AUTHOR=Dong Yingyue , Zhang Dandan , Cao Yingri , Zhang Yanfei , Sun Xiaozhe , Chen Tongsheng , Zhang Yuanyuan , Xu Guoheng 

TITLE=Mathematical analysis for spatial distribution of vessels, mast cells and adipocytes in superficial fascia

JOURNAL=Frontiers in Physiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.1026019

DOI=10.3389/fphys.2022.1026019

ISSN=1664-042X

ABSTRACT=As a novel origin of adipocytes, the superficial fascia has abundant adipocytes and preadipocytes, which are accompanied by a large number of mast cells, and blood vessels pass through the fascia to form a network structure. This paper aims to adopt the Guidolin’s statistical analytical methods came from epidemiology and ecology to quantitatively analyze the distribution pattern and correlations among blood vessels, adipocytes, and mast cells. Image processing software and self-written computer programs were used to analyze the images of whole-mounted fascia, and the relevant data were measured automatically. Vascular network is nonuniformly distributed has been proved based on Voronoi model. Quantitative histological analysis according to distance between cells and vessels indicated that mast cells and adipocytes were distributed along blood vessels, which indicated that 81.16% of mast cells and 74.74% of adipocytes are distributed within 60 μ m from blood vessels on the fascia with an average area of about 3.75 cm2. And the Spearman’s correlation coefficient (rs) with greater than 0.7 proved the co-distribution of two types of cells under different areas. Moreover, the ridge regression analysis furtherly revealed the spatial correlation among blood vessels, fat and mast cells. Through this study, a very complete calculation process was constructed to analyze the spatial distribution relationship between point structures (such as cells) and linear structures (such as blood vessels and nerves). Due to using computer programs to ensure the accuracy and objectivity of the data, this method can be widely used in a variety of histomorphology studies.