BackgroundPokémon GO is a location‐based augmented reality game. Using GPS and the camera on a smartphone, the game requires players to travel in real world to capture animated creatures, called Pokémon. We examined the impact of Pokémon GO on physical activity (PA).Methods and ResultsA pre‐post observational study of 167 Pokémon GO players who were self‐enrolled through recruitment flyers or online social media was performed. Participants were instructed to provide screenshots of their step counts recorded by the iPhone Health app between June 15 and July 31, 2016, which was 3 weeks before and 3 weeks after the Pokémon GO release date. Of 167 participants, the median age was 25 years (interquartile range, 21–29 years). The daily average steps of participants at baseline was 5678 (SD, 2833; median, 5718 [interquartile range, 3675–7279]). After initiation of Pokémon GO, daily activity rose to 7654 steps (SD, 3616; median, 7232 [interquartile range, 5041–9744], pre‐post change: 1976; 95% CI, 1494–2458, or a 34.8% relative increase [P<0.001]). On average, 10 000 “XP” points (a measure of game progression) was associated with 2134 additional steps per day (95% CI, 1673–2595), suggesting a potential dose‐response relationship. The number of participants achieving a goal of 10 000+ steps per day increased from 15.3% before to 27.5% after (odds ratio, 2.06; 95% CI, 1.70–2.50). Increased PA was also observed in subgroups, with the largest increases seen in participants who spent more time playing Pokémon GO, those who were overweight/obese, or those with a lower baseline PA level.ConclusionsPokémon GO participation was associated with a significant increase in PA among young adults. Incorporating PA into gameplay may provide an alternative way to promote PA in persons who are attracted to the game.Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT02888314.
A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.
Background Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people’s physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors. Objective This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19. Methods We used the web-crawling tool Scrapy to gather data published by People’s Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens’ comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent’s Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors. Results Our results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02). Conclusions Our findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency.
Introduction: Direct oral anticoagulants (DOACs) are increasingly used as alternatives to warfarin for secondary prevention in ischemic stroke patients with atrial fibrillation. Despite demonstrated efficacy in clinical trials, there are few real-world experiences of DOACs vs. warfarin in community practice. Methods: We analyzed ischemic stroke survivors with atrial fibrillation discharged from the Get With The Guidelines Stroke hospitals between 2011-2014 and linked to Medicare claims for longitudinal outcomes through 2015. A propensity score overlap weighting method was used to compare DOACs vs. warfarin. The primary outcomes were major adverse cardiovascular events (MACE) and home time, a patient-centered outcome reflecting desire of “being alive at home, without recurrent stroke, or being hospitalized for complications.” Results: Among 11,662 stroke survivors (median age 80), 4,041 (34.7%) were discharged on DOACs (dabigatran, rivaroxaban, or apixaban) and 7,621 on warfarin. Except for NIHSS (median 4 [IQR 1-9] vs. 5 [2-11]), baseline demographics, medical history, and clinical characteristics were similar between two cohorts. Compared with warfarin, patients discharged on DOACs were less likely to experience MACE (33.95% vs. 40.36% per year, adjusted hazard ratio 0.89, 99% CI 0.83-0.96) and had more days at home (mean 287 vs. 263 days during the first year post discharge, adjusted difference 15.6 days, 99% CI 9.0-22.1) ( Table ). Additionally, there were fewer deaths, all-cause readmissions, cardiovascular readmissions, hemorrhagic strokes, and bleeding hospitalizations in DOAC-treated patients, although no significant differences in fatal bleeding, ischemic stroke readmission, systemic embolism, pneumonia, or sepsis (two negative outcome controls) between the two cohorts. Conclusions: In ischemic stroke survivors with atrial fibrillation, DOACs were associated with improved long-term clinical outcomes compared with warfarin.
