Illness cognitions in head and neck squamous cell carcinoma: predicting quality of life outcome

Goals of work: This paper presents an observational study of the longitudinal effects of cancer treatment on quality of life (QoL) in patients treated for head and neck squamous cell carcinoma (HNSCC), and evaluated the contribution of patients' baseline illness cognitions to the prediction of QoL 2 years after diagnosis. Patients and methods: One hundred seventy-seven patients eligible for primary treatment for HNSCC completed the Illness Perception Questionnaire-Revised at baseline and the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire-30 at baseline, at 1-year and 2-year follow-ups. Main results Compared to baseline, patients reported better emotional functioning at both follow-ups (p<0.001), worse social functioning at 12 months (p<0.05), and better global health

Multiple effects of toxins isolated from Crotalus durissus terrificus on the hepatitis C virus life cycle

Hepatitis C virus (HCV) is one of the main causes of liver disease and transplantation worldwide. Current therapy is expensive, presents additional side effects and viral resistance has been described. Therefore, studies for developing more efficient antivirals against HCV are needed. Compounds isolated from animal venoms have shown antiviral activity against some viruses such as Dengue virus, Yellow fever virus and Measles virus. In this study, we evaluated the effect of the complex crotoxin (CX) and its subunits crotapotin (CP) and phospholipase A2 (PLA2-CB) isolated from the venom of Crotalus durissus terrificus on HCV life cycle. Huh 7.5 cells were infected with HCVcc JFH-1 strain in the presence or absence of these toxins and virus was titrated by focus formation units assay or by qPCR. Toxins were added to the cells at different time points depending on the stage of virus life cycle to be evaluated. The results showed that treatment with PLA2-CB inhibited HCV entry and replication but no effect on HCV release was observed. CX reduced virus entry and release but not replication. By treating cells with CP, an antiviral effect was observed on HCV release, the only stage inhibited by this compound. Our data demonstrated the multiple antiviral effects of toxins from animal venoms on HCV life cycle

Development of methods for the preparation of radiopure ⁸²Se sources for the SuperNEMO neutrinoless double-beta decay experiment

A radiochemical method for producing 82Se sources with an ultra-low level of contamination of natural radionuclides (40K, decay products of 232Th and 238U) has been developed based on cation-exchange chromatographic purification with reverse removal of impurities. It includes chromatographic separation (purification), reduction, conditioning (which includes decantation, centrifugation, washing, grinding, and drying), and 82Se foil production. The conditioning stage, during which highly dispersed elemental selenium is obtained by the reduction of purified selenious acid (H2SeO3) with sulfur dioxide (SO2) represents the crucial step in the preparation of radiopure 82Se samples. The natural selenium (600 g) was first produced in this procedure in order to refine the method. The technique developed was then used to produce 2.5 kg of radiopure enriched selenium (82Se). The produced 82Se samples were wrapped in polyethylene (12 μm thick) and radionuclides present in the sample were analyzed with the BiPo-3 detector. The radiopurity of the plastic materials (chromatographic column material and polypropylene chemical vessels), which were used at all stages, was determined by instrumental neutron activation analysis. The radiopurity of the 82Se foils was checked by measurements with the BiPo-3 spectrometer, which confirmed the high purity of the final product. The measured contamination level for 208Tl was 8-54 μBq/kg, and for 214Bi the detection limit of 600 μBq/kg has been reached.</p

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation