BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment

Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants.Comment: Accepted version to be published in 2020, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, Canad

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Background: Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke. Methods: We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515. Findings: Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p<0·0001 for non-inferiority; p=0·0006 for superiority). The incidence of acute pancreatitis (ten patients in the albiglutide group and seven patients in the placebo group), pancreatic cancer (six patients in the albiglutide group and five patients in the placebo group), medullary thyroid carcinoma (zero patients in both groups), and other serious adverse events did not differ between the two groups. There were three (<1%) deaths in the placebo group that were assessed by investigators, who were masked to study drug assignment, to be treatment-related and two (<1%) deaths in the albiglutide group. Interpretation: In patients with type 2 diabetes and cardiovascular disease, albiglutide was superior to placebo with respect to major adverse cardiovascular events. Evidence-based glucagon-like peptide 1 receptor agonists should therefore be considered as part of a comprehensive strategy to reduce the risk of cardiovascular events in patients with type 2 diabetes. Funding: GlaxoSmithKline

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Poirazi-Lab/dendrify: Dendrify 2.0 release

New and improved implementation of dendritic spikes. New PointNeuronModel class for creating point-neuron models. New way for specifying the electrophysiological properties of neurons. Significantly improved error catching and exception handling. Fixed compatibility issues with Jupyter notebooks. More stable and robust code overall. Added tutorials and code examples. Improved documentation page. Added a support e-mail address. Many minor improvements, bug fixes and quality of life improvements. New logo. Special thanks to Marcel Stimberg, Spyros Chavlis, Nikos Malakasis, Christos Karageorgiou Kaneen and Elisavet Kapetanou for their valuable feedback and suggestions for improving Dendrify

Comparing water and paraffin PCM as storage mediums for thermal energy storage applications

A CFD analysis is performed in two different heat storage mediums, water and paraffin phase change material (PCM), in order to evaluate and compare the two mediums for use in heating thermal energy storage (HTES) applications. The two mediums use different heat storing mechanisms, namely water uses Sensible Heat Storage, and the PCM Latent heat storage. The applied computational domain represents a single tube of a heat exchanger (HE), and so it comprises of a copper tube with aluminium fins. The geometric characteristics of the domain are taken in accordance with commercially used HE’s for HTES applications [1]. The characteristics studied are the stored energy of the system, the temperature of the heat transfer fluid (HTF) in the outlet and the temperature of the storage medium. The results of the simulations showed that for the same mass of storage mediums, the PCM can store more energy than water, for the same temperature of the HTF, as expected. Also, the temperature of the medium for the sensible heat storage rises linearly with the energy stored inside it, while in the latent heat storage mechanism, the temperature of the medium rises linearly till the melting (or solidification) of it, then stays almost steady until the melting of the whole volume and then rises again until it reaches the temperature of the HTF

Testing the performance of a prototype thermal energy storage tank working with organic phase change material for space heating application conditions

A prototype Latent Heat Thermal Energy Storage (LHTES) unit has been designed, constructed, and experimentally analysed for its thermal storage performance under different operational conditions considering heating application and exploiting solar and geothermal energy. The system consists of a rectangular tank filled with Phase Change Material (PCM) and a finned tube staggered Heat Exchanger (HE) while water is used as Heat Transfer Fluid (HTF). Different HTF inlet temperatures and flow rates were tested to find out their effects on LHTES performance. Thermal quantities such as HTF outlet temperature, heat transfer rate, stored energy, were evaluated as a function of the conditions studied. Two commercial organic PCMs were tested A44 and A46. Results indicate that A44 is more efficient during the charging period, taking into account the two energy sources, solar and heat pump. During the discharging process, it exhibits higher storage capacity than A46. Concluding, the developed methodology can be applied to study different PCMs and building applications

Computational Approach of Charging and Discharging Phases in a Novel Compact Solar Collector with Integrated Thermal Energy Storage Tank: Study of Different Phase Change Materials

A numerical study was carried out to investigate charging and discharging processes of different phase change materials (PCMs) used for thermal storage in an innovative solar collector, targeting domestic hot water (DHW) requirements. The aim was to study PCMs that meet all application requirements, considering their thermal performance in terms of stored and retrieved energy, outlet temperatures, and water flow rate. Work was carried out for three flat-plate solar panels of different sizes. For each panel, a PCM tank with a heat exchanger was attached on the back plate. Simulations were conducted on a 2D domain using the enthalpy–porosity technique. Three paraffin-based PCMs were studied, two (A53, P53) with phase-change temperatures of approximately 53 °C and one of approximately 58 °C (A58H). Results showed that, during charging, A58H can store the most energy and A53 the least (12.30 kWh and 10.54 kWh, respectively, for the biggest unit). However, the biggest unit, A58H, takes the most time to be fully charged, i.e., 6.43 h for the fastest feed rate, while the A53 unit charges the fastest, at 4.25 h. The behavior of P53 lies in between A53 and A58H, considering stored energy and charging time. During discharging, all PCMs could provide an adequate DHW amount, even in the worst case, that is, a small unit with a high hot water consumption rate. The A58H unit provides hot water above 40 °C for 10 min, P53 for 11 min, and A53 for 12 min. The DHW production duration increased if a bigger unit was used or if the consumption rate was lower