Accordingly, there was support for a significant indirect negative association between childhood emotional abuse and pain tolerance. The serial mediation statistical procedure demonstrated that anxiety and emotional dysregulation mediated the effect of childhood emotional abuse on pain resilience among individuals with AUD. Conclusions Targeting emotional dysregulation and physical pain that can result from childhood trauma may have particular therapeutic utility among individuals treated for AUD.The glutamatergic system has previously been shown to be involved in the pathophysiology of schizophrenia and the mechanisms of action of antipsychotic treatment. The present study aimed to investigate the relationship between the levels of glutamate (Glu) or Glu/total creatine (Glu/Cr+PCr) in the anterior cingulate cortex (ACC) and psychiatric symptoms as well as the response to antipsychotic treatment. We performed proton magnetic resonance spectroscopy (1H-MRS) to measure Glu and Glu/Cr+PCr in the ACC of 35 drug-naïve first-episode schizophrenia (FES) patients and 40 well-matched healthy controls (HCs). After scanning, we treated the patients with risperidone for eight weeks. Remission status was based on the Positive and Negative Syndrome Scale (PANSS) scores at week 8. At baseline, there were no significant differences in the levels of Glu or Glu/Cr+PCr in the ACC between drug-naïve FES patients and HCs. Lower baseline levels of Glu/Cr+PCr but not Glu in the ACC were associated with more severe negative symptoms of schizophrenia.  https://www.selleckchem.com/products/CX-3543.html  Compared to the remission group (RM), the non-remission group (NRM) had lower baseline ACC Glu levels (P less then 0.05). Our results suggest that ACC Glu levels may be related to the severity of symptoms in the early stages of schizophrenia and therefore may be a marker with which to evaluate the treatment effect of antipsychotics in schizophrenia patients.Objective Identifying high-risk groups with an increased genetic liability for bipolar disorder (BD) will provide insights into the etiology of BD and contribute to early detection of BD. We used the BD polygenic risk score (PRS) derived from BD genome-wide association studies (GWAS) to explore how such genetic risk manifests in young, high-risk adults. We postulated that BD-PRS would be associated with risk factors for BD. Methods A final sample of 185 young, high-risk German adults (aged 18-35 years) were grouped into three risk groups and compared to a healthy control group (n = 1,100). The risk groups comprised 117 cases with attention deficit hyperactivity disorder (ADHD), 45 with major depressive disorder (MDD), and 23 help-seeking adults with early recognition symptoms [ER positive family history for BD, (sub)threshold affective symptomatology and/or mood swings, sleeping disorder]. BD-PRS was computed for each participant. Logistic regression models (controlling for sex, age, and the first five ancestry principal components) were used to assess associations of BD-PRS and the high-risk phenotypes. Results We observed an association between BD-PRS and combined risk group status (OR = 1.48, p less then 0.001), ADHD diagnosis (OR = 1.32, p = 0.009), MDD diagnosis (OR = 1.96, p less then 0.001), and ER group status (OR = 1.7, p = 0.025; not significant after correction for multiple testing) compared to healthy controls. Conclusions In the present study, increased genetic risk for BD was a significant predictor for MDD and ADHD status, but not for ER. These findings support an underlying shared risk for both MDD and BD as well as ADHD and BD. Improving our understanding of the underlying genetic architecture of these phenotypes may aid in early identification and risk stratification.Psychiatric research is often confronted with complex abstractions and dynamics that are not readily accessible or well-defined to our perception and measurements, making data-driven methods an appealing approach. Deep neural networks (DNNs) are capable of automatically learning abstractions in the data that can be entirely novel and have demonstrated superior performance over classical machine learning models across a range of tasks and, therefore, serve as a promising tool for making new discoveries in psychiatry. A key concern for the wider application of DNNs is their reputation as a "black box" approach-i.e., they are said to lack transparency or interpretability of how input data are transformed to model outputs. In fact, several existing and emerging tools are providing improvements in interpretability. However, most reviews of interpretability for DNNs focus on theoretical and/or engineering perspectives. This article reviews approaches to DNN interpretability issues that may be relevant to their application in psychiatric research and practice. It describes a framework for understanding these methods, reviews the conceptual basis of specific methods and their potential limitations, and discusses prospects for their implementation and future directions.
  Astrocytes in the hippocampus are immediately relevant to depressive-like behavior. By regulating their activities, Xiaoyaosan (XYS), a traditional Chinese medicine compound, works in the treatment of depression.
 
  Chronic unpredictable mild stress (CUMS) rat model was established to observe the regulation of XYS. We investigated the behavioral changes of CUMS, the expression of corticosterone (CORT) of the hypothalamo-pituitary-adrenal (HPA) axis, the expression of Glu-NMDA receptor and astrocytes glial fibrillary acidic protein (GFAP) in the hippocampus. We also investigated whether these changes were linked to XYS.
 
  80 adult SD rats were randomly divided into four groups, control group, CUMS group, XYS group, and fluoxetine group. The rats in the control group and the CUMS group received 0.5 ml of deionized water once a day by intragastrically administration. Rats in the two treatment groups received XYS (2.224g/kg/d) and fluoxetine (2.0mg/kg/d) once a day, respectively. Rat hippocampus GFAP and Glu-NMDAP and Glu-NMDA receptor.
 Changes in the hippocampus GFAP and Glu-NMDA receptor may be an essential mechanism of depression. Besides, XYS may be critical to the treatment of depression by intervention the HPA axis, GFAP and Glu-NMDA receptor.