沙尘天气大气颗粒物对学龄儿童最大呼气流速的影响

目的 研究沙尘天气颗粒物浓度与学龄儿童最大呼气流速(PEFR)之间的关系.探讨沙尘天气颗粒物对儿童肺功能的影响.方法 于2006年4月27日-6月5日连续40d对内蒙古包头市1所小学107名四年级小学生进行每日3次PEFR的测定,同时监测和收集每日大气PM2.5、PM1O、NO2和SO2浓度以及气温和相对湿度,通过问卷调查了解儿童年龄、性别、身高、体重、哮喘病史、慢性呼吸系统疾病家族史、被动吸烟等情况.应用线性混合效应模型,在控制了个体特征、气象因素的情况下估计PM2.5和PM10对儿童PEFR的影响.结果 单污染物模型和多污染物模型均显示,PM2.5和PM10的日均浓度与沙尘天气当日及之后3 d内儿童的PEFR日均值都存在明显的负相关(P<0.01),其中以滞后1 d的效应最强.在多污染物模型中调整了NO2和SO2的影响之后,PM2.5和PM10的日均浓度每增加10μg/m3,儿童PEFR在沙尘天气1 d之后的日均值就分别降低0.245和0.121 L/min,有统计学意义(P<0.01).结论 学龄儿童PEFR日均值下降与包头市沙尘天气颗粒物浓度的升高有关.     

Brain structure and allelic associations in Alzheimer's disease

Background

Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic.

Aims

This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations.

Materials and Methods

The participants, ages 65–85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues.

Results

We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models.

Discussion

In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC.

Conclusion

This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.