Depressive symptom trajectories among girls in the juvenile justice system: 24-month outcomes of an RCT of Multidimensional Treatment Foster Care

Youth depression is a significant and growing international public health problem. Youth who engage in high levels of delinquency are at particularly high risk for developing problems with depression. The present study examined the impact of a behavioral intervention designed to reduce delinquency (Multidimensional Treatment Foster Care; MTFC) compared to a group care intervention (GC; i.e., services as usual) on trajectories of depressive symptoms among adolescent girls in the juvenile justice system. MTFC has documented effects on preventing girls' recidivism, but its effects on preventing the normative rise in girls' depressive symptoms across adolescence have not been examined. This indicated prevention sample included 166 girls (13-17 years at T1) who had at least one criminal referral in the past 12 months and who were mandated to out-of-home care; girls were randomized to MTFC or GC. Intent-to-treat analyses examined the main effects of MTFC on depression symptoms and clinical cut-offs, and whether benefits were greatest for girls most at risk. Depressive symptom trajectories were specified in hierarchical linear growth models over a 2 year period using five waves of data at 6 month intervals. Depression clinical cut-off scores were specified as nonlinear probability growth models. Results showed significantly greater rates of deceleration for girls in MTFC versus GC for depressive symptoms and for clinical cut-off scores. The MTFC intervention also showed greater benefits for girls with higher levels of initial depressive symptoms. Possible mechanisms of effect are discussed, given MTFC's effectiveness on targeted and nontargeted outcomes. © 2013 Society for Prevention Research

Epidemiologic heterogeneity of common mood and anxiety disorders over the lifecourse in the general population: a systematic review

Background Clinical evidence has long suggested there may be heterogeneity in the patterns and predictors of common mood and anxiety disorders; however, epidemiologic studies have generally treated these outcomes as homogenous entities. The objective of this study was to systematically review the epidemiologic evidence for potential patterns of heterogeneity of common mood and anxiety disorders over the lifecourse in the general population. Methods We reviewed epidemiologic studies examining heterogeneity in either the nature of symptoms experienced ( symptom syndromes ) or in patterns of symptoms over time ( symptom trajectories ). To be included, studies of syndromes were required to identify distinct symptom subtypes, and studies of trajectories were required to identify distinct longitudinal patterns of symptoms in at least three waves of follow-up. Studies based on clinical or patient populations were excluded. Results While research in this field is in its infancy, we found growing evidence that, not only can mood and anxiety disorders be differentiated by symptom syndromes and trajectories, but that the factors associated with these disorders may vary between these subtypes. Whether this reflects a causal pathway, where genetic or environmental factors influence the nature of the symptom or trajectory subtype experienced by an individual, or whether individuals with different subtypes differed in their susceptibility to different environmental factors, could not be determined. Few studies addressed issues of comorbidity or transitions in symptoms between common disorders. Conclusion Understanding the diversity of these conditions may help us identify preventable factors that are only associated with some subtypes of these common disorders

The endocannabinoid system controls food intake via olfactory processes

Comment in Sensory systems: the hungry sense. [Nat Rev Neurosci. 2014] Inhaling: endocannabinoids and food intake. [Nat Neurosci. 2014]; International audience; Hunger arouses sensory perception, eventually leading to an increase in food intake, but the underlying mechanisms remain poorly understood. We found that cannabinoid type-1 (CB1) receptors promote food intake in fasted mice by increasing odor detection. CB1 receptors were abundantly expressed on axon terminals of centrifugal cortical glutamatergic neurons that project to inhibitory granule cells of the main olfactory bulb (MOB). Local pharmacological and genetic manipulations revealed that endocannabinoids and exogenous cannabinoids increased odor detection and food intake in fasted mice by decreasing excitatory drive from olfactory cortex areas to the MOB. Consistently, cannabinoid agonists dampened in vivo optogenetically stimulated excitatory transmission in the same circuit. Our data indicate that cortical feedback projections to the MOB crucially regulate food intake via CB1 receptor signaling, linking the feeling of hunger to stronger odor processing. Thus, CB1 receptor-dependent control of cortical feedback projections in olfactory circuits couples internal states to perception and behavior

Flow-Dependent Mass Transfer May Trigger Endothelial Signaling Cascades

It is well known that fluid mechanical forces directly impact endothelial signaling pathways. But while this general observation is clear, less apparent are the underlying mechanisms that initiate these critical signaling processes. This is because fluid mechanical forces can offer a direct mechanical input to possible mechanotransducers as well as alter critical mass transport characteristics (i.e., concentration gradients) of a host of chemical stimuli present in the blood stream. However, it has recently been accepted that mechanotransduction (direct mechanical force input), and not mass transfer, is the fundamental mechanism for many hemodynamic force-modulated endothelial signaling pathways and their downstream gene products. This conclusion has been largely based, indirectly, on accepted criteria that correlate signaling behavior and shear rate and shear stress, relative to changes in viscosity. However, in this work, we investigate the negative control for these criteria. Here we computationally and experimentally subject mass-transfer limited systems, independent of mechanotransduction, to the purported criteria. The results showed that the negative control (mass-transfer limited system) produced the same trends that have been used to identify mechanotransduction-dominant systems. Thus, the widely used viscosity-related shear stress and shear rate criteria are insufficient in determining mechanotransduction-dominant systems. Thus, research should continue to consider the importance of mass transfer in triggering signaling cascades

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Mapping Developmental Precursors of Cyber-Aggression: Trajectories of Risk Predict Perpetration and Victimization

Technologically mediated contexts are social arenas in which adolescents can be both perpetrators and victims of aggression. Yet, there remains little understanding of the developmental etiology of cyber aggression, itself, as experienced by either perpetrators or victims. The current study examines 3-year latent within-person trajectories of known correlates of cyber-aggression: problem behavior, (low) self-esteem, and depressed mood, in a large and diverse sample of youth (N = 1,364; 54.6 % female; 12–14 years old at T1). Findings demonstrate that developmental increases in problem behavior across grades 8–10 predict both cyber-perpetration and victimization in grade 11. Developmental decreases in self-esteem also predicted both grade 11 perpetration and victimization. Finally, early depressed mood predicted both perpetration and victimization later on, regardless of developmental change in depressed mood in the interim. Our results reveal a clear link between risky developmental trajectories across the early high school years and later cyber-aggression and imply that mitigating trajectories of risk early on may lead to decreases in cyber-aggression at a later date

Big data in mHealth

The proliferation of mobile technologies has paved the way for the widespread use of mobile health (mHealth) devices. This in turn generates a large amount of data, which is essentially big data, that can be used for various purposes. In order to obtain the maximum benefit from mHealth data, emerging big data technologies can be employed. In this chapter, the relationship between mHealth and big data is investigated from a sociotechnical perspective. Following an overview of the state-of-the-art, stakeholders and their interests are identified, and the impact of big data on such interests is presented. The opportunities of using big data technologies in the mHealth domain are considered from several viewpoints. Social and economic implications of using big data technologies toward these ends are highlighted. Various challenges exist in the implementation and adoption of mHealth data processing. While there are social challenges including privacy, safety, and a false sense of confidence, there are also technical challenges such as security, standardization, correctness, timely analysis, and domain expertise. Some of these coincide with the challenges of the big data domain, and the others are related to human nature and human capabilities. The use of existing big data platforms requires significant expertise and know-how in data science domain which may hinder the adoption of big data technologies in mHealth. Hence, a solution in the form of a framework that provides higher abstraction level programming models is suggested to facilitate widespread user adoption. Accordingly, user aspects associated with big data in the mHealth domain are discussed