High-Throughput Computing on High-Performance Platforms: A Case Study

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan---a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner

The construct validity and reliability of the Turkish version of Spreitzer's psychological empowerment scale

<p>Abstract</p> <p>Background</p> <p>Today, many organizations have adopted some kind of empowerment initiative for at least part of their workforce. Over the last two decades, two complementary perspectives on empowerment at work have emerged: structural and psychological empowerment. Psychological empowerment is a motivational construct manifested in four cognitions: meaning, competence, self-determination and impact. The aim of this article is to examine the construct validity and reliability of the Turkish translation of Spreitzer's psychological empowerment scale in a culturally diverse environment.</p> <p>Methods</p> <p>The scale contains four dimensions over 12 statements. Data were gathered from 260 nurses and 161 physicians. The dimensionality of the scale was evaluated by exploratory factor analyses. To investigate the multidimensional nature of the empowerment construct and the validity of the scale, first- and second-order confirmatory factor analysis was conducted. Furthermore, Cronbach alpha coefficients were assessed to investigate reliability.</p> <p>Results</p> <p>Exploratory factor analyses revealed that four factors in both solutions. The first- and second-order factor analysis indicated an acceptable fit between the data and the theoretical model for nurses and physicians. Cronbach alpha coefficients varied between 0.81-0.94 for both groups, which may be considered satisfactory.</p> <p>Conclusions</p> <p>The analyses indicated that the psychometric properties of the Turkish version of the scale can be considered satisfactory.</p

Severe Neuro-COVID is associated with peripheral immune signatures, autoimmunity and neurodegeneration: a prospective cross-sectional study

Growing evidence links COVID-19 with acute and long-term neurological dysfunction. However, the pathophysiological mechanisms resulting in central nervous system involvement remain unclear, posing both diagnostic and therapeutic challenges. Here we show outcomes of a cross-sectional clinical study (NCT04472013) including clinical and imaging data and corresponding multidimensional characterization of immune mediators in the cerebrospinal fluid (CSF) and plasma of patients belonging to different Neuro-COVID severity classes. The most prominent signs of severe Neuro-COVID are blood-brain barrier (BBB) impairment, elevated microglia activation markers and a polyclonal B cell response targeting self-antigens and non-self-antigens. COVID-19 patients show decreased regional brain volumes associating with specific CSF parameters, however, COVID-19 patients characterized by plasma cytokine storm are presenting with a non-inflammatory CSF profile. Post-acute COVID-19 syndrome strongly associates with a distinctive set of CSF and plasma mediators. Collectively, we identify several potentially actionable targets to prevent or intervene with the neurological consequences of SARS-CoV-2 infection

Analysis of in vitro bioactivity data extracted from drug discovery literature and patents: Ranking 1654 human protein targets by assayed compounds and molecular scaffolds

<p>Abstract</p> <p>Background</p> <p>Since the classic Hopkins and Groom druggable genome review in 2002, there have been a number of publications updating both the hypothetical and successful human drug target statistics. However, listings of research targets that define the area between these two extremes are sparse because of the challenges of collating published information at the necessary scale. We have addressed this by interrogating databases, populated by expert curation, of bioactivity data extracted from patents and journal papers over the last 30 years.</p> <p>Results</p> <p>From a subset of just over 27,000 documents we have extracted a set of compound-to-target relationships for biochemical <it>in vitro </it>binding-type assay data for 1,736 human proteins and 1,654 gene identifiers. These are linked to 1,671,951 compound records derived from 823,179 unique chemical structures. The distribution showed a compounds-per-target average of 964 with a maximum of 42,869 (Factor Xa). The list includes non-targets, failed targets and cross-screening targets. The top-278 most actively pursued targets cover 90% of the compounds. We further investigated target ranking by determining the number of molecular frameworks and scaffolds. These were compared to the compound counts as alternative measures of chemical diversity on a per-target basis.</p> <p>Conclusions</p> <p>The compounds-per-protein listing generated in this work (provided as a supplementary file) represents the major proportion of the human drug target landscape defined by published data. We supplemented the simple ranking by the number of compounds assayed with additional rankings by molecular topology. These showed significant differences and provide complementary assessments of chemical tractability.</p

Impact of familial risk factors on management and survival of early-onset breast cancer: a population-based study

This population-based study evaluates the impact of a strong family history of breast cancer on management and survival of women with early-onset disease. We identified all breast cancer patients ⩽50 years, recorded between 1990 and 2001 at the Geneva familial breast cancer registry. We compared patients at high familial risk and low familial risk in terms of tumour characteristics, method of detection, treatment, survival and breast cancer mortality risk. Compared to patients at low familial risk (n=575), those at high familial risk (n=58) received significantly more often systemic therapy, especially for node-negative or receptor-positive disease. Five-year disease-specific survival rates of patients at high vs low familial risk were 86 and 90%, respectively. After adjustment, there was no difference in breast cancer mortality in general. A strong family history nonsignificantly increased breast cancer mortality in patients ⩽40 years (adjusted hazard ratio (HR) 4.0, 95% CI 0.8–19.7) and in patients treated without chemotherapy (adjusted HR 2.7, 95% CI 0.6–12.5). A strong family history of breast cancer is associated with an increased use of systemic therapy in early-onset patients. Although a strong family history does not seem to affect survival in general, it may impair survival of very young patients and patients treated without adjuvant chemotherapy. Owing to the limited number of patients in this study, these results should be used only to generate hypotheses