清胰汤对急性坏死性胰腺炎大鼠基因表达谱的影响

目的 探讨清胰汤(QYD)对牛磺胆酸钠诱导的急性坏死性胰腺炎(ANP)大鼠胰腺基因表达谱的影响.方法 60只SD大鼠按随机数字法分为假手术组(SO组)、ANP组和QYD组,每组20只.4％牛磺胆酸钠胰胆管逆行注射复制ANP模型,SO组注射生理盐水,QYD组3次灌胃治疗(0.75 ml/100 g).观测大鼠存活率、血清淀粉酶和C-反应蛋白(CRP)变化;HE染色观察胰腺、肺组织病理改变;Illumina大鼠全基因组表达谱基因芯片分析胰腺表达谱变化;荧光定量RT-PCR验证部分基因(热休克蛋白A8和热休克蛋白b1).结果 QYD组存活率较ANP组高(80％比65％,P=0.031),而血清淀粉酶、CRP明显下降[(5789±798)比(7256± 1221) U/L,P=0.001;(78.6±18.5)比(126.4±24.3) mg/L,P=0.012],Schmidt胰腺病理评分好转.与ANP组比较,QYD组筛选出575个差异基因,其中上调92个,下调483个.基因本体论(GO)功能分析涉及到转录调节因子活性负调节、氧化还原酶类活性、酶抑制剂活性等.KEGG生物学通路主要涉及丝裂原活化蛋白激酶(MAPK)信号通路、NOD受体样信号通路、细胞周期、代谢通路、氧化还原酶类活性等.定量RT-PCR(热休克蛋白A8和热休克蛋白b1 mRNA)验证了基因芯片结果.结论 QYD可有效治疗实验性ANP,其机制涉及到MAPK信号通路、NOD受体样信号通路、细胞周期、代谢通路、氧化还原酶类活性等.     

Identification of a Prognostic Signature Based on the Expression of Genes Related to the Insulin Pathway in Early Breast Cancer

IntroductionInsulin and the insulin-like growth factor (IGF) family play a key role in breast cancer (BC).ObjectiveIn this study, we evaluated on a genomic scale the potential prognostic value of insulin signaling in early BC.MethodsCandidate genes were selected from the published literature and gene expression profiling experiments. Three publicly available BC datasets, containing gene expression data on 502 cases, were used to test the prognostic ability of the score. The gene signature was developed on {"type":"entrez-geo","attrs":{"text":"GSE1456","term_id":"1456"}}GSE1456, containing microarray data from 159 patients, split into a training set (102 breast tumors) and a validation set (n = 57). {"type":"entrez-geo","attrs":{"text":"GSE3494","term_id":"3494"}}GSE3494 and {"type":"entrez-geo","attrs":{"text":"GSE2990","term_id":"2990"}}GSE2990 (350 patients) were used for external validation. Univariate Mann-Whitney test was used to identify genes differentially expressed between relapsed and nonrelapsed patients. Expression of genes significantly correlated with relapse was combined in a linear score. Patients were classified as low or high risk with respect to the median value.ResultsOn the training set, 15 genes turned out to be differentially expressed: 8-year disease-free survival (DFS) was 51 and 91% in the high- and low-risk group (p < 0.001), respectively. In the validation set, DFS was 97 and 54% (p = 0.009), respectively. External validation: 8-year DFS was 72 and 61%, respectively, in {"type":"entrez-geo","attrs":{"text":"GSE3494","term_id":"3494"}}GSE3494 (p = 0.03) and 74 and 55% in {"type":"entrez-geo","attrs":{"text":"GSE2990","term_id":"2990"}}GSE2990 (p = 0.03). By multivariate analyses, the insulin signature was significantly associated with DFS, independently of age, hormone receptor status, nodal status, and grade.ConclusionsOur findings indicate that the insulin pathway is involved in BC prognosis at a genomic level and provide a window of selectivity for preventive and treatment strategies targeting the insulin/IGF pathway in BC patients.     

Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships

The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships.     

