Intuitive Eating Behavior, Diet Quality and Metabolic Health in the Postpartum in Women with Gestational Diabetes

Little is known regarding intuitive eating (IE), diet quality and adherence. We investigated the associations between IE, diet quality and metabolic health after gestational diabetes (GDM), who have an increased diabetes risk. Data from 179 women with GDM from MySweetheart trial (NCT02872974) were analyzed. IE was assessed using the eating for physical rather than emotional reasons (EPR) and reliance on hunger and satiety cues (RHSC) subscales of the French Intuitive Eating Scale-2. Metabolic outcomes included weight, central body fat and insulin resistance. Diet quality was calculated using the Alternative Health Eating Index (AHEI) and compliance with national recommendations was evaluated. Both IE subscales were associated with lower BMI and fat mass (BIA) at 1-year postpartum (all p ≤ 0.034). The EPR subscale inversely correlated with fat mass (DXA) and visceral adipose tissue (both p ≤ 0.028), whereas RHSC with higher insulin sensitivity (Matsuda, p = 0.034). RHSC during pregnancy predicted increased AHEI (p = 0.043) at 1-year postpartum, whilst EPR predicted lower fat mass and insulin resistance (HOMA-IR) (all p ≤ 0.04). In longitudinal analyses, both subscales were associated with increased adherence to dairy and fiber intake recommendations (both p ≤ 0.023). These data suggest IE may be an interesting approach to improve diet quality and metabolic outcomes in women with GDM

Consequences of gestational diabetes mellitus on neonatal cardiovascular health: MySweetHeart Cohort study

Hyperglycaemic disorders of pregnancy are associated with offspring cardiovascular alterations. MySweetHeart cohort study aimed to assess the effect of maternal gestational diabetes (GDM) on offsprings' cardiovascular health. Newborns underwent clinical and echocardiographic examinations between 2016 and 2020. Compared to mothers without GDM (n = 141), mothers with GDM (n = 123) were more likely to have had GDM in previous pregnancies and had higher weight, BMI, blood glucose, and HbA1c. Newborns of both groups showed similar clinical characteristics. Echocardiography was performed on the 3rd (interquartile range, IQR, 2nd-4th) day of life in 101 offsprings of mothers without and 116 offsprings of mothers with GDM. Left ventricular (LV) mass was similar. Children born to mothers with GDM had a thicker posterior LV wall (z-score +0.15, IQR -0.38/0.62, versus +0.47, IQR -0.11/+1.1, p = 0.004), a smaller end-systolic (1.3 mL, IQR 1.0-1.5 mL, versus 1.4 mL, IQR 1.2-1.8 mL, p = 0.044) but a similar end-diastolic LV volume. They also had shorter tricuspid valve flow duration and aortic valve ejection time, lower tricuspid E-wave and pulmonary valve velocities. Newborns of mothers with or without GDM had similar clinical characteristics and LV mass. However, some echocardiographic differences were detected, suggesting an altered myocardial physiology among infants of mothers with GDM. ClinicalTrials.gov (NCT02872974). Hyperglycaemic disorders of pregnancy are known to be associated with offspring cardiovascular alterations. Clinical characteristics and estimated left ventricular (LV) mass were similar in children issued from mothers with and without gestational diabetes (GDM). Children born to mothers with GDM had a thicker posterior LV wall and a smaller end-systolic LV volume. Although LV mass is not different, myocardial physiology may be altered in these infants. Further studies should investigate the endothelial function of this population and the cardiovascular evolution of these children over time

Effect of the MySweetheart randomized controlled trial on birth, anthropometric and psychobehavioral outcomes in offspring of women with GDM

IntroductionGestational diabetes mellitus (GDM) may negatively affect offspring outcomes. A lifestyle intervention may therefore not only improve maternal, but also offspring outcomes. The effects of lifestyle interventions on birth, anthropometric, and psychobehavioral outcomes in offspring of women with GDM need further evidence.DesignThe MySweetheart trial is a monocentric single-blind randomized controlled trial in 211 women with GDM. It tested the effect of a pre- and postpartum multidimensional interdisciplinary lifestyle and psychosocial intervention focusing on both the mothers and their infants and its effects on maternal (primary outcomes) and offspring (secondary outcomes) metabolic and psychobehavioral outcomes compared with guidelines-based usual-care. This paper focuses on offspring’s birth, anthropometric, and maternal report of psychobehavioral outcomes at singular timepoints.MethodsWomen with GDM aged ≥18 years, between 24-32 weeks of gestation, speaking French or English were included and randomly allocated to either the intervention or to an active guidelines-based usual-care group using a 1:1 allocation ratio. The intervention lasted from pregnancy until 1 year postpartum and focused on improving diet, physical activity, and mental health in the mother. For the offspring it focused on supporting breastfeeding, delaying the timing of introduction of solid foods, reducing the consumption of sweetened beverages, increasing physical activity of the family, and improving parental responsiveness to infant distress, hunger, satiety and sleeping cues, and difficult behavior.ResultsAdverse birth and neonatal outcomes rarely occurred overall. There were no differences between groups in offspring birth, neonatal, anthropometric, or psychobehavioral outcomes up to one year. After adjustments for maternal age and the offspring’s sex and age, there was a borderline significant between-group difference in birth length (β:-0.64, CI:-1.27; -0.01, p: 0.05), i.e., offspring of mothers in the intervention group were born 0.64 cm shorter compared to those in the usual-care group.ConclusionThis is the first pre- and postpartum multidimensional interdisciplinary lifestyle and psychosocial intervention in GDM focusing on both the mother and the offspring. It did not lead to a significant improvement in most birth, anthropometric, and psychobehavioral outcomes in offspring of women with GDM. ClinicalTrials.gov Identifier: NCT0289069

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

Exploring deep microbial life in coal-bearing sediment down to ~2.5 km below the ocean floor

Peer reviewedPostprin

Building a transdisciplinary expert consensus on the cognitive drivers of performance under pressure: An international multi-panel Delphi study

IntroductionThe ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure.MethodsInternational experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance.ResultsSixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control—Performance Monitoring; (3) Arousal and Regulatory Systems—Arousal; (4) Cognitive Control—Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control—Response Selection and Inhibition/Suppression; (6) Working memory—Flexible Updating; (7) Working memory—Active Maintenance; (8) Perception and Understanding of Self—Self-knowledge; (9) Working memory—Interference Control, and (10) Expert-suggested—Shifting.DiscussionOur results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Gestational Diabetes Mellitus

Based on the Hyperglycemia and Adverse Pregnancy Outcome study, new universal screening recommendations and cut-offs for gestational diabetes mellitus (GDM) have been proposed. In addition to the immediate perinatal risk, GDM carries an increased risk of metabolic disease in the mother and child. Maternal obesity has even been shown to be associated with increased all-cause mortality in offspring. In addition to known risk factors, excessive gestational weight gain, increased fat consumption, a low vitamin D level, psychological stress and negative mood are risk factors for GDM. Regarding therapy, the US Preventive Task Force concluded in 2013 that GDM treatment significantly reduces the risks of pre-eclampsia, macrosomia and shoulder dystocia (relative risks of 0.62, 0.5 and 0.42, respectively). Although nutrition therapy represents a cornerstone in GDM management, the results of studies are not clear regarding which types of dietary advice are the most suitable. Most physical activity interventions improve glucose control and/or reduce insulin use. Recent studies have evaluated and provided more information about treatment with metformin or glyburide. Postpartum management is essential and should focus on long-term screening and diabetes prevention strategies