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Background Loneliness, a major public health concern, could be alleviated through social interventions with nature contact as a primary component. “Friends in Nature” is a complex nature-based social intervention designed to be implemented as part of “Reimagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces\" (RECETAS). This project aims to alleviate loneliness and promote health-related quality of life in six different geographic areas worldwide. Feasibility studies are crucial to assess the viability of complex interventions and study procedures before conducting definitive studies. This paper aims to describe the design, implementation, and evaluation of the six-related feasibility studies on the “Friends in Nature” intervention. These studies specifically evaluate feasibility of recruitment and study procedures, intervention implementation, and data collection and distribution. Methods We defined a comprehensive set of indicators to assess the feasibility of “Friends in Nature.” For the first domain, recruitment procedures were assessed to determine their adequacy, while attrition rates were examined to assess participant retention. For the second domain, the implementation of interventions was evaluated, along with the study design’s ability to adapt to unexpected situations and participant adherence to the intervention. Finally, for the third domain, completion rates and the acceptability of the study activities were also analyzed. The feasibility of using specific scales to assess loneliness and well-being was also explored. Results The feasibility indicators defined for this study were useful to assess the feasibility of “Friends in Nature.” Recruitment procedures were generally found to be adequate, and the number of dropouts was low. Interventions were implemented with minor adjustments, and facilitators played a vital role in the well-functioning of the interventions. Although some unexpected situations occurred during the study, adaptations were made, and participants were generally satisfied with the activities proposed. Scales used to assess loneliness and quality of life showed potential for measuring the effects of nature-based social prescribing in the full trial. Conclusion This paper offers valuable insights into the design and execution of feasibility studies for complex interventions like “Friends in Nature.” Findings from these assessments explore the feasibility of “Friends in Nature” and will inform the main RECETAS studies, which are designed to strengthen the evidence base to support the use of nature-based social prescribing to reduce loneliness and promote quality of life. Trial registration Barcelona trial: NCT05488496, Prague trial: NCT05522140, and Helsinki trial: NCT05507684.

Background The negative effects of loneliness on population health and wellbeing requires interventions that transcend the medical system and leverage social, cultural, and public health system resources. Group-based social interventions are a potential method to alleviate loneliness. Moreover, nature, as part of our social and health infrastructure, may be an important part of the solutions that are needed to address loneliness. The RECETAS European project H2020 (Re-imagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces) is an international research project aiming to develop and test the effectiveness of nature-based social interventions to reduce loneliness and increase health-related quality of life. Methods This article describes the three related randomized controlled trials (RCTs) that will be implemented: the RECETAS-BCN Trial in Barcelona (Spain) is targeting people 18+ from low socio-economic urban areas; the RECETAS-PRG Trial in Prague (Czech Republic) is addressing community-dwelling older adults over 60 years of age, and the RECETAS-HLSNK trial is reaching older people in assisted living facilities. Each trial will recruit 316 adults suffering from loneliness at least sometimes and randomize them to nature-based social interventions called “Friends in Nature” or to the control group. “Friends in Nature” uses modifications of the “Circle of Friends” methodology based on group processes of peer support and empowerment but including activities in nature. Participants will be assessed at baseline, at post-intervention (3 months), and at 6- and 12-month follow-up after baseline. Primary outcomes are the health-related quality-of-life according to 15D measure and The De Jong Gierveld 11-item loneliness scale. Secondary outcomes are health and psychosocial variables tailored to the specific target population. Nature exposure will be collected throughout the intervention period. Process evaluation will explore context, implementation, and mechanism of impact. Additionally, health economic evaluations will be performed. Discussion The three RECETAS trials will explore the effectiveness of nature-based social interventions among lonely people from various ages, social, economic, and cultural backgrounds. RECETAS meets the growing need of solid evidence for programs addressing loneliness by harnessing the beneficial impact of nature on enhancing wellbeing and social connections. Trial registration Barcelona (Spain) trial: ClinicalTrials.gov, ID: NCT05488496. Registered 29 July 2022. Prague (Czech Republic) trial: ClinicalTrials.gov, ID: NCT05522140. Registered August 25, 2022. Helsinki (Finland) trial: ClinicalTrials.gov, ID: NCT05507684. Registered August 12, 2022.

The designation of the Baltic Sea as a sulfur emission control area (SECA) in May 2006, with subsequent tightening of regulations in 2010 and 2015, has reduced the sulfuric emission from shipping traffic. This study assesses the impacts of SECA on observed SO2 concentrations by providing a long-term analysis of 1 min time-resolution air quality data from 2006 to 2020 on Utö (an island in the Baltic Sea) supported by the predictions from the Ship Traffic Emissions Assessment Model (STEAM). Additionally, 1 h resolution data from 2003 to 2005 are utilized to investigate changes due to the SECA limits set in 2006. The observed SO2 concentrations on Utö have continuously decreased since 2003 due to an overall decrease in SO2 emissions in northern Europe, combined with reduced emissions from shipping traffic due to SECA regulations. The 3-year average SO2 concentration dropped from pre-SECA (2003–2005) to post-SECA (2007–2009, 2011–2013, 2016–2018) periods by 38 %, 39 %, and 67 %, respectively. No clear trends were observed in the concentrations of other measured pollutants. Furthermore, we investigated wind-direction-resolved SO2 concentrations for 2 selected years (2014 and 2019), and the results showed a significant decrease in high-SO2-concentration shipping plumes due to the implementation of SECA in 2015. Our study brings out the importance of long-term, high-time-resolution air quality observations at a remote marine research station by providing means for both quantitative and qualitative analyses of the impacts of regulatory environmental legislation.

Background Loneliness is common among older adults in institutional settings. It leads to adverse effects on health and wellbeing, for which nature contact with peers in turn may have positive impact. However, the effects of nature engagement among older adults have not been studied in randomised controlled trials (RCT). The “Friends in Nature” (FIN) group intervention RCT for lonely older adults in Helsinki assisted living facilities (ALFs) aims to explore the effects of peer-related nature experiences on loneliness and health-related quality of life (HRQoL). In this study we aim describe the participants’ baseline characteristics of the RCT, feasibility of FIN intervention and intervention participants’ feedback on the FIN. Methods Lonely participants were recruited from 22 ALFs in Helsinki area, Finland, and randomised into two groups: 1) nature-based social intervention once a week for nine weeks ( n  = 162) and 2) usual care ( n  = 157). Demographics, diagnoses and medication use were retrieved from medical records, and baseline cognition, functioning, HRQoL, loneliness and psychological wellbeing were assessed. Primary trial outcomes will be participants’ loneliness (De Jong Giervald Loneliness Scale) and HRQoL (15D). Results The mean age of participants was 83 years, 73% were female and mean Minimental State Examination of 21 points. The participants were living with multiple co-morbidities and/or disabilities. The intervention and control groups were comparable at baseline. The adherence with intervention was moderate, with a mean attendance of 6.8 out of the nine sessions. Of the participants, 14% refused, fell ill or were deceased, and therefore, participated three sessions or less. General subjective alleviation of loneliness was achieved in 57% of the intervention participants. Of the respondents, 96% would have recommended a respective group intervention to other older adults. Intervention participants appreciated their nature excursions and experiences. Conclusions We have successfully randomised 319 lonely residents in assisted living facilities into a trial about the effects of nature experiences in a group-format. The feedback from participants was favourable. The trial will provide important information about possibilities of alleviating loneliness with peer-related nature-based experiences in frail residents. Trial registration ClinicalTrials.gov, ID: NCT05507684. Registration 19/08/2022.

Multisite pain is a prevalent and significant issue among adolescents, often associated with adverse physical, psychological, and social outcomes. We aimed to (1) predict multisite pain incidence in the whole body and in the musculoskeletal sites in adolescents, and (2) explore the sex-specific predictors of multisite pain incidence using a novel machine learning (ML) approach (random forest, AdaBoost, and support vector classifier). A 2-year longitudinal observational study (2013-2015) was conducted in a population-based sample of Finnish adolescents (  = 410, 57% girls, 12.5 years (SD = 1.2) at baseline). Three different data sets were used. First data included 48 pre-selected variables relevant for adolescents' health and wellbeing. The second data included nine physical fitness variables related to the Finnish national 'Move!' monitoring system for health-related fitness. The third data set included all available baseline data (392 variables). Multisite pain was self-reported weekly pain during the past 3 months manifesting in at least three sites and not related to any known disease or injury. Musculoskeletal pain sites included the neck/shoulder, upper extremities, chest, upper back, low back, buttocks, and lower extremities. Whole body pain sites also included the head and abdominal areas. Overall, 16% of boys and 28% of girls developed multisite pain in the whole body and 10% and 15% in the musculoskeletal area during the 2-year follow-up. The prediction ability of ML reached area under the receiver operating characteristic curve 0.78 at highest but remained mainly < 0.7 for the majority of the methods. With ML, a broad variety of predictors were identified, with up to 33 variables showing predictive power in girls and 13 in boys. The results highlight that rather than any isolated variable, a variety of factors contribute to future multisite pain.

To better understand large-effect pathogenic variation associated with autism, we generated long-read sequencing (LRS) data to construct phased and near-complete genome assemblies (average contig N50 = 43 Mbp, QV = 56) for 189 individuals from 51 families with unsolved cases. We applied read- and assembly-based strategies to facilitate comprehensive characterization of de novo mutations, structural variants (SVs), and DNA methylation. Using LRS pangenome controls, we efficiently filtered >97% of common SVs exclusive to 87 offspring. We find no evidence of increased autosomal SV burden for probands when compared to unaffected siblings yet observe a suggestive trend toward an increased SV burden on the X chromosome among affected females. We establish a workflow to prioritize potential pathogenic variants by integrating autism risk genes and putative noncoding regulatory elements defined from ATAC-seq and CUT&Tag data from the developing cortex. In total, we identified three pathogenic variants in TBL1XR1 , MECP2 , and SYNGAP1 , as well as nine candidate de novo and biallelic inherited homozygous SVs, most of which were missed by short-read sequencing. Our work highlights the potential of phased genomes to discover complex more pathogenic mutations and the power of the pangenome to restrict the focus on an increasingly smaller number of SVs for clinical evaluation.

ObjectivesTo assess the ability to predict individual unfavourable future status and development in the 20m shuttle run test (20MSRT) during adolescence with machine learning (random forest (RF) classifier).MethodsData from a 2-year observational study (2013‒2015, 12.4±1.3 years, n=633, 50% girls), with 48 baseline characteristics (questionnaires (demographics, physical, psychological, social and lifestyle factors), objective measurements (anthropometrics, fitness characteristics, physical activity, body composition and academic scores)) were used to predict: (Task 1) unfavourable future 20MSRT status (identification of individuals in the lowest 20MSRT tertile after 2 years), and (Task 2) unfavourable 20MSRT development (identification of individuals with 20MSRT development in the lowest tertile among adolescents with baseline 20MSRT below median level).ResultsPrediction performance for future 20MSRT status (Task 1) was (area under the receiver operating characteristic curve, AUC) 83% and 76%, sensitivity 80% and 60%, and specificity 78% and 79% in girls and boys, respectively. Twenty variables showed predictive power in boys, 14 in girls, including fitness characteristics, physical activity, academic scores, adiposity, life enjoyment, parental support, social status in school and perceived fitness.Prediction performance for future development (Task 2) was lower and differed statistically from random level only in girls (AUC 68% and 40% in girls and boys).ConclusionRF classifier predicted future unfavourable status in 20MSRT and identified potential individuals for interventions based on a holistic profile (14‒20 baseline characteristics). The MATLAB script and functions employing the RF classifier of this study are available for future precision exercise medicine research.

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and structurally polymorphic regions of the genome unmapped. Consequently, existing variant benchmarks, generated by the same methods, fail to assess these complex regions. To address this limitation, we present a telomere-to-telomere genome benchmark that achieves near-perfect accuracy (i.e. no detectable errors) across 99.4% of the complete, diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), totaling 15.3% of the genome that was absent from prior benchmarks. We also provide a diploid annotation of genes, transposable elements, segmental duplications, and satellite repeats, including 39,144 protein-coding genes across both haplotypes. To facilitate application of the benchmark, we developed tools for measuring the accuracy of sequencing reads, phased variant call sets, and genome assemblies against a diploid reference. Genome-wide analyses show that state-of-the-art de novo assembly methods resolve 2-7% more sequence and outperform variant calling accuracy by an order of magnitude, yielding just one error per 100 kb across 99.9% of the benchmark regions. Adoption of genome-based benchmarking is expected to accelerate the development of cost-effective methods for complete genome sequencing, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.