Reconstruction and control of a time-dependent two-electron wave packet

The concerted motion of two or more bound electrons governs atomic1 and molecular2,3 non-equilibrium processes including chemical reactions, and hence there is much interest in developing a detailed understanding of such electron dynamics in the quantum regime. However, there is no exact solution for the quantumthree-body problem, and as a result even the minimal system of two active electrons and a nucleus is analytically intractable4. This makes experimental measurements of the dynamics of two bound and correlated electrons, as found in the helium atom, an attractive prospect.However, although the motion of single active electrons and holes has been observed with attosecond time resolution5-7, comparable experiments on two-electron motion have so far remained out of reach. Here we showthat a correlated two-electron wave packet can be reconstructed froma 1.2-femtosecondquantumbeatamong low-lying doubly excited states in helium.The beat appears in attosecond transient-absorption spectra5,7-9 measured with unprecedentedly high spectral resolution and in the presence of an intensity-tunable visible laser field.Wetune the coupling10-12 between the two low-lying quantum states by adjusting the visible laser intensity, and use the Fano resonance as a phase-sensitive quantum interferometer13 to achieve coherent control of the two correlated electrons. Given the excellent agreement with large-scalequantum-mechanical calculations for thehelium atom, we anticipate thatmultidimensional spectroscopy experiments of the type we report here will provide benchmark data for testing fundamental few-body quantumdynamics theory in more complex systems. Theymight also provide a route to the site-specificmeasurement and control of metastable electronic transition states that are at the heart of fundamental chemical reactionsWe thank E. Lindroth for calculating the dipole moment (2p2|r|sp2,3+), and also A. Voitkiv, Z.-H. Loh, and R. Moshammer for helpful discussions. We acknowledge financial support by the Max-Planck Research Group Program of the Max-Planck Gesellschaft (MPG) and the European COST Action CM1204 XLIC. L. A. and F. M. acknowledge computer time from the CCC-UAM and Mare Nostrum supercomputer centers and financial support by the European Research Council under the ERC Advanced Grant no. 290853 XCHEM, the Ministerio de Economía y Competitividad projects FIS2010-15127, FIS2013-42002-R and ERA-Chemistry PIM2010EEC-00751, and the European grant MC-ITN CORIN

Modeling of Environmental Effects in Genome-Wide Association Studies Identifies SLC2A2 and HP as Novel Loci Influencing Serum Cholesterol Levels

Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWAS in order to identify novel loci affecting total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. The Swedish (SE) EUROSPAN cohort (NSE = 656) was screened for candidate genes and the non-Swedish (NS) EUROSPAN cohorts (NNS = 3,282) were used for replication. In total, 3 SNPs were associated in the Swedish sample and were replicated in the non-Swedish cohorts. While SNP rs1532624 was a replication of the previously published association between CETP and HDL cholesterol, the other two were novel findings. For the latter SNPs, the p-value for association was substantially improved by inclusion of environmental covariates: SNP rs5400 (pSE,unadjusted = 3.6×10−5, pSE,adjusted = 2.2×10−6, pNS,unadjusted = 0.047) in the SLC2A2 (Glucose transporter type 2) and rs2000999 (pSE,unadjusted = 1.1×10−3, pSE,adjusted = 3.8×10−4, pNS,unadjusted = 0.035) in the HP gene (Haptoglobin-related protein precursor). Both showed evidence of association with total cholesterol. These results demonstrate that inclusion of important environmental factors in the analysis model can reveal new genetic susceptibility loci

Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review

<p>Abstract</p> <p>Background</p> <p>The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations).</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes.</p> <p>Results</p> <p>Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported.</p> <p>Conclusions</p> <p>A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.</p

Computerized clinical decision support systems for drug prescribing and management: A decision-maker-researcher partnership systematic review

<p>Abstract</p> <p>Background</p> <p>Computerized clinical decision support systems (CCDSSs) for drug therapy management are designed to promote safe and effective medication use. Evidence documenting the effectiveness of CCDSSs for improving drug therapy is necessary for informed adoption decisions. The objective of this review was to systematically review randomized controlled trials assessing the effects of CCDSSs for drug therapy management on process of care and patient outcomes. We also sought to identify system and study characteristics that predicted benefit.</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We updated our earlier reviews (1998, 2005) by searching MEDLINE, EMBASE, EBM Reviews, Inspec, and other databases, and consulting reference lists through January 2010. Authors of 82% of included studies confirmed or supplemented extracted data. We included only randomized controlled trials that evaluated the effect on process of care or patient outcomes of a CCDSS for drug therapy management compared to care provided without a CCDSS. A study was considered to have a positive effect (<it>i.e.</it>, CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive.</p> <p>Results</p> <p>Sixty-five studies met our inclusion criteria, including 41 new studies since our previous review. Methodological quality was generally high and unchanged with time. CCDSSs improved process of care performance in 37 of the 59 studies assessing this type of outcome (64%, 57% of all studies). Twenty-nine trials assessed patient outcomes, of which six trials (21%, 9% of all trials) reported improvements.</p> <p>Conclusions</p> <p>CCDSSs inconsistently improved process of care measures and seldomly improved patient outcomes. Lack of clear patient benefit and lack of data on harms and costs preclude a recommendation to adopt CCDSSs for drug therapy management.</p

Imaging findings in craniofacial childhood rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is the commonest paediatric soft-tissue sarcoma constituting 3–5% of all malignancies in childhood. RMS has a predilection for the head and neck area and tumours in this location account for 40% of all childhood RMS cases. In this review we address the clinical and imaging presentations of craniofacial RMS, discuss the most appropriate imaging techniques, present characteristic imaging features and offer an overview of differential diagnostic considerations. Post-treatment changes will be briefly addressed

