| 1 | 斯堪的纳维亚半岛地方性和区域性大气颗粒污染对健康影响的比较评价显示文摘正在实施的'欧洲清洁空气计划'(CAFE)是欧盟委员会(TheEU Commission)的一个倡议,其目的是开展一项旨在改善欧盟空气质量的协调一致的行动。该项目关注的焦点是已经证明对人类健康有着巨大影响的颗粒物质。CAFE要求世界卫生组织(WHO)作了一份关于大气污染物和人类健康关系的最新研究进展的综述,以便在此基础上进行不同大气污染物及其对人类健康影响的评估。WHO所作的关于欧洲空气污染物对健康影响方面的综述证实,即使是较低颗粒物水平,也会对人类健康构成明显的威胁。在瑞典人口中,使用推荐的统一风险系数对颗粒物质影响的评估表明,不考虑污染源,与远程传输的人为造成的颗粒物有关的过早死亡人数,估计大概每年有3500人;相应地预期寿命减少大约7个月。当考虑地方性污染源,把现有的风险系数和暴露数据联系起来时,由于存在大量不确定因素,对地方性污染源影响的估计显得更加困难,但是估计值表明,每年大约有1800人过早死亡,他们的平均寿命大约减少了2~3个月。然而,暴露在局部污染严重、高污染物浓度下的一部分人口, 其预期寿命可能遭受更大幅度的减少。越来越多的文献资料支持燃烧形成的颗粒物具有更高相对风险的假设,因而,进一步的研究可能会转移污染控制战略的重点。CAFE项目建立了一个全面高效的降低大气颗粒物策略。根据对背景暴露值的研究,我们的结果表明,在瑞典,远程传输富含硫酸盐的颗粒是造成颗粒物质健康影响的主导因素。在整个斯堪的纳维亚半岛和很多受到越界空气污染影响的国家都会发现相同的研究结果。然而,一些包括采用高空间分辨率方法的流行病学等健康研究都表明,机动车尾气颗粒比其它颗粒物对健康更具危害性。这些互相矛盾的研究成果必须被理解,同时,应由专家给出特定污染源对人类健康影响的估算,否则不可能在欧洲找到全面高效降低大气污染性物质最有效的解决方案。我们不应满足于目前的研究结果,即认为每一种降低颗粒物浓度的措施对单位物质浓度的变化具有相同的作用。显然,我们非常需要引进更有针对性的暴露变量、更高地理分辨率的流行病学方法和健康影响效应评估。 | Bertil Forsberg Hans-Christen Hansson Christer Johansson Hans Areskoug Karin Persson Bengt Jrvholm 王丽荣 | 2005 | AMBIO-人类环境杂志2005，34，1： | 2 |
| 2 | 药物不良反应的药物经济学显示文摘药物不良反应(ADRs)是引起住院的常见原因,往往造成极大的社会成本。然而,由于大多数ADRs从未引起过临床的重视,所以住院治疗的成本仅仅是由ADRs所造成的社会总成本中的一部分。与ADRs相关的成本主要有两项:为治疗由ADRs引起的疾病而产生的成本以及为避免发生ADRs而产生的成本。本文主要从经济学的角度来讨论ADRs的社会成本。通过文献回顾并对其中有关ADRs发生和其成本的研究文献进行总结后,得出如下3种评价ADRs成本的不同方法:第一种方法是成本研究,必须通过以下三步来估算ADRs的成本:(1)定义ADRs;(2)判断是否为ADRs;(3)测算ADRs的成本。大多数有关成本的研究主要集中在由ADRs所引起的住院治疗上,并且文献显示所有住院治疗中约有3%~7%是由ADRs引起的。第二种方法是关于安全性的成本和效益。对处方、使用、调剂或者生产某药物,在决策涉及到成本和效益时,决策者必须对如下两方面成本进行权衡:(1)为治疗由ADRs引起的疾病而产生的成本;(2)为避免发生ADRs而产生的成本。第三种方法是讨论使药物治疗的成本和效益之间达到最佳平衡所需的法规和机制。从经济学的角度讲,ADRs的问题不是最小化而是最优化问题,是在成本和效益之间找到恰当的平衡关系。 | Jonas Lundkvist Bengt Jnsson 张力 | 2008 | 中国药物经济学2008，3，2： | 2 |
| 4 | Comparison of bacterial quantities in left and right colon biopsies and faeces显示文摘AIM:To compare quantities of predominant and pathogenic bacteria in mucosal and faecal samples.METHODS:Twenty patients undergoing diagnostic colonoscopy with endoscopically and histologically normal mucosa were recruited to the study,14 subjects of which also supplied faecal(F) samples between 15 d to 105 d post colonoscopy.Mucosal biopsies were taken from each subject from the midportion of the ascending colon(right side samples,RM) and the sigmoid(left side samples,LM).Predominant intestinal and mucosal bacteria including clostridial 16S rRNA gene clusters Ⅳ and ⅩⅣab,Bacteroidetes,Enterobacteriaceae,Bifidobacterium spp.,Akkermansia muciniphila(A.muciniphila),Veillonella spp.,Collinsella spp.,Faecalibacterium prausnitzii(F.prausnitzii) and putative pathogens such asEscherichia coli(E.coli),Clostridium difficile(C.difficile),Helicobacter pylori(H.pylori) and Staphylococcus aureus(S.aureus) were analysed by quantitative polymerase