Regulatory T cell deficient scurfy mice exhibit a Th2/M2-like inflammatory response in the skin.

BACKGROUND: Scurfy mice have a functional defect in regulatory T cells (Treg), which leads to lethal multi-organ inflammation. The missing Treg function results in uncontrolled autoimmune cellular and humoral inflammatory responses. We and others have previously shown that during the course of disease scurfy mice develop severe skin inflammation and autoantibodies including anti-nuclear autoantibodies (ANA). OBJECTIVE: Autoimmune skin inflammation and ANA are hallmarks for the diagnosis of autoimmune connective tissue diseases; therefore we analyzed scurfy mice for typical signs of these diseases. METHODS: Indirect immunofluorescence was used to specify the ANA pattern in scurfy mice. Skin fibrosis was assessed by cutaneous collagen accumulation (Goldeners trichrome staining), collagen crosslinking/disorganization (Sirus red polarimetry) and quantitative PCR for fibrosis-related transcripts. The cellular components of the inflammatory infiltrates in scurfy skin were analyzed by flow cytometry and intracellular cytokine staining. RESULTS: The majority of scurfy mice developed ANA with a predominant AC-5 pattern typical for mixed connective tissue disease, especially scleroderma. Scurfy mice showed higher skin collagen content compared to WT controls with a significant tendency in upregulation of TIMP-1. CD3+CD4+ T cells in scurfy skin exhibited a strong Th2 deviation with a significant increase of IL-4, IL-5 and IL-13, and M2-polarized CD11b+MHCII+ macrophages compared to WT mice. CONCLUSION: We show that Scurfy mice show a predominant AC-5 ANA pattern typical for mixed connective tissue disease as in scleroderma. The autoimmune inflammation in scurfy skin mainly consists of CD4+ T cells with Th2 differentiation and alternatively-activated (M2) macrophages as it is found in scleroderma with advanced fibrosis.

Alignment of CT images of skull dysmorphology using anatomy-based perpendicular axes.

Rigid body registration of 3D CT scans, based on manual identification of homologous landmarks, is useful for the visual analysis of skull dysmorphology. In this paper, a robust and simple alignment method was proposed to allow for the comparison of skull morphologies, within and between individuals with craniofacial anomalies, based on 3D CT scans, and the minimum number of anatomical landmarks, under rigidity and uniqueness constraints. Three perpendicular axes, extracted from anatomical landmarks, define the absolute coordinate system, through a rigid body transformation, to align multiple CT images for different patients and acquisition times. The accuracy of the alignment method depends on the accuracy of the localized landmarks and target points. The numerical simulation generalizes the accuracy requirements of the alignment method. Experiments using a human dried skull specimen, and ten sets of skull CT images (the pre- and post-operative CT scans of four plagiocephaly, and one fibrous dysplasia patients), demonstrated the feasibility of the technique in clinical practice.