150 research outputs found

    Effects of structured involvement of the primary care team versus standard care after a cancer diagnosis on patient satisfaction and healthcare use: the GRIP randomised controlled trial

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    Background: The growing number of cancer survivors and treatment possibilities call for more personalised and integrated cancer care. Primary care seems well positioned to support this. We aimed to assess the effects of structured follow-up of a primary care team after a cancer diagnosis. Methods: We performed a multicentre randomised controlled trial enrolling patients curatively treated for breast, lung, colorectal, gynaecologic cancer or melanoma. In addition to usual cancer care in the control group, patients randomized to intervention were offered a “Time Out consultation” (TOC) with the general practitioner (GP) after diagnosis, and subsequent follow-up during and after treatment by a home care oncology nurse (HON). Primary outcomes were patient satisfaction with care (questionnaire: EORTC-INPATSAT-32) and healthcare utilisation. Intention-to-treat linear mixed regression analyses were used for satisfaction with care and other continuous outcome variables. The difference in healthcare utilisation for categorical data was calculated with a Pearson Chi-Square or a Fisher exact test and count data (none versus any) with a log-binomial regression. Results: We included 154 patients (control n = 77, intervention n = 77) who were mostly female (75%), mainly diagnosed with breast cancer (51%), and had a mean age of 61 (SD ± 11.9) years. 81% of the intervention patients had a TOC and 68% had HON contact. Satisfaction with care was high (8 out of 10) in both study groups. At 3 months after treatment, GP satisfaction was significantly lower in the intervention group on 3 of 6 subscales, i.e., quality (− 14.2 (95%CI -27.0;-1.3)), availability (− 15,9 (− 29.1;-2.6)) and information provision (− 15.2 (− 29.1;-1.4)). Patients in the intervention group visited the GP practice and the emergency department more often ((RR 1.3 (1.0;1.7) and 1.70 (1.0;2.8)), respectively). Conclusions: In conclusion, the GRIP intervention, which was designed to involve the primary care team during and after cancer treatment, increased the number of primary healthcare contacts. However, it did not improve patient satisfaction with care and it increased emergency department visits. As the high uptake of the intervention suggests a need of patients, future research should focus on optimizing the design and implementation of the intervention. Trial registration: GRIP is retrospectively (21/06/2016) registered in the ‘Netherlands Trial Register’ (NTR5909)

    Predicting response to neoadjuvant chemotherapy with liquid biopsies and multiparametric MRI in patients with breast cancer

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    Accurate prediction of response to neoadjuvant chemotherapy (NAC) can help tailor treatment to individual patients’ needs. Little is known about the combination of liquid biopsies and computer extracted features from multiparametric magnetic resonance imaging (MRI) for the prediction of NAC response in breast cancer. Here, we report on a prospective study with the aim to explore the predictive potential of this combination in adjunct to standard clinical and pathological information before, during and after NAC. The study was performed in four Dutch hospitals. Patients without metastases treated with NAC underwent 3 T multiparametric MRI scans before, during and after NAC. Liquid biopsies were obtained before every chemotherapy cycle and before surgery. Prediction models were developed using penalized linear regression to forecast residual cancer burden after NAC and evaluated for pathologic complete response (pCR) using leave-one-out-cross-validation (LOOCV). Sixty-one patients were included. Twenty-three patients (38%) achieved pCR. Most prediction models yielded the highest estimated LOOCV area under the curve (AUC) at the post-treatment timepoint. A clinical-only model including tumor grade, nodal status and receptor subtype yielded an estimated LOOCV AUC for pCR of 0.76, which increased to 0.82 by incorporating post-treatment radiological MRI assessment (i.e., the “clinical-radiological” model). The estimated LOOCV AUC was 0.84 after incorporation of computer-extracted MRI features, and 0.85 when liquid biopsy information was added instead of the radiological MRI assessment. Adding liquid biopsy information to the clinical-radiological resulted in an estimated LOOCV AUC of 0.86. In conclusion, inclusion of liquid biopsy-derived markers in clinical-radiological prediction models may have potential to improve prediction of pCR after NAC in breast cancer

