Suicidal behavior is a major concern for patients who suffer from major depressive disorder (MDD), especially among adolescents and young adults. Machine learning models with the capability of suicide risk identification at an individual level could improve suicide prevention among high-risk patient population.
 
  A cross-sectional assessment was conducted on a sample of 66 adolescents/young adults diagnosed with MDD. The structural T1-weighted MRI scan of each subject was processed using the FreeSurfer software. The classification model was conducted using the Support Vector Machine - Recursive Feature Elimination (SVM-RFE) algorithm to distinguish suicide attempters and patients with suicidal ideation but without attempts.
 
  The SVM model was able to correctly identify suicide attempters and patients with suicidal ideation but without attempts with a cross-validated prediction balanced accuracy of 78.59%, the sensitivity was 73.17% and the specificity was 84.0%. The positive predictive value of suicide attempt was 88.24%, and the negative predictive value was 65.63%. Right lateral orbitofrontal thickness, left caudal anterior cingulate thickness, left fusiform thickness, left temporal pole volume, right rostral anterior cingulate volume, left lateral orbitofrontal thickness, left posterior cingulate thickness, right pars orbitalis thickness, right posterior cingulate thickness, and left medial orbitofrontal thickness were the 10 top-ranked classifiers for suicide attempt.
 
  The findings indicated that structural MRI data can be useful for the classification of suicide risk. The algorithm developed in current study may lead to identify suicide attempt risk among MDD patients.
 The findings indicated that structural MRI data can be useful for the classification of suicide risk. The algorithm developed in current study may lead to identify suicide attempt risk among MDD patients.
  Neurocognitive impairments might play a key role in the development of Borderline Personality Disorder (BPD), however, the pathophysiological mechanism underlying cognitive impairment of BPD is largely unknown. This study was aimed to examine the electrophysiological mechanism of deficits in set-shifting processing in patients with BPD.
 
  Twenty-seven drug-naïve patients with BPD and twenty-four healthy controls were recruited. Demographicvariables and clinical characteristics of all subjects were collected. Behavioral data and event-related potentials (ERPs) were recorded when subjects were performing the task-switching paradigm, which was applied to investigate the set-shifting function. The P2, N2 and P3 components in the task-switching paradigm would be analyzed.
 
  Patients with BPD had significantly higher level of impulsivity, depression and anxiety than healthy controls. When performing the switching task, the BPD group had lower P2 amplitude and higher N2 amplitude than the control group. In the BPD group, the P2 latency at Fz electrode in repeat task was correlated positively with the level of depression, and P2 latency at Pz electrode in repeat task and switch task both had significantly negative relationships with the the level of anxiety.
 
  This cross-sectional designed study did not clarify the causal relationship of the electrophysiological characteristics and the development of BPD.
 
  Patients with BPD might have abnormal brain activities when overcoming the inhibition of current task and inhibiting the effects of prior task, and their top-down control function might be impaired. These findings provide some useful clues for the underlying pathophysiological mechanism of BPD.
 Patients with BPD might have abnormal brain activities when overcoming the inhibition of current task and inhibiting the effects of prior task, and their top-down control function might be impaired. These findings provide some useful clues for the underlying pathophysiological mechanism of BPD.
  Adaptive recovery from stress promotes healthy cognitive affective functioning, whereas maladaptive recovery is linked to poor psychological outcomes.  https://www.selleckchem.com/products/ly333531.html  Neural regions, like the anterior cingulate and hippocampus, play critical roles in psychosocial stress responding and serve as hubs in the corticolimbic neural system. To date, however, it is unknown how cognitive emotion regulation traits (cER), adaptive and maladaptive, influence corticolimbic stress recovery. Here, we examined acute psychosocial stress neural recovery, accounting for cER.
 
  Functional neuroimaging data were collected while forty-seven healthy participants performed blocks of challenging, time-sensitive, mental calculations. Participants immediately received performance feedback (positive/negative/neutral) and their ranking, relative to fictitious peers. Participants rested for 90 seconds after each feedback, allowing for a neural stress recovery period. Collected before scanning, cER scores were correlated with neural activity during eachm positive stress within corticolimbic regions. Positive feedback may be potentially threatening to individuals with poor stress regulation. Identifying positive stress-induced activation patterns in corticolimbic neural networks linked to M-cER creates the possibility to identify these neural responses as risk factors for social-emotional dysregulation subsequent to rewarding social information, often witnessed in affective disorders, like depression.
  Treatment-resistant depression (TRD) is considered a common clinical condition often associated with relevant suicidal ideation and characterized by a severe functional impairment lifetime. Among the available drugs for the TRD treatment, second-generation antipsychotics (SGAs) have been reported as effective. In this context, the aim of this study was to review the clinical studies evaluating the efficacy of SGAs as add-on therapy in TRD.
 
  A comprehensive search on PubMed, Medline and PsychINFO of all randomized clinical trials (RCTs) assessing the augmentation with antipsychotics in TRD, published from January 2000 until March 2020, was performed. Sixteen RCTs studies met the inclusion criteria.
 
  The reviewed studies showed that the add-on therapy with aripiprazole could be beneficial in the treatment of TRD. Furthermore, RCTs on quetiapine augmentation support its use in TRD, especially when comorbid anxiety or insomnia are present. The effects of risperidone and olanzapine as add-on in TRD were less studied, but preliminary data indicated an efficacy respect to placebo, making them a possible therapeutic option in TRD.