A Comparison of Feature-Combination for Example-Based Super Resolution

[[abstract]]Super resolution (SR) in computer vision is an important task. In this paper, we compared several common used features in image super resolution of example-based algorithms. To combine features, we develop a cascade framework to both solve the problem of deciding weights among features and to improve computation efficiency. Finally, we modify the framework to have an adaptive threshold such that not only the computation load is much reduced but the modified framework is suitable to any query image as well as various image databases.[[sponsorship]]the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)[[conferencetype]]國際[[conferencedate]]2014, 5/13 - 5/16[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tainan, Taiwa

Development of Risk Prediction Equations for Incident Chronic Kidney Disease

IMPORTANCE ‐ Early identification of individuals at elevated risk of developing chronic kidney disease  could improve clinical care through enhanced surveillance and better management of underlying health  conditions.  OBJECTIVE – To develop assessment tools to identify individuals at increased risk of chronic kidney  disease, defined by reduced estimated glomerular filtration rate (eGFR).  DESIGN, SETTING, AND PARTICIPANTS – Individual level data analysis of 34 multinational cohorts from  the CKD Prognosis Consortium including 5,222,711 individuals from 28 countries. Data were collected  from April, 1970 through January, 2017. A two‐stage analysis was performed, with each study first  analyzed individually and summarized overall using a weighted average. Since clinical variables were  often differentially available by diabetes status, models were developed separately within participants  with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external  cohorts (N=2,253,540). EXPOSURE Demographic and clinical factors.  MAIN OUTCOMES AND MEASURES – Incident eGFR <60 ml/min/1.73 m2.  RESULTS – In 4,441,084 participants without diabetes (mean age, 54 years, 38% female), there were  660,856 incident cases of reduced eGFR during a mean follow‐up of 4.2 years. In 781,627 participants  with diabetes (mean age, 62 years, 13% female), there were 313,646 incident cases during a mean follow‐up of 3.9 years. Equations for the 5‐year risk of reduced eGFR included age, sex, ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, BMI, and albuminuria. For participants  with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction  between the two. The risk equations had a median C statistic for the 5‐year predicted probability of  0.845 (25th – 75th percentile, 0.789‐0.890) in the cohorts without diabetes and 0.801 (25th – 75th percentile, 0.750‐0.819) in the cohorts with diabetes. Calibration analysis showed that 9 out of 13 (69%) study populations had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was  similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 out of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. CONCLUSIONS AND RELEVANCE – Equations for predicting risk of incident chronic kidney disease developed in over 5 million people from 34 multinational cohorts demonstrated high discrimination and  variable calibration in diverse populations

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Perivascular adipose tissue inhibits endothelial function of rat aortas via caveolin-1.

Perivascular adipose tissue (PVAT)-derived factors have been proposed to play an important role in the pathogenesis of atherosclerosis. Caveolin-1 (Cav-1), occupying the calcium/calmodulin binding site of endothelial NO synthase (eNOS) and then inhibiting nitric oxide (NO) production, is also involved in the development of atherosclerosis. Thus, we investigated whether PVAT regulated vascular tone via Cav-1 and/or endothelial NO pathways. Isometric tension studies were carried out in isolated thoracic aortas from Wistar rats in the presence and absence of PVAT. Concentration-response curves of phenylephrine, acetylcholine, and sodium nitroprusside were illustrated to examine the vascular reactivity and endothelial function. The protein expressions of eNOS and Cav-1 were also examined in aortic homogenates. Our results demonstrated that PVAT significantly enhanced vasoconstriction and inhibited vasodilatation via endothelium-dependent mechanism. The aortic NO production was diminished after PVAT treatment, whereas protein expression and activity of eNOS were not significantly affected. In addition, Cav-1 protein expression was significantly increased in aortas with PVAT transfer. Furthermore, a caveolae depleter methyl-β-cyclodextrin abolished the effect of PVAT on the enhancement of vasoconstriction, and reversed the impairment of aortic NO production. In conclusion, unknown factor(s) released from PVAT may inhibit endothelial NO production and induce vasocontraction via an increase of Cav-1 protein expression