Selecting significant genes by randomization test for cancer classification using gene expression data

Gene selection is an important task in bioinformatics studies, because the accuracy of cancer classification generally depends upon the genes that have biological relevance to the classifying problems. In this work, randomization test (RT) is used as a gene selection method for dealing with gene expression data. In the method, a statistic derived from the statistics of the regression coefficients in a series of partial least squares discriminant analysis (PLSDA) models is used to evaluate the significance of the genes. Informative genes are selected for classifying the four gene expression datasets of prostate cancer, lung cancer, leukemia and non-small cell lung cancer (NSCLC) and the rationality of the results is validated by multiple linear regression (MLR) modeling and principal component analysis (PCA). With the selected genes, satisfactory results can be obtained.     

Partial least squares and logistic regression random-effects estimates for gene selection in supervised classification of gene expression data

Our main interest in supervised classification of gene expression data is to infer whether the expressions can discriminate biological characteristics of samples. With thousands of gene expressions to consider, a gene selection has been advocated to decrease classification by including only the discriminating genes. We propose to make the gene selection based on partial least squares and logistic regression random-effects (RE) estimates before the selected genes are evaluated in classification models. We compare the selection with that based on the two-sample t-statistics, a current practice, and modified t-statistics. The results indicate that gene selection based on logistic regression RE estimates is recommended in a general situation, while the selection based on the PLS estimates is recommended when the number of samples is low. Gene selection based on the modified t-statistics performs well when the genes exhibit moderate-to-high variability with moderate group separation. Respecting the characteristics of the data is a key aspect to consider in gene selection.     

正常血钾型周期性麻痹一家系28例分析

目的：报道一正常血钾型周期性麻痹（normoKPP）家系,以提高对该病的认识。方法：调查一normoKPP家系,分析其家系中28例normo KPP患者的临床表现、辅助检查以及治疗结果,并复习相关文献。结果：患者均于儿童期起病,周期性发作四肢迟缓性瘫痪,发作期血钾正常,葡萄糖酸钙治疗有效。结论：normoKPP 是少见的常染色体显性遗传的骨骼肌病,依据其家族史、临床表现及相关辅助检查可诊断,基因分析可确诊。     

Toll‐Like Receptor 2 Knockdown Modulates Interleukin (IL)‐6 and IL‐8 but not Stromal Derived Factor‐1 (SDF‐1/CXCL12) in Human Periodontal Ligament and Gingival Fibroblasts

Background: Fibroblasts are now seen as active components of the immune response because these cells express Toll‐like receptors (TLRs), recognize pathogen‐associated molecular patterns, and mediate the production of cytokines and chemokines during inflammation. The innate host response to lipopolysaccharide (LPS) from Porphyromonas gingivalis is unusual inasmuch as different studies have reported that it can be an agonist for Toll‐like receptor 2 (TLR2) and an antagonist or agonist for Toll‐like receptor 4 (TLR4). This study investigates and compares whether signaling through TLR2 or TLR4 could affect the secretion of interleukin (IL)‐6, IL‐8, and stromal derived factor‐1 (SDF‐1/CXCL12) in both human gingival fibroblasts (HGF) and human periodontal ligament fibroblasts (HPDLF). Methods: After small interfering RNA‐mediated silencing of TLR2 and TLR4, HGF and HPDLF from the same donors were stimulated with P. gingivalis LPS or with two synthetic ligands of TLR2, Pam2CSK4 and Pam3CSK4, for 6 hours. IL‐6, IL‐8, and CXCL12 mRNA expression and protein secretion were evaluated by quantitative polymerase chain reaction and enzyme‐linked immunosorbent assay, respectively. Results: TLR2 mRNA expression was upregulated in HGF but not in HPDLF by all the stimuli applied. Knockdown of TLR2 decreased IL‐6 and IL‐8 in response to P. gingivalis LPS, or Pam2CSK4 and Pam3CSK4, in a similar manner in both fibroblasts subpopulations. Conversely, CXCL12 remained unchanged by TLR2 or TLR4 silencing. Conclusion: These results suggest that signaling through TLR2 by gingival and periodontal ligament fibroblasts can control the secretion of IL‐6 and IL‐8, which contribute to periodontal pathogenesis, but do not interfere with CXCL12 levels, an important chemokine in the repair process.     

