Background: Treatment of cranial deformity is often performed during infancy in cases such as craniosynostosis and deformational plagiocephaly. To acquire morphologic standards for the treatment goals of these conditions, we created cranial average models and elucidated the growth patterns of the cranium of healthy infants in 3-dimension (3D) using homologous modeling. Methods: Homologous modeling is a technique that enables mathematical analysis of different 3D objects by converting the objects into homologous models that share the same number of vertices with the same spatial relationships. Craniofacial computed tomographic data of 120 healthy infants ranging in age from 1 to 17 months were collected. Based on the computed tomographic data, we created 120 homologous models. Six average 3D models (20 individuals each for 6 different age groups) were created by averaging the vertices of the models. Three-dimensional growth patterns of the cranium were clarified by comparing the 6 average models. Results: We successfully created 6 average models and visualized the growth patterns of the cranium. From 1-month-old to 5-month-old infants, the entire cranium except for the occipital region grows, and the cranium tended to be brachycephalic (cephalic index at 4–5 months: 87.1–97.3), but the growth was thereafter localized to specific areas. Conclusions: Three-dimensional growth patterns of the cranium of healthy infants were clarified. These findings will support the understanding and treatment of the conditions that cause cranial deformity. To our knowledge, this is the first report to visualize the growth patterns of the entire cranium of healthy infants in 3D.
Wound healing is a complex biological process, and imbalances of various substances in the wound environment may prolong healing and lead to excessive scarring. Keloid is abnormal proliferation of scar tissue beyond the original wound margins with excessive deposition of extracellular matrix (ECM) and chronic inflammation. Despite numerous previous research efforts, the pathogenesis of keloid remains unknown. Vascular endothelial cells (VECs) are a major type of inductive cell in inflammation and fibrosis. Despite several studies on vascular morphology in keloid formation, there has been no functional analysis of the role of VECs. In the present study, we isolated living VECs from keloid tissues and investigated gene expression patterns using microarray analysis. We obtained 5 keloid tissue samples and 6 normal skin samples from patients without keloid. Immediately after excision, tissue samples were gently minced and living cells were isolated. Magnetic-activated cell sorting of VECs was performed by negative selection of fibroblasts and CD45 + cells and by positive selection of CD31 + cells. After RNA extraction, gene expression analysis was performed to compare VECs isolated from keloid tissue (KVECs) with VECs from normal skin (NVECs). After cell isolation, the percentage of CD31 + cells as measured by flow cytometry ranged from 81.8%-98.6%. Principal component analysis was used to identify distinct molecular phenotypes in KVECs versus NVECs and these were divided into two subgroups. In total, 15 genes were upregulated, and 3 genes were downregulated in KVECs compared with NVECs using the t-test (< 0.05). Quantitative RT-PCR and immunohistochemistry showed 16fold and 11-fold overexpression of SERPINA3 and LAMC2, respectively. SERPINA3 encodes the serine protease inhibitor, α1-antichymotripsin. Laminin γ2-Chain (LAMC2) is a subunit of laminin-5 that induces retraction of vascular endothelial cells and enhances vascular permeability. This is the first report of VEC isolation and gene expression analysis in keloid tissue. Our data suggest that SERPINA3 and LAMC2 upregulation in KVECs may contribute to the development of fibrosis and prolonged inflammation in keloid. Further functional investigation of these genes will help clarify the mechanisms of abnormal scar tissue proliferation.
Objective: Data on cranial morphology of healthy individuals can be used as the guide in the treatment of cranial deformity. There are many reports analyzing the cranial morphology of healthy children in the past. But most of them focus on 2-dimensional values, and there are only a few reports, which analyzed the cranial morphology of Japanese healthy infants. We report a novel method that enables the comprehensive analysis of cranial morphology of Japanese healthy infants in 3D. Methods: Craniofacial CT data of 20 healthy infants (9 males, 11 females) ranging in age from 1 to 11 months were collected. Based on the CT data, we created 20 homologous models of cranium using software specifically designed to support homologous modeling. We averaged vertex coordinates of the homologous models to create average model. We further performed principal component analysis, and created virtual models based on each principal component. The contribution rate was calculated, and the features described by each principal component were interpreted. Results: We created the average cranial model of Japanese healthy infants. Seven principal components (cumulative contribution rate: 89.218%) were interpreted as to which part of the cranial shape each component was related to. The elements were extracted that may characterize the cranial morphology of some of the clinical conditions such as dolico/brachycephaly and deformational plagiocephaly. Some of these elements have not been mentioned in the past literature. Conclusion: Homologous modeling was considered to be valid and strong tool for comprehensive analysis of cranial morphology.
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