Bacterial vaginosis as a risk factor for high-grade cervical lesions and cancer in HIV-seropositive women.

OBJECTIVE: To assess the effect of bacterial vaginosis (BV) on the risk of high-grade squamous intraepithelial lesions (HSIL) among HIV-seropositive women. METHODS: A hospital-based prospective cohort study of HIV-seropositive women was conducted in Johannesburg, South Africa from January 2005 to September 2009. Multivariate log-binomial and Poisson regressions were used to estimate prevalence and rate ratios, respectively. RESULTS: Among 1954 HIV-seropositive women, the baseline prevalence of HSIL was 17%. BV prevalence was high (54%) and showed no association with prevalence of HSIL (adjusted prevalence ratio, 1.12; 95% confidence intervals (CI), 0.92-1.35) nor with cervical lesion progression at follow-up visit (n=503) (adjusted rate ratio: 1.00; 95% CI, 0.65-1.53). CONCLUSION: Among HIV-seropositive women, BV was not associated with an increased risk of HSIL or cervical lesion progression.

G protein signaling and vein graft intimal hyperplasia: reduction of intimal hyperplasia in vein grafts by a Gbetagamma inhibitor suggests a major role of G protein signaling in lesion development.

Vein grafting results in the development of intimal hyperplasia with accompanying changes in guanine nucleotide-binding (G) protein expression and function. Several serum mitogens that act through G protein-coupled receptors, such as lysophosphatidic acid, stimulate proliferative pathways that are dependent on the G protein betagamma subunit (Gbetagamma)-mediated activation of p21ras. This study examines the role of Gbetagamma signaling in intimal hyperplasia by targeting a gene encoding a specific Gbetagamma inhibitor in an experimental rabbit vein graft model. This inhibitor, the carboxyl terminus of the beta-adrenergic receptor kinase (betaARK(CT)), contains a Gbetagamma-binding domain. Vein graft intimal hyperplasia was significantly reduced by 37% (P<0.01), and physiological studies demonstrated that the normal alterations in G protein coupling phenotypically seen in this model were blocked by betaARK(CT) treatment. Thus, it appears that Gbetagamma-mediated pathways play a major role in intimal hyperplasia and that targeting inhibitors of Gbetagamma signaling offers novel intraoperative therapeutic modalities to inhibit the development of vein graft intimal hyperplasia and subsequent vein graft failure.

Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging

This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single- and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.

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.