7,179 research outputs found

    Erratum: Vital Signs During the COVID-19 Outbreak: A Retrospective Analysis of 19,960 Participants in Wuhan and Four Nearby Capital Cities in China (Global Heart (2021) 16: 1 (47) DOI: 10.5334/gh.913)

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    This article details a correction to: Li J-W, Guo Y-T, Di Tanna GL, Neal B, Chen Y-D, Schutte AE. Vital Signs During the COVID-19 Outbreak: A Retrospective Analysis of 19,960 Participants in Wuhan and Four Nearby Capital Cities in China. Global Heart. 2021;16(1):47. DOI: http://doi.org/10.5334/gh.913. CORRECTION The original article was published without complete funding details. It listed one funder, the National Natural Science Foundation of China (H2501), National Key Research and Development Project of China (2018YFC2001200). There was another funder missing from the original article, the Chinese Military Health Care (20BJZ26). The originally listed funder covered expenses for enrolment and follow-up of patients, and the purchase and maintenance of necessary equipment. The second funder covered the costs of publication. COMPETING INTERESTS J.L. held an International Postdoctoral Exchange Fellowship Program China (20170103) during the course of this work. G. Tao has no disclosures. A.E. Schutte received speaker honoraria from Omron Healthcare, Takeda Pharmaceuticals, Novartis, Servier, and serves on research advisory board for Abbott. She is President of the International Society of Hypertension, 2018-2020. G.L. Di Tanna has no disclosures. B. Neal is supported by an Australian National Health and Medical Research Council Principal Research Fellowship; holds a research grant for this study from Janssen; and has held research grants for other large-scale cardiovascular outcome trials from Roche, Servier, and Merck Schering Plough; and his institution has received consultancy, honoraria, or travel support for contributions he has made to advisory boards and/or the continuing medical education programs of Abbott, Janssen, Novartis, Pfizer, Roche, and Servier. Y. Chen has no disclosures

    Testing and comparing two self-care-related instruments among older Chinese adults

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    Objectives The study aimed to test and compare the reliability and validity, including sensitivity and specificity of the two self-care-related instruments, the Self-care Ability Scale for the Elderly (SASE), and the Appraisal of Self-care Agency Scale-Revised (ASAS-R), among older adults in the Chinese context. Methods A cross-sectional design was used to conduct this study. The sample consisted of 1152 older adults. Data were collected by a questionnaire including the Chinese version of SASE (SASE-CHI), the Chinese version of ASAS-R (ASAS-R-CHI) and the Exercise of Self-Care Agency scale (ESCA). Homogeneity and stability, content, construct and concurrent validity, and sensitivity and specificity were assessed. Results The Cronbach's alpha (α) of SASE-CHI was 0.89, the item-to-total correlations ranged from r = 0.15 to r = 0.81, and the test-retest correlation coefficient (intra-class correlation coefficient, ICC) was 0.99 (95% CI, 0.99±1.00; P<0.001). The Cronbach's α of ASAS-R-CHI was 0.78, the item-to-total correlations ranged from r = 0.20 to r = 0.65, and the test-retest ICC was 0.95 (95% CI, 0.92±0.96; P<0.001). The content validity index (CVI) of SASE-CHI and ASAS-R-CHI was 0.96 and 0.97, respectively. The findings of exploratory and confirmatory factor analyses (EFA and CFA) confirmed a good construct validity of SASE-CHI and ASAS-R-CHI. The Pearson's rank correlation coefficients, as a measure of concurrent validity, between total score of SASE-CHI and ESCA and ASAS-R-CHI and ESCA were assessed to 0.65 (P<0.001) and 0.62 (P<0.001), respectively. Regarding ESCA as the criterion, the area under the receiver operator characteristic (ROC) curve for the cut-point of SASE-CHI and ASAS-R-CHI were 0.93 (95% CI, 0.91±0.94) and 0.83 (95% CI, 0.80±0.86), respectively. Conclusion There is no significant difference between the two instruments. Each has its own characteristics, but SASE-CHI is more suitable for older adults. The key point is that the users can choose the most appropriate scale according to the specific situation.publishedVersionNivå

    Health-related quality of life as measured with EQ-5D among populations with and without specific chronic conditions: A population-based survey in Shaanxi province, China

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    © 2013 Tan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Introduction: The aim of this study was to examine health-related quality of life (HRQoL) as measured by EQ-5D and to investigate the influence of chronic conditions and other risk factors on HRQoL based on a distributed sample located in Shaanxi Province, China. Methods: A multi-stage stratified cluster sampling method was performed to select subjects. EQ-5D was employed to measure the HRQoL. The likelihood that individuals with selected chronic diseases would report any problem in the EQ-5D dimensions was calculated and tested relative to that of each of the two reference groups. Multivariable linear regression models were used to investigate factors associated with EQ VAS. Results: The most frequently reported problems involved pain/discomfort (8.8%) and anxiety/depression (7.6%). Nearly half of the respondents who reported problems in any of the five dimensions were chronic patients. Higher EQ VAS scores were associated with the male gender, higher level of education, employment, younger age, an urban area of residence, access to free medical service and higher levels of physical activity. Except for anemia, all the selected chronic diseases were indicative of a negative EQ VAS score. The three leading risk factors were cerebrovascular disease, cancer and mental disease. Increases in age, number of chronic conditions and frequency of physical activity were found to have a gradient effect. Conclusion: The results of the present work add to the volume of knowledge regarding population health status in this area, apart from the known health status using mortality and morbidity data. Medical, policy, social and individual attention should be given to the management of chronic diseases and improvement of HRQoL. Longitudinal studies must be performed to monitor changes in HRQoL and to permit evaluation of the outcomes of chronic disease intervention programs. © 2013 Tan et al.National Nature Science Foundation (No. 8107239

