| 31. |
- Aprile, E., et al.
(författare)
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Double-weak decays of 124Xe and 136Xe in the XENON1T and XENONnT experiments
- 2022
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Ingår i: Physical Review C. - 2469-9985 .- 2469-9993. ; 106:2
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Tidskriftsartikel (refereegranskat)abstract
- We present results on the search for two-neutrino double-electron capture (2νECEC) of 124Xe and neutrinoless double-β decay (0νββ) of 136Xe in XENON1T. We consider captures from the K shell up to the N shell in the 2νECEC signal model and measure a total half-life of T2νECEC1/2=(1.1±0.2stat±0.1sys)×1022yr with a 0.87 kg yr isotope exposure. The statistical significance of the signal is 7.0σ. We use XENON1T data with 36.16 kg yr of 136Xe exposure to search for 0νββ. We find no evidence of a signal and set a lower limit on the half-life of T0νββ1/2>1.2×1024 yr at 90%CL. This is the best result from a dark matter detector without an enriched target to date. We also report projections on the sensitivity of XENONnT to 0νββ. Assuming a 275 kg yr 136Xe exposure, the expected sensitivity is T0νββ1/2>2.1×1025 yr at 90%CL, corresponding to an effective Majorana mass range of ⟨mββ⟩<(0.19–0.59)eV/c2.
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| 32. |
- Cearns, M., et al.
(författare)
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- 2022
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Ingår i: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 220:4, s. 219-228
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Tidskriftsartikel (refereegranskat)abstract
- Background Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. Aims To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. Method This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi(+)Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. Results The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. Conclusions Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
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| 33. |
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| 34. |
- Le Clerc, S., et al.
(författare)
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HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
- 2021
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 x 10(-3); FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
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| 35. |
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| 36. |
- Aprile, E., et al.
(författare)
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An approximate likelihood for nuclear recoil searches with XENON1T data
- 2022
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Ingår i: European Physical Journal C. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 82:11
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Tidskriftsartikel (refereegranskat)abstract
- The XENON collaboration has published stringent limits on specific dark matter – nucleon recoil spectra from dark matter recoiling on the liquid xenon detector target. In this paper, we present an approximate likelihood for the XENON1T 1 t-year nuclear recoil search applicable to any nuclear recoil spectrum. Alongside this paper, we publish data and code to compute upper limits using the method we present. The approximate likelihood is constructed in bins of reconstructed energy, profiled along the signal expectation in each bin. This approach can be used to compute an approximate likelihood and therefore most statistical results for any nuclear recoil spectrum. Computing approximate results with this method is approximately three orders of magnitude faster than the likelihood used in the original publications of XENON1T, where limits were set for specific families of recoil spectra. Using this same method, we include toy Monte Carlo simulation-derived binwise likelihoods for the upcoming XENONnT experiment that can similarly be used to assess the sensitivity to arbitrary nuclear recoil signatures in its eventual 20 t-year exposure.
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| 37. |
- Aprile, E., et al.
(författare)
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Application and modeling of an online distillation method to reduce krypton and argon in XENON1T
- 2022
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Ingår i: Progress of Theoretical and Experimental Physics. - : Oxford University Press (OUP). - 2050-3911. ; 2022:5
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Tidskriftsartikel (refereegranskat)abstract
- A novel online distillation technique was developed for the XENON1T dark matter experiment to reduce intrinsic background components more volatile than xenon, such as krypton or argon, while the detector was operating. The method is based on a continuous purification of the gaseous volume of the detector system using the XENON1T cryogenic distillation column. A krypton-in-xenon concentration of (360 +/- 60) ppq was achieved. It is the lowest concentration measured in the fiducial volume of an operating dark matter detector to date. A model was developed and fitted to the data to describe the krypton evolution in the liquid and gas volumes of the detector system for several operation modes over the time span of 550 days, including the commissioning and science runs of XENON1T. The online distillation was also successfully applied to remove Ar-37 after its injection for a low-energy calibration in XENON1T. This makes the usage of Ar-37 as a regular calibration source possible in the future. The online distillation can be applied to next-generation liquid xenon time projection chamber experiments to remove krypton prior to, or during, any science run. The model developed here allows further optimization of the distillation strategy for future large-scale detectors.
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| 38. |
- Aprile, E., et al.
(författare)
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Emission of single and few electrons in XENON1T and limits on light dark matter
- 2022
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Ingår i: Physical Review D. - 2470-0010 .- 2470-0029. ; 106:2
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Tidskriftsartikel (refereegranskat)abstract
- Delayed single- and few-electron emissions plague dual-phase time projection chambers, limiting their potential to search for light-mass dark matter. This paper examines the origins of these events in the XENON1T experiment. Characterization of the intensity of delayed electron backgrounds shows that the resulting emissions are correlated, in time and position, with high-energy events and can effectively be vetoed. In this work we extend previous S2-only analyses down to a single electron. From this analysis, after removing the correlated backgrounds, we observe rates <30 events/(electron×kg×day) in the region of interest spanning 1 to 5 electrons. We derive 90% confidence upper limits for dark matter-electron scattering, first direct limits on the electric dipole, magnetic dipole, and anapole interactions, and bosonic dark matter models, where we exclude new parameter space for dark photons and solar dark photons.
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| 39. |
- Aprile, E., et al.
(författare)
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Search for New Physics in Electronic Recoil Data from XENONnT
- 2022
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Ingår i: Physical Review Letters. - : American Physical Society. - 0031-9007 .- 1079-7114. ; 129:16
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Tidskriftsartikel (refereegranskat)abstract
- We report on a blinded analysis of low-energy electronic recoil data from the first science run of the XENONnT dark matter experiment. Novel subsystems and the increased 5.9 ton liquid xenon target reduced the background in the (1, 30) keV search region to (15.8±1.3) events/(ton×year×keV), the lowest ever achieved in a dark matter detector and ∼5 times lower than in XENON1T. With an exposure of 1.16 ton-years, we observe no excess above background and set stringent new limits on solar axions, an enhanced neutrino magnetic moment, and bosonic dark matter.
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| 40. |
- Schubert, K. O., et al.
(författare)
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Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients
- 2021
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Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi(+)Gen; ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
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