Childhood Differences in Healthcare Utilization Between Extremely Preterm Infants and the General Population.

Post-discharge clinical needs of extremely preterm (EP) infants are not well defined. The aim of this study is to evaluate healthcare utilization after discharge in infants born EP and compare it to the general pediatric population. This study involved a post hoc analysis of infants born 24-0/7 to 27-6/7 weeks' gestation enrolled in the Preterm Erythropoietin Neuroprotection (PENUT) Trial who had at least one follow-up survey representing their course between 24 and 60 months of age.

Screen Time Is Associated With Cardiometabolic and Cardiovascular Disease Risk in Childhood and Adolescence.

Background: Screen time in children and adolescents may be linked to cardiometabolic and cardiovascular risk.

Methods: We analyzed data from >1000 participants in the COPSAC2010 and COPSAC2000 (Copenhagen Prospective Studies on Asthma in Childhood) mother-child 2000 and 2010 cohorts. Discretionary screen time, reported by parents or self, was assessed in relation to a composite cardiometabolic risk score based on scores of waist circumference, systolic blood pressure, high-density lipoprotein cholesterol, triglycerides, and glucose.

A Mg-Chelatase Subunit I Missense Mutant in Barley Exhibits a Cold-Sensitive Phenotype Under Field Conditions.

The pale-green barley mutant xan-h.chli-1 has a HvCHLI subunit of Mg-chelatase with an Arg-to-Lys substitution at position 298 and exhibits a unique cold-sensitive phenotype. Under winter field conditions, xan-h.

Risk behaviours and non-atopic comorbidities of adolescents with asthma.

Background: Risk behaviours, obesity, and neuropsychiatric comorbidity have been demonstrated in various chronic diseases but are less well described among adolescents with asthma.

Methods: We clinically assessed asthma status at the 18-year follow-up visit of the Danish Copenhagen Prospective Studies on Asthma in Childhood (COPSAC) birth cohort born to mothers with asthma, and we investigated risk behaviours and non-atopic comorbidities. We included obesity and neuropsychiatric diseases captured from medical records and electronic questionnaires on behavioural traits and psychopathology.

Establishment of a Stable BK Polyomavirus-Secreting Cell Line: Characterization of Viral Genome Integration and Replication Dynamics Through Comprehensive Analysis.

Polyomaviruses have the potential to cause significant morbidity not only in transplant medicine, but also in other forms of disease or variants of immunosuppression. In kidney transplant recipients or recipients of human stem cell transplants, the BK-Virus is the major proponent of manifestations such as BKPyV-associated nephropathy or hemorrhagic cystitis. As no polyomavirus-specific drug with proven in vivo effects has been developed so far, methods to screen for such drugs are important.

Maternal interleukin 6 in pregnancy is associated with executive functioning in 10-year-old children.

Background: Elevated maternal interleukin 6 (IL-6) during pregnancy has been associated with adverse fetal brain development and neurodevelopmental disorders, which often involve executive functioning (EF) impairments. However, the association between maternal IL-6 levels during pregnancy and EF remains largely unexplored.

Methods: The COPSYCH study is based on the prospective COPSAC2010 birth cohort of 700 mother-child pairs, recruited during pregnancy.

Maternal dietary patterns, breastfeeding duration, and their association with child cognitive function and head circumference growth: A prospective mother-child cohort study.

Background: Early life is a critical period for neurodevelopment, where factors such as maternal nutrition and breastfeeding duration significantly impact the growth of head circumference and cognitive development in children. Our study aimed to explore the associations between maternal dietary patterns during pregnancy, duration of breastfeeding, and their impacts on child head circumference and cognitive outcomes.

Methods And Findings: Our study utilised data from the Copenhagen Prospective Studies on Asthma in Childhood 2010 cohort, which enrolled 700 mother-child pairs between 2008 and 2010 with 86% clinical follow-up at age 10.

Mutations in HEADING DATE 1 affect transcription and cell wall composition in rice.

Plants utilize environmental information to modify their developmental trajectories for optimal survival and reproduction. Over a century ago, day length (photoperiod) was identified as a major factor influencing developmental transitions, particularly the shift from vegetative to reproductive growth. In rice (Oryza sativa), exposure to day lengths shorter than a critical threshold accelerates flowering, while longer days inhibit this process.

