Feasibility of a controlled trial aiming to prevent excessive pregnancy-related weight gain in primary health care

<p>Abstract</p> <p>Background</p> <p>Excessive gestational weight gain and postpartum weight retention may predispose women to long-term overweight and other health problems. Intervention studies aiming at preventing excessive pregnancy-related weight gain are needed. The feasibility of implementing such a study protocol in primary health care setting was evaluated in this pilot study.</p> <p>Methods</p> <p>A non-randomized controlled trial was conducted in three intervention and three control maternity and child health clinics in primary health care in Finland. Altogether, 132 pregnant and 92 postpartum women and 23 public health nurses (PHN) participated in the study. The intervention consisted of individual counselling on physical activity and diet at five routine visits to a PHN and of an option for supervised group exercise until 37 weeks' gestation or ten months postpartum. The control clinics continued their usual care. The components of the feasibility evaluation were 1) recruitment and participation, 2) completion of data collection, 3) realization of the intervention and 4) the public health nurses' experiences.</p> <p>Results</p> <p>1) The recruitment rate was slower than expected and the recruitment period had to be prolonged from the initially planned three months to six months. The average participation rate of eligible women at study enrolment was 77% and the drop-out rate 15%. 2) In total, 99% of the data on weight, physical activity and diet and 96% of the blood samples were obtained. 3) In the intervention clinics, 98% of the counselling sessions were realized, their contents and average durations were as intended, 87% of participants regularly completed the weekly records for physical activity and diet, and the average participation percentage in the group exercise sessions was 45%. 4) The PHNs regarded the extra training as a major advantage and the high additional workload as a disadvantage of the study.</p> <p>Conclusion</p> <p>The study protocol was mostly feasible to implement, which encourages conducting large trials in comparable settings.</p> <p>Trial registration</p> <p>Current Controlled Trials ISRCTN21512277</p

Reproductive protein evolution in two cryptic species of marine chordate

<p>Abstract</p> <p>Background</p> <p>Reproductive character displacement (RCD) is a common and taxonomically widespread pattern. In marine broadcast spawning organisms, behavioral and mechanical isolation are absent and prezygotic barriers between species often operate only during the fertilization process. Such barriers are usually a consequence of differences in the way in which sperm and egg proteins interact, so RCD can be manifest as faster evolution of these proteins between species in sympatry than allopatry. Rapid evolution of these proteins often appears to be a consequence of positive (directional) selection. Here, we identify a set of candidate gamete recognition proteins (GRPs) in the ascidian <it>Ciona intestinalis </it>and showed that these GRPs evolve more rapidly than control proteins (those not involved in gamete recognition). Choosing a subset of these gamete recognition proteins that show evidence of positive selection (CIPRO37.40.1, CIPRO60.5.1, CIPRO100.7.1), we then directly test the RCD hypothesis by comparing divergence (omega) and polymorphism (McDonald-Kreitman, Tajima's D, Fu and Li's D and F, Fay and Wu's H) statistics in sympatric and allopatric populations of two distinct forms of <it>C. intestinalis </it>(Types A and B) between which there are strong post-zygotic barriers.</p> <p>Results</p> <p>Candidate gamete recognition proteins from two lineages of <it>C. intestinalis </it>(Type A and B) are evolving more rapidly than control proteins, consistent with patterns seen in insects and mammals. However, ω (d_N/d_S) is not significantly different between the sympatric and allopatric populations, and none of the polymorphism statistics show significant differences between sympatric and allopatric populations.</p> <p>Conclusions</p> <p>Enhanced prezygotic isolation in sympatry has become a well-known feature of gamete recognition proteins in marine broadcast spawners. But in most cases the evolutionary process or processes responsible for this pattern have not been identified. Although gamete recognition proteins in <it>C. intestinalis </it>do appear to evolve more rapidly, on average, than proteins with other functions, rates of evolution are not different in allopatric and sympatric populations of the two reproductively isolated forms. That sympatry is probably human-mediated, and therefore recent, may explain the absence of RCD.</p

Problems recruiting and retaining postnatal women to a pilot randomised controlled trial of a web-delivered weight loss intervention ISRCTN48086713 ISRCTN

Abstract Objective This paper highlights recruitment and retention problems identified during a pilot randomised controlled trial and process evaluation. The pilot trial aimed to evaluate the feasibility and acceptability of a web-delivered weight loss intervention for postnatal women and associated trial protocol. Results General practice database searches revealed low rates of eligible postnatal women per practice. 16 (10%) of the 168 identified women were recruited and randomised, seven to the intervention and nine to the control. 57% (4/7) of the intervention women completed 3 month follow-up measurements in comparison to 56% (5/9) in the control group. By 12 months, retention in the intervention group was 43% (3/7), with 2/7 women active on the website, in comparison to 44% (4/9) of the control group. Interview findings revealed the web as an acceptable method for delivery of the intervention, with the suggestion of an addition of a mobile application. Alternative recruitment strategies, using health visitor appointments, midwifery departments or mother and baby/toddler groups, should be explored. Greater involvement of potential users should enable better recruitment methods to be developed. Trial registration ISRCTN: ISRCTN48086713, Registered 26 October 201

Computational study of noise in a large signal transduction network

<p>Abstract</p> <p>Background</p> <p>Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor.</p> <p>Results</p> <p>We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and <it>β </it>isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased.</p> <p>Conclusions</p> <p>We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies.</p