Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.

Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.

Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.

These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.

Evidence has suggested that emotional dysregulation is a transdiagnostic feature in schizophrenia and major affective disorders. However, the relationship between emotional dysregulation and appetite hormone disturbance remains unknown in nonobese adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder.

In total, 22 adolescents with schizophrenia; 31 with bipolar disorder; 33 with major depressive disorder; and 41 healthy age-, sex-, and body mass index (BMI)/BMI percentile-matched controls were enrolled for assessing levels of appetite hormones, namely leptin, ghrelin, insulin, and adiponectin. Emotional regulation symptoms were measured using the parent-reported Child Behavior Checklist―Dysregulation Profile.

Adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder exhibited greater emotional dysregulation symptoms than the control group (P = .037). Adolescents with bipolar disorder demonstrated higher log-transformed levels of insulin (P = .029) and lower log-transformed levels of leptin (P = .018) compared with the control group. BMI (P < .05) and log-transformed ghrelin levels (P = .028) were positively correlated with emotional dysregulation symptoms.

Emotional dysregulation and appetite hormone disturbance may occur in the early stage of severe mental disorders. Further studies are required to clarify the unidirectional or bidirectional association of emotional dysregulation with BMI/BMI percentile and appetite hormones among patients with severe mental disorder.

With the disease spectrum changing in China, type 2 diabetes mellitus (T2DM) has become the main chronic disease which affects people’s health severely, bring patients serious economic burden of disease. For T2DM patients, reliable quality of evidence in decision-making are significant, improving the efficiency of the adjustment of the National Reimbursement Drug List (NRDL). Based on the Consolidated Health Economic Evaluation Reporting Standards (CHEERS), we aimed to evaluate the quality of all published pharmacoeconomic evaluations on T2DM drugs in 2020 NRDL.

Because the 2020 NRDL came into effect on 1 March 2021, we searched all published pharmacoeconomic evaluations about T2DM drugs in 2020 NRDL before March 2021 in China National Knowledge Infrastructure (CNKI), Wan fang Data, China Science and Technology Journal Database (VIP), PubMed, and Web of Science. According to the criterion of inclusion and exclusion, all documents were screened and then relevant basic information of targeted documents was extracted. The quality was evaluated by calculating the final scores based on CHEERS. Two reviewers assessed each publication’s quality using the CHEERS instrument and summarized study quality.

A total of 910 papers were searched, and 24 papers were included. These involved six T2DM drugs, specifically IDegAsp, exenatide, liraglutide, lixisenatide, dapagliflozin and empagliflozin. The average score was 18.31, the standard deviation was 3.67, and the average scoring rate was 77.41 percent. Among all items, “characterizing heterogeneity” scored 0.04, least satisfied with requirements. “Setting and location”, “choice of health outcomes” and “assumptions” scored one, most satisfied with requirements. Among the average scores of all parts, “results” scored lowest at 0.55, and “methods” scored highest at 0.85. The Wilcoxon sum-rank tests showed that score rate which represented reporting quality of economic evaluation (EE) was significantly related to “journal type”, “EEs type”, “model choice” and “study perspective”.

The methodological quality of pharmacoeconomic evaluations about T2DM drugs in 2020 NRDL needs to be improved. Improving the quality of literature is the basic guarantee of scientific decision-making in national medical insurance negotiation.

Although attentional bias modification training (ABM) and cognitive behavioural therapy (CBT) are two effective methods to decrease the symptoms of generalized anxiety disorders (GAD), to date, no randomized controlled trials have yet evaluated the effectiveness of an intervention combining internet-based cognitive behavioural therapy (ICBT) and ABM for adults with GAD.

This study aimed to investigate the effectiveness of an intervention combining ICBT and ABM for adults with GAD.

Sixty-three participants diagnosed with GAD were randomly assigned to the treatment group (ICBT with ABM; 31 participants) or the control group (ICBT with ABM placebo; 32 participants), and received 8 weeks of treatment and three evaluations. The CBT, ABM and ABM-placebo training were conducted via the internet. The evaluations were conducted at baseline, 8 weeks later, and 1 month later, respectively.

Both the treatment and control groups reported significantly reduced anxiety symptoms and attentional bias, with no clear superiority of either intervention. However, the treatment group showed a greater reduction in negative automatic thoughts than the control group after treatment and at 1-month follow-up (η2 = 0.123).

The results suggest that although not differing in therapeutic efficacy, the intervention combining ICBT and ABM is superior to the intervention combining ICBT and ABM-placebo in the reduction of negative automatic thoughts. ABM may be a useful augmentation of ICBT on reducing anxiety symptoms.

Caregiver-mediated intervention (CMI), based on parent skills training, is a family-mediated intervention model for children with neurodevelopmental disorders, in particular autism spectrum disorder. This study aimed to evaluate the effectiveness of CMI.

Thirty-three children (aged 22–69 months from our department) and their caregivers participated in a two-week training course of ten 90-minute lessons. Caregivers were encouraged to try their best to apply intervention skills in both home routines and play routines to encourage the development of cognition, motion, social adaptability, and behavior of children. Demographic information, video-recorded data, and diagnostic scales were collected at two key time points: baseline and post-training (PT – within six months).

Three aspects were assessed – primary variables, secondary variables, and correlation analyses. Results showed an improvement in PT in (1) Adult/Child Interaction Fidelity Rating (P < 0.01) and (2) adaptability of Gesell Developmental Scale and stereotyped behaviors and limited interests of Autism Diagnostic Observation Schedule (P < 0.05, P < 0.01). Moreover, a negative correlation occurred between caregiver skill improvement and parent education (P < 0.05), but without correlations with other demographics.

As an efficacious family intervention for both children and their caregivers, CMI is worth being generalized widely.

Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM).

CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants.

The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect.

These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.

To investigate the association between folate levels and the risk of gestational diabetes mellitus (GDM) risk during the whole pregnancy.

In this retrospective cohort study of pregnant women, serum folate levels were measured before 24 gestational weeks (GW). GDM was diagnosed between 24th and 28th GW based on the criteria of the International Association of Diabetes and Pregnancy Study Groups. General linear models were performed to examine the association of serum folate with plasma glucose (i.e. linear regressions) and risk of GDM (i.e. log-binomial regressions) after controlling for confounders. Restricted cubic spline regression was conducted to test the dosage–response relationship between serum folate and the risk of GDM.

A sigle, urban hospital in Shanghai, China.

A total of 42 478 women who received antenatal care from April 2013 to March 2017 were included.

Consistent positive associations were observed between serum folate and plasma glucose levels (fasting, 1-h, 2-h). The adjusted relative risks (RR) and 95 % CI of GDM across serum folate quartiles were 1·00 (reference), 1·15 (95 % CI (1·04, 1·26)), 1·40 (95 % CI (1·27, 1·54)) and 1·54 (95 % CI (1·40, 1·69)), respectively (P-for-trend < 0·001). The positive association between serum folate and GDM remained when stratified by vitamin B12 (adequate v. deficient groups) and the GW of serum folate measurement (≤13 GW v. >13 GWs)

The findings of this study may provide important evidence for the public health and clinical guidelines of pregnancy folate supplementation in terms of GDM prevention.

Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.

T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.

As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.

In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.