Watershed science: Coupling hydrological science and water resources management

While there have been advancements in hydrological science and water resources management, the world continues to face a water-supply crisis. In light of studies that report the missing links to be (i) effective collaborations between researchers and practitioners and (ii) interdisciplinary working, we promote the benefits of Watershed Science to address these gaps. Watershed Science incorporates basin hydrology, determines water resource thresholds, promotes water governance that forms partnerships between institutions, and enacts participatory decision making in water resources management. However, such partnerships must recognize the differential power and interests of different actors to ensure that outcomes are not skewed in favour of particular interests. It adds value to existing water management programs and has great potential for bringing disciplines and decision making together to address the global water crisis

A dual point description of mesoscopic superconductors

We present an analysis of the magnetic response of a mesoscopic superconductor, i.e. a system of sizes comparable to the coherence length and to the London penetration depth. Our approach is based on special properties of the two dimensional Ginzburg-Landau equations, satisfied at the dual point $(\kappa = \frac{1}{\sqrt{2}}).$ Closed expressions for the free energy and the magnetization of the superconductor are derived. A perturbative analysis in the vicinity of the dual point allows us to take into account vortex interactions, using a new scaling result for the free energy. In order to characterize the vortex/current interactions, we study vortex configurations that are out of thermodynamical equilibrium. Our predictions agree with the results of recent experiments performed on mesoscopic aluminium disks.Comment: revtex, 20 pages, 9 figure

Women’s beliefs about medicines and adherence to pharmacotherapy in pregnancy: Opportunities for community pharmacists?

Background During pregnancy women might weigh benefits of treatment against potential risks to the unborn child. However, non-adherence to necessary treatment can adversely affect both mother and child. To optimize pregnant women’s beliefs and medication adherence, community pharmacists are ideally positioned to play an important role in primary care. Objective This narrative review aimed to summarize the evidence on 1) pregnant women’s beliefs, 2) medication adherence in pregnancy, and 3) community pharmacists’ counselling during pregnancy. Method Three search strategies were used in Medline and Embase to find original studies evaluating women’s beliefs, medication adherence and community pharmacists’ counselling during pregnancy. All original descriptive and analytic epidemiological studies performed in Europe, North America and Australia, written in English and published from 2000 onwards were included. Results We included 14 studies reporting on women’s beliefs, 11 studies on medication adherence and 9 on community pharmacists’ counselling during pregnancy. Women are more reluctant to use medicines during pregnancy and tend to overestimate the teratogenic risk of medicines. Risk perception varies with type of medicine, level of health literacy, education level and occupation. Furthermore, low medication adherence during pregnancy is common. Finally, limited evidence showed current community pharmacists’ counselling is insufficient. Barriers hindering pharmacists are insufficient knowledge and limited access to reliable information. Conclusion Concerns about medication use and non-adherence are widespread among pregnant women. Community pharmacists’ counselling during pregnancy is insufficient. Further education, training and research are required to support community pharmacists in fulfilling all the opportunities they have when counselling pregnant women

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death

Aims This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation.Methods and results We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality.Conclusion Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed.Cardiolog

Editorial Statement About JCCAP’s 2023 Special Issue on Informant Discrepancies in Youth Mental Health Assessments: Observations, Guidelines, and Future Directions Grounded in 60 Years of Research

Issue 1 of the 2011 Volume of the Journal of Clinical Child and Adolescent Psychology (JCCAP) included a Special Section about the use of multi-informant approaches to measure child and adolescent (i.e., hereafter referred to collectively as “youth”) mental health (De Los Reyes, 2011). Researchers collect reports from multiple informants or sources (e.g., parent and peer, youth and teacher) to estimate a given youth’s mental health. The 2011 JCCAP Special Section focused on the most common outcome of these approaches, namely the significant discrepancies that arise when comparing estimates from any two informant’s reports (i.e., informant discrepancies). These discrepancies appear in assessments conducted across the lifespan (Achenbach, 2020). That said, JCCAP dedicated space to understanding informant discrepancies, because they have been a focus of scholarship in youth mental health for over 60 years (e.g., Achenbach et al., 1987; De Los Reyes & Kazdin, 2005; Glennon & Weisz, 1978; Kazdin et al., 1983; Kraemer et al., 2003; Lapouse & Monk, 1958; Quay et al., 1966; Richters, 1992; Rutter et al., 1970; van der Ende et al., 2012). Thus, we have a thorough understanding of the areas of research for which they reliably appear when clinically assessing youth. For instance, intervention researchers observe informant discrepancies in estimates of intervention effects within randomized controlled trials (e.g., Casey & Berman, 1985; Weisz et al., 2017). Service providers observe informant discrepancies when working with individual clients, most notably when making decisions about treatment planning (e.g., Hawley & Weisz, 2003; Hoffman & Chu, 2015). Scholars in developmental psychopathology observe these discrepancies when seeking to understand risk and protective factors linked to youth mental health concerns (e.g., Hawker & Boulton, 2000; Hou et al., 2020; Ivanova et al., 2022). Thus, the 2011 JCCAP Special Section posed a question: Might these informant discrepancies contain data relevant to understanding youth mental health? Suppose none of the work in youth mental health is immune from these discrepancies. In that case, the answer to this question strikes at the core of what we produce―from the interventions we develop and implement, to the developmental psychopathology research that informs intervention development

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

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