Prophylactic Laparoscopic Gastrectomy for Hereditary Diffuse Gastric Cancer: A Case Series in a Single Family

This study suggests that a laparoscopic approach for prophylactic total gastrectomy for carriers of CDH1 gene mutation can be performed safely and effectively

Ritonavir blocks AKT signaling, activates apoptosis and inhibits migration and invasion in ovarian cancer cells

<p>Abstract</p> <p>Background</p> <p>Ovarian cancer is the leading cause of mortality from gynecological malignancies, often undetectable in early stages. The difficulty of detecting the disease in its early stages and the propensity of ovarian cancer cells to develop resistance to known chemotherapeutic treatments dramatically decreases the 5-year survival rate. Chemotherapy with paclitaxel after surgery increases median survival only by 2 to 3 years in stage IV disease highlights the need for more effective drugs. The human immunodeficiency virus (HIV) infection is characterized by increased risk of several solid tumors due to its inherent nature of weakening of immune system. Recent observations point to a lower incidence of some cancers in patients treated with protease inhibitor (PI) cocktail treatment known as HAART (Highly Active Anti-Retroviral Therapy).</p> <p>Results</p> <p>Here we show that ritonavir, a HIV protease inhibitor effectively induced cell cycle arrest and apoptosis in ovarian cell lines MDH-2774 and SKOV-3 in a dose dependent manner. Over a 3 day period with 20 μM ritonavir resulted in the cell death of over 60% for MDAH-2774 compared with 55% in case of SKOV-3 cell line. Ritonavir caused G1 cell cycle arrest of the ovarian cancer cells, mediated by down modulating levels of RB phosphorylation and depleting the G1 cyclins, cyclin-dependent kinase and increasing their inhibitors as determined by gene profile analysis. Interestingly, the treatment of ritonavir decreased the amount of phosphorylated AKT in a dose-dependent manner. Furthermore, inhibition of AKT by specific siRNA synergistically increased the efficacy of the ritonavir-induced apoptosis. These results indicate that the addition of the AKT inhibitor may increase the therapeutic efficacy of ritonavir.</p> <p>Conclusion</p> <p>Our results demonstrate a potential use of ritonavir for ovarian cancer with additive effects in conjunction with conventional chemotherapeutic regimens. Since ritonavir is clinically approved for human use for HIV, drug repositioning for ovarian cancer could accelerate the process of traditional drug development. This would reduce risks, limit the costs and decrease the time needed to bring the drug from bench to bedside.</p

Sulforaphane induces cell cycle arrest by protecting RB-E2F-1 complex in epithelial ovarian cancer cells

<p>Abstract</p> <p>Background</p> <p>Sulforaphane (SFN), an isothiocyanate phytochemical present predominantly in cruciferous vegetables such as brussels sprout and broccoli, is considered a promising chemo-preventive agent against cancer. In-vitro exposure to SFN appears to result in the induction of apoptosis and cell-cycle arrest in a variety of tumor types. However, the molecular mechanisms leading to the inhibition of cell cycle progression by SFN are poorly understood in epithelial ovarian cancer cells (EOC). The aim of this study is to understand the signaling mechanisms through which SFN influences the cell growth and proliferation in EOC.</p> <p>Results</p> <p>SFN at concentrations of 5 - 20 μM induced a dose-dependent suppression of growth in cell lines MDAH 2774 and SkOV-3 with an IC50 of ~8 μM after a 3 day exposure. Combination treatment with chemotherapeutic agent, paclitaxel, resulted in additive growth suppression. SFN at ~8 μM decreased growth by 40% and 20% on day 1 in MDAH 2774 and SkOV-3, respectively. Cells treated with cytotoxic concentrations of SFN have reduced cell migration and increased apoptotic cell death via an increase in Bak/Bcl-2 ratio and cleavage of procaspase-9 and poly (ADP-ribose)-polymerase (PARP). Gene expression profile analysis of cell cycle regulated proteins demonstrated increased levels of tumor suppressor retinoblastoma protein (RB) and decreased levels of E2F-1 transcription factor. SFN treatment resulted in G1 cell cycle arrest through down modulation of RB phosphorylation and by protecting the RB-E2F-1 complex.</p> <p>Conclusions</p> <p>SFN induces growth arrest and apoptosis in EOC cells. Inhibition of retinoblastoma (RB) phosphorylation and reduction in levels of free E2F-1 appear to play an important role in EOC growth arrest.</p

The Apache Point Observatory Galactic Evolution Experiment: First Detection of High Velocity Milky Way Bar Stars

