Energy density in the diet of workers from São Paulo, Brazil, and associated socio-demographic factors*

Objective: This paper aims at analyzing the energy density (ED) of the diet of workers from the city of São Paulo, Southeastern Brazil, and the way this is associated with socio-demographic characteristics, as well as evaluating the relationship between ED and nutrient intake. Methods: A cross-sectional study evaluated the diet of 852 workers using the 24-hour dietary recall; one recall was applied to all individuals and a second one was applied to a sub-sample in order to adjust intrapersonal variability. The ED of the diet was calculated using three methods: inclusion of all solid foods and beverages, excluding water (ED 1); inclusion of all solid foods and beverages containing at least 5 kcal/100g (ED 2); and inclusion of all solid foods, excluding all beverages (ED 3). Linear regression was used to analyze the relationship between ED and socio-demographic variables and the relationship between ED and nutrients was evaluated using Pearson coefficient correlation. Results: Considering the workers' diet, the ED values observed were 1.18 kcal/g, 1.22 kcal/g and 1.73 kcal/g for the ED 1, ED 2, ED 3 methods, respectively. In the multiple regression models, only the age variable was maintained in the final model and showed an inverse association with all ED methods. ED 3 showed an increase in energy density for non-white individuals. Of all studied nutrients, protein was the only one that was not significantly correlated with ED 3 (p = 0.899). Conclusion: The young adults studied had a higher energy-density diet, representing a priority group for nutrition interventions. Regardless of the calculation method used, there is a correlation between ED and nutrients.Objetivo: Analisar a densidade energética (DE) da dieta de trabalhadores da cidade de São Paulo e sua associação com características sociodemográficas, bem como avaliar a relação entre DE e ingestão de nutrientes. Métodos: Estudo transversal que avaliou a dieta de 852 trabalhadores, por meio de recordatório de 24 horas, sendo um recordatório aplicado a todos os indivíduos e um segundo para subamostra, a fim de corrigir a variabilidade intrapessoal. A DE da dieta foi calculada por três métodos: inclusão de todos os alimentos sólidos e das bebidas, excluindo apenas água (DE 1); inclusão de todos os alimentos sólidos e bebidas calóricas que contêm, no mínimo, 5 kcal/100g (DE 2); inclusão de todos os alimentos sólidos e exclusão de todas as bebidas (DE 3). Para analisar a relação entre a DE e as variáveis sociodemográficas utilizou-se regressão linear, e a relação entre DE e nutrientes foi avaliada por meio do coeficiente de correlação de Pearson. Resultados: Para a dieta dos trabalhadores, os valores de DE observados foram 1,18 kcal/g, 1,22 kcal/g e 1,73 kcal/g, considerando-se os métodos DE 1, DE 2 e DE 3, respectivamente. Nos modelos múltiplos de regressão, apenas a variável idade apresentou associação negativa com todos os métodos de DE. Para a DE 3, houve incremento da DE para indivíduos não brancos. Dentre os nutrientes estudados, o único que não apresentou correlação significativa foi a proteína, para DE 3 (p = 0,899). Conclusão: Os adultos jovens tinham uma alimentação com maior DE, sendo um grupo prioriatário para intervenções nutricionais. Além disso, independente do método de cálculo, há correlação entre a DE e os nutrientes da dieta.Universidade de São Paulo Faculdade de Saude Publica Programa de Pos Graduacao em NutricaoUniversidade Federal de São Paulo (UNIFESP) Instituto de Saude e Sociedade Departamento de Saude, Clinica e InstituicoesUniversidade de São Paulo Faculdade de Saude Publica Departamento de NutricaoUNIFESP, Instituto de Saude e Sociedade Depto. de Saude, Clinica e InstituicoesSciEL