chain reaction(qPCR).Host DNA was quantified from the mucosal samples with human glyceraldehyde 3-phosphate dehydrogenase gene targeting qPCR.Paired t tests and the Pearson correlation were applied for statistical analysis.RESULTS:The most prominent bacterial groups were clostridial groups Ⅳ and ⅩⅣa+b andBacteroidetes and bacterial species F.prausnitzii in both sample types.H.pylori and S.aureus were not detected and C.difficile was detected in only one mucosal sample and three faecal samples.E.coli was detected in less than half of the mucosal samples at both sites,but was present in all faecal samples.All detected bacteria,except Enterobacteriaceae,were present at higher levels in the faeces than in the mucosa,but the different locations in the colon presented comparable quantities(RM,LM and F followed byP 1 for RMvs F,P 2 for LMvs F andP 3 for RM vs LM:4.17 ± 0.60 log 10 /g,4.16 ± 0.56 log 10 /g,5.88 ± 1.92 log 10 /g,P 1 = 0.011,P 2 = 0.0069,P 3 = 0.9778 forA.muciniphila;6.25 ± 1.3 log 10 /g,6.09 ± 0.81 log 10 /g,8.84 ± 1.38 log 10 /g,P 1 < 0.0001,P 2 = 0.0002,P 3 = 0.6893 forBacteroidetes;5.27 ± 1.68 log 10 /g,5.38 ± 2.06 log 10 /g,8.20 ± 1.14 log 10 /g,P 1 < 0.0001,P 2 ≤ 0.0001,P 3 = 0.7535 forBifidobacterium spp.;6.44 ± 1.15 log 10 /g,6.07 ±1.45 log 10 /g,9.74 ±1.13 log 10 /g,P 1 < 0.0001,P 2 ≤ 0.0001,P 3 = 0.637 forClostridium cluster Ⅳ;6.65 ± 1.23 log 10 /g,6.57 ± 1.52 log 10 /g,9.13 ± 0.96 log 10 /g,P 1 < 0.0001,P 2 ≤ 0.0001,P 3 = 0.9317 forClostridium cluster ⅩⅣa;4.57 ± 1.44 log10/g,4.63 ± 1.34 log10/g,7.05 ± 2.48 log 10 /g,P 1 = 0.012,P 2 = 0.0357,P 3 = 0.7973 for Collinsella spp.;7.66 ± 1.50 log 10 /g,7.60 ± 1.05 log 10 /g,10.02 ± 2.02 log 10 /g,P 1 ≤ 0.0001,P 2 = 0.0013,P 3 = 0.9919 forF.prausnitzsii;6.17 ± 1.3 log 10 /g,5.85 ± 0.93 log 10 /g,7.25 ± 1.01 log 10 /g,P 1 = 0.0243,P 2 = 0.0319,P 3 = 0.6982 for Veillonella spp.;4.68 ± 1.21 log 10 /g,4.71 ± 0.83 log 10 /g,5.70 ± 2.00 log 10 /g,P 1 = 0.1927,P 2 = 0.0605,P 3 = 0.6476 forEnterobacteriaceae).TheBifidobacterium spp.counts correlated significantly between mucosal sites and mucosal and faecal samples(Pearson correlation coefficients 0.62,P = 0.040 and 0.81,P = 0.005 between the right mucosal sample and faeces and the left mucosal sample and faeces,respectively).CONCLUSION:Non-invasive faecal samples do not reflect bacterial counts on the mucosa at the individual level,except for bifidobacteria often analysed in probiotic intervention studies. | Anna Lyra Sofia Forssten Peter Rolny Yvonne Wettergren Sampo J Lahtinen Krista Salli Lennart Cedgrd Elisabeth Odin Bengt Gustavsson Arthur C Ouwehand | 2012 | World Journal of Gastroenterology2012，18，32： | 2 |
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