Diet, physical activity, and adiposity in children in poor and rich neighbourhoods: a cross-sectional comparison

BACKGROUND: Obesity in Canadian children increased three-fold in twenty years. Children living in low-income neighborhoods exercise less and are more overweight than those living in more affluent neighborhoods after accounting for family socio-economic status. Strategies to prevent obesity in children have focused on personal habits, ignoring neighborhood characteristics. It is essential to evaluate diet and physical activity patterns in relation to socio-economic conditions to understand the determinants of obesity. The objective of this pilot study was to compare diet, physical activity, and the built environment in two Hamilton area elementary schools serving socio-economically different communities. METHODS: We conducted a cross-sectional study (November 2005-March 2006) in two public elementary schools in Hamilton, Ontario, School A and School B, located in low and high socioeconomic areas respectively. We assessed dietary intake, physical activity, dietary restraint, and anthropometric measures in consenting children in grades 1 and higher. From their parents we assessed family characteristics and walkability of the built environment. RESULTS: 160 children (n = 48, School A and n = 112, School B), and 156 parents (n = 43, School A and n = 113, School B) participated in this study. The parents with children at School A were less educated and had lower incomes than those at School B. The School A neighborhood was perceived to be less walkable than the School B neighborhood. Children at School A consumed more baked foods, chips, sodas, gelatin desserts, and candies and less low fat dairy, and dark bread than those at School B. Children at School A watched more television and spent more time in front of the computer than children studying at School B, but reported spending less time sitting on weekdays and weekends. Children at both schools were overweight but there was no difference in their mean BMI z-scores (School A = 0.65 versus School B = 0.81, p-value = 0.38). CONCLUSION: The determinants of overweight in children may be more complex than imagined. In future intervention programs researchers may consider addressing environmental factors, and customizing lifestyle interventions so that they are closer to community needs

Warming Trend in Antarctic Bottom Water in the Vema Channel in the South Atlantic

The excess heat absorbed from the atmosphere has increased the temperature in the upper layers of the ocean (<2,000 m). In the abyss, infrequently repeated ship sections, deep Argo float measurements, and sparse moored observations have found signs of warming in the Southwest Atlantic, possibly linked to changes in the Weddell Sea. We present a new moored temperature time series sampled near the bottom in the Vema Channel, from February 2019 to August 2020. Together with historical data, the combined record confirms the warming of the abyssal waters, with an increase of 0.059°C in potential temperature between January 1991 and August 2020, embedded within intense high-frequency variability. Moreover, the data suggest the possibility of an accelerated warming, with a change in the temperature trend from 0.0016°C yr−1, between the early 1990s and 2005, to 0.0026°C yr−1 afterwards

Introducing a New Algorithm for Classification of Etiology in Studies on Pediatric Pneumonia: Protocol for the Trial of Respiratory Infections in Children for Enhanced Diagnostics Study

Background: There is a need to better distinguish viral infections from antibiotic-requiring bacterial infections in children presenting with clinical community-acquired pneumonia (CAP) to assist health care workers in decision making and to improve the rational use of antibiotics.Objective: The overall aim of the Trial of Respiratory infections in children for ENhanced Diagnostics (TREND) study is to improve the differential diagnosis of bacterial and viral etiologies in children aged below 5 years with clinical CAP, by evaluating myxovims resistance protein A (MxA) as a biomarker for viral CAP and by evaluating an existing (multianalyte point-of-care antigen detection test system [mariPOC respi] ArcDia International Oy Ltd.) and a potential future point-of-care test for respiratory pathogens.Methods: Children aged 1 to 59 months with clinical CAP as well as healthy, hospital-based, asymptomatic controls will be included at a pediatric emergency hospital in Stockholm, Sweden. Blood (analyzed for MxA and C-reactive protein) and nasopharyngeal samples (analyzed with real-time polymerase chain reaction as the gold standard and antigen-based mariPOC respi test as well as saved for future analyses of a novel recombinase polymerase amplification-based point-of-care test for respiratory pathogens) will be collected. A newly developed algorithm for the classification of CAP etiology will be used as the reference standard.Results: A pilot study was performed from June to August 2017. The enrollment of study subjects started in November 2017. Results are expected by the end of 2019.Conclusions: The findings from the TREND study can be an important step to improve the management of children with clinical CAP

