrol Ameliorates Propionibacterium Acnes/LPS-induced Liver Damage and MSU-induced Gouty Arthritis via Inhibiting K63 Deubiquitination of NLRP3, ” Phytomedicine 80 (2021): 153398.

[307] M. Jiang, X. Liu, D. Zhang, et al., “Celastrol Treatment Protects Against Acute Ischemic Stroke-induced Brain Injury by Promoting an IL-33/ST2 Axis-mediated Microglia/Macrophage M2 Polarization, ” J Neuroinflammation 15, no. 1 (2018): 78.

[308] W. Zhang, J. Wang, C. Yang, “Celastrol, a TFEB (transcription factor EB) Agonist, Is a Promising Drug Candidate for Alzheimer Disease, ” Autophagy 18, no. 7 (2022): 1740-1742.

[309] E. Parnell, T. M. Palmer, S. J. Yarwood, “The Future of EPAC-targeted Therapies: Agonism versus Antagonism, ” Trends in Pharmacological Sciences 36, no. 4 (2015): 203-214.

[310] T. K. Ulland, W. M. Song, S. C. C. Huang, et al., “TREM2 Maintains Microglial Metabolic Fitness in Alzheimer's Disease, ” Cell 170, no. 4 (2017): 649-663. e13.

[311] E. Morenas-Rodríguez, Y. Li, B. Nuscher, et al., “Soluble TREM2 in CSF and Its Association With Other Biomarkers and Cognition in Autosomal-dominant Alzheimer's Disease: A Longitudinal Observational Study, ” Lancet Neurology 21, no. 4 (2022): 329-341.

[312] Y. Zhou, W. M. Song, P. Andhey, et al., “Human and Mouse Single-nucleus Transcriptomics Reveal TREM2-dependent and -independent Cellular Responses in Alzheimer's Disease, ” The Journal of Immunology 204, _Supplement no. 1 (2020): 64.2-64.2.

[313] D. Wang, F. Chen, Z. Han, Z. Yin, X. Ge, P. Lei, “Relationship between Amyloid-β Deposition and Blood-Brain Barrier Dysfunction in Alzheimer's Disease, ” Front Cell Neurosci 15 (2021): 695479.

[314] R. Browaeys, W. Saelens, Y. Saeys, “NicheNet: Modeling Intercellular Communication by Linking Ligands to Target Genes, ” Nature Methods 17, no. 2 (2020): 159-162.

[315] D. Gate, N. Saligrama, O. Leventhal, et al., “Clonally Expanded CD8 T Cells Patrol the Cerebrospinal Fluid in Alzheimer's Disease, ” Nature 577, no. 7790 (2020): 399-404.

[316] M. S. Unger, E. Li, L. Scharnagl, et al., “CD8(+) T-cells Infiltrate Alzheimer's disease Brains and Regulate Neuronal- and Synapse-related Gene Expression in APP-PS1 Transgenic Mice, ” Brain, Behavior, and Immunity 89 (2020): 67-86.

[317] M. Merlini, T. Kirabali, L. Kulic, R. M. Nitsch, M. T. Ferretti, “Extravascular CD3+ T Cells in Brains of Alzheimer Disease Patients Correlate With Tau but Not With Amyloid Pathology: An Immunohistochemical Study, ” Neurodegener Dis 18, no. 1 (2018): 49-56.

[318] T. Togo, H. Akiyama, E. Iseki, et al., “Occurrence of T Cells in the Brain of Alzheimer's Disease and Other Neurological Diseases, ” Journal of Neuroimmunology 124, no. 1-2 (2002): 83-92.

[319] F. Nilsson, P. Storm, E. Sozzi, et al., “Single-Cell Profiling of Coding and Noncoding Genes in Human Dopamine Neuron Differentiation, ” Cells 10, no. 1 (2021): 137.

[320] M. Birtele, P. Storm, Y. Sharma, et al., “Single-cell Transcriptional and Functional Analysis of Dopaminergic Neurons in Organoid-Like Cultures Derived From human Fetal Midbrain, ” Development (Cambridge, England) 149, no. 23 (2022): dev200504.

[321] X. Zeng, W. Geng, J. Jia, Z. Wang, “Advances in Stem Cells Transplantation for the Therapy of Parkinson's Disease, ” Curr Stem Cell Res Ther 16, no. 8 (2021): 958-969.

[322] Y. Chen, J. Shen, K. Ke, X. Gu, “Clinical Potential and Current Progress of Mesenchymal Stem Cells for Parkinson's disease: A Systematic Review, ” Neurol Sci 41, no. 5 (2020): 1051-1061.

