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Low back pain and osteoarthritis pain:a perspective of estrogen 被引量:1
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作者 Huiwen Pang shihui chen +4 位作者 David M.Klyne David Harrich Wenyuan Ding Sidong Yang Felicity Y.Han 《Bone Research》 SCIE CAS CSCD 2023年第3期443-456,共14页
Low back pain(LBP)is the world's leading cause of disability and is increasing in prevalence more rapidly than any other pain condition.Intervertebral disc(IVD)degeneration and facet joint osteoarthritis(FJOA)are ... Low back pain(LBP)is the world's leading cause of disability and is increasing in prevalence more rapidly than any other pain condition.Intervertebral disc(IVD)degeneration and facet joint osteoarthritis(FJOA)are two common causes of LBP,and both occur more frequently in elderly women than in other populations.Moreover,osteoarthritis(OA)and OA pain,regardless of the joint,are experienced by up to twice as many women as men,and this difference is amplified during menopause.Changes in estrogen may be an important contributor to these pain states.Receptors for estrogen have been found within IVD tissue and nearby joints,highlighting the potential roles of estrogen within and surrounding the IVDs and joints.In addition,estrogen supplementation has been shown to be effective at ameliorating IVD degeneration and OA progression,indicating its potential use as a therapeutic agent for people with LBP and OA pain.This review comprehensively examines the relationship between estrogen and these pain conditions by summarizing recent preclinical and clinical findings.The potential molecular mechanisms by which estrogen may relieve LBP associated with IVD degeneration and FJOA and OA pain are discussed. 展开更多
关键词 AGENT DEGENERATION PAIN
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Community Detection in Blockchain Social Networks
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作者 Sissi Xiaoxiao Wu Zixian Wu +2 位作者 shihui chen Gangqiang Li Shengli Zhang 《Journal of Communications and Information Networks》 CSCD 2021年第1期59-71,共13页
In this work,we consider community detection in blockchain networks.We specifically take the Bitcoin network and Ethereum network as two examples,where community detection serves in different ways.For the Bitcoin netw... In this work,we consider community detection in blockchain networks.We specifically take the Bitcoin network and Ethereum network as two examples,where community detection serves in different ways.For the Bitcoin network,we modify the traditional community detection method and apply it to the transaction social network to cluster users with similar characteristics.For the Ethereum network,on the other hand,we define a bipartite social graph based on the smart contract transactions.A novel community detection algorithm which is designed for low-rank signals on graph can help find users’communities based on user-token subscription.Based on these results,two strategies are devised to deliver on-chain advertisements to those users in the same community.We implement the proposed algorithms on real data.By adopting the modified clustering algorithm,the community results in the Bitcoin network are basically consistent with the ground-truth of the betting site community which has been announced to the public.Meanwhile,we run the proposed strategy on real Ethereum data,visualize the results and implement an advertisement delivery on the Ropsten test net. 展开更多
关键词 blockchain Bitcoin Ethereum community detection RECOMMENDATION
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