First Dark Matter Results from the XENON100 Experiment

The XENON100 experiment, in operation at the Laboratori Nazionali del Gran Sasso in Italy, is designed to search for dark matter WIMPs scattering off 62 kg of liquid xenon in an ultra-low background dual-phase time projection chamber. In this letter, we present first dark matter results from the analysis of 11.17 live days of non-blind data, acquired in October and November 2009. In the selected fiducial target of 40 kg, and within the pre-defined signal region, we observe no events and hence exclude spin-independent WIMP-nucleon elastic scattering cross-sections above 3.4 x 10^-44 cm^2 for 55 GeV/c^2 WIMPs at 90% confidence level. Below 20 GeV/c^2, this result constrains the interpretation of the CoGeNT and DAMA signals as being due to spin-independent, elastic, light mass WIMP interactions.Comment: 5 pages, 5 figures. Matches published versio

Dark Matter Results from 100 Live Days of XENON100 Data

We present results from the direct search for dark matter with the XENON100 detector, installed underground at the Laboratori Nazionali del Gran Sasso of INFN, Italy. XENON100 is a two-phase time projection chamber with a 62 kg liquid xenon target. Interaction vertex reconstruction in three dimensions with millimeter precision allows to select only the innermost 48 kg as ultra-low background fiducial target. In 100.9 live days of data, acquired between January and June 2010, no evidence for dark matter is found. Three candidate events were observed in a pre-defined signal region with an expected background of 1.8 +/- 0.6 events. This leads to the most stringent limit on dark matter interactions today, excluding spin-independent elastic WIMP-nucleon scattering cross-sections above 7.0x10^-45 cm^2 for a WIMP mass of 50 GeV/c^2 at 90% confidence level.Comment: 5 pages, 5 figures; matches accepted versio

Mycobacterial catalase–peroxidase is a tissue antigen and target of the adaptive immune response in systemic sarcoidosis

Sarcoidosis is a disease of unknown etiology characterized by noncaseating epithelioid granulomas, oligoclonal CD4+ T cell infiltrates, and immune complex formation. To identify pathogenic antigens relevant to immune-mediated granulomatous inflammation in sarcoidosis, we used a limited proteomics approach to detect tissue antigens that were poorly soluble in neutral detergent and resistant to protease digestion, consistent with the known biochemical properties of granuloma-inducing sarcoidosis tissue extracts. Tissue antigens with these characteristics were detected with immunoglobulin (Ig)G or F(ab′)2 fragments from the sera of sarcoidosis patients in 9 of 12 (75%) sarcoidosis tissues (150–160, 80, or 60–64 kD) but only 3 of 22 (14%) control tissues (all 62–64 kD; P = 0.0006). Matrix-assisted laser desorption/ionization time of flight mass spectrometry identified Mycobacterium tuberculosis catalase–peroxidase (mKatG) as one of these tissue antigens. Protein immunoblotting using anti-mKatG monoclonal antibodies independently confirmed the presence of mKatG in 5 of 9 (55%) sarcoidosis tissues but in none of 14 control tissues (P = 0.0037). IgG antibodies to recombinant mKatG were detected in the sera of 12 of 25 (48%) sarcoidosis patients compared with 0 of 11 (0%) purified protein derivative (PPD)− (P = 0.0059) and 4 of 10 (40%) PPD+ (P = 0.7233) control subjects, suggesting that remnant mycobacterial catalase–peroxidase is one target of the adaptive immune response driving granulomatous inflammation in sarcoidosis

Implications on Inelastic Dark Matter from 100 Live Days of XENON100 Data

The XENON100 experiment has recently completed a dark matter run with 100.9 live-days of data, taken from January to June 2010. Events in a 48kg fiducial volume in the energy range between 8.4 and 44.6 keVnr have been analyzed. A total of three events have been found in the predefined signal region, compatible with the background prediction of (1.8 \pm 0.6) events. Based on this analysis we present limits on the WIMP-nucleon cross section for inelastic dark matter. With the present data we are able to rule out the explanation for the observed DAMA/LIBRA modulation as being due to inelastic dark matter scattering off iodine at a 90% confidence level.Comment: 3 pages, 3 figure

Effect of the 3q26-coding oncogene SEC62 as a potential prognostic marker in patients with ovarian neoplasia

With approximately 220,000 newly diagnosed cases per year, ovarian cancer is among the most frequently occurring cancers among women and the second leading cause of death from gynecological malignancies worldwide. About 70% of these cancers are diagnosed in advanced stages (FIGO IIB–IV), with a 5-year survival rate of 20–30%. Due to the poor prognosis of this disease, research has focused on its pathogenesis and the identification of prognostic factors. One possible approach for the identification of biological markers is the identification of tumor entity-specific genetic “driver mutations”. One such mutation is 3q26 amplification in the tumor driver SEC62, which has been identified as relevant to the pathogenesis of ovarian cancer. This study was conducted to investigate the role of SEC62 in ovarian malignancies. Patients with ovarian neoplasias (borderline tumors of the ovary and ovarian cancer) who were treated between January 2007 and April 2019 at the Department of Gynecology and Obstetrics, Saarland University Hospital, were included in this retrospective study. SEC62 expression in tumor tissue samples taken during clinical treatment was assessed immunohistochemically, with the calculation of immunoreactivity scores according to Remmele and Stegner, Pathologe, 1987, 8, 138–140. Correlations of SEC62 expression with the TNM stage, histological subtype, tumor entity, and oncological outcomes (progression-free and overall survival) were examined. The sample comprised 167 patients (123 with ovarian cancer and 44 with borderline tumors of the ovary) with a median age of 60 (range, 15–87) years. At the time of diagnosis, 77 (46%) cases were FIGO stage III. All tissue slides showed SEC62 overexpression in tumor cells and no SEC62 expression in other cells. Median immunoreactivity scores were 8 (range, 2–12) for ovarian cancer and 9 (range, 4–12) for borderline tumors of the ovary. Patients with borderline tumors of the ovary as well as patients with ovarian cancer and an immunoreactive score (IRS) ≤ 9 showed an improved overall survival compared to those presenting with an IRS score >9 (p = 0.03). SEC62 seems to be a prognostic biomarker for the overall survival of patients with ovarian malignancies

Material screening and selection for XENON100

Results of the extensive radioactivity screening campaign to identify materials for the construction of XENON100 are reported. This Dark Matter search experiment is operated underground at Laboratori Nazionali del Gran Sasso (LNGS), Italy. Several ultra sensitive High Purity Germanium detectors (HPGe) have been used for gamma ray spectrometry. Mass spectrometry has been applied for a few low mass plastic samples. Detailed tables with the radioactive contaminations of all screened samples are presented, together with the implications for XENON100.Comment: 8 pages, 1 figur

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

The last forests on Antarctica: Reconstructing flora and temperature from the Neogene Sirius Group, Transantarctic Mountains

Fossil-bearing deposits in the Transantarctic Mountains, Antarctica indicate that, despite the cold nature of the continent’s climate, a tundra ecosystem grew during periods of ice sheet retreat in the mid to late Neogene (17–2.5 Ma), 480 km from the South Pole. To date, palaeotemperature reconstruction has been based only on biological ranges, thereby calling for a geochemical approach to understanding continental climate and environment. There is contradictory evidence in the fossil record as to whether this flora was mixed angiosperm-conifer vegetation, or whether by this point conifers had disappeared from the continent. In order to address these questions, we have analysed, for the first time in sediments of this age, plant and bacterial biomarkers in terrestrial sediments from the Transantarctic Mountains to reconstruct past temperature and vegetation during a period of East Antarctic Ice Sheet retreat. From tetraether lipids (MBT’/CBT palaeothermometer), we conclude that the mean continental summer temperature was ca. 5 °C, in agreement with previous reconstructions. This was warm enough to have allowed woody vegetation to survive and reproduce even during the austral winter. Biomarkers from vascular plants indicate a low diversity and spatially variable flora consisting of higher plants, moss and algal mats growing in microenvironments in a glacial outwash system. Abietane-type compounds were abundant in some samples, indicating that conifers, most likely Podocarpaceae, grew on the Antarctic continent well into the Neogene. This is supported by the palynological record, but not the macrofossil record for the continent, and has implications for the evolution of vegetation on Antarctica