RESULTS: Of the 250 contacts, 205 (82%) underwent repeat testing. Among 85 contacts with baseline TST-negative/QFT-negative results, TST conversion rates ranged between 7.5% and 13.8%, and QFT conversion rates ranged between 11.8% and 21.2%, depending on the definitions used. Among 109 contacts who were QFT-positive at baseline, seven (6.4%) had QFT reversions. QFT reversions

were most likely when the baseline TST was negative and QFT results were just above the diagnostic cut-off.

CONCLUSIONS: QFT conversions and reversions occurred among contacts of TB cases. Conversion rates seemed selleck compound to vary, depending on the test and definitions used for conversions. These findings need to be verified in larger studies in various settings.”
“Aim: The purpose of the present study was to compare and analyze differences in antepartal fetal heart rate (FHR) parameters during pregnancy

and pregnancy outcomes in normal fetuses and fetuses with nuchal cord (NC).”
“Automated analysis of whole mount tissue sections can provide insights into tumor subtypes and the underlying molecular basis of neoplasm. However, since tumor sections are collected from different laboratories, inherent technical and biological variations impede analysis for very large datasets such as BIX-01294 The Cancer Genome Atlas (TCGA). Our objective is to characterize tumor histopathology, through the delineation of the nuclear regions, from hematoxylin and eosin stained tissue sections. Such a representation can then be mined for intrinsic subtypes across a large dataset for prediction and molecular association. Furthermore, nuclear segmentation is formulated within a multi-reference graph framework with geodesic constraints, which enables computation of multidimensional representations, on a cell-by-cell basis, for functional enrichment and bioinformatics Selleck VX-680 analysis. Here, we present a novel method, multi-reference graph cut (MRGC), for nuclear segmentation that overcomes technical variations associated with sample

preparation by incorporating prior knowledge from manually annotated reference images and local image features. The proposed approach has been validated on manually annotated samples and then applied to a dataset of 377 Glioblastoma Multiforme (GBM) whole slide images from 146 patients. For the GBM cohort, multidimensional representation of the nuclear features and their organization have identified 1) statistically significant subtypes based on several morphometric indexes, 2) whether each subtype can be predictive or not, and 3) that the molecular correlates of predictive subtypes are consistent with the literature.

Data and intermediaries for a number of tumor types (GBM, low grade glial, and kidney renal clear carcinoma) are available at: http://tcga.lbl.gov for correlation with TCGA molecular data. The website also provides an interface for panning and zooming of whole mount tissue sections with/without overlaid segmentation results for quality control.