The Things You Do:Internal Models of Others' Expected Behaviour Guide Action Observation

Predictions allow humans to manage uncertainties within social interactions. Here, we investigate how explicit and implicit person models-how different people behave in different situations-shape these predictions. In a novel action identification task, participants judged whether actors interacted with or withdrew from objects. In two experiments, we manipulated, unbeknownst to participants, the two actors action likelihoods across situations, such that one actor typically interacted with one object and withdrew from the other, while the other actor showed the opposite behaviour. In Experiment 2, participants additionally received explicit information about the two individuals that either matched or mismatched their actual behaviours. The data revealed direct but dissociable effects of both kinds of person information on action identification. Implicit action likelihoods affected response times, speeding up the identification of typical relative to atypical actions, irrespective of the explicit knowledge about the individual's behaviour. Explicit person knowledge, in contrast, affected error rates, causing participants to respond according to expectations instead of observed behaviour, even when they were aware that the explicit information might not be valid. Together, the data show that internal models of others' behaviour are routinely re-activated during action observation. They provide first evidence of a person-specific social anticipation system, which predicts forthcoming actions from both explicit information and an individuals' prior behaviour in a situation. These data link action observation to recent models of predictive coding in the non-social domain where similar dissociations between implicit effects on stimulus identification and explicit behavioural wagers have been reported

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Differences in Healthcare Transition Views, Practices, and Barriers Among North American Pediatric Rheumatology Providers from 2010 to 2018

Background/Purpose: Healthcare transition is the “purposeful, planned movement of adolescents and young adults with chronic physical and medical conditions from child-centered to adult-oriented health care systems.” The American College of Physicians has partnered with national organizations, including the ACR, to develop guidelines and tools to promote a smooth transition to adult care. We aim to assess current transition practices and beliefs among North American pediatric rheumatology providers and to identify differences from a 2010 provider survey published by Chira et al. Methods: In April 2018, Childhood Arthritis and Rheumatology Research Alliance (CARRA) members received a 25-item online survey about healthcare transition. Got Transition’s Current Assessment of Health Care Transition Activities for Transitioning Youth to Adult Health Care Providers was used to measure clinical transition processes on a scale of 1 (basic) to 4 (comprehensive). Bivariate data analysis was used to compare 2010 and 2018 survey findings. Results: Over half of CARRA members completed the 2018 survey. Participants included pediatric rheumatologists (74%), adult- and pediatric-trained rheumatologists (4%), pediatric rheumatology fellows (18%), and other (4%), including emeritus faculty and mid-level providers. Most belonged to university-affiliated practices (87%) in the U.S. (91%). Providers aim to transfer patients at age 18 (23%) or 21 (33%), but the actual age of transfer is often 21 or older (56%). The most common target age to begin transition planning was 15-17 (49%). Few providers use the ACR transition tools (31%) or have a dedicated transition clinic (23%). Only 17% have a transition policy in place; 63% do not consistently address healthcare transition. Transition outcomes of interest included an adult rheumatology visit within 6 months of the last pediatric visit (80%), adherence to medications and plan of care (78%), continuous insurance coverage (78%), and patient-reported gaps in access to care (76%). When compared to the 2010 survey, improvement was noted in 3 of 12 transition barriers: availability of adult primary care providers, availability of adult rheumatologists, and transition knowledge and skills of pediatric staff (p\u3c0.001). However, more providers cited the close bond among adolescents, parents and pediatric providers as a barrier (Figure 1). Conclusion: This survey of pediatric rheumatology providersdemonstrates some improvement in transition barriers since 2010, though most practices still maintain minimal support for patients and providers around healthcare transition. Further research is needed to understand how to effectively facilitate transition to adult care for young adults with childhood-onset rheumatic diseases

Differences in Healthcare Transition Views, Practices, and Barriers Among North American Pediatric Rheumatology Clinicians From 2010 to 2018.

Objective. Since 2010, the rheumatology community has developed guidelines and tools to improve healthcare transition. In this study, we aimed to compare current transition practices and beliefs among Childhood Arthritis and Rheumatology Research Alliance (CARRA) rheumatology providers with transition practices from a provider survey published in 2010. Methods. In 2018, CARRA members completed a 25-item online survey about healthcare transition. Got Transition\u27s Current Assessment of Health Care Transition Activities was used to measure clinical transition processes on a scale of 1 (basic) to 4 (comprehensive). Bivariate analyses were used to compare 2010 and 2018 survey findings. Results. Over half of CARRA members completed the survey (202/396), including pediatric rheumatologists, adult- and pediatric-trained rheumatologists, pediatric rheumatology fellows, and advanced practice providers. The most common target age to begin transition planning was 15-17 years (49%). Most providers transferred patients prior to age 21 years (75%). Few providers used the American College of Rheumatology transition tools (31%) or have a dedicated transition clinic (23%). Only 17% had a transition policy in place, and 63% did not consistently address healthcare transition with patients. When compared to the 2010 survey, improvement was noted in 3 of 12 transition barriers: availability of adult primary care providers, availability of adult rheumatologists, and pediatric staff transition knowledge and skills (P \u3c 0.001 for each). Nevertheless, the mean current assessment score was \u3c 2 for each measurement. Conclusion. This study demonstrates improvement in certain transition barriers and practices since 2010, although implementation of structured transition processes remains inconsistent