Browsing by Author "Li, Chen"

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    Compensatory adaptation of parallel motor pathways promotes skilled forelimb recovery after spinal cord injury
    (Elsevier, 2024-11-13) Sheikh, Imran S.; Keefe, Kathleen M.; Sterling, Noelle A.; Junker, Ian P.; Li, Chen; Chen, Jie; Xu, Xiao-Ming; Kirby, Lynn G.; Smith, George M.; Neurology, School of Medicine
    Skilled forelimb patterning is regulated by the corticospinal tract (CST) with support from brainstem regions. When the CST is lesioned, there is a loss of forelimb function; however, if indirect pathways remain intact, rehabilitative training can facilitate recovery. Following spinal cord injury, rehabilitation is thought to enhance the reorganization and plasticity of spared supraspinal-propriospinal circuits, aiding functional recovery. This study focused on the roles of cervical propriospinal interneurons (PNs) and rubrospinal neurons (RNs) in the recovery of reaching and grasping behaviors in rats with bilateral lesions of the CST and dorsal columns at C5. The lesions resulted in a 50% decrease in pellet retrieval, which normalized over four weeks of training. Silencing PNs or RNs after recovery resulted in reduced retrieval success. Notably, silencing both pathways corresponded to greater functional loss, underscoring their parallel contributions to recovery, alongside evidence of CST fiber sprouting in the spinal cord and red nucleus.
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    Spatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers
    (MDPI, 2022-10-04) Alsaleh, Lujain; Li, Chen; Couetil, Justin L.; Ye, Ze; Huang, Kun; Zhang, Jie; Chen, Chao; Johnson, Travis S.; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Background: Cancer is the leading cause of death worldwide with breast and prostate cancer the most common among women and men, respectively. Gene expression and image features are independently prognostic of patient survival; but until the advent of spatial transcriptomics (ST), it was not possible to determine how gene expression of cells was tied to their spatial relationships (i.e., topology). Methods: We identify topology-associated genes (TAGs) that correlate with 700 image topological features (ITFs) in breast and prostate cancer ST samples. Genes and image topological features are independently clustered and correlated with each other. Themes among genes correlated with ITFs are investigated by functional enrichment analysis. Results: Overall, topology-associated genes (TAG) corresponding to extracellular matrix (ECM) and Collagen Type I Trimer gene ontology terms are common to both prostate and breast cancer. In breast cancer specifically, we identify the ZAG-PIP Complex as a TAG. In prostate cancer, we identify distinct TAGs that are enriched for GI dysmotility and the IgA immunoglobulin complex. We identified TAGs in every ST slide regardless of cancer type. Conclusions: These TAGs are enriched for ontology terms, illustrating the biological relevance to our image topology features and their potential utility in diagnostic and prognostic models.