This research by Yuan et al. focused on developing a comprehensive human skin cell atlas, analyzing various cell types and diseases, and introduced a deep learning method, scSEA, for unbiased reference mapping, potentially discovering new cell types.
The researchers developed a comprehensive human skin cell atlas using data from various studies and established a consensus nomenclature for normal human skin in this project, which also includes a deep learning-based method for more effective reference mapping of new cells.
April 2023 in “Journal of Investigative Dermatology” This study found that single-nucleus RNA sequencing identified more relevant keratinocyte clusters and specific markers than single-cell RNA sequencing, offering a new perspective on skin cell differentiation and function.
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January 2018 in “Journal of Investigative Dermatology” This study identified at least four distinct fibroblast populations in adult human skin, each with unique functional properties, suggesting potential therapeutic applications for wound healing and fibrosis-related diseases.
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July 2024 in “Journal of Investigative Dermatology” This study used single-cell RNA-sequencing data from mouse skin to reveal that fibroblasts show high transcriptional plasticity during wound healing, forming transient microniches early on and stratifying scar tissue into distinct molecular layers over time.