A western dietary pattern during pregnancy is associated with neurodevelopmental disorders in childhood and adolescence.

Despite the high prevalence of neurodevelopmental disorders, the influence of maternal diet during pregnancy on child neurodevelopment remains understudied. Here we show that a western dietary pattern during pregnancy is associated with child neurodevelopmental disorders. We analyse self-reported maternal dietary patterns at 24 weeks of pregnancy and clinically evaluated neurodevelopmental disorders at 10 years of age in the COPSAC2010 cohort (n = 508).

Boosting photosynthesis opens new opportunities for agriculture sustainability and circular economy: The BEST-CROP research and innovation action.

There is a need for ground-breaking technologies to boost crop yield, both grains and biomass, and their processing into economically competitive materials. Novel cereals with enhanced photosynthesis and assimilation of greenhouse gasses, such as carbon dioxide and ozone, and tailored straw suitable for industrial manufacturing, open a new perspective for the circular economy. Here we describe the vision, strategies, and objectives of BEST-CROP, a Horizon-Europe and United Kingdom Research and Innovation (UKRI) funded project that relies on an alliance of academic plant scientists teaming up with plant breeding companies and straw processing companies to use the major advances in photosynthetic knowledge to improve barley biomass and to exploit the variability of barley straw quality and composition.

Longitudinal Metabolomics Data Analysis Informed by Mechanistic Models.

: Metabolomics measurements are noisy, often characterized by a small sample size and missing entries. While data-driven methods have shown promise in terms of analyzing metabolomics data, e.g.

Integrative structural analysis of Pseudomonas phage DEV reveals a genome ejection motor.

DEV is an obligatory lytic Pseudomonas phage of the N4-like genus, recently reclassified as Schitoviridae. The DEV genome encodes 91 ORFs, including a 3398 amino acid virion-associated RNA polymerase (vRNAP). Here, we describe the complete architecture of DEV, determined using a combination of cryo-electron microscopy localized reconstruction, biochemical methods, and genetic knockouts.

A missense mutation in the barley Xan-h gene encoding the Mg-chelatase subunit I leads to a viable pale green line with reduced daily transpiration rate.

The barley mutant xan-h.chli-1 shows phenotypic features, such as reduced leaf chlorophyll content and daily transpiration rate, typical of wild barley accessions and landraces adapted to arid climatic conditions. The pale green trait, i.

Revealing static and dynamic biomarkers from postprandial metabolomics data through coupled matrix and tensor factorizations.

Introduction: Longitudinal metabolomics data from a meal challenge test contains both fasting and dynamic signals, that may be related to metabolic health and diseases. Recent work has explored the multiway structure of time-resolved metabolomics data by arranging it as a three-way array with modes: subjects, metabolites, and time. The analysis of such dynamic data (where the fasting data is subtracted from postprandial states) reveals dynamic markers of various phenotypes, and differences between fasting and dynamic states.

Characterizing human postprandial metabolic response using multiway data analysis.

Introduction: Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time.

Objectives: Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.

Fish oil supplementation during pregnancy, anthropometrics, and metabolic health at age ten: A randomized clinical trial.

Background: We previously reported that children of mothers who received fish oil supplementation during pregnancy had higher body mass index [BMI (in kg/m)] at 6 y of age as well as a concomitant increase in fat-, muscle, and bone mass, but no difference in fat percentage.

Objectives: Here, we report follow-up at age 10 y including assessment of metabolic health.

Methods: This is a follow-up analysis of a randomized clinical trial conducted among 736 pregnant females and their offspring participating in the Copenhagen Prospective Studies on Asthma in Childhood mother-child cohort.

Vertical Metabolome Transfer from Mother to Child: An Explainable Machine Learning Method for Detecting Metabolomic Heritability.

