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Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

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BackgroundIn recent years, the rapid development of mobile medical technology has provided multiple ways for the long-term management of chronic diseases, especially diabetes. As a new type of management model, smartphone apps are global, convenient, cheap, and interactive. Although apps were proved to be more effective at glycemic control, compared with traditional computer- and Web-based telemedicine technologies, how to gain a further and sustained improvement is still being explored.ObjectiveThe objective of this study was to investigate the effectiveness of an app-based interactive management model by a professional health care team on glycemic control in Chinese patients with poorly controlled diabetes.MethodsThis study was a 6-month long, single-center, prospective randomized controlled trial. A total of 276 type 1 or type 2 diabetes patients were enrolled and randomized to the control group (group A), app self-management group (group B), and app interactive management group (group C) in a 1:1:1 ratio. The primary outcome was the change in glycated hemoglobin (HbA1c) level. Missing data were handled by multiple imputation.ResultsAt months 3 and 6, all 3 groups showed significant decreases in HbA1c levels (all P<.05). Patients in the app interactive management group had a significantly lower HbA1clevel than those in the app self-management group at 6 months (P=.04). The average HbA1c reduction in the app interactive management group was larger than that in the app self-management and control groups at both months 3 and 6 (all P<.05). However, no differences in HbA1c reduction were observed between the app self-management and control groups at both months 3 and 6 (both P>.05). Multivariate line regression analyses also showed that the app interactive management group was associated with the larger reduction of HbA1c compared with groups A and B at both months 3 and 6 (all P>.05). In addition, the app interactive management group had better control of triglyceride and high-density lipoprotein cholesterol levels at both months 3 and 6 compared with baseline (both P<.05).ConclusionsIn Chinese patients with poorly controlled diabetes, it was difficult to achieve long-term effective glucose improvement by using app self-management alone, but combining it with interactive management can help achieve rapid and sustained glycemic control.Trial RegistrationClinicalTrials.gov NCT02589730; https://clinicaltrials.gov/ct2/show/NCT02589730.

The goals were twofold: To estimate the depression and anxiety levels among caregivers of patients with eating disorders (ED) in China during the COVID-19 pandemic when compared with a control group, and to assess whether an online education program was effective in decreasing the anxiety and depression of the caregivers of patients with ED, and associated factors. Method: Caregivers of patients with ED (n = 254) and a comparison group of non-ED caregivers (N = 254) were recruited at baseline. Additionally, caregivers of patients with ED were invited into a free 4-week online education program, with an additional online group as support. Depression and anxiety levels were assessed at baseline and after the intervention. Results: Caregivers of patients with ED showed significantly higher levels of depression and anxiety than the comparison group of non-ED caregivers. The online education program showed no significant effect on decreasing depression and anxiety levels of caregivers of patients with ED overall. Caregivers who had older loved ones and not living with them were more likely to decrease their depression levels. Caregivers of patients with longer illness duration were less likely to decrease their anxiety levels. Discussion: These results showed that caregivers of ED patients suffered more serious psychological distress during the pandemic. A more structured and intensive online intervention with a limited number of participants might be required to address caregivers' distress in post-COVID-19 China.

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This paper uses quantile regression, while accounting for spatial autocorrelation, to examine the simultaneous space-time impact of foreclosures on neighborhood property values. We find that negative price externalities associated with neighborhood foreclosures are greatest (1) among lower-priced homes, (2) within 250 feet of the property and (3) in the 12 months following a foreclosure auction. By using quantile regression, we are able to also investigate changes in the distribution of house prices associated with varying levels of neighborhood foreclosures.

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