Recapitulation of tumor heterogeneity and molecular signatures in a 3D brain cancer model with decreased sensitivity to histone deacetylase inhibition

INTRODUCTION Physiologically relevant pre-clinical ex vivo models recapitulating CNS tumor micro-environmental complexity will aid development of biologically-targeted agents. We present comprehensive characterization of tumor aggregates generated using the 3D Rotary Cell Culture System (RCCS). METHODS CNS cancer cell lines were grown in conventional 2D cultures and the RCCS and comparison with a cohort of 53 pediatric high grade gliomas conducted by genome wide gene expression and microRNA arrays, coupled with immunohistochemistry, ex vivo magnetic resonance spectroscopy and drug sensitivity evaluation using the histone deacetylase inhibitor, Vorinostat. RESULTS Macroscopic RCCS aggregates recapitulated the heterogeneous morphology of brain tumors with a distinct proliferating rim, necrotic core and oxygen tension gradient. Gene expression and microRNA analyses revealed significant differences with 3D expression intermediate to 2D cultures and primary brain tumors. Metabolic profiling revealed differential profiles, with an increase in tumor specific metabolites in 3D. To evaluate the potential of the RCCS as a drug testing tool, we determined the efficacy of Vorinostat against aggregates of U87 and KNS42 glioblastoma cells. Both lines demonstrated markedly reduced sensitivity when assaying in 3D culture conditions compared to classical 2D drug screen approaches. CONCLUSIONS Our comprehensive characterization demonstrates that 3D RCCS culture of high grade brain tumor cells has profound effects on the genetic, epigenetic and metabolic profiles of cultured cells, with these cells residing as an intermediate phenotype between that of 2D cultures and primary tumors. There is a discrepancy between 2D culture and tumor molecular profiles, and RCCS partially re-capitulates tissue specific features, allowing drug testing in a more relevant ex vivo system

Differential Proteome Analysis of Bone Marrow Mesenchymal Stem Cells from Adolescent Idiopathic Scoliosis Patients

Adolescent idiopathic scoliosis (AIS) is a complex three-dimensional deformity of the spine. The cause and pathogenesis of scoliosis and the accompanying generalized osteopenia remain unclear despite decades of extensive research. In this study, we utilized two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) coupled with mass spectrometry (MS) to analyze the differential proteome of bone marrow mesenchymal stem cells (BM-MSCs) from AIS patients. In total, 41 significantly altered protein spots were detected, of which 34 spots were identified by MALDI-TOF/TOF analysis and found to represent 25 distinct gene products. Among these proteins, five related to bone growth and development, including pyruvate kinase M2, annexin A2, heat shock 27 kDa protein, γ-actin, and β-actin, were found to be dysregulated and therefore selected for further validation by Western blot analysis. At the protein level, our results supported the previous hypothesis that decreased osteogenic differentiation ability of MSCs is one of the mechanisms leading to osteopenia in AIS. In summary, we analyzed the differential BM-MSCs proteome of AIS patients for the first time, which may help to elucidate the underlying molecular mechanisms of bone loss in AIS and also increase understanding of the etiology and pathogenesis of AIS

Promotoras as Mental Health Practitioners in Primary Care: A Multi-Method Study of an Intervention to Address Contextual Sources of Depression

We assessed the role of promotoras—briefly trained community health workers—in depression care at community health centers. The intervention focused on four contextual sources of depression in underserved, low-income communities: underemployment, inadequate housing, food insecurity, and violence. A multi-method design included quantitative and ethnographic techniques to study predictors of depression and the intervention’s impact. After a structured training program, primary care practitioners (PCPs) and promotoras collaboratively followed a clinical algorithm in which PCPs prescribed medications and/or arranged consultations by mental health professionals and promotoras addressed the contextual sources of depression. Based on an intake interview with 464 randomly recruited patients, 120 patients with depression were randomized to enhanced care plus the promotora contextual intervention, or to enhanced care alone. All four contextual problems emerged as strong predictors of depression (chi square, p < .05); logistic regression revealed housing and food insecurity as the most important predictors (odds ratios both 2.40, p < .05). Unexpected challenges arose in the intervention’s implementation, involving infrastructure at the health centers, boundaries of the promotoras’ roles, and “turf” issues with medical assistants. In the quantitative assessment, the intervention did not lead to statistically significant improvements in depression (odds ratio 4.33, confidence interval overlapping 1). Ethnographic research demonstrated a predominantly positive response to the intervention among stakeholders, including patients, promotoras, PCPs, non-professional staff workers, administrators, and community advisory board members. Due to continuing unmet mental health needs, we favor further assessment of innovative roles for community health workers

Language in international business: a review and agenda for future research

A fast growing number of studies demonstrates that language diversity influences almost all management decisions in modern multinational corporations. Whereas no doubt remains about the practical importance of language, the empirical investigation and theoretical conceptualization of its complex and multifaceted effects still presents a substantial challenge. To summarize and evaluate the current state of the literature in a coherent picture informing future research, we systematically review 264 articles on language in international business. We scrutinize the geographic distributions of data, evaluate the field’s achievements to date in terms of theories and methodologies, and summarize core findings by individual, group, firm, and country levels of analysis. For each of these dimensions, we then put forward a future research agenda. We encourage scholars to transcend disciplinary boundaries and to draw on, integrate, and test a variety of theories from disciplines such as psychology, linguistics, and neuroscience to gain a more profound understanding of language in international business. We advocate more multi-level studies and cross-national research collaborations and suggest greater attention to potential new data sources and means of analysis

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging