Resilience and corpus callosum microstructure in adolescence

Background. Resilience is the capacity of individuals to resist mental disorders despite exposure to stress. Little is known about its neural underpinnings. The putative variation of white-matter microstructure with resilience in adolescence, a critical period for brain maturation and onset of high-prevalence mental disorders, has not been assessed by diffusion tensor imaging (DTI). Lower fractional anisotropy (FA) though, has been reported in the corpus callosum (CC), the brain’s largest white-matter structure, in psychiatric and stress-related conditions. We hypothesized that higher FA in the CC would characterize stress-resilient adolescents. Method. Three groups of adolescents recruited from the community were compared: resilient with low risk of mental disorder despite high exposure to lifetime stress (n = 55), at-risk of mental disorder exposed to the same level of stress (n = 68), and controls (n = 123). Personality was assessed by the NEO-Five Factor Inventory (NEO-FFI). Voxelwise statistics of DTI values in CC were obtained using tract-based spatial statistics. Regional projections were identified by probabilistic tractography. Results. Higher FA values were detected in the anterior CC of resilient compared to both non-resilient and control adolescents. FA values varied according to resilience capacity. Seed regional changes in anterior CC projected onto anterior cingulate and frontal cortex. Neuroticism and three other NEO-FFI factor scores differentiated non-resilient participants from the other two groups. Conclusion. High FA was detected in resilient adolescents in an anterior CC region projecting to frontal areas subserving cognitive resources. Psychiatric risk was associated with personality characteristics. Resilience in adolescence may be related to white-matter microstructure

The Effectiveness of Pharmacological and Non-Pharmacological Interventions for Improving Glycaemic Control in Adults with Severe Mental Illness: A Systematic Review and Meta-Analysis

People with severe mental illness (SMI) have reduced life expectancy compared with the general population, which can be explained partly by their increased risk of diabetes. We conducted a meta-analysis to determine the clinical effectiveness of pharmacological and non-pharmacological interventions for improving glycaemic control in people with SMI (PROSPERO registration: CRD42015015558). A systematic literature search was performed on 30/10/2015 to identify randomised controlled trials (RCTs) in adults with SMI, with or without a diagnosis of diabetes that measured fasting blood glucose or glycated haemoglobin (HbA1c). Screening and data extraction were carried out independently by two reviewers. We used random effects meta-analysis to estimate effectiveness, and subgroup analysis and univariate meta-regression to explore heterogeneity. The Cochrane Collaboration’s tool was used to assess risk of bias. We found 54 eligible RCTs in 4,392 adults (40 pharmacological, 13 behavioural, one mixed intervention). Data for meta-analysis were available from 48 RCTs (n = 4052). Both pharmacological (mean difference (MD), -0.11mmol/L; 95% confidence interval (CI), [-0.19, -0.02], p = 0.02, n = 2536) and behavioural interventions (MD, -0.28mmol//L; 95% CI, [-0.43, -0.12], p<0.001, n = 956) were effective in lowering fasting glucose, but not HbA1c (pharmacological MD, -0.03%; 95% CI, [-0.12, 0.06], p = 0.52, n = 1515; behavioural MD, 0.18%; 95% CI, [-0.07, 0.42], p = 0.16, n = 140) compared with usual care or placebo. In subgroup analysis of pharmacological interventions, metformin and antipsychotic switching strategies improved HbA1c. Behavioural interventions of longer duration and those including repeated physical activity had greater effects on fasting glucose than those without these characteristics. Baseline levels of fasting glucose explained some of the heterogeneity in behavioural interventions but not in pharmacological interventions. Although the strength of the evidence is limited by inadequate trial design and reporting and significant heterogeneity, there is some evidence that behavioural interventions, antipsychotic switching, and metformin can lead to clinically important improvements in glycaemic measurements in adults with SMI

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Dopaminergic receptor blockade changes a functional connectivity network centred on the amygdala.

