On different qq-systems in nonextensive thermostatistics

It is known that the nonextensive statistics was originally formulated for the systems composed of subsystems having same $q$. In this paper, the existence of composite system with different $q$ subsystems is investigated by fitting the power law degree distribution of air networks with $q$-exponential distribution. Then a possible extension the nonextensive statistics to different $q$ systems is provided on the basis of an entropy nonadditivity rule and an unnormalized expectation of energy.Comment: 17 pages, 4 figures, will be published in Euro. Phys. J. B (2006

Proceedings from the 2\u3csup\u3end\u3c/sup\u3eNext Gen Therapies for Systemic Juvenile Idiopathic Arthritis and Macrophage Activation Syndrome symposium held on October 3-4, 2019

© 2020 The Author(s). For reasons poorly understood, and despite the availability of biological medications blocking IL-1 and IL-6 that have markedly improved overall disease control, children with Systemic Juvenile Idiopathic Arthritis (SJIA) are now increasingly diagnosed with life-threatening chronic complications, including hepatitis and lung disease (SJIA-LD). On October 3-4, 2019, a two-day meeting, NextGen Therapies for Systemic Juvenile Idiopathic Arthritis (SJIA) & macrophage activation syndrome (MAS) organized by the Systemic JIA Foundation (www.systemicjia.org/) in Washington, DC brought together scientists, clinicians, parents and FDA representatives with the objectives (1) to integrate clinical and research findings in MAS and SJIA-LD, and (2) to develop a shared understanding of this seemingly new pulmonary complication of SJIA. The current manuscript summarizes discussions and conclusions of the meeting

A prospective investigation of interleukin-8 levels in pediatric acute respiratory failure and acute respiratory distress syndrome

© 2019 The Author(s). Background: The association of plasma interleukin-8 (IL-8), or IL-8 genetic variants, with pediatric acute respiratory distress syndrome (PARDS) in children with acute respiratory failure at risk for PARDS has not been examined. The purpose of this study was to examine the association of early and sequential measurement of plasma IL-8 and/or its genetic variants with development of PARDS and other clinical outcomes in mechanically ventilated children with acute respiratory failure. Methods: This was a prospective cohort study of children 2 weeks to 17 years of age with acute airways and/or parenchymal lung disease done in 22 pediatric intensive care units participating in the multi-center clinical trial, Randomized Evaluation of Sedation Titration for Respiratory Failure (RESTORE). Plasma IL-8 levels were measured within 24 h of consent and 24 and 48 h later. DNA was purified from whole blood, and IL-8 single nucleotide polymorphisms, rs4073, rs2227306, and rs2227307, were genotyped. Results: Five hundred forty-nine patients were enrolled; 480 had blood sampling. Plasma IL-8 levels ranged widely from 4 to 7373 pg/mL. Highest IL-8 levels were observed on the day of intubation with subsequent tapering. Levels of IL-8 varied significantly across primary diagnoses with the highest levels occurring in patients with sepsis and the lowest levels in those with asthma. Plasma IL-8 was strongly correlated with oxygenation defect and severity of illness. IL-8 was consistently higher in PARDS patients compared to those without PARDS; levels were 4-12 fold higher in non-survivors compared to survivors. On multivariable analysis, IL-8 was independently associated with death, duration of mechanical ventilation, and PICU length of stay on all days measured, but was not associated with PARDS development. There was no association between the IL-8 single nucleotide polymorphisms, rs4073, rs2227306, and rs2227307, and PARDS development or plasma IL-8 level. Conclusions: When measured sequentially, plasma IL-8 was robustly associated with multiple, relevant clinical outcomes including mortality, but was not associated with PARDS development. The wide range of plasma IL-8 levels exhibited in this cohort suggests that further study into the heterogeneity of this patient population and its impact on individual responses to PARDS treatment is warranted

Elliptic flow of charged particles in Pb-Pb collisions at 2.76 TeV

We report the first measurement of charged particle elliptic flow in Pb-Pb collisions at 2.76 TeV with the ALICE detector at the CERN Large Hadron Collider. The measurement is performed in the central pseudorapidity region (|$\eta$|<0.8) and transverse momentum range 0.2< $p_{\rm T}$< 5.0 GeV/$c$. The elliptic flow signal v$_2$, measured using the 4-particle correlation method, averaged over transverse momentum and pseudorapidity is 0.087 $\pm$ 0.002 (stat) $\pm$ 0.004 (syst) in the 40-50% centrality class. The differential elliptic flow v$_2(p_{\rm T})$ reaches a maximum of 0.2 near $p_{\rm T}$ = 3 GeV/$c$. Compared to RHIC Au-Au collisions at 200 GeV, the elliptic flow increases by about 30%. Some hydrodynamic model predictions which include viscous corrections are in agreement with the observed increase.Comment: 10 pages, 4 captioned figures, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/389

Strange particle production in proton-proton collisions at s=0.9\sqrt{s}=0.9 TeV with ALICE at the LHC

The production of mesons containing strange quarks (K$^0_s$, $\phi$) and both singly and doubly strange baryons ($\Lambda$, Anti-$\Lambda$, and $\Xi$+Anti-$\Xi$) are measured at central rapidity in pp collisions at $\sqrt{s}$ = 0.9 TeV with the ALICE experiment at the LHC. The results are obtained from the analysis of about 250 k minimum bias events recorded in 2009. Measurements of yields (dN/dy) and transverse momentum spectra at central rapidities for inelastic pp collisions are presented. For mesons, we report yields () of 0.184 $\pm$ 0.002 stat. $\pm$ 0.006 syst. for K$^0_s$ and 0.021 $\pm$ 0.004 stat. $\pm$ 0.003 syst. for $\phi$. For baryons, we find = 0.048 $\pm$ 0.001 stat. $\pm$ 0.004 syst. for $\Lambda$, 0.047 $\pm$ 0.002 stat. $\pm$ 0.005 syst. for Anti-$\Lambda$ and 0.0101 $\pm$ 0.0020 stat. $\pm$ 0.0009 syst. for $\Xi$+Anti-$\Xi$. The results are also compared with predictions for identified particle spectra from QCD-inspired models and provide a baseline for comparisons with both future pp measurements at higher energies and heavy-ion collisions.Comment: 33 pages, 21 captioned figures, 10 tables, authors from page 28, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/387

Big data from electronic health records for early and late translational cardiovascular research: challenges and potential.

AIMS: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research. METHODS AND RESULTS: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health. CONCLUSION: High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare