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Duo Li
Researcher at Qingdao University
Publications - 359
Citations - 11451
Duo Li is an academic researcher from Qingdao University. The author has contributed to research in topics: Polyunsaturated fatty acid & Docosahexaenoic acid. The author has an hindex of 48, co-authored 329 publications receiving 9060 citations. Previous affiliations of Duo Li include Hangzhou University & Ruhr University Bochum.
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Journal ArticleDOI
Effects of dietary fat on gut microbiota and faecal metabolites, and their relationship with cardiometabolic risk factors: a 6-month randomised controlled-feeding trial
Yi Wan,Fenglei Wang,Jihong Yuan,Jie Li,Dandan Jiang,Jingjing Zhang,Hao Li,Ruoyi Wang,Jun Tang,Tao Huang,Ju-Sheng Zheng,Andrew J. Sinclair,Jim Mann,Duo Li +13 more
TL;DR: Higher-fat consumption by healthy young adults whose diet is in a state of nutrition transition appeared to be associated with unfavourable changes in gut microbiota, faecal metabolomic profiles and plasma proinflammatory factors, which might confer adverse consequences for long-term health outcomes.
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Cardiovascular disease mortality and cancer incidence in vegetarians: a meta-analysis and systematic review.
TL;DR: It is suggested that vegetarians have a significantly lower ischemic heart disease mortality and overall cancer incidence than nonvegetarians.
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Intake of fish and marine n-3 polyunsaturated fatty acids and risk of breast cancer: meta-analysis of data from 21 independent prospective cohort studies
TL;DR: Higher consumption of dietary marine n-3 PUFA is associated with a lower risk of breast cancer and the associations of fish and alpha linolenic acid intake with risk warrant further investigation of prospective cohort studies.
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Fish consumption and CHD mortality: an updated meta-analysis of seventeen cohort studies
TL;DR: It is indicated that either low (1 serving/week) or moderate fish consumption (2–4 servings/ week) has a significantly beneficial effect on the prevention of CHD mortality and high fish consumption possesses only a marginally protective effect onCHD mortality.
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Comparison of random forest, support vector machine and back propagation neural network for electronic tongue data classification: Application to the recognition of orange beverage and Chinese vinegar
TL;DR: Results suggest that RF may be a promising pattern recognition method for E-tongue data processing, because it can deal with classification problems of unbalanced, multiclass and small sample data without data preprocessing procedures.