Role of mast cells in inflammatory bowel disease and inflammation-associated colorectal neoplasia in IL-10-deficient mice.

BACKGROUND: Inflammatory bowel disease (IBD) is hypothesized to result from stimulation of immune responses against resident intestinal bacteria within a genetically susceptible host. Mast cells may play a critical role in IBD pathogenesis, since they are typically located just beneath the intestinal mucosal barrier and can be activated by bacterial antigens. METHODOLOGY/PRINCIPAL FINDINGS: This study investigated effects of mast cells on inflammation and associated neoplasia in IBD-susceptible interleukin (IL)-10-deficient mice with and without mast cells. IL-10-deficient mast cells produced more pro-inflammatory cytokines in vitro both constitutively and when triggered, compared with wild type mast cells. However despite this enhanced in vitro response, mast cell-sufficient Il10(-/-) mice actually had decreased cecal expression of tumor necrosis factor (TNF) and interferon (IFN)-gamma mRNA, suggesting that mast cells regulate inflammation in vivo. Mast cell deficiency predisposed Il10(-/-) mice to the development of spontaneous colitis and resulted in increased intestinal permeability in vivo that preceded the development of colon inflammation. However, mast cell deficiency did not affect the severity of IBD triggered by non-steroidal anti-inflammatory agents (NSAID) exposure or helicobacter infection that also affect intestinal permeability. CONCLUSIONS/SIGNIFICANCE: Mast cells thus appear to have a primarily protective role within the colonic microenvironment by enhancing the efficacy of the mucosal barrier. In addition, although mast cells were previously implicated in progression of sporadic colon cancers, mast cells did not affect the incidence or severity of colonic neoplasia in this inflammation-associated model.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

Altered expression of the septin gene, SEPT9, in ovarian neoplasia.

The septin family of genes has been implicated in a variety of cellular processes including cytokinesis, membrane transport and fusion, exocytosis, and apoptosis. One member of the septin family maps to chromosome 17q25.3, a region commonly deleted in sporadic ovarian and breast tumours, and has also been identified as a fusion partner of MLL in acute myeloid leukaemias. The present study demonstrates that the pattern of expression of multiple splice variants of this septin gene is altered in ovarian tumours and cell lines. In particular, expression of the zeta transcript is detectable in the majority of tumours and cell lines, but not in a range of non-malignant adult and fetal tissues. Zeta expression is accompanied by loss of the ubiquitous beta transcript. Somatic mutations of the gene were not detected in ovarian tumours, but it was demonstrated that beta expression in tumour cell lines can be reactivated by 5-azacytidine treatment, suggesting a role for methylation in the control of expression of this gene. Copyright © 2003 John Wiley & Sons, Ltd.

An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.