Trust between couples is a prerequisite for stable and satisfactory romantic relationships. However, there has been no valid research tool to assess partner-specific trust behavior including costly investments in the trustworthiness of the romantic partner. We here present a comprehensive validation of the newly developed Trust Game for Couples (TGC) by means of various self-report and implicit relationship-related measures. The TGC operationalizes trust by measuring an individual's willingness to invest his or her own financial resources in pro-relationship attitudes of their romantic partner (collected by dichotomous responses to relationship-relevant items, e.g., answering yes to "I am absolutely sure that I love my partner"). Thirty-five healthy couples between 20 and 34 years completed the TGC in an interactive (both partners present), but anonymous setting (no information on the partner's responses revealed). Trust, as measured by the TGC, correlates positively with self-reported trust, satisfaction, and felt closeness in the relationship, but not with general interpersonal trust, confirming both its convergent and discriminant validity. In addition to explicit criteria for construct validity, implicit measures of partner valence and confidence explained variance in the TGC, demonstrating that it constitutes an economical measure of implicit and explicit ingredients of trust between couples. In sum, the TGC provides a novel, specific behavioral tool for a sensitive assessment of trust in dyadic relationships with potential for numerous research fields.The gradient vector flow (GVF) is an effective external force to deform the active contours. However, it suffers from high computational cost. For efficiency, the virtual electric field (VEF) model has been proposed, which can be implemented in real time thanks to fast Fourier transform (FFT). The VEF model has large capture range and low computation cost, but it has the limitations of sensitivity to noise and leakage on weak edge. The recently proposed CONVEF (Convolutional Virtual Electric Field) model takes the VEF model as a convolutional operation and employed another convolution kernel to overcome the drawbacks of the VEF model. In this paper, we employ an edge stopping function similar to that in the anisotropic diffusion to further improve the CONVEF model, and the proposed model is referred to as MCONVEF (Modified CONVEF) model. In addition, a piecewise constant approximation algorithm is borrowed to accelerate the calculation of the MCONVEF model. The proposed MCONVEF model is compared with the GVF and VEF models, and the experimental results are presented to demonstrate its superiority in terms of noise robustness, weak edge preserving and deep concavity convergence.INTRODUCTION Angioedema is a subcutaneous swelling typically affecting the face, larynx or pharynx. It is a known adverse drug reaction (ADR) of ACE inhibitors (ACEi), angiotensin-II-receptor blockers (ARBs) and aliskiren (renin inhibitor). Several studies have reported pathophysiological mechanisms and risk factors of ACEi-associated angioedemas, whereas little is known for ARBs and aliskiren. The aim of the study was to analyze comparatively ACEi versus ARBs and aliskiren angioedema reports contained in the European ADR database EudraVigilance with regard to reported risk factors and clinical phenotypes. METHODS All spontaneous angioedema reports received between 01/2010-06/2017 reporting either an ACEi, ARB, or aliskiren as "suspected/interacting" drug were identified using the Standardized MedDRA Query "angioedema (narrow)". In order to perform a comparative analysis, odds ratios (ORs) were calculated for angioedema reports of ACEi (n = 3.194) versus ARBs (n = 687) and aliskiren (n = 162). RESULTS More pafirm our observation and elucidate the underyling causes.[This corrects the article DOI 10.1371/journal.pone.0227341.].INTRODUCTION Smoking is a strong risk factor for disease severity in Crohn's disease (CD) and cessation improves outcomes. The nicotine metabolite ratio (NMR) predicts cessation success with pharmacotherapy varenicline doubles cessation over nicotine replacement therapy (NRT) for "normal", but not "slow" metabolizers. Varenicline side effects are heightened in slow metabolizers. Methods using NMR to optimize cessation pharmacotherapy have not been evaluated in CD. AIMS We aim to determine the prevalence of smoking in a CD population and then assess these smokers' attitudes toward a personalized metabolism-informed care (MIC) approach to cessation. YAP-TEAD Inhibitor 1 mw METHODS In this observational study, we surveyed 1098 patients visiting an inflammatory bowel disease center about their smoking history. We then evaluated a subgroup of individuals with CD (n = 32) who participated in a randomized controlled trial of smoking cessation using MIC versus usual care. For MIC, medication selection was informed by the NMR (normal ≥0.31 vs. slow less then 0.31). The primary outcomes were intervention satisfaction and match rates between NMR and medication choice. RESULTS The baseline prevalence of smoking in our CD population was 13%. Intervention participants reported high rates of satisfaction (85%) and chose a medication that matched their NMR result more often in the MIC group (100% vs. 64%, p = 0.01). Six of 16 (37.5%) patients prescribed varenicline discontinued due to side effects. CONCLUSION MIC produced high rates of satisfaction and matching between NMR and medication in CD patients, supporting patient acceptance and feasibility of precision smoking cessation in this population. To reduce smoking in CD, therapies such as MIC are needed to maximize efficacy and minimize side effects.The quantitative understanding of human behavior is a key issue in modern science. Recently, inhomogeneous human activities have been described by bursts (consecutive activities separated by long periods of inactivity) and characterized by fat-tailed inter-event time (interval between two activities) distributions. However, the dynamics between number of activities and activity duration are still unclear. In this study, we analyzed 133 million toll-free call records from China to study the dynamics between call frequency and call duration. We confirmed that both call frequency and call duration exhibit circadian cycles and weekly cycles. By analyzing intraday patterns of these two metrics, we found the opposite volatility and clustered distributions. Results of clustering analysis showed that calling activity to toll-free numbers can be clustered into four clusters. In the "Work" cluster, the distribution of call duration was significantly different from that in the other clusters. The corresponding time of "Work" cluster was much shorter than estimates based on common sense.