    Sources of and Solutions to Toxic Metal and Metalloid Contamination in Small Rural Drinking Water Systems: A Rapid Review

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    Exposure to toxic metals and metalloids (TMs) such as arsenic and lead at levels of concern is associated with lifelong adverse health consequences. As exposure to TMs from paint, leaded gasoline, canned foods, and other consumer products has decreased in recent decades, the relative contribution of drinking water to environmental TM exposure and associated disease burdens has increased. We conducted a rapid review from June to September 2019 to synthesize information on the sources of TM contamination in small rural drinking water systems and solutions to TM contamination from these sources, with an emphasis on actionable evidence applicable to small rural drinking water systems worldwide. We reviewed publications from five databases (ProQuest, PubMed, Web of Science, Embase, and Global Health Library) as well as grey literature from expert groups including WHO, IWA, and others; findings from 61 eligible review publications were synthesized. Identified sources of TMs in included studies were natural occurrence (geogenic), catchment pollution, and corrosion of water distribution system materials. The review found general support for preventive over corrective actions. This review informs a useful planning and management framework for preventing and mitigating TM exposure from drinking water based on water supply characteristics, identified contamination sources, and other context-specific variables

    Seeing two faces together: preference formation in humans and rhesus macaques

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    Humans, great apes and old world monkeys show selective attention to faces depending on conspecificity, familiarity, and social status supporting the view that primates share similar face processing mechanisms. Although many studies have been done on face scanning strategy in monkeys and humans, the mechanisms influencing viewing preference have received little attention. To determine how face categories influence viewing preference in humans and rhesus macaques (Macaca mulatta), we performed two eye-tracking experiments using a visual preference task whereby pairs of faces from different species were presented simultaneously. The results indicated that viewing time was significantly influenced by the pairing of the face categories. Humans showed a strong bias towards an own-race face in an Asian–Caucasian condition. Rhesus macaques directed more attention towards non-human primate faces when they were paired with human faces, regardless of the species. When rhesus faces were paired with faces from Barbary macaques (Macaca sylvanus) or chimpanzees (Pan troglodytes), the novel species’ faces attracted more attention. These results indicate that monkeys’ viewing preferences, as assessed by a visual preference task, are modulated by several factors, species and dominance being the most influential

    Heightened immune response to autocitrullinated porphyromonas gingivalis peptidylarginine deiminase: a potential mechanism for breaching immunologic tolerance in rheumatoid arthritis

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    Background: Rheumatoid arthritis (RA) is characterised by autoimmunity to citrullinated proteins, and there is increasing epidemiologic evidence linking Porphyromonas gingivalis to RA. P gingivalis is apparently unique among periodontal pathogens in possessing a citrullinating enzyme, peptidylarginine deiminase (PPAD) with the potential to generate antigens driving the autoimmune response. Objectives: To examine the immune response to PPAD in patients with RA, individuals with periodontitis (PD) and controls (without arthritis), confirm PPAD autocitrullination and identify the modified arginine residues. Methods: PPAD and an inactivated mutant (C351A) were cloned and expressed and autocitrullination of both examined by immunoblotting and mass spectrometry. ELISAs using PPAD, C351A and another P gingivalis protein arginine gingipain (RgpB) were developed and antibody reactivities examined in patients with RA (n=80), individuals with PD (n=44) and controls (n=82). Results: Recombinant PPAD was a potent citrullinating enzyme. Antibodies to PPAD, but not to Rgp, were elevated in the RA sera (median 122 U/ml) compared with controls (median 70 U/ml; p&#60;0.05) and PD (median 60 U/ml; p&#60;0.01). Specificity of the anti-peptidyl citrullinated PPAD response was confirmed by the reaction of RA sera with multiple epitopes tested with synthetic citrullinated peptides spanning the PPAD molecule. The elevated antibody response to PPAD was abolished in RA sera if the C351A mutant was used on ELISA. Conclusions: The peptidyl citrulline-specific immune response to PPAD supports the hypothesis that, as a bacterial protein, it might break tolerance in RA, and could be a target for therapy

    PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment

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    <p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) are crucial for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. Given the importance of PPIs, several methods have been developed to detect them. Since the experimental methods are time-consuming and expensive, developing computational methods for effectively identifying PPIs is of great practical significance.</p> <p>Findings</p> <p>Most previous methods were developed for predicting PPIs in only one species, and do not account for probability estimations. In this work, a relatively comprehensive prediction system was developed, based on a support vector machine (SVM), for predicting PPIs in five organisms, specifically humans, yeast, <it>Drosophila</it>, <it>Escherichia coli</it>, and <it>Caenorhabditis elegans</it>. This PPI predictor includes the probability of its prediction in the output, so it can be used to assess the confidence of each SVM prediction by the probability assignment. Using a probability of 0.5 as the threshold for assigning class labels, the method had an average accuracy for detecting protein interactions of 90.67% for humans, 88.99% for yeast, 90.09% for <it>Drosophila</it>, 92.73% for <it>E. coli</it>, and 97.51% for <it>C. elegans</it>. Moreover, among the correctly predicted pairs, more than 80% were predicted with a high probability of ≥0.8, indicating that this tool could predict novel PPIs with high confidence.</p> <p>Conclusions</p> <p>Based on this work, a web-based system, Pred_PPI, was constructed for predicting PPIs from the five organisms. Users can predict novel PPIs and obtain a probability value about the prediction using this tool. Pred_PPI is freely available at <url>http://cic.scu.edu.cn/bioinformatics/predict_ppi/default.html</url>.</p

    Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

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    Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure