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A comprehensive guide for the accurate classification of murine hair follicles in distinct hair cycle stages

期刊

JOURNAL OF INVESTIGATIVE DERMATOLOGY
卷 117, 期 1, 页码 3-15

出版社

ELSEVIER SCIENCE INC
DOI: 10.1046/j.0022-202x.2001.01377.x

关键词

alkaline phosphatase; anagen; catagen; dermal papilla; telogen

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Numerous strains of mice with defined mutations display pronounced abnormalities of hair follicle cycling, even in the absence of overt alterations of the skin and hair phenotype; however, in order to recognize even subtle, hair cycle-related abnormalities, it is critically important to be able to determine accurately and classify the major stages of the normal murine hair cycle, In this comprehensive guide, we present pragmatic basic and auxiliary criteria for recognizing key stages of hair follicle growth (anagen), regression (catagen) and quiescence (telogen) in C57BL/6NCrlBR mice, which are largely based on previous work from other authors, For each stage, a schematic drawing and representative micrographs are provided in order to illustrate these criteria. The basic criteria can be employed for all mouse strains and require only routine histochemical techniques. The auxiliary criteria depend on the immunohistochemical analysis of three markers (interleukin-1 receptor type I, transforming growth factor-beta receptor type II, and neural cell-adhesion molecule), which allow a refined analysis of anatomical hair follicle compartments during all hair cycle stages. In contrast to prior staging systems, we suggest dividing anagen III into three distinct substages, based on morphologic differences, onset and progression of melanogenesis, and the position of the dermal papilla in the subcutis, The computer-generated schematic representations of each stage are presented with the aim of standardizing reports on follicular gene and protein expression patterns. This guide should become a useful tool when screening new mouse mutants or mice treated with pharmaceuticals for discrete morphologic abnormalities of hair follicle cycling in a highly reproducible, easily applicable, and quantifiable manner.

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