Semiautomatic robust regression clustering of international trade data

The purpose of this paper is to show in regression clustering how to choose the most relevant solutions, analyze their stability, and provide information about best combinations of optimal number of groups, restriction factor among the error variance across groups and level of trimming. The procedure is based on two steps. First we generalize the information criteria of constrained robust multivariate clustering to the case of clustering weighted models. Differently from the traditional approaches which are based on the choice of the best solution found minimizing an information criterion (i.e. BIC), we concentrate our attention on the so called optimal stable solutions. In the second step, using the monitoring approach, we select the best value of the trimming factor. Finally, we validate the solution using a confirmatory forward search approach. A motivating example based on a novel dataset concerning the European Union trade of face masks shows the limitations of the current existing procedures. The suggested approach is initially applied to a set of well known datasets in the literature of robust regression clustering. Then, we focus our attention on a set of international trade datasets and we provide a novel informative way of updating the subset in the random start approach. The Supplementary material, in the spirit of the Special Issue, deepens the analysis of trade data and compares the suggested approach with the existing ones available in the literature

Combined lymphocyte/monocyte count, D-dimer and iron status predict COVID-19 course and outcome in a long-term care facility

Background: The Sars-CoV-2 can cause severe pneumonia with multiorgan disease; thus, the identification of clinical and laboratory predictors of the progression towards severe and fatal forms of this illness is needed. Here, we retrospectively evaluated and integrated laboratory parameters of 45 elderly subjects from a long-term care facility with Sars-CoV-2 outbreak and spread, to identify potential common patterns of systemic response able to better stratify patients’ clinical course and outcome. Methods: Baseline white blood cells, granulocytes’, lymphocytes’, and platelets’ counts, hemoglobin, total iron, ferritin, D-dimer, and interleukin-6 concentration were used to generate a principal component analysis. Statistical analysis was performed by using R statistical package version 4.0. Results: We identified 3 laboratory patterns of response, renamed as low-risk, intermediate-risk, and high-risk, strongly associated with patients’ survival (p < 0.01). D-dimer, iron status, lymphocyte/monocyte count represented the main markers discriminating high- and low-risk groups. Patients belonging to the high-risk group presented a significantly longer time to ferritin decrease (p: 0.047). Iron-to-ferritin-ratio (IFR) significantly segregated recovered and dead patients in the intermediate-risk group (p: 0.012). Conclusions: Our data suggest that a combination of few laboratory parameters, i.e. iron status, D-dimer and lymphocyte/monocyte count at admission and during the hospital stay, can predict clinical progression in COVID-19

The transplant iron score as a predictor of stem cell transplant survival

Recent studies have suggested that the presence of iron overload prior to stem cell transplantation is associated with decreased survival. Within these studies, the criteria used to define iron overload have varied considerably. Given the lack of consensus regarding the definition of iron overload in the transplant setting, we sought to methodically examine iron status among transplant patients. We studied 78 consecutive patients at risk for transfusion-related iron overload (diagnoses included AML, ALL, MDS, and aplastic anemia) who received either autologous or allogeneic stem cell transplant. Multiple measures of iron status were collected prior to transplantation and examined for their association with survival. Using this data, three potentially prognostic iron measures were identified and incorporated into a rational and unified scoring system. The resulting Transplant Iron Score assigns a point for each of the following variables: (1) greater than 25 red cell units transfused prior to transplantation; (2) serum ferritin > 1000 ng/ml; and (3) a semi-quantitative bone marrow iron stain of 6+. In our cohort, the score (range 0 to 3) was more closely associated with survival than any available single iron parameter. In multivariate analysis, we observed an independent effect of iron overload on transplant survival (p = 0.01) primarily attributable to an increase in early treatment-related deaths (p = 0.02) and lethal infections. In subgroup analysis, the predictive power of the iron score was most pronounced among allogeneic transplant patients, where a high score (≥ 2) was associated with a 50% absolute decrease in survival at one year. In summary, our results lend further credence to the notion that iron overload prior to transplant is detrimental and suggest iron overload may predispose to a higher rate of lethal infections

A narrow band neutrino beam with high precision flux measurements

The ENUBET facility is a proposed narrow band neutrino beam where lepton production is monitored at single particle level in the instrumented decay tunnel. This facility addresses simultaneously the two most important challenges for the next generation of cross section experiments: a superior control of the flux and flavor composition at source and a high level of tunability and precision in the selection of the energy of the outcoming neutrinos. We report here the latest results in the development and test of the instrumentation for the decay tunnel. Special emphasis is given to irradiation tests of the photo-sensors performed at INFN-LNL and CERN in 2017 and to the first application of polysiloxane-based scintillators in high energy physics.Comment: Poster presented at NuPhys2017 (London, 20-22 December 2017). 5 pages, 2 figure

The ENUBET Beamline

The ENUBET ERC project (2016-2021) is studying a narrow band neutrino beam where lepton production can be monitored at single particle level in an instrumented decay tunnel. This would allow to measure $\nu_{\mu}$ and $\nu_{e}$ cross sections with a precision improved by about one order of magnitude compared to present results. In this proceeding we describe a first realistic design of the hadron beamline based on a dipole coupled to a pair of quadrupole triplets along with the optimisation guidelines and the results of a simulation based on G4beamline. A static focusing design, though less efficient than a horn-based solution, results several times more efficient than originally expected. It works with slow proton extractions reducing drastically pile-up effects in the decay tunnel and it paves the way towards a time-tagged neutrino beam. On the other hand a horn-based transferline would ensure higher yields at the tunnel entrance. The first studies conducted at CERN to implement the synchronization between a few ms proton extraction and a horn pulse of 2-10 ms are also described.Comment: Poster presented at NuPhys2018 (London 19-21 December 2018). 4 pages, 3 figure

evaluation of liver fibrosis concordance analysis between noninvasive scores apri and fib 4 evolution and predictors in a cohort of hiv infected patients without hepatitis c and b infection

Background. There is lack of data on the incidence of liver fibrosis (LF) progression in patients with human immunodeficiency virus (HIV) monoinfection and risk factors for LF. Methods. We performed an observational prospective study in a cohort of HIV-infected patients who had initiated highly active antiretroviral therapy (HAART). FIB-4 and aspartate aminotransferase (AST)-to-platelet ratio index (APRI) were assessed. The concordance between the 2 scores was assessed by weighted kappa coefficient. Kaplan-Meier analysis was used to estimate the incidence of LF. Cox regression analysis was used to assess the predictors of transition. Results. A total of 1112 patients were observed for a mean of 2249 days of follow-up. The concordance between FIB-4 and APRI was moderate (kappa = .573). The incidence of transition to higher FIB-4 classes was 0.064 (95% confidence interval [CI], 0.056―0.072) per person-year of follow-up (PYFU), whereas the incidence of transition to higher APRI classes was 0.099 (95% CI, 0.089-0.110) per PYFU. The incidence of transition to FIB-4 >3.25 was 0.013 per PYFU (95% CI, 0.010-0.017) and 0.018 per PYFU (95% CI, 0.014―0.022) for APRI >1.5. In multivariate analyses, for transition to higher classes, HIV RNA level 3.25 and APRI> 1.5 as study outcomes. Conclusions. Overall, our results suggest a possible benefit associated with earlier HAART initiation, provided that the effectiveness of HAART is sustained and treatment with DDX is avoided

Primate rhythmic categories analyzed on an individual basis

Rhythm is a fundamental feature characterizing communicative displays, and recent studies showed that primate songs encompass categorical rhythms falling on small integer ratios observed in humans. We individually assessed the presence and sexual dimorphism of rhythmic categories, analyzing songs emitted by 39 wild indris. Considering the intervals between the units given during each song, we extracted 13556 interval ratios and found three peaks (at around 0.33, 0.47, and 0.70). Two peaks indicated rhythmic categories corresponding to small integer ratios (1:1, 2:1). All individuals showed a peak at 0.70, and most showed those at 0.47 and 0.33. In addition, we found sex differences in the peak at 0.47 only, with males showing lower values than females. This work investigates the presence of individual rhythmic categories in a non-human species; further research may highlight the significance of rhythmicity and untie selective pressures that guided its evolution across species, including humans