The intercellular adhesion molecule-1 K469E polymorphism in type 1 diabetes

Type 1 (insulin-dependent) diabetes is a complex trait. The region harboring the ICAM1 gene on 19p13 links to type 1 diabetes, and a growing body of evidence indicates that intercellular adhesion molecule-1 (ICAM-1) could play a role in type 1 diabetes development. Recently, association studies of an ICAM-1 K469E polymorphism in type 1 diabetes populations have reported conflicting results. Hence, we performed a transmission disequilibrium test analysis of the ICAM-1 K469E variations in 253 Danish type 1 diabetes families. Linkage and association was not found between the ICAM-1 K469E variation and type 1 diabetes in Danish patients (P(tdt)> or =0.48), and our data did not indicate an interaction between ICAM1 and IDDM1 in predisposition to type 1 diabetes in Danes (P=0.78). We did not observe significant association with late-onset type 1 diabetes (P(tdt)> or =0.12) or differences in transmission patterns between groups of affected offspring stratified for age at onset (P> or =0.19), as suggested in Japanese patients. Combined analysis of the present and previously reported transmission data comprising 728 affected offspring of Romanian, Finnish, and Danish ancestry suggested association between the ICAM-1 E469 allele and type 1 diabetes (P(tdt)=0.013), but association was not found in the combined Scandinavian material. In conclusion, we found no association of the ICAM-1 K469E polymorphism with type 1 diabetes or its subsets stratified for age at onset and HLA risk in Danish patients. Analysis of ICAM-1 K469E transmissions reported in three populations suggested association to type 1 diabetes, but also demonstrated heterogeneity between populations.     

应用16S rRNA基因V—2高变区序列进行链霉莲分子分类

用16S rRNA部分序列对Williams数值分类系统所包含的链霉菌属种或种群进行系统进货分析,以包含16S rRNA基因V－2高变区在内的120bp长核苷酸序列所作的系统进化树表明：这些链霉菌可分为34个簇,其中大簇5个（包括27－85株菌株）;中等大小簇3个（包括9－12株菌）;小簇8个（包括2－6株菌）;单成员簇19个。结果同时表明,Williams数值分析系统中根据形态、生理、生化特征进行归类而得到的种或种群内存在较大异质性。     

吸烟对呼吸道感染患者的微生态影响

呼吸道感染是常见病多发病,而呼吸道感染可导致微生态失调。有报道,宿主的任何病理变化都可作为生态失调的微观环境因素。微观环境对正常微生物群的影响是直接的;而且是主要的。为此,我们对吸烟和被动吸烟者的微生态变化及呼吸道感染患者微生态的变化以及二者之间的关系进行了研究。以进一步探讨吸烟对呼吸道感染患者直接或间接的影响。研究结果表明,吸烟及被动吸烟者患反复呼吸道感染的年发生率明显高于不吸烟者。健康对照组与患者口咽部菌群数相比有显著差异,无论是吸烟还是不吸烟的患者菌群含量均高于健康对照组（Ｐ＜００５）。结果表明,吸烟不仅有害于自身健康,而且危害被动吸烟者,其对呼吸道微生态的影响都是一致的,即可导致微生态失调,从而导致呼吸道疾病     

酪氨酸对大鼠离体Leydig细胞睾酮和cAMP生成的影响

本实验采用胶原酶消化,Ficoll 密度梯度离心,制备大鼠睾丸 Leydig 细胞悬浮液进行体外培养(每管内含有10~6 细胞),以研究酪氨酸对 Leydig 细胞睾酮和cAMP 生成的影响。实验结果表明,hCG(100mIU)能明显地促进Leydig 细胞睾酮和 cAMP的生成。睾酮从对照组的3.08±0.58ng(X±SD,下同)增加到41.61±1.52ng,cAMP 含量从19.62±2.56pmol增加到153.24±5.92pmol。若将酪氨酸(60μg)与hCG同时加入到细胞培养液中,则睾酮和cAMP 含量分别下降到 19.22±.0.52ng(P<0.01)和92.63±6.02pmol(P<0.05)。但是,酪氨酸羟化酶抑制剂(α-甲基酪氨酸)对酪氨酸抗hCG致睾酮生成作用无阻断效应,而酪氨酸对外源cAMP(2.5mM)诱导的睾酮生成,则有明显的抑制作用,睾酮含量从27.56±1.53ng降至 19.50±0.47ng(P<0.01)。以上实验结果表明,酪氨酸抗hCG致睾酮生成的作用机理与cAMP有关。     

Dinocrocuta gigantea头骨的发现

本文记述了甘肃和政县晚中新世地层中发现的一个完整的巨鬣狗头骨;讨论了它的分类地位,修正了 Schlosser 1903年建种时的一些鉴定错误.巨鬣狗是鬣狗科中一个十分特化的成员,应代表一个独立的属.根据命名规则,我们采用 N. schmidt-Kittler 1976年所创的 Dinocrocuta. 因此,这个种应订正为 Dinocrocuta gigantea (schlosser, 1903).     

微生物脂肪酶的研究进展

详细综述了脂态酶微生物产生菌的选育、诱变育种及发酵生产技术,对微生物脂肪酶的性质、分离、纯化、固定化技术及应用进行了简要概述     

Meta-analysis of Correlated Traits via Summary Statistics from GWASs with an Application in Hypertension

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple—even distinct—traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10⁻⁸) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10⁻⁷) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.