Ageing is often accompanied with a decline in immune system function,resulting in immune ageing.Numerous studies have focussed on the changes in different lymphocyte subsets in diseases and immunosenescence.The change...Ageing is often accompanied with a decline in immune system function,resulting in immune ageing.Numerous studies have focussed on the changes in different lymphocyte subsets in diseases and immunosenescence.The change in immune phenotype is a key indication of the diseased or healthy status.However,the changes in lymphocyte number and phenotype brought about by ageing have not been comprehensively analysed.Here,we analysed T and natural killer(NK)cell subsets,the phenotype and cell differentiation states in 43,096 healthy individuals,aged 20–88 years,without known diseases.Thirty-six immune parameters were analysed and the reference ranges of these subsets were established in different age groups divided into 5-year intervals.The data were subjected to random forest machine learning for immune-ageing modelling and confirmed using the neural network analysis.Our initial analysis and machine modelling prediction showed that na.ve T cells decreased with ageing,whereas central memory T cells(Tcm)and effector memory T cells(Tem)increased cluster of differentiation(CD)28-associated T cells.This is the largest study to investigate the correlation between age and immune cell function in a Chinese population,and provides insightful differences,suggesting that healthy adults might be considerably influenced by age and sex.The age of a person's immune system might be different from their chronological age.Our immune-ageing modelling study is one of the largest studies to provide insights into‘immune-age’rather than‘biological-age’.Through machine learning,we identified immune factors influencing the most through ageing and built a model for immune-ageing prediction.Our research not only reveals the impact of age on immune parameter differences within the Chinese population,but also provides new insights for monitoring and preventing some diseases in clinical practice.展开更多
As coronavirus disease 2019(COVID-19) threatens human health globally,infectious disorders have become one of the most challenging problem for the medical community.Natural products(NP) have been a prolific source of ...As coronavirus disease 2019(COVID-19) threatens human health globally,infectious disorders have become one of the most challenging problem for the medical community.Natural products(NP) have been a prolific source of antimicrobial agents with widely divergent structures and a range of vast biological activities.A dataset comprising 618 articles,including 646 NP-based compounds from 672 species of natural sources with biological activities against 21 infectious pathogens from five categories,was assembled through manual selection of published articles.These data were used to identify 268 NP-based compounds classified into ten groups,which were used for network pharmacology analysis to capture the most promising lead-compounds such as agelasine D,dicumarol,dihydroartemisinin and pyridomycin.The distribution of maximum Tanimoto scores indicated that compounds which inhibited parasites exhibited low diversity,whereas the chemistries inhibiting bacteria,fungi,and viruses showed more structural diversity.A total of 331 species of medicinal plants with compounds exhibiting antimicrobial activities were selected to classify the family sources.The family Asteraceae possesses various compounds against C.neoformans,the family Anacardiaceae has compounds against Salmonella typhi,the family Cucurbitacea against the human immunodeficiency virus(HIV),and the family Ancistrocladaceae against Plasmodium.This review summarizes currently available data on NPbased antimicrobials against refractory infections to provide information for further discovery of drugs and synthetic strategies for anti-infectious agents.展开更多
基金supported by National Key Research and Development Program of China(2020YFA0803502 to Z.Y.)National Natural Science Foundation of China(32030036 and 31830021 to Z.Y.)+6 种基金the 111 Project(B16021 to Z.Y.)Natural Science Foundation of China(81971301 and 32050410285 to O.J.L.)Guangzhou Planned Project of Science and Technology(202002020039 to O.J.L.)Guangdong Basic and Applied Basic Research Foundation(2021A1515110734 to Z.R.)Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology,The First Affiliated Hospital,Sun Yat-sen University,Guangzhou,China(2013A061401007,2017B030314018,2020B1212060026)Guangdong Provincial International Cooperation Base of Science and Technology(Organ Transplantation)The First Affiliated Hospital,Sun Yat-sen University,Guangzhou,China(2015B050501002,2020A0505020003).
文摘Ageing is often accompanied with a decline in immune system function,resulting in immune ageing.Numerous studies have focussed on the changes in different lymphocyte subsets in diseases and immunosenescence.The change in immune phenotype is a key indication of the diseased or healthy status.However,the changes in lymphocyte number and phenotype brought about by ageing have not been comprehensively analysed.Here,we analysed T and natural killer(NK)cell subsets,the phenotype and cell differentiation states in 43,096 healthy individuals,aged 20–88 years,without known diseases.Thirty-six immune parameters were analysed and the reference ranges of these subsets were established in different age groups divided into 5-year intervals.The data were subjected to random forest machine learning for immune-ageing modelling and confirmed using the neural network analysis.Our initial analysis and machine modelling prediction showed that na.ve T cells decreased with ageing,whereas central memory T cells(Tcm)and effector memory T cells(Tem)increased cluster of differentiation(CD)28-associated T cells.This is the largest study to investigate the correlation between age and immune cell function in a Chinese population,and provides insightful differences,suggesting that healthy adults might be considerably influenced by age and sex.The age of a person's immune system might be different from their chronological age.Our immune-ageing modelling study is one of the largest studies to provide insights into‘immune-age’rather than‘biological-age’.Through machine learning,we identified immune factors influencing the most through ageing and built a model for immune-ageing prediction.Our research not only reveals the impact of age on immune parameter differences within the Chinese population,but also provides new insights for monitoring and preventing some diseases in clinical practice.
基金supported by the Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences (CI2021A04013)the Fundamental Research Funds for the Central Public Welfare Research Institutes (L2021029)。
文摘As coronavirus disease 2019(COVID-19) threatens human health globally,infectious disorders have become one of the most challenging problem for the medical community.Natural products(NP) have been a prolific source of antimicrobial agents with widely divergent structures and a range of vast biological activities.A dataset comprising 618 articles,including 646 NP-based compounds from 672 species of natural sources with biological activities against 21 infectious pathogens from five categories,was assembled through manual selection of published articles.These data were used to identify 268 NP-based compounds classified into ten groups,which were used for network pharmacology analysis to capture the most promising lead-compounds such as agelasine D,dicumarol,dihydroartemisinin and pyridomycin.The distribution of maximum Tanimoto scores indicated that compounds which inhibited parasites exhibited low diversity,whereas the chemistries inhibiting bacteria,fungi,and viruses showed more structural diversity.A total of 331 species of medicinal plants with compounds exhibiting antimicrobial activities were selected to classify the family sources.The family Asteraceae possesses various compounds against C.neoformans,the family Anacardiaceae has compounds against Salmonella typhi,the family Cucurbitacea against the human immunodeficiency virus(HIV),and the family Ancistrocladaceae against Plasmodium.This review summarizes currently available data on NPbased antimicrobials against refractory infections to provide information for further discovery of drugs and synthetic strategies for anti-infectious agents.
