Autoimmune conditions and comorbid depression in pregnancy: examining the risk of preterm birth and preeclampsia.

ObjectiveThe objective of this study was to determine whether prenatal depression interacts with autoimmune conditions to further increase the risk of preterm birth or preeclampsia.Study designOur sample included 3034 pregnant women with rheumatoid arthritis (RA), Crohn's disease (CD) or psoriasis, or controls that were prospectively enrolled into MothertoBaby pregnancy studies. We estimated the independent and joint effects of the three autoimmune conditions and depression on the select outcomes.ResultsWe found an increased risk of preterm birth among women with RA (2.10; 95% confidence interval (CI) 1.54, 2.87), CD (1.87; 95% CI 1.25, 2.81) or psoriasis (1.88; 95% CI 1.27, 2.79) independent of depression status. RA was also independently associated with preeclampsia. Prenatal depression was not independently associated with preterm birth or preeclampsia, nor was there any synergism with autoimmune conditions.ConclusionIf these findings are confirmed, the absence of synergism should be encouraging news to the many women with select autoimmune conditions and depression in pregnancy

Training response inhibition to reduce food consumption: Mechanisms, stimulus specificity and appropriate training protocols.

Published onlineJournal ArticleThis is the final version of the article. Available from Elsevier via the DOI in this record.Training individuals to inhibit their responses towards unhealthy foods has been shown to reduce food intake relative to a control group. Here we aimed to further explore these effects by investigating the role of stimulus devaluation, training protocol, and choice of control group. Restrained eaters received either inhibition or control training using a modified version of either the stop-signal or go/no-go task. Following training we measured implicit attitudes towards food (Study 1) and food consumption (Studies 1 and 2). In Study 1 we used a modified stop-signal training task with increased demands on top-down control (using a tracking procedure and feedback to maintain competition between the stop and go processes). With this task, we found no evidence for an effect of training on implicit attitudes or food consumption, with Bayesian inferential analyses revealing substantial evidence for the null hypothesis. In Study 2 we removed the feedback in the stop-signal training to increase the rate of successful inhibition and revealed a significant effect of both stop-signal and go/no-go training on food intake (compared to double-response and go training, respectively) with a greater difference in consumption in the go/no-go task, compared with the stop-signal task. However, results from an additional passive control group suggest that training effects could be partly caused by increased consumption in the go control group whereas evidence for reduced consumption in the inhibition groups was inconclusive. Our findings therefore support evidence that inhibition training tasks with higher rates of inhibition accuracy are more effective, but prompt caution for interpreting the efficacy of laboratory-based inhibition training as an intervention for behaviour change.This project was supported by a PhD studentship from the School of Psychology, Cardiff University (to R. Adams) and a Biotechnology and Biological Sciences Research Council Grant (BB/K008277/1) to C. Chambers and F. Verbruggen. F Verbruggen is supported by a starting grant from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC Grant Agreement No. 312445. R. Adams was principally responsible for all parts of the paper. N. Lawrence, F. Verbruggen and C. Chambers made substantial contributions to all parts of the paper. C. Chambers was senior author and oversaw the project

Winning and losing: Effects on impulsive action

In the present study, we examined the effect of wins and losses on impulsive action in gambling (Experiments 1-3) and non-gambling tasks (Experiments 4-5). In each experiment, subjects performed a simple task in which they had to win points. On each trial, they had to choose between a gamble and a non-gamble. The gamble was always associated with a higher amount but a lower probability of winning than the non-gamble. After subjects indicated their choice (i.e. gamble or not), feedback was presented. They had to press a key to start the next trial. Experiments 1-3 showed that, compared to the non-gambling baseline, subjects were faster to initiate the next trial after a gambled loss, indicating that losses can induce impulsive actions. In Experiments 4 and 5, subjects alternated between the gambling task and a neutral decision-making task in which they could not win or lose points. Subjects were faster in the neutral decision-making task if they had just lost in the gambling task, suggesting that losses have a general effect on action. Our results challenge the dominant idea that humans become more cautious after suboptimal outcomes. Instead, they indicate that losses in the context of potential rewards are emotional events that increase impulsivity.This work was supported by an Economic and Social Research Council Grant (ES/J00815X/1) to FV, CDC & IPLM, a starting grant to FV from the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007-2013)/ ERC Grant Agreement No. 312445, and a Biotechnology and Biological Sciences Research Council Grant (BB/K008277/1) to CDC and FV