Variational approximation for mixtures of linear mixed models

Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm. The conventional approach to determining a suitable number of components is to compare different mixture models using penalized log-likelihood criteria such as BIC.We propose fitting MLMMs with variational methods which can perform parameter estimation and model selection simultaneously. A variational approximation is described where the variational lower bound and parameter updates are in closed form, allowing fast evaluation. A new variational greedy algorithm is developed for model selection and learning of the mixture components. This approach allows an automatic initialization of the algorithm and returns a plausible number of mixture components automatically. In cases of weak identifiability of certain model parameters, we use hierarchical centering to reparametrize the model and show empirically that there is a gain in efficiency by variational algorithms similar to that in MCMC algorithms. Related to this, we prove that the approximate rate of convergence of variational algorithms by Gaussian approximation is equal to that of the corresponding Gibbs sampler which suggests that reparametrizations can lead to improved convergence in variational algorithms as well.Comment: 36 pages, 5 figures, 2 tables, submitted to JCG

Editorial: Addressing community priorities in autism research

Autism is a form of neurodiversity, currently characterized by differences compared to the neurotypical population across multiple domains including sensory processing (Proff et al., 2021), social communication style (Crompton et al., 2021), attentional processing (Murray et al., 2005), and movement and motor processing (Miller et al., 2021). Historically, autism (and thus autistic people) has been studied through a medical lens (Chapman and Carel, 2022), owing primarily to the characterization of autism as a disorder of childhood development. These conceptualizations led to dehumanizing narratives about autistic people (Botha) and have impacted on who we consider to be knowledgeable about what it is like to be autistic (Kourti). In recent years, there has been a shift toward recognition of autism as a form of neurodivergence; a naturally occurring variation in the human population that may lead to a differential profile of strengths and challenges in comparison to the non-autistic population (Den Houting, 2019). This shift has been primarily driven by the autistic self-advocacy and neurodiversity movements (Kapp et al., 2013; Walker, 2021), which have campaigned for better understanding of autistic people

Electrostatic and electrokinetic contributions to the elastic moduli of a driven membrane

We discuss the electrostatic contribution to the elastic moduli of a cell or artificial membrane placed in an electrolyte and driven by a DC electric field. The field drives ion currents across the membrane, through specific channels, pumps or natural pores. In steady state, charges accumulate in the Debye layers close to the membrane, modifying the membrane elastic moduli. We first study a model of a membrane of zero thickness, later generalizing this treatment to allow for a finite thickness and finite dielectric constant. Our results clarify and extend the results presented in [D. Lacoste, M. Cosentino Lagomarsino, and J. F. Joanny, Europhys. Lett., {\bf 77}, 18006 (2007)], by providing a physical explanation for a destabilizing term proportional to \kps^3 in the fluctuation spectrum, which we relate to a nonlinear ($E^2$) electro-kinetic effect called induced-charge electro-osmosis (ICEO). Recent studies of ICEO have focused on electrodes and polarizable particles, where an applied bulk field is perturbed by capacitive charging of the double layer and drives flow along the field axis toward surface protrusions; in contrast, we predict "reverse" ICEO flows around driven membranes, due to curvature-induced tangential fields within a non-equilibrium double layer, which hydrodynamically enhance protrusions. We also consider the effect of incorporating the dynamics of a spatially dependent concentration field for the ion channels.Comment: 22 pages, 10 figures. Under review for EPJ

Physical Processes in Star Formation

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00693-8.Star formation is a complex multi-scale phenomenon that is of significant importance for astrophysics in general. Stars and star formation are key pillars in observational astronomy from local star forming regions in the Milky Way up to high-redshift galaxies. From a theoretical perspective, star formation and feedback processes (radiation, winds, and supernovae) play a pivotal role in advancing our understanding of the physical processes at work, both individually and of their interactions. In this review we will give an overview of the main processes that are important for the understanding of star formation. We start with an observationally motivated view on star formation from a global perspective and outline the general paradigm of the life-cycle of molecular clouds, in which star formation is the key process to close the cycle. After that we focus on the thermal and chemical aspects in star forming regions, discuss turbulence and magnetic fields as well as gravitational forces. Finally, we review the most important stellar feedback mechanisms.Peer reviewedFinal Accepted Versio

The SPECTRA Collaboration OMERACT Special Interest Group: Current Research and Future Directions

Objective High-resolution peripheral quantitative computed tomography (HR-pQCT) has the potential to improve radiographic progression determination in clinical trials and longitudinal observational studies. The goal of this work was to describe the current state of research presented at Outcome Measures in Rheumatology (OMERACT) 2016 and ensuing future directions outlined during discussion among attendees. Methods At OMERACT 2016, SPECTRA (Study grouP for xtrEme-Computed Tomography in Rheumatoid Arthritis) introduced efforts to (1) validate the HR-pQCT according to OMERACT guidelines, focusing on rheumatoid arthritis (RA), and (2) find alternatives for automated joint space width (JSW) analysis. The Special Interest Group (SIG) was presented to patient research partners, physicians/researchers, and SIG leaders followed by a 40-min discussion on future directions. Results A consensus definition for RA erosion using HR-pQCT was demonstrated through a systematic literature review and a Delphi exercise. Histopathology and perfusion studies were presented that analyzed the true characteristics of cortical breaks in HR-pQCT images, and to provide criterion validity. Results indicate that readers were able to discriminate between erosion and small vascular channels. Moderate reliability (ICC 0.206–0.871) of direct erosion size measures was shown, which improved (> 0.9) only when experienced readers were considered. Quantification of erosion size was presented for scoring, direct measurement, and volumetric approaches, as well as a reliability exercise for direct measurement. Three methods for JSW measurement were compared, all indicating excellent reproducibility with differences at the extremes (i.e., near-zero and joint edge thickness). Conclusion Initial reports on HR-pQCT are promising; however, to consider its use in clinical trials and longitudinal observational studies, it is imperative to assess the responsiveness of erosion measurement quantification

Teaching open and reproducible scholarship: a critical review of the evidence base for current pedagogical methods and their outcomes.

YesIn recent years, the scientific community has called for improvements in the credibility, robustness and reproducibility of research, characterized by increased interest and promotion of open and transparent research practices. While progress has been positive, there is a lack of consideration about how this approach can be embedded into undergraduate and postgraduate research training. Specifically, a critical overview of the literature which investigates how integrating open and reproducible science may influence student outcomes is needed. In this paper, we provide the first critical review of literature surrounding the integration of open and reproducible scholarship into teaching and learning and its associated outcomes in students. Our review highlighted how embedding open and reproducible scholarship appears to be associated with (i) students' scientific literacies (i.e. students' understanding of open research, consumption of science and the development of transferable skills); (ii) student engagement (i.e. motivation and engagement with learning, collaboration and engagement in open research) and (iii) students' attitudes towards science (i.e. trust in science and confidence in research findings). However, our review also identified a need for more robust and rigorous methods within pedagogical research, including more interventional and experimental evaluations of teaching practice. We discuss implications for teaching and learning scholarship.UKRI/ESRC rapid call grant, ealth Research Board Applying Researchinto Policy and Practice Fellowship, John Templeton Foundation (grant ID: 62631), Northern Ireland Department for the Economy Research Studentshi

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

Scholarly publishing depends on peer reviewers

The peer-review crisis is posing a risk to the scholarly peer-reviewed journal system. Journals have to ask many potential peer reviewers to obtain a minimum acceptable number of peers accepting reviewing a manuscript. Several solutions have been suggested to overcome this shortage. From reimbursing for the job, to eliminating pre-publication reviews, one cannot predict which is more dangerous for the future of scholarly publishing. And, why not acknowledging their contribution to the final version of the article published? PubMed created two categories of contributors: authors [AU] and collaborators [IR]. Why not a third category for the peer-reviewer?Scopu