66 research outputs found

    Anxious/depressed symptoms are related to microstructural maturation of white matter in typically developing youths

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    AbstractThere are multiple recent reports of an association between anxious/depressed (A/D) symptomatology and the rate of cerebral cortical thickness maturation in typically developing youths. We investigated the degree to which anxious/depressed symptoms are tied to age-related microstructural changes in cerebral fiber pathways. The participants were part of the NIH MRI Study of Normal Brain Development. Child Behavior Checklist A/D scores and diffusion imaging were available for 175 youths (84 males, 91 females; 241 magnetic resonance imagings) at up to three visits. The participants ranged from 5.7 to 18.4 years of age at the time of the scan. Alignment of fractional anisotropy data was implemented using FSL/Tract-Based Spatial Statistics, and linear mixed model regression was carried out using SPSS. Child Behavior Checklist A/D was associated with the rate of microstructural development in several white matter pathways, including the bilateral anterior thalamic radiation, bilateral inferior longitudinal fasciculus, left superior longitudinal fasciculus, and right cingulum. Across these pathways, greater age-related fractional anisotropy increases were observed at lower levels of A/D. The results suggest that subclinical A/D symptoms are associated with the rate of microstructural development within several white matter pathways that have been implicated in affect regulation, as well as mood and anxiety psychopathology.</jats:p

    Time-Dependent Inhibition and Estimation of CYP3A Clinical Pharmacokinetic Drug-Drug Interactions Using Plated Human Cell Systems

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    ABSTRACT: The current studies assessed the utility of freshly plated hepatocytes, cryopreserved plated hepatocytes, and cryopreserved plated HepaRG cells for the estimation of inactivation parameters k inact and K I for CYP3A. This was achieved using a subset of CYP3A time-dependent inhibitors (fluoxetine, verapamil, clarithromycin, troleandomycin, and mibefradil) representing a range of potencies

    Ventromedial prefrontal volume in adolescence predicts hyperactive/inattentive symptoms in adulthood

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    Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1,104 participants (M = 14.52 yrs, SD = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -.274, p < .001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms

    Inattention and reaction time variability are linked to ventromedial prefrontal volume in adolescents

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    Background Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) have most commonly reported volumetric abnormalities in the basal ganglia, cerebellum, and prefrontal cortices. Few studies have examined the relationship between ADHD symptomatology and brain structure in population-based samples. We investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability—an index of lapses in attention. We also tested for associations between brain structural correlates of ADHD symptomatology and maps of dopaminergic gene expression. Methods Psychopathology and imaging data were available for 1538 youths. Parent ratings of ADHD symptoms were obtained using the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire (SDQ). Self-reports of ADHD symptoms were assessed using the youth version of the SDQ. Reaction time variability was available in a subset of participants. For each measure, whole-brain voxelwise regressions with gray matter volume were calculated. Results Parent ratings of ADHD symptoms (Development and Well-Being Assessment and SDQ), adolescent self-reports of ADHD symptoms on the SDQ, and reaction time variability were each negatively associated with gray matter volume in an overlapping region of the ventromedial prefrontal cortex. Maps of DRD1 and DRD2 gene expression were associated with brain structural correlates of ADHD symptomatology. Conclusions This is the first study to reveal relationships between ventromedial prefrontal cortex structure and multi-informant measures of ADHD symptoms in a large population-based sample of adolescents. Our results indicate that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology. These findings extend previous research implicating the default mode network and dopaminergic dysfunction in ADHD

    Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology

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    Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n=758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents

    Counseling patients about sexual health when considering post-prostatectomy radiation treatment

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    Prostate cancer is the second most frequently diagnosed cancer in men in the United States. Many men with clinically localized prostate cancer survive for 15 years or more. Although early detection and successful definitive treatments are increasingly common, a debate regarding how aggressively to treat prostate cancer is ongoing because of the effect of aggressive treatment on the quality of life, including sexual functioning. We examined current research on the effect of post-prostatectomy radiation treatment on sexual functioning, and suggest a way in which patient desired outcomes might be taken into consideration while making decisions with regard to the timing of radiation therapy after prostatectomy

    Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning

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    International audienceAbstract While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naĂŻve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development
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