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Abstract Xenon dual-phase time projections chambers (TPCs) have proven to be a successful technology in studying physical phenomena that require low-background conditions. With $$40\,\textrm{t}$$ 40 t of liquid xenon (LXe) in the TPC baseline design, DARWIN will have a high sensitivity for the detection of particle dark matter, neutrinoless double beta decay ( $$0\upnu \upbeta \upbeta $$ 0 ν β β ), and axion-like particles (ALPs). Although cosmic muons are a source of background that cannot be entirely eliminated, they may be greatly diminished by placing the detector deep underground. In this study, we used Monte Carlo simulations to model the cosmogenic background expected for the DARWIN observatory at four underground laboratories: Laboratori Nazionali del Gran Sasso (LNGS), Sanford Underground Research Facility (SURF), Laboratoire Souterrain de Modane (LSM) and SNOLAB. We present here the results of simulations performed to determine the production rate of $${}^{137}$$ 137 Xe, the most crucial isotope in the search for $$0\upnu \upbeta \upbeta $$ 0 ν β β of $${}^{136}$$ 136 Xe. Additionally, we explore the contribution that other muon-induced spallation products, such as other unstable xenon isotopes and tritium, may have on the cosmogenic background.

Background: The prevalence of Major Depressive Disorder (MDD) is twice as high in women as in men and this difference already emerges during adolescence. Because the mechanisms underlying this sex-difference remain poorly understood, we took a bottom-up approach to identify factors explaining the sex-MDD relationship., Methods: Data came from the TRacking Adolescents' Individual Lives Survey (TRAILS), a population study investigating youths' development from age 11 into adulthood. We assessed multiple baseline covariates (e.g., demographic, social and psychological) at ages 11-13 years and MDD onset at ages 19 and 25 years. In regression analyses, each covariate's role in the sex-MDD association as an effect modifier or confounder/explanatory variable was investigated. Replicability was evaluated in an independent sample., Results: The analyses identified no effect-modifiers. Baseline internalizing problems, behavioral inhibition, dizziness, comfort in classroom, physical complaints, attention problems, cooperation, self/effortful control, interpersonal life events and computer use partially explained the association between sex and MDD at age 19. The association between sex and MDD at age 25 was explained by largely the same variables, but also by shyness, acne, antisocial behavior, aggression, affection from peers and time spent shopping. The explanatory roles of internalizing problems, behavioral inhibition, negative events involving gossip/rumors and leisure-time spending (computer-use/shopping) were replicated., Limitations: Potentially important baseline variables were not included or had low response rates. Gender roles or identification were not considered. Baseline MDD was not adjusted for., Conclusion: The sex-MDD association is partially explained by sex differences in symptoms and vulnerability factors already present in early adolescence., Competing Interests: Declaration of competing interest None of the authors declare any conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Combining non-specialists and digital technologies in mental health interventions could decrease the mental healthcare gap in resource scarce countries. This systematic review examined different combinations of non-specialists and digital technologies in mental health interventions and their effectiveness in reducing the mental healthcare gap in low-and middle-income countries., Methods: Literature searches were conducted in four databases (September 2023), three trial registries (January-February 2022), and using forward and backward citation searches (May-June 2022). The review included primary studies on mental health interventions combining non-specialists and digital technologies in low-and middle-income countries. The outcomes were: (1) the mental health of intervention receivers and (2) the competencies of non-specialists to deliver mental health interventions. Data were expressed as standardised effect sizes (Cohen's d) and narratively synthesised. Risk of bias assessment was conducted using the Cochrane risk-of-bias tools for individual and cluster randomised and non-randomised controlled trials., Results: Of the 28 included studies (n = 32 interventions), digital technology was mainly used in non-specialist primary-delivery treatment models for common mental disorders or subthreshold symptoms. The competencies of non-specialists were improved with digital training (d ≤ 0.8 in 4/7 outcomes, n = 4 studies, 398 participants). The mental health of receivers improved through non-specialist-delivered interventions, in which digital technologies were used to support the delivery of the intervention (d > 0.8 in 24/40 outcomes, n = 11, 2469) or to supervise the non-specialists' work (d = 0.2-0.8 in 10/17 outcomes, n = 3, 3096). Additionally, the mental health of service receivers improved through digitally delivered mental health services with non-specialist involvement (d = 0.2-0.8 in 12/27 outcomes, n = 8, 2335). However, the overall certainty of the evidence was poor., Conclusion: Incorporating digital technologies into non-specialist mental health interventions tended to enhance non-specialists' competencies and knowledge in intervention delivery, and had a positive influence on the severity of mental health problems, mental healthcare utilization, and psychosocial functioning outcomes of service recipients, primarily within primary-deliverer care models. More robust evidence is needed to compare the magnitude of effectiveness and identify the clinical relevance of specific digital functions. Future studies should also explore long-term and potential adverse effects and interventions targeting men and marginalised communities., (© 2023. The Author(s).)