The relation between proximity to and characteristics of green spaces to physical activity and health:A multi-dimensional sensitivity analysis in four European cities

Introduction: Non-communicable diseases are the global disease burden of our time, with physical inactivity identified as one major risk factor. Green spaces are associated with increased physical activity of nearby residents. But there are still gaps in understanding which proximity and what characteristics of green spaces can trigger physical activity. This study aims to unveil these differences with a rigorous sensitivity analysis. Methods: We gathered data on self-reported health and physical activity from 1365 participants in selected neighbourhoods in Porto, Nantes, Sofia, and Høje-Taastrup. Spatial data were retrieved from OpenStreetMap. We followed the PRIGSHARE guidelines to control for bias. Around the residential addresses, we generated seven different green space indicators for 15 distances (100–1500 m) using the AID-PRIGSHARE tool. We then analysed each of these 105 green space indicators together with physical activity and health in 105 adjusted structural equation models. Results: Green space accessibility and green space uses indicators showed a pattern of significant positive associations to physical activity and indirect to health at distances of 1100 m or less, with a peak at 600 m for most indicators. Greenness in close proximity (100 m) had significant positive effects on physical activity and indirect effects on health. Surrounding greenness showed positive direct effects on health at 500–1100 m and so do green corridors in 800 m network distance. In contrast, a high quantity of green space uses, and surrounding greenness measured in a larger radius (1100–1500 m) showed a negative relationship with physical activity and indirect health effects. Conclusions: Our results provide insight into how green space characteristics can influence health at different scales, with important implications for urban planners on how to integrate accessible green spaces into urban structures and public health decision-makers on the ability of green spaces to combat physical inactivity.</p

Decision-making (in)flexibility in gambling disorder

Background: Behavioral flexibility –the ability to dynamically readjust our behavior in response to reward contingency changes– is often investigated using probabilistic reversal learning tasks (PRLT). Poor PRLT performance has been proposed as a proxy for compulsivity, and theorized to be related to perseverative gambling. Previous attempts to measure inflexibility with the PRLT in patients with gambling disorder have, however, used a variety of indices that may conflate inflexibility with more general aspects of performance in the task. Methods: Trial-by-trial PRLT acquisition and reacquisition curves in 84 treatment-seeking patients with gambling disorder and 64 controls (non-gamblers and non-problem recreational gamblers) were analyzed to distinguish between (a) variability in acquisition learning, and (b) reacquisition learning in reversed contingency phases. Complementarily, stay/switch responses throughout the task were analyzed to identify (c) premature switching, and (d) sensitivity to accumulated negative feedback. Results and interpretation: Even after controlling for differences in acquisition learning, patients were slower to readjust their behavior in reversed contingency phases, and were more prone to maintain their decisions despite accumulated negative feedback. Inflexibility in patients with gambling disorder is thus a robust phenomenon that could predate gambling escalation, or result from massive exposure to gambling activities.This work was supported by grants from the Spanish Government (PSI2017-85488-P: Ministerio de Economía y Competitividad, Secretaría de Estado de Investigación, Desarrollo e Innovación, Convocatoria 2017 de Proyectos I+ D de Excelencia, Spain, co-funded by the Fondo Europeo de Desarrollo Regional, FEDER, European Commission; and PSI2013-45055: Ministerio de Economía y Competitividad, Secretaría de Estado de Invetigación, Desarrollo e Innovación, Convocatoria 2013 de Proyectos I+ D de Excelencia). Additionally, JFN was supported by a grant from the Spanish Government (PSI2017-85159-P. Ministerio de Ciencia, Innovación y Universidades). Funding agencies had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication

Goal-directed and habitual decision making under stress in Gambling Disorder: an fMRI study

The development of addictive behaviors has been suggested to be related to a transition from goal-directed to habitual decision making. Stress is a factor known to prompt habitual behavior and to increase the risk for addiction and relapse. In the current study, we therefore used functional MRI to investigate the balance between goal-directed ‘model-based’ and habitual ‘model-free’ control systems and whether acute stress would differentially shift this balance in gambling disorder (GD) patients compared to healthy controls (HCs). Using a within-subject design, 22 patients with GD and 20 HCs underwent stress induction or a control condition before performing a multistep decision-making task during fMRI. Salivary cortisol levels showed that the stress induction was successful. Contrary to our hypothesis, GD patients showed intact goal-directed decision making, which remained similar to HCs after stress induction. Bayes factors provided substantial evidence against a difference between the groups or a group-by-stress interaction on the balance between model-based and model-free decision making. Similarly, neural estimates did not differ between groups and conditions. These results challenge the notion that GD is related to an increased reliance on habitual (or decreased goal-directed) control, even during stress

Global urbanization and food production in direct competition for land:Leverage places to mitigate impacts on SDG2 and on the Earth System

