Divergent thinking is a critical creative cognitive process. Its neural mechanisms have been well-studied through structural and functional imaging in healthy individuals but are less explored in patients with bipolar disorder (BD). Because of the traditional link between creativity and BD, this study investigated the structural correlates of divergent thinking in patients with BD through surface-based morphometry.

Fifty-nine patients diagnosed with BD I or BD II (35.3 ± 8.5 years) and 56 age- and sex-matched controls (33.9 ± 7.4 years) were recruited. The participants underwent structural magnetic resonance imaging and an evaluation of divergent thinking by using the Chinese version of the Abbreviated Torrance Test for Adults (ATTA). FreeSurfer 7.0 was used to generate thickness and surface area maps for each participant. Brainwise regression of the association between cortical thickness or surface area and ATTA performance was conducted using general linear models.

Divergent thinking performance did not differ significantly between the patients with BD and the healthy controls. In these patients, total ATTA score was negatively correlated with cortical thickness in the right middle frontal gyrus, right occipital, and left precuneus but positively correlated with the surface area of the right superior frontal gyrus. By contrast, total ATTA scores and cortical thickness or surface area were not significantly correlated among the controls.

The findings indicate that divergent thinking involves cerebral structures for executive control, mental imagery, and visual processing in patients with BD, and the right prefrontal cortex might be the most crucial of these structures.

The aim of this study was to identify the potential electrophysiological biomarkers of human responses by comparing the electroencephalogram brain wave changes towards lavender versus normal saline in a healthy human population.

This study included a total of 44 participants without subjective olfactory disturbances. Lavender and normal saline were used as the olfactory stimulant and control. Electroencephalogram was recorded and power spectra were analysed by the spectral analysis for each alpha, beta, delta, theta and gamma bandwidth frequency upon exposure to lavender and normal saline independently.

The oscillatory brain activities in response to the olfactory stimulant indicated that the lavender smell decreased the beta activity in the left frontal (F7 electrode) and central region (C3 electrode) with a reduction in the gamma activity in the right parietal region (P4 electrode) (p < 0.05).

Olfactory stimulants result in changes of electrical brain activities in different brain regions, as evidenced by the topographical brain map and spectra analysis of each brain wave.

About a fourth of Chinese adolescents developed clinically significant depressive symptoms following a disaster. However, little is known about whether and how post-trauma negative life events and a sense of security are associated with depressive symptoms in this population. This study examined the psychological experiences of Chinese young people who had experienced the 2013 Ya’an earthquake in Sichuan, China.

This cross-sectional study was conducted in 2019. A total of 693 Chinese middle school students completed a questionnaire that measured their level of depressive symptoms, trauma exposure, stressful life events, and sense of security.

Results of hierarchical multiple-regression analyses showed that the level of life stress from stressful life events was positively associated with the level of depressive symptoms (β = 0.416, P < 0.001) and the level of the sense of security was negatively associated with the level of depressive symptoms (β = −0.352, P < 0.001) when analysis controlled for age, gender, and trauma exposure.

These findings highlight the importance of considering the influence of life stressors and the sense of security in devising measures and strategies for the prevention of the manifestation of depression among young people, particularly those who were exposed to disasters.

Support vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.

The resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).

We found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.

The findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.

Although poverty associated with severe mental illness (SMI) has been documented in many studies, little long-term evidence of social drift exists. This study aimed to unravel the poverty transitions among persons with SMI in a fast change community in China.

Two mental health surveys, using the International Classification of Disease (ICD-10), were conducted in the same six townships of Xinjin county, Chengdu, China in 1994 and 2015. A total of 308 persons with SMI identified in 1994 were followed up in 2015. The profiles of poverty transitions were identified and regression modelling methods were applied to determine the predictive factors of poverty transitions.

The poverty rate of persons with SMI increased from 39.9% to 49.4% in 1994 and 2015. A larger proportion of them had fallen into poverty (27.3%) rather than moved out of it (17.8%). Those persons with SMI who had lost work ability, had physical illness and more severe mental disabilities in 1994, as well as those who had experienced negative changes on these factors were more likely to live in persistent poverty or fall into poverty. Higher education level and medical treatment were major protective factors of falling into poverty.