Targeted reprogramming of H3K27me3 resets epigenetic memory in plant paternal chromatin

Epigenetic marks are reprogrammed in the gametes to reset genomic potential in the next generation. In mammals, paternal chromatin is extensively reprogrammed through the global erasure of DNA methylation and the exchange of histones with protamines(1,2). Precisely how the paternal epigenome is reprogrammed in flowering plants has remained unclear since DNA is not demethylated and histones are retained in sperm(3,4). Here, we describe a multi-layered mechanism by which H3K27me3 is globally lost from histone-based sperm chromatin in Arabidopsis. This mechanism involves the silencing of H3K27me3 writers, activity of H3K27me3 erasers and deposition of a sperm-specific histone, H3.10 (ref. (5)), which we show is immune to lysine 27 methylation. The loss of H3K27me3 facilitates the transcription of genes essential for spermatogenesis and pre-configures sperm with a chromatin state that forecasts gene expression in the next generation. Thus, plants have evolved a specific mechanism to simultaneously differentiate male gametes and reprogram the paternal epigenome

Why is the Winner the Best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work

Selection of Salmonella enterica Serovar Typhi Genes Involved during Interaction with Human Macrophages by Screening of a Transposon Mutant Library

The human-adapted Salmonella enterica serovar Typhi (S. Typhi) causes a systemic infection known as typhoid fever. This disease relies on the ability of the bacterium to survive within macrophages. In order to identify genes involved during interaction with macrophages, a pool of approximately 105 transposon mutants of S. Typhi was subjected to three serial passages of 24 hours through human macrophages. Mutants recovered from infected macrophages (output) were compared to the initial pool (input) and those significantly underrepresented resulted in the identification of 130 genes encoding for cell membrane components, fimbriae, flagella, regulatory processes, pathogenesis, and many genes of unknown function. Defined deletions in 28 genes or gene clusters were created and mutants were evaluated in competitive and individual infection assays for uptake and intracellular survival during interaction with human macrophages. Overall, 26 mutants had defects in the competitive assay and 14 mutants had defects in the individual assay. Twelve mutants had defects in both assays, including acrA, exbDB, flhCD, fliC, gppA, mlc, pgtE, typA, waaQGP, SPI-4, STY1867-68, and STY2346. The complementation of several mutants by expression of plasmid-borne wild-type genes or gene clusters reversed defects, confirming that the phenotypic impairments within macrophages were gene-specific. In this study, 35 novel phenotypes of either uptake or intracellular survival in macrophages were associated with Salmonella genes. Moreover, these results reveal several genes encoding molecular mechanisms not previously known to be involved in systemic infection by human-adapted typhoidal Salmonella that will need to be elucidated

ISSN exercise & sport nutrition review: research & recommendations

Sports nutrition is a constantly evolving field with hundreds of research papers published annually. For this reason, keeping up to date with the literature is often difficult. This paper is a five year update of the sports nutrition review article published as the lead paper to launch the JISSN in 2004 and presents a well-referenced overview of the current state of the science related to how to optimize training and athletic performance through nutrition. More specifically, this paper provides an overview of: 1.) The definitional category of ergogenic aids and dietary supplements; 2.) How dietary supplements are legally regulated; 3.) How to evaluate the scientific merit of nutritional supplements; 4.) General nutritional strategies to optimize performance and enhance recovery; and, 5.) An overview of our current understanding of the ergogenic value of nutrition and dietary supplementation in regards to weight gain, weight loss, and performance enhancement. Our hope is that ISSN members and individuals interested in sports nutrition find this review useful in their daily practice and consultation with their clients

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing