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Ying Mao

As seen in: Arthritis & Rheumatology, Nature, Wiley Online Library, PLOS, Frontiers, MDPI, Taylor & Francis Online, BMC Cancer, Royal Society of Chemistry, BioRxiv and
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Articles

Leptomeningeal fibroblasts promote glioblastoma progression by regulating cerebrospinal fluid dynamics

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By Maoyuan Sun, Shan Jiang, Wenli Zhang, Zhen Fan, Beining Liu, Yue Wang, Zhen Li, Yun Guan, Yulai Zeng, Jiawen Chen, Songlin Yan, Qisheng Tang, Yudan Chi, Zhiyong Qin, Houshi Xu, Chong Liu, Ying Mao, Zhifeng Shi, Ruize Zhu, Weiqiu Ping, Yanlin Teng
| Nature Verified
Abstract Cerebrospinal fluid contributes to homeostasis in the central nervous system, but how its dynamics are altered in glioblastoma is unclear. We find that glioblastoma drives leptomeningeal perivascular fibrosis that is associated with impaired fluid transport and clearance. Lineage tracing and single-cell analyses in male tumor-bearing mice identify leptomeningeal fibroblasts as the principal source of this fibrotic response, with limited contribution from pericytes.
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Publisher Correction: Targeting cancer-specific mutations with RNA-triggered chromatin shredding

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By Jingkun Zeng, Zhiyuan Cheng, Huadong Chen, Zhaojun Wang, Jared Thompson, Kadin T. Crosby, Hesong Han, Arushi Singhal, Wayne Ngo, Chenglong Xia, Daniel Rosas-Rivera, Zeyuan Zhang, Min Hyung Kang, Ying Mao, Morgan E. Diolaiti, Giselle Lee, John F. X. Diffley, Yixuan Song, Longhui Qiu, Nathan M. Krah, Niren Murthy, Ryan Jackson, Yang Liu Verified, Alan Ashworth Verified, Jennifer Doudna
| Nature Verified
Correction to: Nature https://doi.org/10.1038/s41586-026-10738-7 Published online 8 June 2026 In the version of this article initially published, in Fig. 4c, the label currently reading “TP53R280K transcript” appeared originally as “TP53R248Q transcript.” The figure is amended in the HTML and PDF versions of the article. About this article Zeng, J., Cheng, Z., Chen, H. et al. Publisher Correction: Targeting cancer-specific mutations with RNA-triggered chromatin shredding. Nature (2026).
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Automated limb motor assessment in Parkinson’s disease via a time-frequency state-space model

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By Tianyao Zhang, Chen Xu, Yuechen Liu, Pei Huang, Feifei Zhou, Ming Jing, Fuxin Wei, Jian Wan, Kang Ren, Ying Mao, HUI LU, Shengdi Chen, Siqiong Yao
| Nature Verified
Abstract Assessment of limb motor function is central to the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), but current practice relies on subjective visual inspection. Existing deep learning approaches remain limited in characterizing the non-stationary and nonlinear dynamics of pathological extremity movement, including bradykinesia and intermittent tremor.
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