The Healthcare Future for the iGeneration: Integrating the Patient and the Healthcare System

Objective: To propose a vision to integrate patients, their health-related data, and their wellness plans into the healthcare system using smartphone and tablet computer technology. Setting: Ambulatory care and community practice Practice Innovation: Utilization of smartphone and tablet computer technology to assess health care conditions, educate and involve patients, and facilitate seamless communication between the patient, electronic health record, pharmacy system, third-party payers, point-of-care testing, and all health-care providers. Main Outcome Measures: By providing integrated and customized information at the point of use, medication adherence and access to care will be increased and patients will engage in healthy behaviors more often resulting in an improved level of care for patients. Results: In the future, the authors believe if the vision is achieved, the health care system and patients will see improved health outcomes and more efficient utilization of the healthcare system. Conclusions: Our proposed use of technology provides an opportunity to empower patients to positively improve their own health which could be a vital advancement in health care, especially in the areas of medication adherence, improving access to care, and health behavior support. As pharmacists, we may also embrace technology opportunities to expand our roles as health care professionals as we continue to partner with patients and the health care team to improve outcomes.   Type: Idea Pape

Interactive Feedforward for Improving Performance and Maintaining Intrinsic Motivation in VR Exergaming

Exergames commonly use low to moderate intensity exercise protocols. Their effectiveness in implementing high intensity protocols remains uncertain. We propose a method for improving performance while maintaining intrinsic motivation in high intensity VR exergaming. Our method is based on an interactive adaptation of the feedforward method: a psychophysical training technique achieving rapid improvement in performance by exposing participants to self models showing previously unachieved performance levels. We evaluated our method in a cycling-based exergame. Participants competed against (i) a self model which represented their previous speed; (ii) a self model representing their previous speed but increased resistance therefore requiring higher performance to keep up; or (iii) a virtual competitor at the same two levels of performance. We varied participants' awareness of these differences. Interactive feedforward led to improved performance while maintaining intrinsic motivation even when participants were aware of the interventions, and was superior to competing against a virtual competitor

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 x 10(-8)) with GDM, mapping to/near MTNR1B (P = 4.3 x 10(-54)), TCF7L2 (P = 4.0 x 10(-16)), CDKAL1 (P = 1.6 x 10(-4)), CDKN2A-CDKN2B (P = 4.1 x 10(-9)) and HKDC1 (P = 2.9 x 10(-8)). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.Peer reviewe

Global Oceans

Global Oceans is one chapter from the State of the Climate in 2019 annual report and is avail-able from https://doi.org/10.1175/BAMS-D-20-0105.1. Compiled by NOAA’s National Centers for Environmental Information, State of the Climate in 2019 is based on contr1ibutions from scien-tists from around the world. It provides a detailed update on global climate indicators, notable weather events, and other data collected by environmental monitoring stations and instru-ments located on land, water, ice, and in space. The full report is available from https://doi.org /10.1175/2020BAMSStateoftheClimate.1

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe