Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

Introduction Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. Methods Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. Results A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. Conclusions The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Measuring Unpaid Care Work in Household Surveys

Caring for people and domestic work, such as cooking, cleaning and fetching water, is essential for personal wellbeing and survival. But across the world, care work is overwhelmingly done by women, which restricts their opportunities for education, employment, political engagement and leisure.This research case study discusses the successes and challenges of the time use measurements used in Oxfam's Household Care Surveys. The surveys, supported by Oxfam's Women's Economic Empowerment and Care (WE-Care) programme, aimed to measure adults' and children's time spent on unpaid care work and other factors that could influence this distribution within the household

Infrastructure and Equipment for Unpaid Care Work: Household survey findings from the Philippines, Uganda and Zimbabwe - 2017 Household Care Survey report

Care work is essential for personal wellbeing, a healthy society and a functioning economy. But across the world, it is overwhelmingly done by women, which restricts their opportunities. Policy makers rarely recognize the public responsibility for facilitating unpaid care and domestic work through investments in infrastructure and care services.In 2017, Oxfam's Women's Economic Empowerment and Care (WE-Care) initiative conducted a Household Care Survey (HCS), collecting data in the Philippines, Uganda and Zimbabwe, to inform the design of public policies and local development programmes. The study tests which infrastructure, equipment and other factors influence care-work patterns. It finds that access to improved water sources is associated with reduced hours of care work, and household equipment facilitates men's participation in care. It also finds that heavy workloads related to long hours of unpaid care can impact women's health and well-being. Perceptions of care work, community expectations and fear of sanctions for deviating from social norms play an essential part in maintaining the gendered division of care work.The report presents recommendations for government and private sector decision-makers, development practitioners and researchers in the area of women's economic empowerment on how they can contribute to facilitate the recognition, reduction and redistribution of unpaid care work.  

Women's Economic Empowerment and Care: Evidence for influencing

Development actors increasingly identify care responsibilities as a factor restricting women's empowerment outcomes, yet there is limited evidence on determinants of long hours or gender inequality in care work. To gain a clearer understanding of care work and pathways of change to promote more equitable care provision, Oxfam conducted a Household Care Survey in communities of rural Colombia, Ethiopia, the Philippines, Uganda and Zimbabwe. Data were collected on household characteristics, members' time use, socioeconomic status, social norms, labour-saving equipment and public infrastructure. For each country, linear regression models were built using forward stepwise model selection.Results highlight that gender inequality exists in all measures of care work, with women and girls doing significantly more primary and secondary care activities, and supervision of dependants, than men and boys.The determinants of care are context-specific. Education and relative household wealth are less relevant as determinants of length, intensity or inequality in care hours than might be expected. Women's paid/productive activities and access to labour-saving stoves and improved water systems are sometimes associated with decreases in women's hours of care work. The findings emphasise unequal care responsibilities by gender and age, and encourage further research on determinants of care work in specific contexts

Factors and Norms Influencing Unpaid Care Work: Household survey evidence from five rural communities in Colombia, Ethiopia, the Philippines, Uganda and Zimbabwe

In order to address 'heavy' and 'unequal' care work and to raise the profile of care as a cross-cutting development issue, Oxfam and its partners implemented a baseline Household Care Survey (HCS) in five countries in which the WE-Care project was active. In November/December 2015, a revised version of the HCS was carried out in these same communities. As a follow-up survey, the 2015 HCS monitored change and impact from the project's interventions and gathered evidence on 'what works' to address care work in specific contexts. The aim is to generate evidence that helps local organizations address problematic aspects of care work, contributing to women's ability to participate, lead and benefit from development initiatives. This evidence is then used to develop project interventions that recognize, reduce and redistribute existing unpaid care work within the household, the immediate community (civil society), the market (private sector) and the state authority (central and local governments)

Exploring the Need for Gender-Equitable Fiscal Policies for a Human Economy: Evidence from Uganda and Zimbabwe

Fiscal policy can be a powerful tool for governments to help achieve a 'human economy', if these policies are designed to address gender inequalities and the gender biases in current macroeconomic thinking. This report uses the case of one element of fiscal policy - public spending - to demonstrate how such policy design could help achieve gender equality and improve human development outcomes in developing countries.The report identifies unpaid care and domestic work as a key area where fiscal policy has a significant impact on gender equality. Using data from Oxfam's 2017 Household Care Survey in Uganda and Zimbabwe, the report explores the impact on adults' and children's/adolescents' time use of access to improved water sources, electricity, healthcare and childcare. It also considers secondary impacts on measures of well-being and women's empowerment, including women's health and decision making.

