Dietary patterns during pregnancy and maternal and birth outcomes in women with type 1 diabetes: the Environmental Determinants of Islet Autoimmunity (ENDIA) study.

Aims/hypothesis: Dietary patterns characterised by high intakes of vegetables may lower the risk of pre-eclampsia and premature birth in the general population. The effect of dietary patterns in women with type 1 diabetes, who have an increased risk of complications in pregnancy, is not known. The aim of this study was to investigate the relationship between dietary patterns and physical activity during pregnancy and maternal complications and birth outcomes in women with type 1 diabetes.

Protocol for the Australian Type 1 Diabetes National Screening Pilot: Assessing the feasibility and acceptability of three general population screening models in children.

Aim: One third of Australian children diagnosed with type 1 diabetes present with life-threatening diabetic ketoacidosis (DKA) at diagnosis. Screening for early-stage, presymptomatic type 1 diabetes, with ongoing follow-up, can substantially reduce this risk (<5% risk). Several screening models are being trialled internationally, without consensus on the optimal approach.

Environmental Determinants of Islet Autoimmunity (ENDIA) longitudinal prospective pregnancy to childhood cohort study of Australian children at risk of type 1 diabetes: parental demographics and birth information.

Introduction: The Environmental Determinants of Islet Autoimmunity (ENDIA) Study is an ongoing Australian prospective cohort study investigating how modifiable prenatal and early-life exposures drive the development of islet autoimmunity and type 1 diabetes (T1D) in children. In this profile, we describe the cohort's parental demographics, maternal and neonatal outcomes and human leukocyte antigen (HLA) genotypes.

Research Design And Methods: Inclusion criteria were an unborn child, or infant aged less than 6 months, with a first-degree relative (FDR) with T1D.

SEMA: A free smartphone platform for daily life surveys.

Traditionally, behavioral, social, and health science researchers have relied on global/retrospective survey methods administered cross-sectionally (i.e., on a single occasion) or longitudinally (i.

A review of genetic variant databases and machine learning tools for predicting the pathogenicity of breast cancer.

Studies continue to uncover contributing risk factors for breast cancer (BC) development including genetic variants. Advances in machine learning and big data generated from genetic sequencing can now be used for predicting BC pathogenicity. However, it is unclear which tool developed for pathogenicity prediction is most suited for predicting the impact and pathogenicity of variant effects.

A surge in serum mucosal cytokines associated with seroconversion in children at risk for type 1 diabetes.

Aims/introduction: Autoantibodies to pancreatic islet antigens identify young children at high risk of type 1 diabetes. On a background of genetic susceptibility, islet autoimmunity is thought to be driven by environmental factors, of which enteric viruses are prime candidates. We sought evidence for enteric pathology in children genetically at-risk for type 1 diabetes followed from birth who had developed islet autoantibodies ("seroconverted"), by measuring mucosa-associated cytokines in their sera.

Protocol for a nested case-control study design for omics investigations in the Environmental Determinants of Islet Autoimmunity cohort.

The Environmental Determinants of Islet Autoimmunity (ENDIA) pregnancy-birth cohort investigates the developmental origins of type 1 diabetes (T1D), with recruitment between 2013 and 2019. ENDIA is the first study in the world with comprehensive data and biospecimen collection during pregnancy, at birth and through childhood from at-risk children who have a first-degree relative with T1D. Environmental exposures are thought to drive the progression to clinical T1D, with pancreatic islet autoimmunity (IA) developing in genetically susceptible individuals.

A GDPR-Compliant Dynamic Consent Mobile Application for the Australasian Type-1 Diabetes Data Network.

Australia has a high prevalence of diabetes, with approximately 1.2 million Australians diagnosed with the disease. In 2012, the Australasian Diabetes Data Network (ADDN) was established with funding from the Juvenile Diabetes Research Foundation (JDRF).

Predicting reliability through structured expert elicitation with the repliCATS (Collaborative Assessments for Trustworthy Science) process.

As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predictions about the replicability of research. This process is a structured expert elicitation approach based on a modified Delphi technique applied to the evaluation of research claims in social and behavioural sciences.

Evaluating untimed and timed abridged versions of Raven's Advanced Progressive Matrices.

Introduction: Raven's Advanced Progressive Matrices (APM) are frequently utilized in clinical and experimental settings to index intellectual capacity. As the APM is a relatively long assessment, abridged versions of the test have been proposed. The psychometric properties of an untimed 12-item APM have received some consideration in the literature, but validity explorations have been limited.

Mental Health During Late Pregnancy and Postpartum in Mothers With and Without Type 1 Diabetes: The ENDIA Study.

Objective: Pregnancy and type 1 diabetes are each associated with increased anxiety and depression, but the combined impact on well-being is unresolved. We compared the mental health of women with and without type 1 diabetes during pregnancy and postpartum and examined the relationship between mental health and glycemic control.

Research Design And Methods: Participants were women enrolled from 2016 to 2020 in the Environmental Determinants of Islet Autoimmunity (ENDIA) study, a pregnancy to birth prospective cohort following children with a first-degree relative with type 1 diabetes.

Women with type 1 diabetes exhibit a progressive increase in gut Saccharomyces cerevisiae in pregnancy associated with evidence of gut inflammation.

Aims: Studies of the gut microbiome have focused on its bacterial composition. We aimed to characterize the gut fungal microbiome (mycobiome) across pregnancy in women with and without type 1 diabetes.

Methods: Faecal samples (n = 162) were collected from 70 pregnant women (45 with and 25 without type 1 diabetes) across all trimesters.

Addressing methodological issues in a study of impulsivity and vulnerability for transition to alcohol use disorder.

Background: Heightened behavioral impulsivity has been advocated as a preexisting risk factor for the development of alcohol use disorder (AUD). Nonetheless, studies investigating impulsivity in adolescent/young adult at-risk drinkers-who are at increased risk of developing AUD-report mixed findings. This may be due to methodological limitations related to definitions of at-risk drinking, the retrospective assessment of alcohol intake, and/or the relatively modest sample size of some studies.

Type 1 diabetes in pregnancy is associated with distinct changes in the composition and function of the gut microbiome.

Background: The gut microbiome changes in response to a range of environmental conditions, life events and disease states. Pregnancy is a natural life event that involves major physiological adaptation yet studies of the microbiome in pregnancy are limited and their findings inconsistent. Pregnancy with type 1 diabetes (T1D) is associated with increased maternal and fetal risks but the gut microbiome in this context has not been characterized.

Changes in pancreatic exocrine function in young at-risk children followed to islet autoimmunity and type 1 diabetes in the ENDIA study.

Backgrounds: We aimed to monitor pancreatic exocrine function longitudinally in relation to the development of islet autoimmunity (IA) and type 1 diabetes (T1D) in at-risk children with a first-degree relative with T1D, who were followed prospectively in the Environmental Determinants of Islet Autoimmunity (ENDIA) study.

Methods: Fecal elastase-1 (FE-1) concentration was measured longitudinally in 85 ENDIA children from median age 1.0 (IQR 0.

Comparison of Optimization-Modelling Methods for Metabolites Production in Escherichia coli.

The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite's production.

Overnight/first-morning urine free metanephrines and methoxytyramine for diagnosis of pheochromocytoma and paraganglioma: is this an option?

Objective: Sympathoadrenal activity is decreased during overnight rest. This study assessed whether urinary-free normetanephrine, metanephrine and methoxytyramine in overnight/first-morning urine collections might offer an alternative to measurements in 24-h collections or plasma for diagnosis of pheochromocytoma and paraganglioma (PPGL).

Design And Methods: Prospective multicenter cross-sectional diagnostic study involving 706 patients tested for PPGL, in whom tumors were confirmed in 79 and excluded in 627 after follow-up.

Higher frequency of vertebrate-infecting viruses in the gut of infants born to mothers with type 1 diabetes.

Background: Microbial exposures in utero and early life shape the infant microbiome, which can profoundly impact on health. Compared to the bacterial microbiome, very little is known about the virome. We set out to characterize longitudinal changes in the gut virome of healthy infants born to mothers with or without type 1 diabetes using comprehensive virome capture sequencing.

Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv.

Background: The automation of data analysis in the form of scientific workflows has become a widely adopted practice in many fields of research. Computationally driven data-intensive experiments using workflows enable automation, scaling, adaptation, and provenance support. However, there are still several challenges associated with the effective sharing, publication, and reproducibility of such workflows due to the incomplete capture of provenance and lack of interoperability between different technical (software) platforms.

A non-dominated sorting Differential Search Algorithm Flux Balance Analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout.

Metabolic engineering is defined as improving the cellular activities of an organism by manipulating the metabolic, signal or regulatory network. In silico reaction knockout simulation is one of the techniques applied to analyse the effects of genetic perturbations on metabolite production. Many methods consider growth coupling as the objective function, whereby it searches for mutants that maximise the growth and production rate.

A Smartphone App to Assess Alcohol Consumption Behavior: Development, Compliance, and Reactivity.

Background: There are disadvantages-largely related to cost, participant burden, and missing data-associated with traditional electronic methods of assessing drinking behavior in real time. This potentially diminishes some of the advantages-namely, enhanced sample size and diversity-typically attributed to these methods. Download of smartphone apps to participants' own phones might preserve these advantages.

Distinct Gut Virome Profile of Pregnant Women With Type 1 Diabetes in the ENDIA Study.

Background: The importance of gut bacteria in human physiology, immune regulation, and disease pathogenesis is well established. In contrast, the composition and dynamics of the gut virome are largely unknown; particularly lacking are studies in pregnancy. We used comprehensive virome capture sequencing to characterize the gut virome of pregnant women with and without type 1 diabetes (T1D), longitudinally followed in the Environmental Determinants of Islet Autoimmunity study.

Predictors of Adverse Alcohol Use Consequences Among Tertiary Students.

Background: The alcohol consumption patterns of young adults are of concern. Critically, tertiary students consume greater quantities of alcohol, are at increased risk of injury/harm, and have higher rates of alcohol use disorders as compared to their nonuniversity enrolled peers. The Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ) is one of several tools utilized to explore adverse alcohol-related outcomes among tertiary students.

Identifying a Gene Knockout Strategy Using a Hybrid of Simple Constrained Artificial Bee Colony Algorithm and Flux Balance Analysis to Enhance the Production of Succinate and Lactate in Escherichia Coli.

In recent years, metabolic engineering has gained central attention in numerous fields of science because of its capability to manipulate metabolic pathways in enhancing the expression of target phenotypes. Due to this, many computational approaches that perform genetic manipulation have been developed in the computational biology field. In metabolic engineering, conventional methods have been utilized to upgrade the generation of lactate and succinate in E.