Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in ...large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level.
A study on cosmic muons has been performed for the two identical near and far neutrino detectors of the Double Chooz experiment, placed at ∼120 and ∼300 m.w.e. underground respectively, including the ...corresponding simulations using the MUSIC simulation package. This characterization has allowed us to measure the muon flux reaching both detectors to be (3.64 ± 0.04) × 10{sup −4} cm{sup −2}s{sup −1} for the near detector and (7.00 ± 0.05) × 10{sup −5} cm{sup −2}s{sup −1} for the far one. The seasonal modulation of the signal has also been studied observing a positive correlation with the atmospheric temperature, leading to an effective temperature coefficient of α {sub T} = 0.212 ± 0.024 and 0.355 ± 0.019 for the near and far detectors respectively. These measurements, in good agreement with expectations based on theoretical models, represent one of the first measurements of this coefficient in shallow depth installations.
We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a ...pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient's risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients.
We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date.
Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations.
This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of ...patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.
Proliferation of Leishmania infantum depends on exogenous inorganic phosphate (P(i)) but little is known about energy metabolism and transport of P(i) across the plasma membrane in Leishmania sp.
We ...investigated the kinetics of 32P(i) transport, the influence of H+ and K+ ionophores and inhibitors, and expression of the genes for the Na+:P(i) and H+:P(i) cotransporters.
The proton ionophore FCCP, bafilomycin A1 (vacuolar ATPase inhibitor), nigericin (K+ ionophore) and SCH28080 (an inhibitor of H+, K(+)-ATPase) all inhibited the transport of P(i). This transport showed Michaelis-Menten kinetics with K0.5 and V(max) values of 0.016 +/- 0.002 mM and 564.9 +/- 18.06 pmol x h(-1) x 10(-7) cells, respectively. These values classify the P(i) transporter of L. infantum among the high-affinity transporters, a group that includes Pho84 of Saccharomyces cerevisiae. Two sequences were identified in the L. infantum genome that code for phosphate transporters. However, transcription of the PHO84 transporter was 10-fold higher than the PHO89 transporter in this parasite. Accordingly, P(i) transport and LiPho84 gene expression were modulated by environmental P(i) variations.
These findings confirm the presence of a P(i) transporter in L. infantum, similar to PHO84 in S. cerevisiae, that contributes to the acquisition of inorganic phosphate and could be involved in growth and survival of the promastigote forms of L. infantum.
This work provides the first description of a PHO84-like P(i) transporter in a Trypanosomatide parasite of the genus Leishmania, responsible for many infections worldwide.
At least three B cell subsets, B-1a, B-1b and B-2 are present circulating peripherally in the mouse. In these animals, B-1 cells constitute a minor fraction of B cells in spleen and are absent in ...lymph nodes although they represent the main B cell population in peritoneal and pleural cavities. Currently these cells are identified by a surface phenotypic repertoire; they express Mac-1, IgM(high), and B220(low). B-1a cells express CDS. The aim of this work emerged from the fact that the morphology of B-1 cells is not fully characterized. Here we identified B-1 cells using colloidal gold immunocytochemical assays and purified B-1 cells from supernatants of adherent peritoneal cell cultures by a magnetic bead technique. These techniques lead us to demonstrate that, in mice, either B-1a or B-1b cells have a unique morphology distinct from that of B-2 cells.
A
bstract
The Double Chooz collaboration presents a measurement of the neutrino mixing angle
θ
13
using reactor
ν
e
¯
observed via the inverse beta decay reaction in which the neutron is captured on ...hydrogen. This measurement is based on 462.72 live days data, approximately twice as much data as in the previous such analysis, collected with a detector positioned at an average distance of 1050 m from two reactor cores. Several novel techniques have been developed to achieve significant reductions of the backgrounds and systematic uncertainties. Accidental coincidences, the dominant background in this analysis, are suppressed by more than an order of magnitude with respect to our previous publication by a multi-variate analysis. These improvements demonstrate the capability of precise measurement of reactor
ν
e
¯
without gadolinium loading. Spectral distortions from the
ν
e
¯
reactor flux predictions previously reported with the neutron capture on gadolinium events are confirmed in the independent data sample presented here. A value of sin
2
2
θ
13
= 0.095
− 0.039
+ 0.038
(stat+syst) is obtained from a fit to the observed event rate as a function of the reactor power, a method insensitive to the energy spectrum shape. A simultaneous fit of the hydrogen capture events and of the gadolinium capture events yields a measurement of sin
2
2
θ
13
= 0
.
088 ± 0
.
033(stat+syst).
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