A Systematic Review and Quantitative Analysis of Interteaching

Interteaching is a behavioral teaching method that departs from the traditional lecture format (Boyce & Hineline in BA 25:215–226, 2002). We updated and expanded previous interteaching reviews and conducted a meta-analysis on its effectiveness. Systematic searches identified 38 relevant studies spanning the years 2005–2018. The majority of these studies were conducted in undergraduate face-to-face courses. The most common independent variables were manipulations of the configuration of interteaching or comparisons to traditional-lecture format. The most common dependent variables were quiz or examination scores. Only 24% of all studies implemented at least five of the seven components of interteaching. Prep guides, discussions, record sheets, and frequent assessments were the most commonly implemented. Meta-analyses indicated that interteaching is more effective than traditional lecture or other control conditions, with an overall large effect size. Furthermore, variations in the configuration of the interteaching components do not seem to substantially limit its effectiveness, as long as the discussion component is included. Future research informed by the present review includes: (a) investigating the efficacy of interteaching in additional academic areas, online environments, workplace training, and continuing education, (b) testing alternative outcome measures, generalization, and procedural integrity, (c) conducting systematic component analyses, and (d) measuring social validity from the instructor’s perspective. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10864-021-09452-3

Polygenic risk for immuno-metabolic markers and specific depressive symptoms: A multi-sample network analysis study.

BACKGROUND: About every fourth patient with major depressive disorder (MDD) shows evidence of systemic inflammation. Previous studies have shown inflammation-depression associations of multiple serum inflammatory markers and multiple specific depressive symptoms. It remains unclear, however, if these associations extend to genetic/lifetime predisposition to higher inflammatory marker levels and what role metabolic factors such as Body Mass Index (BMI) play. It is also unclear whether inflammation-symptom associations reflect direct or indirect associations, which can be disentangled using network analysis. METHODS: This study examined associations of polygenic risk scores (PRSs) for immuno-metabolic markers (C-reactive protein [CRP], interleukin [IL]-6, IL-10, tumour necrosis factor [TNF]-α, BMI) with seven depressive symptoms in one general population sample, the UK Biobank study (n = 110,010), and two patient samples, the Munich Antidepressant Response Signature (MARS, n = 1058) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D, n = 1143) studies. Network analysis was applied jointly for these samples using fused graphical least absolute shrinkage and selection operator (FGL) estimation as primary analysis and, individually, using unregularized model search estimation. Stability of results was assessed using bootstrapping and three consistency criteria were defined to appraise robustness and replicability of results across estimation methods, network bootstrapping, and samples. RESULTS: Network analysis results displayed to-be-expected PRS-PRS and symptom-symptom associations (termed edges), respectively, that were mostly positive. Using FGL estimation, results further suggested 28, 29, and six PRS-symptom edges in MARS, STAR*D, and UK Biobank samples, respectively. Unregularized model search estimation suggested three PRS-symptom edges in the UK Biobank sample. Applying our consistency criteria to these associations indicated that only the association of higher CRP PRS with greater changes in appetite fulfilled all three criteria. Four additional associations fulfilled at least two consistency criteria; specifically, higher CRP PRS was associated with greater fatigue and reduced anhedonia, higher TNF-α PRS was associated with greater fatigue, and higher BMI PRS with greater changes in appetite and anhedonia. Associations of the BMI PRS with anhedonia, however, showed an inconsistent valence across estimation methods. CONCLUSIONS: Genetic predisposition to higher systemic inflammatory markers are primarily associated with somatic/neurovegetative symptoms of depression such as changes in appetite and fatigue, consistent with previous studies based on circulating levels of inflammatory markers. We extend these findings by providing evidence that associations are direct (using network analysis) and extend to genetic predisposition to immuno-metabolic markers (using PRSs). Our findings can inform selection of patients with inflammation-related symptoms into clinical trials of immune-modulating drugs for MDD.Wellcome Trust (grant code: 201486/Z/16/Z