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Background: Suicide among youth is a major public health challenge, attracting increasing attention. However, the neurobiological mechanisms and the pathophysiology underlying suicidal behavior in depressed youths are still unclear. The fMRI enables a better understanding of functional changes in the brains of young suicide attempters with depressive disorder through detecting spontaneous neural activity. The purpose of this study was to identify the relationship between abnormalities involving local brain function and suicidal attempts in depressed youths using resting-state fMRI (RS-fMRI).Method: Thirty-five depressed youths aged between 15 and 29 years with a history of suicidal attempts (SU group), 18 patients without suicidal attempts (NSU group) and 47 gender-, age- and education-matched healthy controls (HC) underwent psychological assessment and R-fMRI. The differences in fractional amplitude of low-frequency fluctuation (ALFF) among the three groups were compared. The clinical factors correlated with z-score ALFF in the regions displaying significant group differences were investigated. The ROC method was used to evaluate these clusters as markers to screen patients with suicidal behavior.Results: Compared with the NSU and HC groups, the SU group showed increased zALFF in the right superior temporal gyrus (r-STG), left middle temporal gyrus (L-MTG) and left middle occipital gyrus (L-MOG). Additionally, significantly decreased zALFF values in the L-SFG and L-MFG were found in the SU group compared with the NSU group, which were negatively correlated with BIS scores in the SU group. Further ROC analysis revealed that the mean zALFF values in these two regions (sensitivity=83.3% and specificity=71.4%) served as markers to differentiate the two patient subtypes.Conclusion: The SU group had abnormal spontaneous neural activity during the resting state, and decreased activity in L-SFG and L-MFG was associated with increased impulsivity in SU group. Our results suggested that abnormal neural activity in these brain regions may represent a potential neurobiological diathesis or predisposition to suicidal behavior in youth depression. [ABSTRACT FROM AUTHOR]

• This was the first study on suicidal and self-harm ideation (SSI) in hospital staff during a public health crisis. • 744 (6.47%) hospital staff reported a suicidal and self-harm ideation. • The epidemic-related factors, the psychological status and need, and the perceived stress and support were associated with SSI in hospital staff. • The current SSI in the initial phase of a pandemic might lower than that in non-pandemic days. The COVID-19 pandemic put global medical systems under massive pressure for its uncertainty, severity, and persistence. For detecting the prevalence of suicidal and self-harm ideation (SSI) and its related risk factors among hospital staff during the COVID-19 pandemic, this cross-sectional study collected the sociodemographic data, epidemic-related information, the psychological status and need, and perceived stress and support from 11507 staff in 46 hospitals by an online survey from February 14 to March 2, 2020. The prevalence of SSI was 6.47%. Hospital staff with SSI had high family members or relatives infected number and the self-rated probability of infection. Additionally, they had more perceived stress, psychological need, and psychological impact. On the contrary, hospital staff without SSI reported high self-rated health, willingness to work in a COVID-19 ward, confidence in defeating COVID-19, and perceived support. Furthermore, they reported better marital or family relationship, longer sleep hours, and shorter work hours. The infection of family members or relatives, poor marital status, poor self-rated health, the current need for psychological intervention, perceived high stress, perceived low support, depression, and anxiety were independent factors to SSI. A systematic psychological intervention strategy during a public health crisis was needed for the hospital staff's mental well-being. [ABSTRACT FROM AUTHOR]

Background: 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.Methods: 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.Results: 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.Conclusions: 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. [ABSTRACT FROM AUTHOR]

Internet addiction (IA) is common among young students. This study aimed to examine the influence and mechanisms of IA and susceptible personality traits on the impact of suicidal ideation in adolescent students in China. This cross-sectional study (09/2012–09/2015) used stratified cluster sampling with "school type" for stratification; 136,266 students from 63 schools completed the questionnaire. Logistic regression analysis was performed to estimate the effect of IA (Young's Internet Addiction Test) and susceptible personality (Barratt impulsiveness scale, Buss & Perry Aggression Questionnaire; and Eysenck Personality Questionnaire-R Short Scale) on suicidal ideation (Scale of Suicidal Ideation). Suicidal ideation was observed in 20,218 (14.77%) of the students, and IA was detected in 28,836 (21.16%) subjects. Compared with those without IA, students with IA had a higher prevalence of suicidal ideation (P < 0.0001). No planning impulsiveness had a predictive effect on suicidal ideation in the impulsive personality trait, while in the aggressive personality trait, hostility and self-aggression had a predictive effect on suicidal ideation (all P < 0.0001). High psychoticism and neuroticism were impact factors for suicidal ideation, but extroversion was a protective factor (all P < 0.0001). These results highlight the importance of assessing personality traits and reducing IA as a possible means of lessening suicidal ideation. Susceptible personality (such as high psychoticism, high neuroticism, and low extroversion) play a prominent role in influencing the probability of having suicidal behavior among those recently exposed to IA. IA and susceptible personality traits were significantly correlated with suicidal and self-harm ideation among adolescent students. [ABSTRACT FROM AUTHOR]

• Targeted sequencing of SLC6A4 in adolescent and young adult MDD patients with SI. • Six SLC6A4 rare heterozygous variants were found in all MDD patients with SI. • Rare variants in SLC6A4 may contribute to adolescents and young adults suffering MDD with SI. Suicidal ideation (SI) is the most serious symptom of major depressive disorder (MDD) and considered an extreme state. The serotonin transporter gene (SLC6A4) plays a significant role in MDD and suicide pathophysiology. Previous studies have revealed an association between common variants of SLC6A4 with the risk of MDD and suicide. However, very few studies have so far focused on the degree to which rare variants of SLC6A4 are responsible for the depression observed in adolescent and young adult suicide patients. The aim of this study was to examine the impact of common and rare variants of SLC6A4 on the risk of Han Chinese adolescents and young adults suffering MDD with SI. Targeted sequencing of the SLC6A4 gene was conducted using FastTarget technology in Han Chinese adolescents and young adults, of which 74 were MDD patients with SI and 150 were healthy controls. Gene-based association analyses of rare variants were performed using enrichment analysis and a cumulative allele test. An allele association study was performed against common variants. After sequencing and bioinformatics analysis, a total of 15 single nucleotide variants (SNVs) were detected in the targeted regions from all participants, including 9 common and 6 rare variants. Among these, 5 rare variants were identified within the study group. Enrichment analysis of rare variants demonstrated a statistical difference (p = 0.042) between the study and control groups. Using cumulative allele analysis, alternative alleles in the SLC6A4 gene exhibited an association with MDD patients with SI (cumulative allele: OR = 10.18, 95% CI = 1.18–87.32, p = 0.017). No significant association was found between the 9 common SLC6A4 variants and MDD patients with SI. Our results suggest that rare variants of SLC6A4 may contribute to a genetic risk of adolescents and young adults suffering MDD with SI. [ABSTRACT FROM AUTHOR]