Resting-state connectivity has become an increasingly important measure in characterizing the functional integrity of brain circuits in neuro-psychiatric conditions. One approach that has recently gained prominence in this regard-and which we use in this study-is to investigate how resting-state connectivity depends on the integrity of certain neuromodulator systems. Here, we use a pharmacological challenge in combination with functional magnetic resonance imaging to investigate the impact of dopaminergic receptor blockade on whole brain functional connectivity in twenty healthy human subjects. Administration of the D2-receptor antagonist haloperidol led to a profound change in functional integration in network nodes linked to the amygdala. Compared to placebo and baseline measurements, network-based statistics and pairwise connectivity analyses revealed reduced connectivity and decreased link strength between the amygdala and the bilateral posterior cingulate cortex and other cortical areas. This was complemented by less extensive but very circumscribed enhanced connectivity between the amygdala and the right putamen during D2-receptor blockade. It will be interesting to investigate whether these pharmacologically induced shifts in resting-state connectivity will similarly be evident in clinical conditions that involve a dysfunction of the dopaminergic system. Our findings might also aid in interpreting alterations in more complex states, such as those seen psychiatric conditions and their treatment. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc

The Effect of Risperidone on Cognitive Symptoms of Schizophrenia : A Comparison with Haloperidol

Background and purpose: Several studies have demonstrated, that atypical antipsychotics attenuate cognitive symptoms of schizophrenia more than first generation of antipsychotics. Because there was no comprehensive and reliable study on evaluating these effects in Iranian population, the research group decided to compare the effects of haloperidol and risperidone, both Iranian drug laboratories' products, on the cognitive symptoms of patients with schizophrenia.Materials and Methods: 66 patients with the diagnosis of schizophrenia, according to DSM-IVTR criteria, who were hospitalized in Razi's Psychiatric Center, Tehran, were included in the study. After 2 weeks of wash-out period, patients were randomized in two groups, treated with haloperidol and risperidone, and in 8 week period basic and weekly MMSE were performed for all.Results: Both drugs improved cognitive symptoms of patients, and the course of improvement started in the 2nd week of treatment with no significant statistical difference.Conclusion: The study didn't confirm the preferentiality of risperidone vs. haloperidol on the cognitive symptoms of schizophrenia, which was demonstrated in western articles. Therefore, choosing each drug for treating patients must fulfill on other goals, such as the profile of their side effects

Dopaminergic receptor blockade changes a functional connectivity network centred on the amygdala

Resting-state connectivity has become an increasingly important measure in characterizing the functional integrity of brain circuits in neuro-psychiatric conditions. One approach that has recently gained prominence in this regard-and which we use in this study-is to investigate how resting-state connectivity depends on the integrity of certain neuromodulator systems. Here, we use a pharmacological challenge in combination with functional magnetic resonance imaging to investigate the impact of dopaminergic receptor blockade on whole brain functional connectivity in twenty healthy human subjects. Administration of the D2-receptor antagonist haloperidol led to a profound change in functional integration in network nodes linked to the amygdala. Compared to placebo and baseline measurements, network-based statistics and pairwise connectivity analyses revealed reduced connectivity and decreased link strength between the amygdala and the bilateral posterior cingulate cortex and other cortical areas. This was complemented by less extensive but very circumscribed enhanced connectivity between the amygdala and the right putamen during D2-receptor blockade. It will be interesting to investigate whether these pharmacologically induced shifts in resting-state connectivity will similarly be evident in clinical conditions that involve a dysfunction of the dopaminergic system. Our findings might also aid in interpreting alterations in more complex states, such as those seen psychiatric conditions and their treatment. Hum Brain Mapp 37:4148-4157, 2016. © 2016 Wiley Periodicals, Inc

The influence of distributed chemical reaction groups in a multiphase coffee bean roasting model

The coffee industry relies on fundamental research to improve the techniques and processes related to its products. While recent theoretical and modelling work has focused on the heat and mass transfer processes within roasting coffee beans, modelling and analysis of chemical reactions in the context of multiphase models of roasting beans has not been well-studied. In this paper, we incorporate modified evaporation rates and chemical reaction groups to improve existing mathematical models of roasting coffee beans. We model the phase change from liquid to vapour water within the bean during roasting using first-order Arrhenius-like global reactions, and for other components of the bean, we consider a threecomponent solid phase model which includes sucrose, reducing sugars, and other organic compounds, which allows for porosity of the solid matrix to vary during the roasting process. We non-dimensionalise and then solve the multiphase model numerically, comparing the simulations with data we have collected through full bean and chopped bean experiments. We demonstrate that numerical solutions of the enhanced multiphase model with global water reactions and three-component solid phase reactions agree with experimental data for the average moisture content in whole beans and small chunks of bean, but that the data allows for a range to possible parameter values. We discuss other experimental data that might be collected to more firmly determine the parameters and hence the behaviour more generally. The indeterminacy of the parameters ensures that the additional effects included in the model will enable better understanding the coffee bean roasting process