Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies

Background Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. Methods and findings We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. Conclusions This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.This collaborative project received funding from the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 733206 LifeCycle, Grand Recipient VWVJ; Grant Agreement No. 824989 EUCAN-Connect, Grand Recipient AMNA). Please, see S1 Appendix for list of cohort-specific funding/support. DAL is supported by the UK Medical Research Council (MC_UU_00011/6) and British Heart Foundation (CH/F/20/90003 and AA/18/7/34219). RCW is supported by UKRI Innovation Fellowship with Health Data Research UK [MR/S003959/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Comparison of early-, late-, and non-participants in a school-based asthma management program for urban high school students

<p>Abstract</p> <p>Background</p> <p>To assess bias and generalizability of results in randomized controlled trials (RCT), investigators compare participants to non-participants or early- to late-participants. Comparisons can also inform the recruitment approach, especially when working with challenging populations, such as urban adolescents. In this paper, we describe characteristics by participant status of urban teens eligible to participate in a RCT of a school-based, web-based asthma management program.</p> <p>Methods</p> <p>The denominator for this analysis was all students found to be eligible to participate in the RCT. Data were analyzed for participants and non-participants of the RCT, as well as for students that enrolled during the initially scheduled recruitment period (early-participants) and persons that delayed enrollment until the following fall when recruitment was re-opened to increase sample size (late-participants). Full Time Equivalents (FTEs) of staff associated with recruitment were estimated.</p> <p>Results</p> <p>Of 1668 teens eligible for the RCT, 386 enrolled early, and 36 enrolled late, leaving 1246 non-participants. Participants were younger (p < 0.01), more likely to be diagnosed, use asthma medication, and have moderate-to-severe disease than non-participants, odds ratios (95% Confidence Intervals) = 2.1(1.7-2.8), 1.7(1.3-2.1), 1.4(1.0-1.8), respectively. ORs were elevated for the association of late-participation with Medicaid enrollment, 1.9(0.7-5.1) and extrinsic motivation to enroll, 1.7(0.6-5.0). Late-participation was inversely related to study compliance for teens and caregivers, ORs ranging from 0.1 to 0.3 (all p-values < 0.01). Early- and late-participants required 0.45 FTEs/100 and 3.3 FTEs/100, respectively.</p> <p>Conclusions</p> <p>Recruitment messages attracted youth with moderate-to-severe asthma, but extending enrollment was costly, resulting in potentially less motivated, and certainly less compliant, participants. Investigators must balance internal versus external validity in the decision to extend recruitment. Gains in sample size and external validity may be offset by the cost of additional staff time and the threat to internal validity caused by lower participant follow-up.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00201058">NCT00201058</a></p

The two phases of the Cambrian Explosion

Abstract The dynamics of how metazoan phyla appeared and evolved – known as the Cambrian Explosion – remains elusive. We present a quantitative analysis of the temporal distribution (based on occurrence data of fossil species sampled in each time interval) of lophotrochozoan skeletal species (n = 430) from the terminal Ediacaran to Cambrian Stage 5 (~545 – ~505 Million years ago (Ma)) of the Siberian Platform, Russia. We use morphological traits to distinguish between stem and crown groups. Possible skeletal stem group lophophorates, brachiopods, and molluscs (n = 354) appear in the terminal Ediacaran (~542 Ma) and diversify during the early Cambrian Terreneuvian and again in Stage 2, but were devastated during the early Cambrian Stage 4 Sinsk extinction event (~513 Ma) never to recover previous diversity. Inferred crown group brachiopod and mollusc species (n = 76) do not appear until the Fortunian, ~537 Ma, radiate in the early Cambrian Stage 3 (~522 Ma), and with minimal loss of diversity at the Sinsk Event, continued to diversify into the Ordovician. The Sinsk Event also removed other probable stem groups, such as archaeocyath sponges. Notably, this diversification starts before, and extends across the Ediacaran/Cambrian boundary and the Basal Cambrian Carbon Isotope Excursion (BACE) interval (~541 to ~540 Ma), ascribed to a possible global perturbation of the carbon cycle. We therefore propose two phases of the Cambrian Explosion separated by the Sinsk extinction event, the first dominated by stem groups of phyla from the late Ediacaran, ~542 Ma, to early Cambrian stage 4, ~513 Ma, and the second marked by radiating bilaterian crown group species of phyla from ~513 Ma and extending to the Ordovician Radiation

Studying microRNAs in lymphoma

MicroRNAs (miRNAs) play important roles in development, differentiation, homeostasis, and also in diseases such as lymphoma. This chapter describes methods to study the role of miRNAs in lymphoma. First, we describe a multiplex RT reaction followed by qPCR that can be used to determine differential expression of candidate miRNAs. Second, we provide a protocol for stable overexpression of miRNAs using lentiviral-based ectopic expression systems. Third, we describe a straightforward assay to determine whether the candidate miRNA may function as an oncogene or a tumor suppressor gene in lymphomagenesis

A methodology for modelling energy-related human behaviour: Application to window opening behaviour in residential buildings

An energy simulation of a building is a mathematical representation of its physical behaviour considering all the thermal, lighting, acoustics aspects. However, a simulation cannot precisely replicate a real construction because all the simulations are based on a number of key assumptions that affect the results accuracy. Above all, the real energy performance can be affected by the actual behaviour of the building occupants. Thus, there are great benefits to be derived from improving models that simulate the behaviour of human beings within the context of engineered complex systems. The occupant behaviour related to the building control potentialities is a very complex process that has been studied only in the last years with some focuses related to natural ventilation (window opening behaviour), space heating energy demand (in particular the adjustments in the temperature set-point) and natural light (focusing on window blinds adjustments). In this paper, a methodology is presented to model the user behaviour in the context of real energy use and applied to a case study. The methodology, based on a medium/long-term monitoring, is aimed at shifting towards a probabilistic approach for modelling the human behaviour related to the control of indoor environment. The procedure is applied at models of occupants' interactions with windows (opening and closing behaviour). Models of occupants' window opening behaviour were inferred based on measurements and implemented in a simulation program. Simulation results were given as probability distributions of energy consumption and indoor environmental quality depending on user behaviou