    Dead layer on silicon p–i–n diode charged-particle detectors

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    Semiconductor detectors in general have a dead layer at their surfaces that is either a result of natural or induced passivation, or is formed during the process of making a contact. Charged particles passing through this region produce ionization that is incompletely collected and recorded, which leads to departures from the ideal in both energy deposition and resolution. The silicon p-i-n diode used in the KATRIN neutrinomass experiment has such a dead layer. We have constructed a detailed Monte Carlo model for the passage of electrons from vacuum into a silicon detector, and compared the measured energy spectra to the predicted ones for a range of energies from 12 to 20 keV. The comparison provides experimental evidence that a substantial fraction of the ionization produced in the "dead" layer evidently escapes by diffusion, with 46% being collected in the depletion zone and the balance being neutralized at the contact or by bulk recombination. The most elementary model of a thinner dead layer from which no charge is collected is strongly disfavored

    On the sensitivity of the HAWC observatory to gamma-ray bursts

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    We present the sensitivity of HAWC to Gamma Ray Bursts (GRBs). HAWC is a very high-energy gamma-ray observatory currently under construction in Mexico at an altitude of 4100 m. It will observe atmospheric air showers via the water Cherenkov method. HAWC will consist of 300 large water tanks instrumented with 4 photomultipliers each. HAWC has two data acquisition (DAQ) systems. The main DAQ system reads out coincident signals in the tanks and reconstructs the direction and energy of individual atmospheric showers. The scaler DAQ counts the hits in each photomultiplier tube (PMT) in the detector and searches for a statistical excess over the noise of all PMTs. We show that HAWC has a realistic opportunity to observe the high-energy power law components of GRBs that extend at least up to 30 GeV, as it has been observed by Fermi LAT. The two DAQ systems have an energy threshold that is low enough to observe events similar to GRB 090510 and GRB 090902b with the characteristics observed by Fermi LAT. HAWC will provide information about the high-energy spectra of GRBs which in turn could help to understanding about e-pair attenuation in GRB jets, extragalactic background light absorption, as well as establishing the highest energy to which GRBs accelerate particles

    The design, construction, and commissioning of the KATRIN experiment

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    The KArlsruhe TRItium Neutrino (KATRIN) experiment, which aims to make a direct and model-independent determination of the absolute neutrino mass scale, is a complex experiment with many components. More than 15 years ago, we published a technical design report (TDR) [1] to describe the hardware design and requirements to achieve our sensitivity goal of 0.2 eV at 90% C.L. on the neutrino mass. Since then there has been considerable progress, culminating in the publication of first neutrino mass results with the entire beamline operating [2]. In this paper, we document the current state of all completed beamline components (as of the first neutrino mass measurement campaign), demonstrate our ability to reliably and stably control them over long times, and present details on their respective commissioning campaigns

    Focal-plane detector system for the KATRIN experiment

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    The focal-plane detector system for the KArlsruhe TRItium Neutrino (KATRIN) experiment consists of a multi-pixel silicon p-i-n-diode array, custom readout electronics, two superconducting solenoid magnets, an ultra high-vacuum system, a high-vacuum system, calibration and monitoring devices, a scintillating veto, and a custom data-acquisition system. It is designed to detect the low-energy electrons selected by the KATRIN main spectrometer. We describe the system and summarize its performance after its final installation.Comment: 28 pages. Two figures revised for clarity. Final version published in Nucl. Inst. Meth.

    Measurement of the Îœe and total 8B solar neutrino fluxes with the Sudbury Neutrino Observatory phase-III data set

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    This paper details the solar neutrino analysis of the 385.17-day phase-III data set acquired by the Sudbury Neutrino Observatory (SNO). An array of 3He proportional counters was installed in the heavy-water target to measure precisely the rate of neutrino-deuteron neutral-current interactions. This technique to determine the total active 8B solar neutrino flux was largely independent of the methods employed in previous phases. The total flux of active neutrinos was measured to be 5.54-0.31+0.33(stat.)-0.34+0.36(syst.)×106 cm-2 s-1, consistent with previous measurements and standard solar models. A global analysis of solar and reactor neutrino mixing parameters yielded the best-fit values of Δm2=7.59-0.21+0.19×10 -5eV2 and ξ=34.4-1.2+1.3degrees

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    The ATLAS trigger system for LHC Run 3 and trigger performance in 2022

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    The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025)

    Search for the Zγ decay mode of new high-mass resonances in pp collisions at √s = 13 TeV with the ATLAS detector

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    This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The √s = 13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb−1. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV
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