Time-integrated luminosity recorded by the BABAR detector at the PEP-II e+e- collider

This article is the Preprint version of the final published artcile which can be accessed at the link below.We describe a measurement of the time-integrated luminosity of the data collected by the BABAR experiment at the PEP-II asymmetric-energy e+e- collider at the ϒ(4S), ϒ(3S), and ϒ(2S) resonances and in a continuum region below each resonance. We measure the time-integrated luminosity by counting e+e-→e+e- and (for the ϒ(4S) only) e+e-→μ+μ- candidate events, allowing additional photons in the final state. We use data-corrected simulation to determine the cross-sections and reconstruction efficiencies for these processes, as well as the major backgrounds. Due to the large cross-sections of e+e-→e+e- and e+e-→μ+μ-, the statistical uncertainties of the measurement are substantially smaller than the systematic uncertainties. The dominant systematic uncertainties are due to observed differences between data and simulation, as well as uncertainties on the cross-sections. For data collected on the ϒ(3S) and ϒ(2S) resonances, an additional uncertainty arises due to ϒ→e+e-X background. For data collected off the ϒ resonances, we estimate an additional uncertainty due to time dependent efficiency variations, which can affect the short off-resonance runs. The relative uncertainties on the luminosities of the on-resonance (off-resonance) samples are 0.43% (0.43%) for the ϒ(4S), 0.58% (0.72%) for the ϒ(3S), and 0.68% (0.88%) for the ϒ(2S).This work is supported by the US Department of Energy and National Science Foundation, the Natural Sciences and Engineering Research Council (Canada), the Commissariat à l’Energie Atomique and Institut National de Physique Nucléaire et de Physiquedes Particules (France), the Bundesministerium für Bildung und Forschung and Deutsche Forschungsgemeinschaft (Germany), the Istituto Nazionale di Fisica Nucleare (Italy), the Foundation for Fundamental Research on Matter (The Netherlands), the Research Council of Norway, the Ministry of Education and Science of the Russian Federation, Ministerio de Ciencia e Innovación (Spain), and the Science and Technology Facilities Council (United Kingdom). Individuals have received support from the Marie-Curie IEF program (European Union) and the A.P. Sloan Foundation (USA)

Observation of the baryonic decay B \uaf 0 \u2192 \u39bc+ p \uaf K-K+

We report the observation of the baryonic decay B\uaf0\u2192\u39bc+p\uafK-K+ using a data sample of 471 7106 BB\uaf pairs produced in e+e- annihilations at s=10.58GeV. This data sample was recorded with the BABAR detector at the PEP-II storage ring at SLAC. We find B(B\uaf0\u2192\u39bc+p\uafK-K+)=(2.5\ub10.4(stat)\ub10.2(syst)\ub10.6B(\u39bc+)) 710-5, where the uncertainties are statistical, systematic, and due to the uncertainty of the \u39bc+\u2192pK-\u3c0+ branching fraction, respectively. The result has a significance corresponding to 5.0 standard deviations, including all uncertainties. For the resonant decay B\uaf0\u2192\u39bc+p\uaf\u3c6, we determine the upper limit B(B\uaf0\u2192\u39bc+p\uaf\u3c6)<1.2 710-5 at 90% confidence level

CONEX: Creating serendipitous connections among Living Labs and Horizon 2020 challenges

This paper presents an online serendipity experiment allowing academic and industrial research labs to quickly identify collaboration opportunities and form H2020 proposal consortia. This work was carried out in the context of a Living Labs Matchmaking session organized during the 4th Living Labs Summer School. A set of 18 Living Labs data and H2020 Challenges data were entered in a software prototype named CONEX. The main objective consisted in identifying collaboration opportunities among participating Living-Labs for collectively answering to the EU Horizon2020 first call-for-proposals. The software prototype used for simulating a serendipity service was developed within previous EU research projects. This work addresses the paradox of systematizing unexpected or serendipitous connections that normally happen quite rarely. The actual findings reveal the feasibility of quickly exploring serendipitous connections in order to efficiently form Open Innovation ecosystems as recommended in the OI2 paradigm. However, findings unveil that terms used in all parsed and indexed content-objects have to be harmonized regardless the type of involved communities (e.g. folksonomy). It also reveals that profiling participating entities in using produced content-objects ensures a higher trust level compared to more traditional declarative approaches

Dynamic landscape of pancreatic carcinogenesis reveals early molecular networks of malignancy.

