Prevalence and Risk Factors of Gestational Diabetes in Twin Pregnancies: Population Based Study

Objective: To assess the prevalence and risk factors of gestational diabetes (GDM) in twin compared with singleton pregnancies. Methods: Population-based study using CDC birth data from 2016-2020. Higher order pregnancies and pre-pregnancy diabetes were excluded. A Chi-square test of independence was performed to identify significant factors associated with GDM in twin versus singleton pregnancies and within each group independently. Multivariable regression analyses were performed first to assess risk factors that are significantly associated with GDM in twins and second to assess the risk of GDM in twin compared with singletons, adjusted for the significant risk factors. P value<0.01 was considered statistically significant Results: Total of 18,173,365 singleton and 611,043 twin pregnancies were included during the study period. Following the regression model, maternal age≥30 years, nulliparous, IVF, chronic hypertension, Hispanic and Non-Hispanic (NH) Asian, foreign-born, overweight and obesity class I/II/II remained significantly associated with GDM in twins. However, maternal age<25 years, NH Black, and W.I.C program reduced that risk. Factors that more than doubled the risk in twins were maternal age≥40 years (OR 2.06 (1.97 – 2.14), P<0.001), NH Asian (OR 2.12 (2.04 – 2.20), P<0.001), and obesity class I, II, and III (OR: 2.22 (2.16 – 2.29), P<0.001, OR:3.01 (2.92 – 3.11), P<0.001, OR: 3.80 (3.67 – 3.93), p<0.001, respectively). Following adjustment for all the significant risk factors, twin pregnancy remained significantly associated with increasing the risk of GDM in twin compared to singleton pregnancies (OR 1.22 (1.21 – 1.23), P<0.001). Conclusion: Of the significant risk factors, maternal age≥40 years, NH Asian, and obesity class I, II, and III more than doubled the risk of GDM in twins. Regardless of maternal demographics, obstetric history, and endocrine factors, twin pregnancy remained significantly associated with GDM compared to singleton pregnancies. These factors can be used in risk prediction models to better counsel and manage twin pregnancies

Formal Model-Based Assurance Cases in Isabelle/SACM : An Autonomous Underwater Vehicle Case Study

Isabelle/SACM is a tool for automated construction of model-based assurance cases with integrated formal methods, based on the Isabelle proof assistant. Assurance cases show how a system is safe to operate, through a human comprehensible argument demonstrating that the requirements are satisfied, using evidence of various provenances. They are usually required for certification of critical systems, often with evidence that originates from formal methods. Automating assurance cases increases rigour, and helps with maintenance and evolution. In this paper we apply Isabelle/SACM to a fragment of the assurance case for an autonomous underwater vehicle demonstrator. We encode the metric unit system (SI) in Isabelle, to allow modelling requirements and state spaces using physical units. We develop a behavioural model in the graphical RoboChart state machine language, embed the artifacts into Isabelle/SACM, and use it to demonstrate satisfaction of the requirements

Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design

Importance Pregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER-Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads. Methods RECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators. Discussion RECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero

The near field in the mixing of a three-dimensional inclined pollutant jet with a crossflow

International audienceAn experimental investigation was carried out to study the structure of the flow field resulting from the interaction of an inclined pollutant jet with a crossflow. The study of the flow field was conducted in a wind tunnel test by means of particle image velocimetry (PIV) system. As the jet was discharged with a variable angle, the resulting flow as been found to be quite complex owing to its three-dimensional nature and the interaction between several flow regions. Results showed the dependence of the emerging jet flow structure on its ratio velocity and the Reynolds number. Extensive wind tunnel experimental results are presented; they concern the Kelvin-Helmholtz vortical structures and the effect of the velocity ratio $v_0/u_\infty$. on the interacting zone. A three-dimensional numerical model with a second-order turbulent model (RSM) and a nonuniform grid system is used to examine the behavior of the emerging jet. The comparison of the numerical and experimental results gives satisfactory agreement

Investigating Intra-Individual Networks of Response Inhibition and Interference Resolution using 7T MRI data

This repository contains the data from the published paper 'Investigating Intra-Individual Networks of Response Inhibition and Interference Resolution using 7T MRI data'. Included files are T1w anatomical images, exam card, top ups, event files, epi images, physiological data, and demographic data. The two tasks used are the stop signal task (SST) and the multi-source interference task (MSIT). For a full description of this data please see the referenced publication.</p

Investigating Intra-Individual Networks of Response Inhibition and Interference Resolution using 7T MRI data

This repository contains the data from the published paper 'Investigating Intra-Individual Networks of Response Inhibition and Interference Resolution using 7T MRI data'. Included files are T1w anatomical images, exam card, top ups, event files, epi images, physiological data, and demographic data. The two tasks used are the stop signal task (SST) and the multi-source interference task (MSIT). For a full description of this data please see the referenced publication.</p