Co-expression of CD173 (H2) and CD174 (Lewis Y) with CD44 suggests that fucosylated histo-blood group antigens are markers of breast cancer-initiating cells

Histo-blood group antigens CD173 (H2) and CD174 (Lewis Y) are known to be developmentally regulated carbohydrate antigens which are expressed to a varying degree on many human carcinomas. We hypothesized that they might represent markers of cancer-initiating cells (or cancer stem cells, CSC). In order to test this hypothesis, we examined the co-expression of CD173 and CD174 with stem cell markers CD44 and CD133 by flow cytometry analysis, immunocytochemistry, and immunohistochemistry on cell lines and tissue sections from breast cancer. In three breast cancer cell lines, the percentage of CD173(+)/CD44(+) cells ranged from 17% to > 60% and of CD174(+)/CD44(+) from 21% to 57%. In breast cancer tissue sections from 15 patients, up to 50% of tumor cells simultaneously expressed CD173, CD174, and CD44 antigens. Co-expression of CD173 and CD174 with CD133 was also observed, but to a lesser percentage. Co-immunoprecipitation and sandwich ELISA experiments on breast cancer cell lines suggested that CD173 and CD174 are carried on the CD44 molecule. The results show that in these tissues CD173 (H2) and CD174 (LeY) are associated with CD44 expression, suggesting that these carbohydrate antigens are markers of cancer-initiating cells or of early progenitors of breast carcinomas.

Somatic mutations of mitochondrial genome in early stage breast cancer

The complete mitochondrial genomes of the primary cancerous, matched paracancerous normal and distant normal tissues from 10 early-stage breast cancer patients were analyzed in this study, with special attempt (i) to investigate whether the reported high

Final report of the baseline data reconstruction for the Quality Assurance for Fish Marketing Project

A baseline survey for the project which had been conducted in 2009 had gaps that could not allow assessment of project performance in the outcome and impact indicators to be made. This study was, therefore, commissioned to reconstruct the baseline data, aligned to the impact and outcome indicators on the project logframe and results framework, against which project achievements could be assessed. The purpose and scope of the study was to reconstruct the baseline data and analysis describing the situation prior to QAFM Project inception, taking 2008 as the baseline year, which was aligned to the project logframe outcome and impact indicators; to collect data on current status to compare project outcome (and where possible impact) in improved fish handling sites in comparison with the baseline as well as with comparable non-improved fish landing sites as control group. The study was conducted through secondary data search from sources at NaFIRRI, DFR and ICEIDA. Field data collection was carried out using a sample survey covering 312 respondents including boat and gear owners, crew members, processors and traders at eight project and two control landing sites. Key Informant Interviews were conducted with DFOs and BMU leaders in the study districts and landing sites respectively.

Live 3D shape reconstruction, recognition and registration

We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Progressive 3D reconstruction of infrastructure with videogrammetry

A number of methods are commonly used today to collect infrastructure's spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic, and cost-efficient at the same time. This paper presents a videogrammetric framework for acquiring spatial data of infrastructure which holds the promise to address this limitation. It uses a calibrated set of low-cost high resolution video cameras that is progressively traversed around the scene and aims to produce a dense 3D point cloud which is updated in each frame. It allows for progressive reconstruction as opposed to point-and-shoot followed by point cloud stitching. The feasibility of the framework is studied in this paper. Required steps through this process are presented and the unique challenges of each step are identified. Results specific to each step are also presented.

Comparison of Camera Motion Estimation Methods for 3D Reconstruction of Infrastructure

Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

Comparison of Image-Based and Time-of-Flight-Based Technologies for 3D Reconstruction of Infrastructure

Image-based (i.e., photo/videogrammetry) and time-of-flight-based (i.e., laser scanning) technologies are typically used to collect spatial data of infrastructure. In order to help architecture, engineering, and construction (AEC) industries make cost-effective decisions in selecting between these two technologies with respect to their settings, this paper makes an attempt to measure the accuracy, quality, time efficiency, and cost of applying image-based and time-of-flight-based technologies to conduct as-built 3D reconstruction of infrastructure. In this paper, a novel comparison method is proposed, and preliminary experiments are conducted. The results reveal that if the accuracy and quality level desired for a particular application is not high (i.e., error < 10 cm, and completeness rate > 80%), image-based technologies constitute a good alternative for time-of-flight-based technologies and significantly reduce the time and cost needed for collecting the data on site.