Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Effectiveness of a patient-centered medical home model of primary care versus standard care on blood pressure outcomes among hypertensive patients

Patients with hypertension and other comorbidities have complex health care needs that are challenging to manage in primary care. However, there is strong evidence suggesting that patient-centered approaches in primary care are effective in managing complex multimorbidity. We aim to evaluate the effectiveness of a patient-centered medical home model called ‘WellNet’ versus that of standard care on blood pressure (BP) outcomes among hypertensive patients. We used a cohort study design with a comparison group and case-series design to assess the ‘between-group’ and ‘within-group’ effectiveness of the WellNet program delivered across six general practices in Sydney, Australia. The treatment group included 447 eligible patients who provided consent and who received general practitioner-led care with the integration of care coordinators. The comparison group included 5237 matched patients receiving usual care at four geographically comparable general practices. To assess changes over time, paired, and independent samples t-tests were used to determine significant differences. In addition, analysis of covariance (ANCOVA) was used to identify any significant differences after adjusting for potential covariates. The adjusted model showed significant reductions in systolic BP (−3.4 mmHg; 95% CI −5.1, −1.7; p value < 0.001) in the treatment group at follow-up. However, no significant mean change was observed in diastolic BP. The proportion of patients within the recommended range was found to be significantly higher in the treatment group than in the comparison group (13.6% versus 6.4%). WellNet patients experienced statistically significant and clinically meaningful improvement in BP during the follow-up. The findings of this study may be beneficial to both patients and providers in terms of improved health outcomes and delivery of care, respectively

Spotlight on measles in Italy: why outbreaks of a vaccine-preventable infection continue in the 21st century

Measles is a serious infectious disease that can lead to significant morbidity and mortality. Remarkable progress has been made through measles vaccination in reducing the number of people dying from measles. In the last years, concerns about the safety of vaccines have led to decline in immunization coverage rates and new outbreaks of measles in many European countries, including Italy. We believe that it is important to reinforce the message that measles vaccine is safe and highly effective through appropriate information campaigns and public awareness

Metabolomic biomarkers in mental disorders : bipolar disorder and schizophrenia

Psychiatric disorders are some of the most impairing human diseases. Among them, bipolar disorder and schizophrenia are the most common. Both have complicated diagnostics due to their phenotypic, biological, and genetic heterogeneity, unknown etiology, and the underlying biological pathways, and molecular mechanisms are still not completely understood. Given the multifactorial complexity of these disorders, identification and implementation of metabolic biomarkers would assist in their early detection and diagnosis and facilitate disease monitoring and treatment responses. To date, numerous studies have utilized metabolomics to better understand psychiatric disorders, and findings from these studies have begun to converge. In this chapter, we briefly describe some of the metabolomic biomarkers found in these two disorders111827129