Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe

Isomeric specific analysis of hydroxyeicosatetraenoic acid in blood samples from obese patients with non-alcoholic and alcoholic steatohepatitis

The aim of the study was to perform isomeric analysis of hydroxyeicosatetraenoic acid (HETE) in blood samples from obese patients with non-alcoholic (NASH) and alcoholic (ASH) steatohepatitis. Sixty nine obese patients with liver steatosis according to abdominal US data and chronic ALT elevation were assign into two groups according to the evaluation of alcohol consumption by GAGE and AUDIT questionnaires: NASH - 39 patients and ASH - 30 patients. The identification and quantification of 5(S)-hydroxyeicosatetraenoic acid (5-HETE), 15-HETE and also non-enzymatic oxidation product 11-HETE in blood plasma were carried out by HPLC-MS-TOF with using 2-hydroxyoctanoic acid as internal standard. The position of hydroxyl group in HETE was elucidated by HPLC-MS/MS. The MS/MS transitions were for 15-HETE m/z 319 → m/z 219; for 11-HETE m/z 319 →m/z 167; for 5-HETE m/z 319→m/z 115. Patients ' body composition was evaluated by bioelectrical impedance, resting energy expenditures (REE) were assessed by indirect calorimetry and nutrition pattern was examined by food frequency questionnaire. Mean age, BMI and ALT serum level were similar in patients from ASH and NASH groups. Blood plasma 8+12-HETE concentration was also similar in both groups of patients, but concentration of 15-HETE (21,6±20,2 vs 11,9±13,7 μg/ml,p=0,02) and 11-HETE (20,8±21,3 vs 11,2±12,9 μg/ml,p=0,03) was significantly higher in NASH patients. ASH patients demonstrated higher lean body mass (68,1±10,6 vs 57,9±9,8 kg, p<0,001) and muscle mass (39,3±6,1 vs 33,2±6,8 kg, p<0,04) and higher rate of protein oxidation (98,5±31 vs 76,2±21,1 g/day,p=0,02) recalculated from REE. There were no differences found in blood lipids content as well as in consumption of total dietary fat, however, there was a trend to difference in saturated/unsaturated fatty acids ratio between groups (2,3±0,2 in NASH and 1,4±0,3 in ASH patients). In conclusion, the rate of production of eicosatetraenoic acid metabolites by lipoxygenase pathway is different in NASH and ASH overweight patients. It means that possibly different mechanisms are responsible for formation of potentially toxic fatty acids metabolites in these two types of patients. It seems likely that differences in fatty acids consumption pattern are related to this metabolic pathway

Allergic Rhinitis and its Impact on Asthma (ARIA) Phase 4 (2018): Change management in allergic rhinitis and asthma multimorbidity using mobile technology

Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline by using the best approach to integrated care pathways using mobile technology in patients with allergic rhinitis (AR) and asthma multimorbidity. The proposed next phase of ARIA is change management, with the aim of providing an active and healthy life to patients with rhinitis and to those with asthma multimorbidity across the lifecycle irrespective of their sex or socioeconomic status to reduce health and social inequities incurred by the disease. ARIA has followed the 8-step model of Kotter to assess and implement the effect of rhinitis on asthma multimorbidity and to propose multimorbid guidelines. A second change management strategy is proposed by ARIA Phase 4 to increase self-medication and shared decision making in rhinitis and asthma multimorbidity. An innovation of ARIA has been the development and validation of information technology evidence-based tools (Mobile Airways Sentinel Network [MASK]) that can inform patient decisions on the basis of a self-care plan proposed by the health care professional. © 2018 American Academy of Allergy, Asthma &amp; Immunolog