Abstract Background: People with severe mental illness (SMI) often suffer from long-lasting symptoms that negatively influence their social functioning, their ability to live a meaningful life, and participation in society. Interventions aimed at increasing physical activity can improve social functioning, but people with SMI experience multiple barriers to becoming physically active. Besides, the implementation of physical activity interventions in day-to-day practice is difficult. In this study, we aim to evaluate the effectiveness and implementation of a physical activity intervention to improve social functioning, mental and physical health. Methods: In this pragmatic stepped wedge cluster randomized controlled trial we aim to include 100 people with SMI and their mental health workers from a supported housing organization. The intervention focuses on increasing physical activity by implementing group sports activities, active guidance meetings, and a serious game to set physical activity goals. We aim to decrease barriers to physical activity through active involvement of the mental health workers, lifestyle courses, and a medication review. Participating locations will be divided into four clusters and randomization will decide the start of the intervention. The primary outcome is social functioning. Secondary outcomes are quality of life, symptom severity, physical activity, cardiometabolic risk factors, cardiorespiratory fitness, and movement disturbances with specific attention to postural adjustment and movement sequencing in gait. In addition, we will assess the implementation by conducting semi-structured interviews with location managers and mental health workers and analyze them by direct content analysis. Discussion: This trial is innovative since it aims to improve social functioning in people with SMI through a physical activity intervention which aims to lower barriers to becoming physically active in a real-life setting. The strength of this trial is that we will also evaluate the implementation of the intervention. Limitations of this study are the risk of poor implementation of the intervention, and bias due to the inclusion of a medication review in the intervention that might impact outcomes. Trial registration: This trial was registered prospectively in The Netherlands Trial Register (NTR) as NTR NL9163 on December 20, 2020. As the The Netherlands Trial Register is no longer available, the trial can now be found in the International Clinical Trial Registry Platform via: https:// trial search. who. int/ Trial2. aspx? Trial ID= NL9163.
OBJECTIVES: To evaluate the effects of exercise interventions on sleep disturbances and sleep quality in patients with mixed cancer diagnoses, and identify demographic, clinical, and intervention-related moderators of these effects.METHODS: Individual patient data (IPD) and aggregated meta-analyses of randomized controlled trials (RCTs). Using data from the Predicting OptimaL cAncer RehabIlitation and Supportive care project, IPD of 2173 adults (mean age = 54.8) with cancer from 17 RCTs were analyzed. A complementary systematic search was conducted (until November 2018) to study the overall effects and test the representativeness of analyzed IPD. Effect sizes of exercise effects on self-reported sleep outcomes were calculated for all included RCTs. Linear mixed-effect models were used to evaluate the effects of exercise on post-intervention outcome values, adjusting for baseline values. Moderator effects were studied by testing interactions for demographic, clinical and intervention-related characteristics.RESULTS: For all 27 eligible RCTs from the updated search, exercise interventions significantly decreased sleep disturbances in adults with cancer (g = -0.09, 95% CI [-0.16; -0.02]). No significant effect was obtained for sleep quality. RCTs included in IPD analyses constituted a representative sample of the published literature. The intervention effects on sleep disturbances were not significantly moderated by any demographic, clinical, or intervention-related factor, nor by sleep disturbances.CONCLUSIONS: This meta-analysis provides some evidence that, compared to control conditions, exercise interventions may improve sleep disturbances, but not sleep quality, in cancer patients, although this effect is of a small magnitude. Among the investigated variables, none was found to significantly moderate the effect of exercise interventions on sleep disturbances.
Worldwide, coral reefs are rapidly declining due to increased sea water temperatures and other environmental stresses (Figure 1). To counter the extinction of major coral reef building species on the island of Bonaire, the non-profit organization Reef Renewal Foundation Bonaire is restoring degraded reef sites using corals that are grown in local nurseries. In these nurseries, corals are propagated on artificial trees using fragmentation. After 6-8 months of growth in the nursery, the corals are transplanted to degraded reef sites around the island. Over the years more than 21.000 corals have been outplanted to reef restoration sites in this way. These corals show high survivorship under natural reef conditions but remain under threat by environmental disturbances, such as increased water temperatures, diseases, and competition with macroalgae. A promising intervention to increase reef persistence and resilience is to manipulate the coral-associated microbiome. At present, the composition of the microbiome in nursery-reared and outplanted corals on Bonaire is unknown. The aim of the current project is to identify and isolate naturally occurring beneficial bacteria that may stimulate the resilience of these corals. Our key objectives are: 1) to assess the presence of functionally beneficial bacteria in corals in nursery and restoration sites on Bonaire using metagenomic screening. 2) to design culture strategies to isolate these functionally beneficial bacteria. In the future, a selection of these beneficial bacteria can be applied to the corals to increase their resilience against environmental disturbances.
Restoring rivers with an integrated approach that combines water safety, nature development and gravel mining remains a challenge. Also for the Grensmaas, the most southern trajectory of the Dutch main river Maas, that crosses the border with Belgium in the south of Limburg. The first plans (“Plan Ooievaar”) were already developed in the 1980s and were highly innovative and controversial, as they were based on the idea of using nature-based solutions combined with social-economic development. Severe floodings in 1993 and 1995 came as a shock and accelerated the process to implement the associated measures. To address the multifunctionality of the river, the Grensmaas consortium was set up by public and private parties (the largest public-private partnership ever formed in the Netherlands) to have an effective, scalable and socially accepted project. However, despite the shared long term vision and the further development of plans during the process it was hard to satisfy all the goals in the long run. While stakeholders agreed on the long-term goal, the path towards that goal remains disputed and depends on the perceived status quo and urgency of the problem. Moreover, internal and external pressures and disturbances like climate change or the economic crisis influenced perception and economic conditions of stakeholders differently. In this research we will identify relevant system-processes connected to the implementation of nature-based solutions through the lens of social-ecological resilience. This knowledge will be used to co-create management plans that effectively improve the long-term resilience of the Dutch main water systems.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