Commissioning observations with the Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey III, have produced radial velocities (RVs) for ~4700 K/M-giant stars in the Milky Way bulge. These high-resolution (R \sim 22,500), high-S/N (>100 per resolution element), near-infrared (1.51-1.70 um; NIR) spectra provide accurate RVs (epsilon_v~0.2 km/s) for the sample of stars in 18 Galactic bulge fields spanning -1-32 deg. This represents the largest NIR high-resolution spectroscopic sample of giant stars ever assembled in this region of the Galaxy. A cold (sigma_v~30 km/s), high-velocity peak (V_GSR \sim +200 km/s) is found to comprise a significant fraction (~10%) of stars in many of these fields. These high RVs have not been detected in previous MW surveys and are not expected for a simple, circularly rotating disk. Preliminary distance estimates rule out an origin from the background Sagittarius tidal stream or a new stream in the MW disk. Comparison to various Galactic models suggests that these high RVs are best explained by stars in orbits of the Galactic bar potential, although some observational features remain unexplained.Comment: 7 pages, 4 figures, accepted for publication in ApJ Letter

Think Outside the Color Box: Probabilistic Target Selection and the SDSS-XDQSO Quasar Targeting Catalog

We present the SDSS-XDQSO quasar targeting catalog for efficient flux-based quasar target selection down to the faint limit of the Sloan Digital Sky Survey (SDSS) catalog, even at medium redshifts (2.5 <~ z <~ 3) where the stellar contamination is significant. We build models of the distributions of stars and quasars in flux space down to the flux limit by applying the extreme-deconvolution method to estimate the underlying density. We convolve this density with the flux uncertainties when evaluating the probability that an object is a quasar. This approach results in a targeting algorithm that is more principled, more efficient, and faster than other similar methods. We apply the algorithm to derive low-redshift (z < 2.2), medium-redshift (2.2 <= z 3.5) quasar probabilities for all 160,904,060 point sources with dereddened i-band magnitude between 17.75 and 22.45 mag in the 14,555 deg^2 of imaging from SDSS Data Release 8. The catalog can be used to define a uniformly selected and efficient low- or medium-redshift quasar survey, such as that needed for the SDSS-III's Baryon Oscillation Spectroscopic Survey project. We show that the XDQSO technique performs as well as the current best photometric quasar-selection technique at low redshift, and outperforms all other flux-based methods for selecting the medium-redshift quasars of our primary interest. We make code to reproduce the XDQSO quasar target selection publicly available

Photometric redshifts and quasar probabilities from a single, data-driven generative model

We describe a technique for simultaneously classifying and estimating the redshift of quasars. It can separate quasars from stars in arbitrary redshift ranges, estimate full posterior distribution functions for the redshift, and naturally incorporate flux uncertainties, missing data, and multi-wavelength photometry. We build models of quasars in flux-redshift space by applying the extreme deconvolution technique to estimate the underlying density. By integrating this density over redshift one can obtain quasar flux-densities in different redshift ranges. This approach allows for efficient, consistent, and fast classification and photometric redshift estimation. This is achieved by combining the speed obtained by choosing simple analytical forms as the basis of our density model with the flexibility of non-parametric models through the use of many simple components with many parameters. We show that this technique is competitive with the best photometric quasar classification techniques---which are limited to fixed, broad redshift ranges and high signal-to-noise ratio data---and with the best photometric redshift techniques when applied to broadband optical data. We demonstrate that the inclusion of UV and NIR data significantly improves photometric quasar--star separation and essentially resolves all of the redshift degeneracies for quasars inherent to the ugriz filter system, even when included data have a low signal-to-noise ratio. For quasars spectroscopically confirmed by the SDSS 84 and 97 percent of the objects with GALEX UV and UKIDSS NIR data have photometric redshifts within 0.1 and 0.3, respectively, of the spectroscopic redshift; this amounts to about a factor of three improvement over ugriz-only photometric redshifts. Our code to calculate quasar probabilities and redshift probability distributions is publicly available

The clustering of massive galaxies at z~0.5 from the first semester of BOSS data

We calculate the real- and redshift-space clustering of massive galaxies at z~0.5 using the first semester of data by the Baryon Oscillation Spectroscopic Survey (BOSS). We study the correlation functions of a sample of 44,000 massive galaxies in the redshift range 0.4<z<0.7. We present a halo-occupation distribution modeling of the clustering results and discuss the implications for the manner in which massive galaxies at z~0.5 occupy dark matter halos. The majority of our galaxies are central galaxies living in halos of mass 10^{13}Msun/h, but 10% are satellites living in halos 10 times more massive. These results are broadly in agreement with earlier investigations of massive galaxies at z~0.5. The inferred large-scale bias (b~2) and relatively high number density (nbar=3e-4 h^3 Mpc^{-3}) imply that BOSS galaxies are excellent tracers of large-scale structure, suggesting BOSS will enable a wide range of investigations on the distance scale, the growth of large-scale structure, massive galaxy evolution and other topics.Comment: 11 pages, 12 figures, matches version accepted by Ap