OBJECTIVE: The initial steps of pancreatic regeneration versus carcinogenesis are insufficiently understood. Although a combination of oncogenic Kras and inflammation has been shown to induce malignancy, molecular networks of early carcinogenesis remain poorly defined. DESIGN: We compared early events during inflammation, regeneration and carcinogenesis on histological and transcriptional levels with a high temporal resolution using a well-established mouse model of pancreatitis and of inflammation-accelerated Kras(G12D)-driven pancreatic ductal adenocarcinoma. Quantitative expression data were analysed and extensively modelled in silico. RESULTS: We defined three distinctive phases-termed inflammation, regeneration and refinement-following induction of moderate acute pancreatitis in wild-type mice. These corresponded to different waves of proliferation of mesenchymal, progenitor-like and acinar cells. Pancreas regeneration required a coordinated transition of proliferation between progenitor-like and acinar cells. In mice harbouring an oncogenic Kras mutation and challenged with pancreatitis, there was an extended inflammatory phase and a parallel, continuous proliferation of mesenchymal, progenitor-like and acinar cells. Analysis of high-resolution transcriptional data from wild-type animals revealed that organ regeneration relied on a complex interaction of a gene network that normally governs acinar cell homeostasis, exocrine specification and intercellular signalling. In mice with oncogenic Kras, a specific carcinogenic signature was found, which was preserved in full-blown mouse pancreas cancer. CONCLUSIONS: These data define a transcriptional signature of early pancreatic carcinogenesis and a molecular network driving formation of preneoplastic lesions, which allows for more targeted biomarker development in order to detect cancer earlier in patients with pancreatitis

The BaBar detector: Upgrades, operation and performance

Contains fulltext : 121729.pdf (preprint version ) (Open Access

Programmed death-ligand 1 expression influenced by tissue sample size. Scoring based on tissue microarrays' and cross-validation with resections, in patients with, stage I-III, non-small cell lung carcinoma of the European Thoracic Oncology Platform Lungscape cohort

PD-L1, as assessed by immunohistochemistry, is a predictive biomarker for immuno-oncology treatment in lung cancer. Different scoring methods have been used to assess its status, resulting in a wide range of positivity rates. We use the European Thoracic Oncology Platform Lungscape non-small cell lung carcinoma cohort to explore this issue. PD-L1 expression was assessed via immunohistochemistry on tissue microarrays (up to four cores per case), using the DAKO 28-8 immunohistochemistry assay, following a two-round external quality assessment procedure. All samples were analyzed under the same protocol. Cross-validation of scoring between tissue microarray and whole sections was performed in 10% randomly selected samples. Cutoff points considered: >= 1, 50 (primarily), and 25%. At the two external quality assessment rounds, tissue microarray scoring agreement rates between pathologists were: 73% and 81%. There were 2008 cases with valid immunohistochemistry tissue microarray results (50% all cores evaluable). Concordant cases at 1, 25, and 50% were: 85, 91, and 93%. Tissue microarray core results were identical for 70% of cases. Sensitivity of the tissue microarray method for 1, 25, and 50% was: 80, 78, and 79% (specificity: 90, 95, 98%). Complete agreement between tissue microarrays and whole sections was achieved for 60% of the cases. Highest sensitivity rates for 1% and 50% cutoffs were detected for higher number of cores. Underestimation of PD-L1 expression on small samples is more common than overestimation. We demonstrated that classification of PD-L1 on small biopsy samples does not represent the overall expression of PD-L1 in all non-small cell cancer carcinoma cases, although the majority of cases are 'correctly' classified. In future studies, sampling more and larger biopsies, recording the biopsy size and tumor load may permit further refinement, increasing predictive accuracy.Pathogenesis and treatment of chronic pulmonary disease

Programmed death-ligand 1 expression influenced by tissue sample size. Scoring based on tissue microarrays’ and cross-validation with resections, in patients with, stage I–III, non-small cell lung carcinoma of the European Thoracic Oncology Platform Lungscape cohort

PD-L1, as assessed by immunohistochemistry, is a predictive biomarker for immuno-oncology treatment in lung cancer. Different scoring methods have been used to assess its status, resulting in a wide range of positivity rates. We use the European Thoracic Oncology Platform Lungscape non-small cell lung carcinoma cohort to explore this issue. PD-L1 expression was assessed via immunohistochemistry on tissue microarrays (up to four cores per case), using the DAKO 28-8 immunohistochemistry assay, following a two-round external quality assessment procedure. All samples were analyzed under the same protocol. Cross-validation of scoring between tissue microarray and whole sections was performed in 10% randomly selected samples. Cutoff points considered: ≥1, 50 (primarily), and 25%. At the two external quality assessment rounds, tissue microarray scoring agreement rates between pathologists were: 73% and 81%. There were 2008 cases with valid immunohistochemistry tissue microarray results (50% all cores evaluable). Concordant cases at 1, 25, and 50% were: 85, 91, and 93%. Tissue microarray core results were identical for 70% of cases. Sensitivity of the tissue microarray method for 1, 25, and 50% was: 80, 78, and 79% (specificity: 90, 95, 98%). Complete agreement between tissue microarrays and whole sections was achieved for 60% of the cases. Highest sensitivity rates for 1% and 50% cutoffs were detected for higher number of cores. Underestimation of PD-L1 expression on small samples is more common than overestimation. We demonstrated that classification of PD-L1 on small biopsy samples does not represent the overall expression of PD-L1 in all non-small cell cancer carcinoma cases, although the majority of cases are ‘correctly’ classified. In future studies, sampling more and larger biopsies, recording the biopsy size and tumor load may permit further refinement, increasing predictive accuracy. © 2019, The Author(s), under exclusive licence to United States &amp; Canadian Academy of Pathology