Food addiction: Implications for the diagnosis and treatment of overeating

This is the final version. Available from MDPI via the DOI in this record. With the obesity epidemic being largely attributed to overeating, much research has been aimed at understanding the psychological causes of overeating and using this knowledge to develop targeted interventions. Here, we review this literature under a model of food addiction and present evidence according to the fifth edition of the Diagnostic and Statistical Manual (DSM-5) criteria for substance use disorders. We review several innovative treatments related to a food addiction model ranging from cognitive intervention tasks to neuromodulation techniques. We conclude that there is evidence to suggest that, for some individuals, food can induce addictive-type behaviours similar to those seen with other addictive substances. However, with several DSM-5 criteria having limited application to overeating, the term ‘food addiction’ is likely to apply only in a minority of cases. Nevertheless, research investigating the underlying psychological causes of overeating within the context of food addiction has led to some novel and potentially effective interventions. Understanding the similarities and differences between the addictive characteristics of food and illicit substances should prove fruitful in further developing these interventions.Biotechnology and Biological Sciences Research CouncilEuropean Research Counci

Prefrontal brain stimulation during food-related inhibition training: effects on food craving, food consumption and inhibitory control

This is the final version. Available on open access from the Royal Society via the DOI in this recordData accessibility: The pre-registered study protocol, anonymised study data and JASP outputs are available on the Open Science Framework (https://osf.io/2597q/).Modulation of dorsolateral prefrontal cortex (DLPFC) activity using non-invasive brain stimulation has been shown to reduce food craving as well as food consumption. Using a preregistered design, we examined whether bilateral transcranial direct current stimulation (tDCS) of the DLPFC could reduce food craving and consumption in healthy participants when administered alongside the cognitive target of inhibitory control training. Participants (N = 172) received either active or sham tDCS (2 mA; anode F4, cathode F3) while completing a food-related Go/No-Go task. State food craving, ad-lib food consumption and response inhibition were evaluated. Compared with sham stimulation, we found no evidence for an effect of active tDCS on any of these outcome measures in a predominantly female sample. Our findings raise doubts about the effectiveness of single-session tDCS on food craving and consumption. Consideration of individual differences, improvements in tDCS protocols and multi-session testing are discussed.Biotechnology and Biological Sciences Research Council (BBSRC)European Research CouncilWellcome Trus

Do restrained eaters show increased BMI, food craving and disinhibited eating? A comparison of the Restraint Scale and the Restrained Eating scale of the Dutch Eating Behaviour Questionnaire

This is the final version. Available on open access from the Royal Society via the DOI in this recordData accessibility: All study data and analysis scripts are freely available on the Open Science Framework (https://osf.io/gsfrj/).Despite being used interchangeably, different measures of restrained eating have been associated with different dietary behaviours. These differences have impeded replicability across the restraint literature and have made it difficult for researchers to interpret results and use the most appropriate measure for their research. Across a total sample of 1731 participants, this study compared the Restraint Scale (RS), and its subscales, to the Dutch Eating Behaviour Questionnaire (DEBQ) across several traits related to overeating. The aim was to explore potential differences between these two questionnaires so that we could help to identify the most suitable measure as a prescreening tool for eating-related interventions. Results revealed that although the two measures are highly correlated with one another (rs = 0.73-0.79), the RS was more strongly associated with external (rs = -0.07 to 0.11 versus -0.18 to -0.01) and disinhibited eating (rs = 0.46 versus 0.31), food craving (rs = 0.12-0.27 versus 0.02-0.13 and 0.22 versus -0.06) and body mass index (rs = 0.25-0.34 versus -0.13 to 0.15). The results suggest that, compared to the DEBQ, the RS is a more appropriate measure for identifying individuals who struggle the most to control their food intake.Biotechnology and Biological Sciences Research Council (BBSRC)European Research Council (ERC