[323] Y. Zhuo, W. Chen, W. Li, “Ischemic-hypoxic Preconditioning Enhances the Mitochondrial Function Recovery of Transplanted Olfactory Mucosa Mesenchymal Stem Cells via miR-181a Signaling in Ischemic Stroke, ” Aging (Albany NY) 13, no. 8 (2021): 11234-11256.

[324] D. Kempuraj, R. Thangavel, P. Natteru, et al., “Neuroinflammation Induces Neurodegeneration, ” J Neurol Neurosurg Spine 1, no. 1 (2016): 1003.

[325] K. Aslan, V. Turco, J. Blobner, et al., “Heterogeneity of Response to Immune Checkpoint Blockade in Hypermutated Experimental Gliomas, ” Nature Communications 11 (2020): 931.

[326] J. Zhao, A. X. Chen, R. D. Gartrell, et al., “Immune and Genomic Correlates of Response to anti-PD-1 Immunotherapy in Glioblastoma, ” Nature Medicine 25, no. 3 (2019): 462.

[327] I. S. C. Verploegh, A. Conidi, R. W. W. Brouwer, et al., “Comparative Single-cell RNA-sequencing Profiling of BMP4-treated Primary Glioma Cultures Reveals Therapeutic Markers, ” Neuro-oncol 24, no. 12 (2022): 2133-2145.

[328] A. R. Pombo Antunes, I. Scheyltjens, F. Lodi, et al., “Single-cell Profiling of Myeloid Cells in Glioblastoma Across Species and Disease Stage Reveals Macrophage Competition and Specialization, ” Nature Neuroscience 24, no. 4 (2021): 595-610.

[329] S. Coy, S. Wang, S. A. Stopka, et al., “Single Cell Spatial Analysis Reveals the Topology of Immunomodulatory Purinergic Signaling in Glioblastoma, ” Nature Communications 13, no. 1 (2022): 4814.

[330] L. Antonioli, S. V. Novitskiy, K. F. Sachsenmeier, M. Fornai, C. Blandizzi, G. Haskó, “Switching off CD73: A Way to Boost the Activity of Conventional and Targeted Antineoplastic Therapies, ” Drug Discovery Today 22, no. 11 (2017): 1686-1696.

[331] P. I, M. Ha, G. P. M, “Blocking Antibodies Targeting the CD39/CD73 Immunosuppressive Pathway Unleash Immune Responses in Combination Cancer Therapies, ” Cell Reports 27, no. 8 (2019): 2411-2425.

[332] L. Song, W. Chen, J. Hou, M. Guo, J. Yang, “Spatially Resolved Mapping of Cells Associated With human Complex Traits, ” Nature 641, no. 8064 (2025): 932-941.

[333] K. Lebrigand, V. Magnone, P. Barbry, R. Waldmann, “High Throughput Error Corrected Nanopore Single Cell Transcriptome Sequencing, ” Nature Communications 11, no. 1 (2020): 4025.

[334] M. Hagemann-Jensen, C. Ziegenhain, P. Chen, et al., “Single-cell RNA Counting at Allele and Isoform Resolution Using Smart-seq3, ” Nature Biotechnology 38, no. 6 (2020): 708-714.

[335] I. Gupta, P. G. Collier, B. Haase, et al., “Single-cell Isoform RNA Sequencing Characterizes Isoforms in Thousands of Cerebellar Cells, ” Nature Biotechnology (2018). Published online October 15, 2018.

[336] K. Lebrigand, J. Bergenstråhle, K. Thrane, et al., “The Spatial Landscape of Gene Expression Isoforms in Tissue Sections, ” Nucleic Acids Research 51, no. 8 (2023): e47-e47.

[337] L. Tarhan, J. Bistline, J. Chang, B. Galloway, E. Hanna, E. Weitz, “Single Cell Portal: An Interactive Home for Single-cell Genomics Data,” BioRxiv 17(2023). Published online July.

[338] A. Regev, S. A. Teichmann, E. S. Lander, et al., “The Human Cell Atlas, ” Elife 6 (2017): e27041.

[339] M. L. Speir, A. Bhaduri, N. S. Markov, et al., “UCSC Cell Browser: Visualize Your Single-cell Data, ” Bioinformatics 37, no. 23 (2021): 4578-4580.

[340] R. C. Jones, J. Karkanias, M. A. Krasnow, et al., “The Tabula Sapiens: A Multiple-organ, Single-cell Transcriptomic Atlas of Humans, ” Science 376, no. 6594 (2022): eabl4896.

[341] HuBMAP Consortium. The human Body at Cellular Resolution: The NIH Human Biomolecular Atlas Program. Nature 2019; 574(7777): 187-192.

RIGHTS & PERMISSIONS

2025 The Author(s). MedComm published by Sichuan International Medical Exchange & Promotion Association (SCIMEA) and John Wiley & Sons Australia, Ltd.