To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
Dysregulated proinflammatory cytokines have been shown to be associated with suicidal behavior. Cognitive deficits in working memory and inhibitory control have been demonstrated in depressed patients and people with suicidal ideation (SI). However, the association between proinflammatory cytokines, SI, and cognitive deficits in patients with major depressive disorder (MDD) remains unclear.
A total of 77 patients with MDD and age-/sex-matched 60 healthy individuals were recruited. MDD patients were divided into two groups: with SI (n = 36) and no SI (n = 41). SI was defined by a score of ≥2 in item 3 of the 17-item Hamilton Rating Scale for Depression. Levels of proinflammatory cytokines, including soluble interleukin-6 receptor, soluble tumor necrosis factor-α receptor type 1, and C-reactive protein (CRP), were measured, and cognitive function was assessed using 2-back task and Go/No-Go task.
Patients with SI had higher levels of CRP than those without SI and controls (P = .007). CRP was positively associated with SI (β = 0.21, P = .037), independent of cognitive function and depressive symptoms. Furthermore, SI was associated with cognitive deficits in working memory and inhibitory control after adjusting for confounding factors (P < .05).
Our findings suggest that higher levels of serum CRP and deficits in working memory and inhibitory control may be associated with higher SI among patients with MDD.
To establish optimal gestational weight gain (GWG) in Chinese pregnant women by Chinese-specific BMI categories and compare the new recommendations with the Institute of Medicine (IOM) 2009 guidelines.
Multicentre, prospective cohort study. Unconditional logistic regression analysis was used to evaluate the OR, 95 % CI and the predicted probabilities of adverse pregnancy outcomes. The optimal GWG range was defined as the range that did not exceed a 1 % increase from the lowest predicted probability in each pre-pregnancy BMI group.
From nine cities in mainland China.
A total of 3731 women with singleton pregnancy were recruited from April 2013 to December 2014.
The optimal GWG (ranges) by Chinese-specific BMI was 15·0 (12·8–17·1), 14·2 (12·1–16·4) and 12·6 (10·4–14·9) kg for underweight, normal weight and overweight pregnant women, respectively. Inappropriate GWG was associated with several adverse pregnancy outcomes. Compared with women gaining weight within our proposed recommendations, women with excessive GWG had higher risk for macrosomia, large for gestational age and caesarean section, whereas those with inadequate GWG had higher risk for low birth weight, small for gestational age and preterm delivery. The comparison between our proposed recommendations and IOM 2009 guidelines showed that our recommendations were comparable with the IOM 2009 guidelines and could well predict the risk of several adverse pregnancy outcomes.
Inappropriate GWG was associated with higher risk of several adverse pregnancy outcomes. Optimal GWG recommendations proposed in the present study could be applied to Chinese pregnant women.
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.
The upsurge in the number of people affected by the COVID-19 is likely to lead to increased rates of emotional trauma and mental illnesses. This article systematically reviewed the available data on the benefits of interventions to reduce adverse mental health sequelae of infectious disease outbreaks, and to offer guidance for mental health service responses to infectious disease pandemic. PubMed, Web of Science, Embase, PsycINFO, WHO Global Research Database on infectious disease, and the preprint server medRxiv were searched. Of 4278 reports identified, 32 were included in this review. Most articles of psychological interventions were implemented to address the impact of COVID-19 pandemic, followed by Ebola, SARS, and MERS for multiple vulnerable populations. Increasing mental health literacy of the public is vital to prevent the mental health crisis under the COVID-19 pandemic. Group-based cognitive behavioral therapy, psychological first aid, community-based psychosocial arts program, and other culturally adapted interventions were reported as being effective against the mental health impacts of COVID-19, Ebola, and SARS. Culturally-adapted, cost-effective, and accessible strategies integrated into the public health emergency response and established medical systems at the local and national levels are likely to be an effective option to enhance mental health response capacity for the current and for future infectious disease outbreaks. Tele-mental healthcare services were key central components of stepped care for both infectious disease outbreak management and routine support; however, the usefulness and limitations of remote health delivery should also be recognized.
Shaded coffee systems can mitigate climate change by fixation of atmospheric carbon dioxide (CO2) in soil. Understanding soil organic carbon (SOC) storage and the factors influencing SOC in coffee plantations are necessary for the development of sound land management practices to prevent land degradation and minimize SOC losses. This study was conducted in the main coffee-growing regions of Yunnan; SOC concentrations and storage of shaded and unshaded coffee systems were assessed in the top 40 cm of soil. Relationships between SOC concentration and factors affecting SOC were analysed using multiple linear regression based on the forward and backward stepwise regression method. Factors analysed were soil bulk density (ρb), soil pH, total nitrogen of soil (N), mean annual temperature (MAT), mean annual moisture (MAM), mean annual precipitation (MAP) and elevations (E). Akaike's information criterion (AIC), coefficient of determination (R2), root mean square error (RMSE) and residual sum of squares (RSS) were used to describe the accuracy of multiple linear regression models. Results showed that mean SOC concentration and storage decreased significantly with depth under unshaded coffee systems. Mean SOC concentration and storage were higher in shaded than unshaded coffee systems at 20–40 cm depth. The correlations between SOC concentration and ρb, pH and N were significant. Evidence from the multiple linear regression model showed that soil bulk density (ρb), soil pH, total nitrogen of soil (N) and climatic variables had the greatest impact on soil carbon storage in the coffee system.
Studies have suggested an association between metabolic and cerebrocardiovascular diseases and major depressive disorder (MDD). However, the risk of metabolic and cerebrocardiovascular diseases in the unaffected siblings of patients with MDD remains uncertain. Using the Taiwan National Health Insurance Research Database, 22,438 unaffected siblings of patients with MDD and 89,752 age-/sex-matched controls were selected and followed up from 1996 to the end of 2011. Individuals who developed metabolic and cerebrocardiovascular diseases during the follow-up period were identified. Compared with the controls, the unaffected siblings of patients with MDD had a higher prevalence of metabolic diseases, such as hypertension (5.0% vs. 4.5%, p = 0.007), dyslipidemia (5.6% vs. 4.8%, p < 0.001), and obesity (1.7% vs. 1.5%, p = 0.028), and cerebrocardiovascular diseases, such as ischemic stroke (0.6% vs. 0.4%, p < 0.005) and ischemic heart disease (2.1% vs. 1.7%, p < 0.001). Logistic regression analyses revealed that the unaffected siblings of patients with MDD were more likely to develop hypertension, dyslipidemia, ischemic stroke, and ischemic heart diseases during the follow-up period than the controls. Our study revealed a familial coaggregation between MDD and metabolic and cerebrocardiovascular diseases. Additional studies are required to investigate the shared pathophysiology of MDD and metabolic and cerebrocardiovascular diseases.
Family coaggregation of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD) and schizophrenia have been presented in previous studies. The shared genetic and environmental factors among psychiatric disorders remain elusive.
This nationwide population-based study examined familial coaggregation of major psychiatric disorders in first-degree relatives (FDRs) of individuals with ASD. Taiwan's National Health Insurance Research Database was used to identify 26 667 individuals with ASD and 67 998 FDRs of individuals with ASD. The cohort was matched in 1:4 ratio to 271 992 controls. The relative risks (RRs) and 95% confidence intervals (CI) of ADHD, ASD, BD, MDD and schizophrenia were assessed among FDRs of individuals with ASD and ASD with intellectual disability (ASD-ID).
FDRs of individuals with ASD have higher RRs of major psychiatric disorders compared with controls: ASD 17.46 (CI 15.50–19.67), ADHD 3.94 (CI 3.72–4.17), schizophrenia 3.05 (CI 2.74–3.40), BD 2.22 (CI 1.98–2.48) and MDD 1.88 (CI 1.76–2.00). Higher RRs of schizophrenia (4.47, CI 3.95–5.06) and ASD (18.54, CI 16.18–21.23) were observed in FDRs of individuals with both ASD-ID, compared with ASD only.
The risk for major psychiatric disorders was consistently elevated across all types of FDRs of individuals with ASD. FDRs of individuals with ASD-ID are at further higher risk for ASD and schizophrenia. Our results provide leads for future investigation of shared etiologic pathways of ASD, ID and major psychiatric disorders and highlight the importance of mental health care delivered to at-risk families for early diagnoses and interventions.
Studies have suggested the detrimental effects of obesity and systemic inflammation on the cognitive function of patients with bipolar or major depressive disorder. However, the complex associations between affective disorder, obesity, systemic inflammation, and cognitive dysfunction remain unclear.
Overall, 110 patients with affective disorder (59 with bipolar I disorder and 51 with major depressive disorder) who scored ≥61 on the Global Assessment of Functioning and 51 age- and sex-matched controls were enrolled. Body mass index ≥25 kg/m2 was defined as obesity or overweight. Levels of proinflammatory cytokines—including interleukin-6, tumor necrosis factor (TNF)-α, and C-reactive protein (CRP)—were measured, and cognitive function was assessed using various methods, including the Wisconsin Card Sorting Test (WCST) and go/no-go task.
Patients with bipolar I disorder or major depressive disorder were more likely to be obese or overweight, had higher CRP and TNF-α levels, and had greater executive dysfunction in the WCST than the controls. TNF-α level (P < .05) but not affective disorder diagnosis or obesity/overweight was significantly associated with cognitive function deficits, although obesity/overweight and diagnosis were significantly associated with increased TNF-α level.
Our findings may indicate that proinflammatory cytokines, but not obesity or overweight, have crucial effects on cognitive function in patients with bipolar I disorder or major depressive disorder, although proinflammatory cytokines and obesity or overweight were found to be strongly associated. The complex relationships between affective disorder diagnosis, proinflammatory cytokine levels, obesity or overweight, and cognitive function require further investigation.
Research suggests an association between metabolic disorders, such as type 2 diabetes mellitus (T2DM), and schizophrenia. However, the risk of metabolic disorders in the unaffected siblings of patients with schizophrenia remains unclear.
Using the Taiwan National Health Insurance Research Database, 3135 unaffected siblings of schizophrenia probands and 12,540 age-/sex-matched control subjects were included and followed up to the end of 2011. Individuals who developed metabolic disorders during the follow-up period were identified.
The unaffected siblings of schizophrenia probands had a higher prevalence of T2DM (3.4% vs. 2.6%, p = 0.010) than the controls. Logistic regression analyses with the adjustment of demographic data revealed that the unaffected siblings of patients with schizophrenia were more likely to develop T2DM (odds ratio [OR]: 1.39, 95% confidence interval [CI]: 1.10–1.75) later in life compared with the control group. Moreover, only female siblings of schizophrenia probands had an increased risk of hypertension (OR: 1.47, 95% CI: 1.07–2.01) during the follow-up compared with the controls.
The unaffected siblings, especially sisters, of schizophrenia probands had a higher prevalence of T2DM and hypertension compared with the controls. Our study revealed a familial link between schizophrenia and T2DM in a large sample. Additional studies are required to investigate the shared pathophysiology of schizophrenia and T2DM.
Attention-deficit hyperactivity disorder (ADHD) increases the risk of suicidal behaviours through psychiatric comorbidities; however, a significant direct association has not been observed between ADHD and suicide attempts.
To evaluate the risk of suicide attempt in adolescents and young adults with ADHD.
Using a nationwide, population-based insurance claims database, this longitudinal cohort study enrolled 20 574 adolescents and young adults with ADHD and 61 722 age- and gender-matched controls between 2001 and 2009. Any suicide attempt was identified from enrolment to 31 December 2011. The association between ADHD medications and the likelihood of suicide attempt was assessed.
ADHD was an independent risk factor for any suicide attempt (hazard ratio = 3.84, 95% CI = 3.19–4.62) and repeated suicide attempts (hazard ratio = 6.52, 95% CI = 4.46–9.53). Subgroup analyses of men, women, adolescents and young adults demonstrated the same trend. Methylphenidate or atomoxetine treatment did not increase the risk of suicide attempt or repeated suicide attempts. Long-term methylphenidate treatment was associated with a significantly decreased risk of repeated suicide attempts in men (hazard ratio = 0.46, 95% CI = 0.22–0.97).
ADHD was a risk factor for suicide attempt and a stronger predictor of repeated suicide attempts, independent of comorbidities. Further investigation is warranted to explore the mechanism underlying the association between ADHD and suicidal behaviours.
Previous evidence has shown positive associations between post-traumatic
stress disorder (PTSD) and hypertension, dyslipidaemia and diabetes
mellitus, which are all risk factors for stroke, but the role of PTSD in
the subsequent development of stroke is still unknown.
To investigate the temporal association between PTSD and the development
Identified from the Taiwan National Health Insurance Research Database,
5217 individuals aged 18 years, with PTSD but with no history of stroke,
and 20 868 age- and gender-matched controls were enrolled between 2002
and 2009, and followed up until the end of 2011 to identify the
development of stroke.
Individuals with PTSD had an increased risk of developing any stroke
(hazard ratio (HR) 3.37, 95% CI 2.44–4.67) and ischaemic stroke (HR =
3.47, 95% CI 2.23–5.39) after adjusting for demographic data and medical
comorbidities. Sensitivity tests showed consistent findings (any stroke
HR = 3.02, 95% CI 2.13–4.28; ischaemic stroke HR = 2.89, 95% CI
1.79–4.66) after excluding the first year of observation.
Individuals with PTSD have an increased risk of developing any stroke and
ischaemic stroke. Further studies are required to investigate the