Cognitive and environmental interventions to encourage healthy eating: evidence-based recommendations for public health policy

This is the final version. Available on open access from the Royal Society via the DOI in this recordPolicymakers are focused on reducing the public health burden of obesity. The UK average percentage of adults classified as obese is 26%, which is double that of the global average. Over a third of UK adults report using at least one weight management aid. Yet, many people still struggle to change their diet-related behaviour, despite having the awareness, intention and capability to do so. This 'intention-behaviour gap' may be because most existing dietary-choice interventions focus on individual decision-making, ignoring the effects of environmental cues on human behaviour. Behaviour change interventions that 'nudge' people into making healthier choices by modifying the food environment have been shown to be effective. However, this type of intervention is typically challenging for policymakers to implement for economic, ethical and public accessibility reasons. To overcome these concerns, policymakers should consider 'boosting' interventions. Boosting involves enhancing competences that help people make decisions consistent with their goals. Here, we outline cognitive training as a boosting intervention to tackle obesity. We synthesize the evidence for one type of cognitive training (go/no-go training) that may be effective at modifying food-related decisions and reducing body weight. We offer evidence-based recommendations for an obesity-focused Public Health Wales behaviour change programme.European Research Council (ERC

Disentangling the Effects of Vapor Pressure Deficit and Soil Water Availability on Canopy Conductance in a Seasonal Tropical Forest During the 2015 El Niño Drought

Water deficit in the atmosphere and soil are two key interactive factors that constrain transpiration and vegetation productivity. It is not clear which of these two factors is more important for the water and carbon flux response to drought stress in ecosystems. In this study, field data and numerical modeling were used to isolate their impact on evapotranspiration (ET) and gross primary productivity (GPP) at a tropical forest site in Barro Colorado Island (BCI), Panama, focusing on their response to the drought induced by the El Niño event of 2015–2016. Numerical simulations were performed using a plant hydrodynamic scheme (HYDRO) and a heuristic approach that ignores stomatal sensitivity to leaf water potential in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). The sensitivity of canopy conductance (Gs) to vapor pressure deficit (VPD) obtained from eddy-covariance fluxes and measured sap flux shows that, at both ecosystem and plant scale, soil water stress is more important in limiting Gs than VPD at BCI during the El Niño event. The model simulations confirmed the importance of water stress limitation on Gs, but overestimated the VPD impact on Gs compared to that estimated from the observations. We also found that the predicted soil moisture is less sensitive to the diversity of plant hydraulic traits than ET and GPP. During the dry season at BCI, seasonal ET, especially soil evaporation at VPD \u3e 0.42 kPa, simulated using HYDRO and ELM, were too strong and will require alternative parameterizations

Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models

PublishedJournal Article© Author(s) 2015. To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into four categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), of both the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for five models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, the situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This response arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully coupled, biogeochemically coupled, and radiatively coupled 1 % yr-1 increasing CO2 experiments. We disaggregate inter-model uncertainty in the globally integrated equilibrium carbon responses to initial turnover times, initial productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model spread in carbon changes arising from initial conditions is dominated by model disagreement on turnover times, whereas inter-model spread in carbon changes from fractional changes to these terms is dominated by model disagreement on changes to productivity in response to both warming and CO2 fertilization. However, the lack of changing turnover time control on carbon responses, for both live and dead carbon pools, in response to the imposed forcings may arise from a common lack of process representation behind changing turnover times (e.g., allocation and mortality for live carbon; permafrost, microbial dynamics, and mineral stabilization for dead carbon), rather than a true estimate of the importance of these processes.This research was supported by the Director, Office of Science, Office of Biological and Environmental Research of the U.S. Department of Energy under Contract no. DE-AC02-05CH11231 as part of their Regional and Global Climate Modeling Program. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups listed in Table 1 for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. CDJ was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101)

Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity