The Muonium Atom as a Probe of Physics beyond the Standard Model

The observed interactions between particles are not fully explained in the successful theoretical description of the standard model to date. Due to the close confinement of the bound state muonium ($M = \mu^+ e^-$) can be used as an ideal probe of quantum electrodynamics and weak interaction and also for a search for additional interactions between leptons. Of special interest is the lepton number violating process of sponteanous conversion of muonium to antimuonium.Comment: 15 pages,6 figure

Baryon polarization in low-energy unpolarized meson-baryon scattering

We compute the polarization of the final-state baryon, in its rest frame, in low-energy meson--baryon scattering with unpolarized initial state, in Unitarized BChPT. Free parameters are determined by fitting total and differential cross-section data (and spin-asymmetry or polarization data if available) for $pK^-$, $pK^+$ and $p\pi^+$ scattering. We also compare our results with those of leading-order BChPT

Prospects for e+e- physics at Frascati between the phi and the psi

We present a detailed study, done in the framework of the INFN 2006 Roadmap, of the prospects for e+e- physics at the Frascati National Laboratories. The physics case for an e+e- collider running at high luminosity at the phi resonance energy and also reaching a maximum center of mass energy of 2.5 GeV is discussed, together with the specific aspects of a very high luminosity tau-charm factory. Subjects connected to Kaon decay physics are not discussed here, being part of another INFN Roadmap working group. The significance of the project and the impact on INFN are also discussed. All the documentation related to the activities of the working group can be found in http://www.roma1.infn.it/people/bini/roadmap.html.Comment: INFN Roadmap Report: 86 pages, 25 figures, 9 table

Clustering identifies endotypes of traumatic brain injury in an intensive care cohort: a CENTER-TBI study

Background While the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classification of traumatic brain injury (TBI) as ‘mild’, ‘moderate’ or ‘severe’ based on this fails to capture enormous heterogeneity in pathophysiology and treatment response. We hypothesized that data-driven characterization of TBI could identify distinct endotypes and give mechanistic insights. Methods We developed an unsupervised statistical clustering model based on a mixture of probabilistic graphs for presentation (< 24 h) demographic, clinical, physiological, laboratory and imaging data to identify subgroups of TBI patients admitted to the intensive care unit in the CENTER-TBI dataset (N = 1,728). A cluster similarity index was used for robust determination of optimal cluster number. Mutual information was used to quantify feature importance and for cluster interpretation. Results Six stable endotypes were identified with distinct GCS and composite systemic metabolic stress profiles, distinguished by GCS, blood lactate, oxygen saturation, serum creatinine, glucose, base excess, pH, arterial partial pressure of carbon dioxide, and body temperature. Notably, a cluster with ‘moderate’ TBI (by traditional classification) and deranged metabolic profile, had a worse outcome than a cluster with ‘severe’ GCS and a normal metabolic profile. Addition of cluster labels significantly improved the prognostic precision of the IMPACT (International Mission for Prognosis and Analysis of Clinical trials in TBI) extended model, for prediction of both unfavourable outcome and mortality (both p < 0.001). Conclusions Six stable and clinically distinct TBI endotypes were identified by probabilistic unsupervised clustering. In addition to presenting neurology, a profile of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refining current TBI classifications with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care

Serum metabolome associated with severity of acute traumatic brain injury

Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain

Rehabilitation and outcomes after complicated vs uncomplicated mild TBI: results from the CENTER-TBI study

Background: Despite existing guidelines for managing mild traumatic brain injury (mTBI), evidence-based treatments are still scarce and large-scale studies on the provision and impact of specific rehabilitation services are needed. This study aimed to describe the provision of rehabilitation to patients after complicated and uncomplicated mTBI and investigate factors associated with functional outcome, symptom burden, and TBI-specific health-related quality of life (HRQOL) up to six months after injury. Methods: Patients (n = 1379) with mTBI from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study who reported whether they received rehabilitation services during the first six months post-injury and who participated in outcome assessments were included. Functional outcome was measured with the Glasgow Outcome Scale – Extended (GOSE), symptom burden with the Rivermead Post Concussion Symptoms Questionnaire (RPQ), and HRQOL with the Quality of Life after Brain Injury – Overall Scale (QOLIBRI-OS). We examined whether transition of care (TOC) pathways, receiving rehabilitation services, sociodemographic (incl. geographic), premorbid, and injury-related factors were associated with outcomes using regression models. For easy comparison, we estimated ordinal regression models for all outcomes where the scores were classified based on quantiles. Results: Overall, 43% of patients with complicated and 20% with uncomplicated mTBI reported receiving rehabilitation services, primarily in physical and cognitive domains. Patients with complicated mTBI had lower functional level, higher symptom burden, and lower HRQOL compared to uncomplicated mTBI. Rehabilitation services at three or six months and a higher number of TOC were associated with unfavorable outcomes in all models, in addition to pre-morbid psychiatric problems. Being male and having more than 13 years of education was associated with more favorable outcomes. Sustaining major trauma was associated with unfavorable GOSE outcome, whereas living in Southern and Eastern European regions was associated with lower HRQOL. Conclusions: Patients with complicated mTBI reported more unfavorable outcomes and received rehabilitation services more frequently. Receiving rehabilitation services and higher number of care transitions were indicators of injury severity and associated with unfavorable outcomes. The findings should be interpreted carefully and validated in future studies as we applied a novel analytic approach. Trial registration: ClinicalTrials.gov NCT02210221

The growth of the working age population : differences between rural and urban regions across Europe

Differences in the growth of the working age population are affected by the direction and size of migration flows, cohort turnover (the balance between the inflow of young people and the outflow of older people) and mortality. This paper aims to analyse differences in the effects of migration and cohort turnover on changes in the size of the working age population between rural and urban regions on the basis of demographic data for NUTS 2 regions. For this purpose we develop a rural‐urban classification on the basis of the classification for NUTS 3 regions published by Eurostat