The spatial distribution, or pattern, of cells within a tissue underlies organ function. However, these are difficult to identify, making it challenging to evaluate how these patterns are established, or how diseases may disrupt and impair their function. To address this, we developed an algorithm that identifies spatial patterns within tissues and used it to study the bone marrow, a specialized microenvironment in which spatial patterning of regulatory cells influences the cell fate of hematopoietic stem cells. Using this algorithm, we discovered clusters of cells within the bone marrow that suggest an organization of micro-niches, which may form the basis of the hematopoietic stem cell microenvironment. This work provides a new tool for the identification of spatial patterns within tissues that can lead to a deeper understanding of tissue function, provide clues for the early onset of disease, and be used for studying the impact of pharmaceutics on tissue regeneration.

中文翻译：

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基于滚动信号的Ripley's K：一种用于识别组织学标本中空间模式的新算法

组织内细胞的空间分布或模式是器官功能的基础。但是，这些很难识别，因此很难评估如何建立这些模式，或者疾病如何破坏和损害其功能。为了解决这个问题，我们开发了一种可识别组织内空间格局的算法，并将其用于研究骨髓（一种特殊的微环境），其中调节细胞的空间格局会影响造血干细胞的细胞命运。使用该算法，我们发现了骨髓内的细胞簇，暗示了微壁an的组织，这可能构成造血干细胞微环境的基础。