Emotion regulation (ER) refers to the “implementation of a conscious or non-conscious goal to start, stop or otherwise modulate the trajectory of an emotion” (Etkin et al., 2015). Whereas multiple brain areas have been found to be involved in ER, relatively little is known about whether and how ER is associated with the global functioning of brain networks. Recent advances in brain connectivity research using graph-theory based analysis have shown that the brain can be organized into complex networks composed of functionally or structurally connected brain areas. Global efficiency is one graphic metric indicating the efficiency of information exchange among brain areas and is utilized to measure global functioning of brain networks. The present study examined the relationship between trait measures of ER (expressive suppression (ES) and cognitive reappraisal (CR)) and global efficiency in resting-state functional brain networks (the whole brain network and ten predefined networks) using structural equation modeling (SEM). The results showed that ES was reliably associated with efficiency in the fronto-parietal network and default-mode network. The finding advances the understanding of neural substrates of ER, revealing the relationship between ES and efficient organization of brain networks.

As a commonly used tool for operationalizing measurement models, confirmatory factor analysis (CFA) requires strong assumptions that can lead to a poor fit of the model to real data. The post-hoc modification model approach attempts to improve CFA fit through the use of modification indexes for identifying significant correlated residual error terms. We analyzed a 28-item emotion measure collected for n = 175 participants. The post-hoc modification approach indicated that 90 item-pair errors were significantly correlated, which demonstrated the challenge in using a modification index, as the error terms must be individually modified as a sequence. Additionally, the post-hoc modification approach cannot guarantee a positive definite covariance matrix for the error terms. We propose a method that enables the entire inverse residual covariance matrix to be modeled as a sparse positive definite matrix that contains only a few off-diagonal elements bounded away from zero. This method circumvents the problem of having to handle correlated residual terms sequentially. By assigning a Lasso prior to the inverse covariance matrix, this Bayesian method achieves model parsimony as well as an identifiable model. Both simulated and real data sets were analyzed to evaluate the validity, robustness, and practical usefulness of the proposed procedure.

Objective To determine the prevalence of anxiety and depression in general practice patients and assess management of these conditions by general practitioners (GPs). Methods A random sample of 212 GPs were approached to be interviewed and to conduct a patient survey and audit on 50 consecutive patient consultations during 1993. Participants 117 GPs (55% response rate) and 4867 patients (85%) who completed questionnaires suitable for analysis. Setting General practices in two areas (divisions of general practice) in Sydney, New South Wales. Results Thirty‐six per cent of patients had abnormal scores on a General Health Questionnaire (GHQ‐12); they were more likely to be women or to be unemployed. Twenty per cent of these patients had been treated for depression or anxiety in the previous 12 months; 52% were prescribed drug therapy, and were more likely to be older, male or unemployed. Seventy per cent of patients reported having been offered therapy by their GP that did not involve drugs. Twenty‐four per cent had been referred to another health professional; they were more likely to be younger, or men, or patients attending their usual doctor. Conclusions A brief screening instrument may improve GPs’ detection rate of patients with anxiety or depression. The high prevalence of these conditions in unemployed people deserves particular attention by GPs. Both drug and non‐drug therapies are being more appropriately applied in general practice than previously.

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a b s t r a c tWhether Cyclophilin A (CyPA) functions as a foldase or a chaperone when assisting protein folding has long been argued. In this study, we engineered four variants of recombinant human Cyclophilin A (rhCyPA), all of which were inactive to tetrapeptide substrate Suc-AAPF-pNA. However, these variants were able to suppress aggregation during arginine kinase (AK) refolding as efficient as wildtype rhCyPA, especially, variant Q63A had even more efficiency to suppress aggregation and improve reactivation yields of AK. These results indicate that rhCyPA have peptidyl-prolyl cis-trans isomerase (PPIase) independent chaperone-like activity during AK folding. In addition, results suggest that surface hydrophobicity of rhCyPA can suppress AK aggregation and binding to rhCyPA hydrophobic active pocket is a prerequisite for chaperoning AK folding.