Vertical transmission of metabolic constituents from mother to child contributes to the manifestation of disease phenotypes in early life. This study probes the vertical transmission of metabolites from mothers to offspring by utilizing machine learning techniques to differentiate between true mother-child dyads and randomly paired non-dyads. Employing random forests (RF), light gradient boosting machine (LGBM), and logistic regression (Elasticnet) models, we analyzed metabolite concentration discrepancies in mother-child pairs, with maternal plasma sampled at 24 weeks of gestation and children's plasma at 6 months.

A Western Dietary Pattern during Pregnancy is Associated with Neurodevelopmental Disorders in Childhood and Adolescence.

Despite the high prevalence of neurodevelopmental disorders, there is a notable gap in clinical studies exploring the impact of maternal diet during pregnancy on child neurodevelopment. This observational clinical study examined the association between pregnancy dietary patterns and neurodevelopmental disorders, as well as their symptoms, in a prospective cohort of 10-year-old children (n=508). Data-driven dietary patterns were derived from self-reported food frequency questionnaires.

Analyzing postprandial metabolomics data using multiway models: a simulation study.

Background: Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as a subjects by metabolites by time points array. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data.

High-dose vitamin D3 supplementation in pregnancy and risk of neurodevelopmental disorders in the children at age 10: A randomized clinical trial.

Background: Vitamin D deficiency in pregnancy may increase the risk of autism and attention deficit hyperactivity disorder (ADHD).

Objective: The objective of this study was to estimate the effect of vitamin D3 supplementation in pregnancy on risk of autism and ADHD.

Design: This randomized clinical trial was part of the COpenhagen Prospective Study on Neuro-PSYCHiatric Development (COPYCH) project nested within the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010) cohort comprising a population-based sample of 700 healthy mother-child pairs enrolled at week 24 of pregnancy.

Maternal inflammation during pregnancy is associated with risk of ADHD in children at age 10.

Introduction: Maternal inflammation during pregnancy may affect early neurodevelopment in offspring as suggested by preclinical and register data. However, clinical evidence for risk of aberrant neurodevelopment later in childhood is scarce. In the population-based COPSAC mother-child cohort, we investigated associations between maternal inflammation levels during pregnancy and the risk of a diagnosis of ADHD as well as the load of ADHD symptoms in the children at age 10.

Effect of diet and genotype on the miRNome of mice with altered lipoprotein metabolism.

The molecular mechanism by which lipid/lipoprotein biosynthesis is regulated in mammals involves a very large number of genes that are subject to multiple levels of regulation. miRNAs are recognized contributors to lipid homeostasis at the post-transcriptional level, although the elucidation of their role is made difficult by the multiplicity of their targets and the ability of more miRNAs to affect the same mRNAs. In this study, an evaluation of how miRNA expression varies in organs playing a key role in lipid/lipoprotein metabolism was conducted in control mice and in two mouse models carrying genetic ablations which differently affect low-density lipoprotein metabolism.

Rice florigens control a common set of genes at the shoot apical meristem including the F-BOX BROADER TILLER ANGLE 1 that regulates tiller angle and spikelet development.

Rice flowering is triggered by transcriptional reprogramming at the shoot apical meristem (SAM) mediated by florigenic proteins produced in leaves in response to changes in photoperiod. Florigens are more rapidly expressed under short days (SDs) compared to long days (LDs) and include the HEADING DATE 3a (Hd3a) and RICE FLOWERING LOCUS T1 (RFT1) phosphatidylethanolamine binding proteins. Hd3a and RFT1 are largely redundant at converting the SAM into an inflorescence, but whether they activate the same target genes and convey all photoperiodic information that modifies gene expression at the SAM is currently unclear.

HaploCoV: unsupervised classification and rapid detection of novel emerging variants of SARS-CoV-2.

Accurate and timely monitoring of the evolution of SARS-CoV-2 is crucial for identifying and tracking potentially more transmissible/virulent viral variants, and implement mitigation strategies to limit their spread. Here we introduce HaploCoV, a novel software framework that enables the exploration of SARS-CoV-2 genomic diversity through space and time, to identify novel emerging viral variants and prioritize variants of potential epidemiological interest in a rapid and unsupervised manner. HaploCoV can integrate with any classification/nomenclature and incorporates an effective scoring system for the prioritization of SARS-CoV-2 variants.