Global urbanization and food production are in direct competition for land. This paper carries out a critical review of how displacing crop production from urban and peri-urban land to other areas – because of issues related to soil quality – will demand a substantially larger proportion of the Earth’s terrestrial land surface than the surface area lost to urban encroachment. Such relationships may trigger further distancing effects and unfair social-ecological teleconnections. It risks also setting in motion amplifying effects within the Earth System. In combination, such multiple stressors set the scene for food riots in cities of the Global South. Our review identifies viable leverage points on which to act in order to navigate urban expansion away from fertile croplands. We first elaborate on the political complexities in declaring urban and peri-urban lands with fertile soils as one global commons. We find that the combination of an advisory global policy aligned with regional policies enabling robust common properties rights for bottom-up actors and movements in urban and peri-urban agriculture (UPA) as multi-level leverage places to intervene. To substantiate the ability of aligning global advisory policy with regional planning, we review both past and contemporary examples where empowering local social-ecological UPA practices and circular economies have had a stimulating effect on urban resilience and helped preserve, restore, and maintain urban lands with healthy soils

Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics

Introduction There is a cumulative risk of 20-40% of developing brain metastases (BM) in solid cancers. Stereotactic radiotherapy (SRT) enables the application of high focal doses of radiation to a volume and is often used for BM treatment. However, SRT can cause adverse radiation effects (ARE), such as radiation necrosis, which sometimes cause irreversible damage to the brain. It is therefore of clinical interest to identify patients at a high risk of developing ARE. We hypothesized that models trained with radiomics features, deep learning (DL) features, and patient characteristics or their combination can predict ARE risk in patients with BM before SRT. Methods Gadolinium-enhanced T1-weighted MRIs and characteristics from patients treated with SRT for BM were collected for a training and testing cohort (N = 1,404) and a validation cohort (N = 237) from a separate institute. From each lesion in the training set, radiomics features were extracted and used to train an extreme gradient boosting (XGBoost) model. A DL model was trained on the same cohort to make a separate prediction and to extract the last layer of features. Different models using XGBoost were built using only radiomics features, DL features, and patient characteristics or a combination of them. Evaluation was performed using the area under the curve (AUC) of the receiver operating characteristic curve on the external dataset. Predictions for individual lesions and per patient developing ARE were investigated. Results The best-performing XGBoost model on a lesion level was trained on a combination of radiomics features and DL features (AUC of 0.71 and recall of 0.80). On a patient level, a combination of radiomics features, DL features, and patient characteristics obtained the best performance (AUC of 0.72 and recall of 0.84). The DL model achieved an AUC of 0.64 and recall of 0.85 per lesion and an AUC of 0.70 and recall of 0.60 per patient. Conclusion Machine learning models built on radiomics features and DL features extracted from BM combined with patient characteristics show potential to predict ARE at the patient and lesion levels. These models could be used in clinical decision making, informing patients on their risk of ARE and allowing physicians to opt for different therapies

Multistate Comparison of Attractants for Monitoring Drosophila suzukii (Diptera: Drosophilidae) in Blueberries and Caneberries

Drosophila suzukii Matsumara, also referred to as the spotted wing drosophila, has recently expanded its global range with significant consequences for its primary host crops: blueberries, blackberries, raspberries, cherries, and strawberries. D. suzukii populations can increase quickly, and their infestation is difficult to predict and prevent. The development of effective tools to detect D. suzukii presence in new areas, to time the beginning of activity within a crop, to track seasonal activity patterns, and to gauge the effectiveness of management efforts has been a key research goal. We compared the efficiency, selectivity, and relationship to fruit infestation of a range of commonly used homemade baits and a synthetic formulated lure across a wide range of environments in 10 locations throughout the United States. Several homemade baits were more efficient than apple cider vinegar, a commonly used standard, and a commercially formulated lure was, in some configurations and environments, comparable with the most effective homemade attractant as well as potentially more selective. All alternative attractants also captured flies between 1 and 2 wk earlier than apple cider vinegar, and detected the presence of D. suzukii prior to the development of fruit infestation. Over half the Drosophila spp. flies captured in traps baited with any of the attractants were not D. suzukii, which may complicate their adoption by nonexpert users. The alternative D. suzukii attractants tested are improvement on apple cider vinegar and may be useful in the development of future synthetic lure

Low anti-staphylococcal IgG responses in granulomatosis with polyangiitis patients despite long-term Staphylococcus aureus exposure

Chronic nasal carriage of the bacterium Staphylococcus aureus in patients with the autoimmune disease granulomatosis with polyangiitis (GPA) is a risk factor for disease relapse. To date, it was neither known whether GPA patients show similar humoral immune responses to S. aureus as healthy carriers, nor whether specific S. aureus types are associated with GPA. Therefore, this study was aimed at assessing humoral immune responses of GPA patients against S. aureus antigens in relation to the genetic diversity of their nasal S. aureus isolates. A retrospective cohort study was conducted, including 85 GPA patients and 18 healthy controls (HC). Humoral immune responses against S. aureus were investigated by determining serum IgG levels against 59 S. aureus antigens. Unexpectedly, patient sera contained lower anti-staphylococcal IgG levels than sera from HC, regardless of the patients' treatment, while total IgG levels were similar or higher. Furthermore, 210 S. aureus isolates obtained from GPA patients were characterized by different typing approaches. This showed that the S. aureus population of GPA patients is highly diverse and mirrors the general S. aureus population. Our combined findings imply that GPA patients are less capable of mounting a potentially protective antibody response to S. aureus than healthy individuals