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| 1 | 抗凝剂治疗非抗磷脂综合征妇女复发性流产(英文)显示文摘目的评价采用抗凝剂(如阿司匹林和肝素)治疗有两次自然流产史或一次近期不明原因(非遗传性血栓形成倾向)宫内胎死妇女的有效性和安全性.方法我们检索了Cochrane妊娠和分娩组临床试验注册库(2004年3月),Cochrane临床对照试验中心注册库(Cochrane图书馆2004年第1期), MEDLINE(1966.1~2004.3)及EMBASE(1980~2004.3). 我们查阅了所有检索到研究的参考文献以避免漏检.纳入对有两次自然流产史或一次近期不明原因(非遗传性血栓形成倾向)宫内胎死妇女,评估抗凝制剂治疗提高活产率效果的随机或半随机临床对照试验.干预措施包括用于预防流产的阿司匹林、未分馏肝素及低分子肝素,与安慰剂比较或互相比较.由两名作者进行文献质量评价和数据提取,数据录入RevMan并交叉核对.结果共纳入两个试验(242例患者)并均对符合评价纳入标准的妇女亚组进行了数据提取.1个试验中,54例抗心肌磷脂抗体阴性的复发性自然流产妊娠妇女随机分入低剂量阿司匹林治疗组和安慰剂组,两组活产率相似[RR=1.00, 95%CI (0.78,1.29)].另一个试验中,一个之前曾有孕20周后流产史的血栓缺陷妇女亚组共20例,随机分入依诺肝素组和阿司匹林组.与低剂量阿司匹林治疗比较,依诺肝素治疗能提高活产率[RR=10.00, 95%CI (1.56,64.20)].结论现有关于使用阿司匹林和肝素治疗该类妇女流产的有效性和安全性证据不足,现有条件下不推荐使用抗凝剂治疗.急需进行大样本安慰剂对照的随机试验. | arcello Di Nisio Louisette W.Peters Saskia Middeldorp 姚巡 | 2005 | 中国循证医学杂志2005，5，9： | 2 |
| 2 | 酮替芬、赛庚啶逆转疟原虫对氯喹抗药性的研究显示文摘用高度抗氯喹约氏疟原虫 Ac—1虫株感染小鼠观察了酮替芬及赛庚啶对氯喹抗药性的逆转作用,1/4治疗剂量的酮替芬及赛庚啶己可使抗氯喹特性被逆转,使抗性虫感染小鼠被敏感株治疗剂量所治愈。提高剂量杀虫作用加强。异博定相应的效果较差且毒性较高。预先或同时加服蛋白质合成抑制剂氯霉素或利福平则未观察到对氯喹抗药性有逆转作用。作者对临床上用氯喹常规剂量合并酮替芬或赛庚啶治疗对氯喹抗药性病人的问题进行了讨论,提出进一步合并加服周效磺胺或具作用类似物可能取得更好的数果。氯代丙咪嗪等则被建议用于研究。 | 潘星清 W.Peters D.Warhurst A.Fairlamb | 1990 | 中国寄生虫病防治杂志1990，3，3： | 2 |
| 3 | 应用集落刺激因子治疗大剂量烷化剂联合化疗及自体骨髓…显示文摘<正> 研究表明对于大剂量化疗及自体骨髓移植(ABMT)治疗后病人应用造血生长因子能加速造血功能的恢复,缩短移植后中性粒细胞减少期,从而降低移植后患病率。作者以骨髓和外周血前体细胞的生长及外周血细胞计数作为乳癌和黑素瘤病人在化疗及 ABMT 后骨髓造血恢复的指标。 | M.J.Laughlin G.Kirkpatrick N.Sabiston W.Peters J.Kurtzberg 向直富 唐锦治 | 1996 | 德国医学1996，13，2： | 0 |
| 4 | 网络新闻界,过劳现象年轻化显示文摘在大多数新闻编辑部,这个玩笑本来平淡无奇。去年愚人节这天,《政客》报的两位总编给全体员工发了一封电子邮件,通知所有记者改从早5点开始上班。 | Jeremy W.Peters 冯雪 | 2010 | 英语文摘2010，，10： | 0 |
| 5 | On-chain analytics for sentiment-driven statistical causality in cryptocurrencies显示文摘This paper establishes a new framework for assessing multimodal statistical causality between cryptocurrency market(cryptomarket)sentiment and cryptocurrency price processes.In order to achieve this,we present an efficient algorithm for multimodal statistical causality analysis based on Multiple-Output Gaussian Processes.Signals from different information sources(modalities)are jointly modelled as a Multiple-Output Gaussian Process,and then using a novel approach to statistical causality based on Gaussian Processes(GPs),we study linear and non-linear causal effects between the different modalities.We demonstrate the effectiveness of our approach in a machine learning application by studying the relationship between cryptocurrency spot price dynamics and sentiment time-series data specific to the crypto sector,which we conjecture influences retail investor behaviour.The investor sentiment is extracted from cryptomarket news data via methods developed in the area of statistical machine learning known as Natural Language Processing(NLP).To capture sentiment,we present a novel framework for text to time-series embedding,which we then use to construct a sentiment index from publicly available news articles.We conduct a statistical analysis of our sentiment statistical index model and compare it to alternative state-of-the-art sentiment models popular in the NLP literature.In regard to the multimodal causality,the investor sentiment is our primary modality of exploration,in addition to price and a blockchain technologyrelated indicator(hash rate).Analysis shows that our approach is effective in modelling causal structures of variable degree of complexity between heterogeneous data sources and illustrates the impact that certain modelling choices for the different modalities can have on detecting causality.A solid understanding of these factors is necessary to gauge cryptocurrency adoption by retail investors and provide sentiment-and technologybased insights about the cryptocurrency market dynamics. | Ioannis Chalkiadakis Anna Zaremba Gareth W.Peters Michael J.Chantler | 2022 | Blockchain(Research and Applications)2022，3，2： | 0 |
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