This study shows long-term evidence on the social drift of persons with SMI during the period of rapid social development in China. Further targeted poverty alleviation interventions should be crucial for improving treatment and mental recovery and alleviating poverty related to SMI.

Network approach has been applied to a wide variety of psychiatric disorders. The aim of the present study was to identify network structures of remitters and non-remitters in patients with first-episode psychosis (FEP) at baseline and the 6-month follow-up.

Participants (n = 252) from the Korean Early Psychosis Study (KEPS) were enrolled. They were classified as remitters or non-remitters using Andreasen's criteria. We estimated network structure with 10 symptoms (three symptoms from the Positive and Negative Syndrome Scale, one depressive symptom, and six symptoms related to schema and rumination) as nodes using a Gaussian graphical model. Global and local network metrics were compared within and between the networks over time.

Global network metrics did not differ between the remitters and non-remitters at baseline or 6 months. However, the network structure and nodal strengths associated with positive-self and positive-others scores changed significantly in the remitters over time. Unique central symptoms for remitters and non-remitters were cognitive brooding and negative-self, respectively. The correlation stability coefficients for nodal strength were within the acceptable range.

Our findings indicate that network structure and some nodal strengths were more flexible in remitters. Negative-self could be an important target for therapeutic intervention.

Recent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).

This study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.

The conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.

These findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.

To alert policy makers early about emerging health technologies that could significantly impact the healthcare system at the clinical, financial and organizational levels, the Agency for Care Effectiveness (ACE) in Singapore established a horizon scanning system (HSS) in 2019. This paper describes the development of the ACE HSS and showcases its application with cell and gene therapy products as the first example.

A literature review of existing HSS methods, including the processes of the EuroScan International Network and other overseas horizon scanning agencies, was done to inform the development of our horizon scanning framework. The framework was first applied to the new and emerging cell and gene therapies.

Identification sources, filtration and prioritization criteria, and horizon scanning outputs for the HSS were developed in alignment to international best practices, with recommendations for technology uptake represented by a traffic light system. For the first horizon scanning exercise on cell and gene therapies, forty therapies passed the filtration step, of which eight were prioritized for further assessment. The few early reports developed were used to inform and prepare the healthcare system for their potential introduction, particularly in terms of the need to develop health and funding policies.

Early assessment of prioritized topics has provided support for strategic efforts within the Ministry of Health. Given that ACE's horizon scanning program is still in its infancy, the framework will continue to evolve to ensure relevance to our stakeholders so that it remains fit for purpose for our healthcare system.

To investigate the impacts of depression screening, diagnosis and treatment on major adverse cardiac events (MACEs) in acute coronary syndrome (ACS).

Prospective cohort study including a nested 24-week randomised clinical trial for treating depression was performed with 5–12 years after the index ACS. A total of 1152 patients recently hospitalised with ACS were recruited from 2006 to 2012, and were divided by depression screening and diagnosis at baseline and 24-week treatment allocation into five groups: 651 screening negative (N), 55 screening positive but no depressive disorder (S), 149 depressive disorder randomised to escitalopram (E), 151 depressive disorder randomised to placebo (P) and 146 depressive disorder receiving medical treatment only (M).

Cumulative MACE incidences over a median 8.4-year follow-up period were 29.6% in N, 43.6% in S, 40.9% in E, 53.6% in P and 59.6% in M. Compared to N, screening positive was associated with higher incidence of MACE [adjusted hazards ratio 2.15 (95% confidence interval 1.63–2.83)]. No differences were found between screening positive with and without a formal depressive disorder diagnosis. Of those screening positive, E was associated with a lower incidence of MACE than P and M. M had the worst outcomes even compared to P, despite significantly milder depressive symptoms at baseline.

Routine depression screening in patients with recent ACS and subsequent appropriate treatment of depression could improve long-term cardiac outcomes.