Adolescent depression varies considerably in its course. However, there remain no biobehavioral predictors of illness trajectory, and follow-up studies in depressed youth are sparse. Here, we sought to examine whether reward function would predict future clinical outcomes in adolescents with depressive symptoms. We utilized the reward flanker fMRI task to assess brain function during distinct reward processes of anticipation, attainment, and positive prediction error (PPE, i.e. receiving uncertain rewards). Subjects were 29 psychotropic-medication-free adolescents with mood and anxiety symptoms and 14 healthy controls (HC). All had psychiatric evaluations at baseline and approximately 24-month follow-up. Thirty-two participants (10 HC) had usable fMRI data. Correlation and hierarchical regression models examined baseline symptom severity measures as predictors of follow-up clinical outcomes. CF-102 agonist clinical trial Whole-brain analyses examined relationships between neural reward processes and follow-up outcomes. Clinically, aenting with significant anhedonia should be carefully monitored for illness progression. Mood disorders and problematic substance use co-occur and confer reciprocal risk for each other. Few studies use analytic approaches appropriate for testing whether specific features of one disorder confer risk for the other. 445 participants (59.8% female, Mean age=20.3 years) completed measures of depression and hypo/mania symptoms and substance use-related impairment; 330 had complete data at follow-up. Of these, 28% reported a history of depression, 4% of bipolar spectrum disorder, 11% of substance use disorder, and 55% reported substance-related impairment. Symptoms and domains of substance-related impairment were modeled in cross-sectional and cross-lagged panel network models. Impulsive and interpersonal impairment were most highly comorbid with mood symptoms. Suicidal ideation, sadness, decreased need for sleep, and guilt were the symptoms most highly comorbid with impairment. Interpersonal impairment due to substance use was the strongest cross-construct predictor of mood symptoms and suicidal c, level. Alterations in energy and activity in bipolar disorder (BD) differ between affective states and compared with healthy control individuals (HC). Measurements of activity could discriminate between BD and HC and in the monitoring of affective states within BD. The aims were to investigate differences in 1) passively collected smartphone-based location data (location data) between BD and HC, and 2) location data in BD between affective states. Daily, patients with BD and HC completed smartphone-based self-assessments of mood for up to nine months. Location data reflecting mobility patterns, routine and location entropy was collected daily. A total of 46 patients with BD and 31 HC providing daily data was included. A total of 4,859 observations of smartphone-based self-assessments of mood and mobility patterns were available from patients with BD and 1,747 observations from HC. Patients with BD had lower location entropy compared with HC (B= -0.14, 95% CI= -0.24; -0.034, p=0.009). Patients with BD during a depressive state were less mobile compared with a euthymic state. Patients with BD during an affective state had lower location entropy compared with a euthymic state (p<0.0001). The AUC of combined location data was rather high in classifying patients with BD compared with HC (AUC 0.83). Individuals willing to use smartphones for daily self-monitoring may represent a more motivated group. Alterations in location data reflecting mobility patterns may be a promising measure of illness and illness activity in patients with BD and may be used to monitor the effects of treatments.Alterations in location data reflecting mobility patterns may be a promising measure of illness and illness activity in patients with BD and may be used to monitor the effects of treatments. Reports showed that elevated proinflammatory cytokines, as detected in patients with psoriasis, was noted in individuals with major depressive disorder (MDD). Therefore, this study aimed to clarify the association of MDD and prospective incidence of psoriasis in human using a nationwide study. This population-based cohort study used the data from the Taiwan National Health Insurance system. 64,486 patients were defined as MDD cohort and 64,486 propensity score matched subjects without MDD were identified as comparison cohort. Each patient was independently tracked for a 5-year study period to assure them for a psoriasis diagnosis after the index date. Stratified Cox proportional hazard models were used to calculate the hazard ratio (HRs) for 5-year psoriasis risk. After adjustments, the HR of psoriasis for MDD patients was 1.32 compared with subjects without MDD. The stratified analyses present that MDD patients had approximately 1.30-fold significantly higher risk of psoriasis than comparison subjects in most subgroups. Furthermore, compared with the matched subjects without MDD, the adjusted HRs of psoriasis in the 2-, 3-, 4- and 5-year study periods were 1.33, 1.32, 1.33 and 1.32, respectively. Several patients with MDD or psoriasis might not include in this study, because of using a medical claims database. This study provides population-based evidence that MDD is an independent risk factor of developing psoriasis, with an increased risk in the male sex. Additional investigations verifying our findings and exploring possible pathological mechanisms would be of great interest and value to the psychiatric field.This study provides population-based evidence that MDD is an independent risk factor of developing psoriasis, with an increased risk in the male sex. Additional investigations verifying our findings and exploring possible pathological mechanisms would be of great interest and value to the psychiatric field.Segmental hair analysis provides information regarding previous long-term drug exposure, which is useful in the evaluation of cause of death for individuals with mental disorders. The aim was to analyze postmortem concentrations of the antipsychotic drug aripiprazole and its active metabolite dehydroaripiprazole in hair segments from individuals with known aripiprazole intake. Hair samples were collected during autopsy. Each sample was segmented into one to six 1cm segments, depending on the length of the hair shaft. Pulverized hair was extracted and analyzed using a previously published ultra-high-performance liquid chromatography-tandem mass spectrometric method. The 10th-90th percentile of aripiprazole concentrations in all hair segments (n=78) from 17 individuals were 0.024ng/mg-11ng/mg with a median of 2.3ng/mg, and the 10th-90th percentile concentrations of dehydroaripiprazole were 0.020ng/mg-11ng/mg, with a median of 2.6ng/mg, in all hair segments (n=71). The metabolite-to-parent drug ratios ranged from 0.