Aims Although atrial fibrillation (AF) frequently coexists with heart failure with preserved ejection fraction (HFpEF), few data are available evaluating AF‐specific care patterns and post‐discharge outcomes in patients hospitalized for HFpEF. We evaluated AF‐specific medical therapies and post‐discharge outcomes among patients hospitalized for heart failure with mildly reduced ejection fraction (HFmrEF) or HFpEF by AF history. Methods and results Trends in AF prevalence were evaluated among patients hospitalized for HFmrEF or HFpEF in the Get With The Guidelines‐Heart Failure Registry from 2014 to 2020. Among those with linked Centers for Medicare & Medicaid Services post‐discharge data, we assessed associations of AF with 12‐month outcomes and determined trends in post‐discharge prescriptions. Among 429 464 patients (median age 76 years [interquartile range 65–85], 57% women), 216 486 (50%) had a history of AF. Over time, the proportion of patients with AF increased slightly. Among the 79 895 patients with post‐discharge data, AF was independently associated with higher risk of mortality and all‐cause readmissions at 12 months, with stronger associations in HFpEF than in HFmrEF (mortality hazard ratio [HR] 1.13, 95% confidence interval [CI] 1.09–1.16 vs. HR 1.03, 95% CI 0.97–1.10; pinteraction = 0.009). Anti‐arrhythmic drug use after heart failure hospitalization was low (18%) and increased modestly over time. Amiodarone accounted for 71% of total anti‐arrhythmic drug prescriptions. Overall use of anticoagulants after heart failure hospitalization has significantly increased from 52% in 2014 to 61% in 2019, but remained modest. Conclusion Prevalence of AF is rising among patients hospitalized with HFpEF. Those with comorbid AF face elevated post‐discharge risks of death and rehospitalization. Current use of pharmacological rhythm control is low.
Purpose: Noninvasive prenatal screening (NIPS) sequences a mixture of the maternal and fetal cell-free DNA. Fetal trisomy can be detected by examining chromosomal dosages estimated from sequencing reads. The traditional method uses the Z-test, which compares a subject against a set of euploid controls, where the information of fetal fraction is not fully utilized. Here we present a Bayesian method that leverages informative priors on the fetal fraction.Method: Our Bayesian method combines the Z-test likelihood and informative priors of the fetal fraction, which are learned from the sex chromosomes, to compute Bayes factors. Bayesian framework can account for nongenetic risk factors through the prior odds, and our method can report individual positive/negative predictive values.Results: Our Bayesian method has more power than the Z-test method. We analyzed 3,405 NIPS samples and spotted at least 9 (of 51) possible Z-test false positives.Conclusion: Bayesian NIPS is more powerful than the Z-test method, is able to account for nongenetic risk factors through prior odds, and can report individual positive/negative predictive values.
Purpose: To assess the potential added value of Optical Genomic Mapping (OGM) for identifying chromosomal aberrations. Methods: We utilized Optical Genomic Mapping (OGM) to determine chromosomal aberrations in 46 children with B-cell Acute lymphoblastic leukemia ALL (B-ALL) and compared the results of OGM with conventional technologies. Partial detection results were verified by WGS and PCR. Results: OGM showed a good concordance with conventional cytogenetic techniques in identifying the reproducible and pathologically significant genomic SVs. Two new fusion genes (LMNB1::PPP2R2B and TMEM272::KDM4B) were identified by OGM and verified by WGS and RT-PCR for the first time. OGM has a greater ability to detect complex chromosomal aberrations, refine complicated karyotypes, and identify more SVs. Several novel fusion genes and single-gene alterations, associated with definite or potential pathologic significance that had not been detected by traditional methods, were also identified. Conclusion: OGM addresses some of the limitations associated with conventional cytogenomic testing. This all-in-one process allows the detection of most major genomic risk markers in one test, which may have important meanings for the development of leukemia pathogenesis and targeted drugs.
It has been argued that vaccine-breakthrough infections of SARS-CoV-2 would likely accelerate the emergence of novel variants with immune evasion. This study explored the evolutionary patterns of the Delta variant in countries/regions with relatively high and low vaccine coverage based on large-scale sequences. Our results showed that (i) the sequences were grouped into two clusters (L and R); the R cluster was dominant, its proportion increased over time and was higher in the high-vaccine-coverage areas; (ii) genetic diversities in the countries/regions with low vaccine coverage were higher than those in the ones with high vaccine coverage; (iii) unique mutations and co-mutations were detected in different countries/regions; in particular, common co-mutations were exhibited in highly occurring frequencies in the areas with high vaccine coverage and presented in increasing frequencies over time in the areas with low vaccine coverage; (iv) five sites on the S protein were under strong positive selection in different countries/regions, with three in non-C to U sites (I95T, G142D and T950N), and the occurring frequencies of I95T in high vaccine coverage areas were higher, while G142D and T950N were potentially immune-pressure-selected sites; and (v) mutation at the N6-methyladenosine site 4 on ORF7a (C27527T, P45L) was detected and might be caused by immune pressure. Our study suggested that certain variation differences existed between countries/regions with high and low vaccine coverage, but they were not likely caused by host immune pressure. We inferred that no extra immune pressures on SARS-CoV-2 were generated with high vaccine coverage, and we suggest promoting and strengthening the uptake of the COVID-19 vaccine worldwide, especially in less developed areas.
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