真核表达载体pIRES2-EGFP-PELP1的构建及其在人牙周膜干细胞中的表达

目的 克隆人源脯氨酸-谷氨酸-亮氨酸富集蛋白1(proline-,glutanic acid-,leucine-rich proteinl,PELP1)基因全长,构建PELP1基因全长过表达载体,研究PELP1基因表达特点,为PELP1基因在不同组织细胞中的功能性研究奠定基础.方法 采用反转录PCR法从MCF-7细胞总RNA中克隆PELP1基因全长,与含有EcoR I与Xho I双酶切位点的真核过表达载体pIRES2-EGFP质粒载体连接,构建重组质粒pIRES2-EGFP-PELP1.经双酶切及测序鉴定重组质粒中PELP1基因的完整性及正确性.运用脂质体将重组质粒转染至人牙周膜干细胞中,运用实时定量PCR(quantitative real-time PCR,qRT-PCR)及蛋白质印迹法分别从基因和蛋白水平对转染细胞中PELP1的表达进行检测.结果 成功克隆出PELP1基因全长,并将其插入至pIRES2-EGFP过表达载体中,经双酶切鉴定和测序鉴定证实目的质粒片段插入无误.重组质粒pIRES2-EGFP-PELP1转染48 h后PELP1基因水平是转染空质粒人牙周膜干细胞的(148.0±1.3)倍,二者差异有统计学意义(P＜ 0.005).蛋白质印迹法结果显示,与转入pIRES2-EGFP的人牙周膜干细胞中PELP1蛋白相对表达量(0.3300±0.0117)相比,转入pIRES2-EGFP-PELP1重组质粒的人牙周膜干细胞中PELP1蛋白相对表达量(0.6200 ±0.0045)显著增高,二者差异有统计学意义(P＜ 0.005).结论 本项研究成功运用qRT-PCR反应从MCF-7细胞中克隆出PELP1全长基因,并成功构建pIRES2-EGFP-PELP1真核过表达载体.     

慢性牙周炎患者白细胞介素-6基因甲基化的研究

目的研究慢性牙周炎人群与牙周健康人群白细胞介素-6(interleukin 6,IL-6)基因启动子甲基化水平差异,探讨IL-6基因启动子甲基化与慢性牙周炎易感性的关系。方法慢性牙周炎组44例,健康对照组45例。颊黏膜棉拭子提取样本DNA,甲基化特异性聚合酶链反应检测IL-6基因启动子的甲基化阳性率。结果慢性牙周炎组IL-6基因启动子甲基化阳性率为68.18%;健康对照组甲基化阳性率为93.33%,两组差异有统计学意义(χ2=9.108,P=0.003)。结论 IL-6基因启动子甲基化可能与慢性牙周炎的易感性相关。     

shRNA慢病毒对人口腔鳞状细胞癌细胞端粒酶卡侯体蛋白1基因的沉默效应

目的：探讨shRNA慢病毒对人口腔鳞状细胞癌Cal27细胞系端粒酶新蛋白,即端粒酶卡侯体蛋白1（TCAB1）基因的沉默效应,以期探索肿瘤基因治疗的新途径。方法：根据TCAB1基因,构建慢病毒shTCAB1-A~D,测定病毒滴度;用重组慢病毒体外感染Cal27细胞,荧光显微镜观察绿色荧光蛋白表达推断感染效率;半定量逆转录聚合酶链反应（RT-PCR）检测TCAB1 mRNA水平;Western blot检测TCAB1蛋白质的表达水平;四甲基偶氮唑盐比色（MTT）法检测细胞体外增殖能力;Transwell小室法检测细胞体外侵袭能力改变。结果：经PCR与测序鉴定证实成功构建靶向TCAB1的慢病毒RNAi载体,病毒滴度为1.5×108~3×108 U·mL-1。荧光显微镜观察显示,绝大部分细胞表达绿色荧光。与空白细胞对照组相比,4种不同的shTCAB1-A~D慢病毒感染组TCAB1 mRNA表达下调48.7%~62.0%;蛋白抑制率达45.6%~77.5%,shTCAB1-C组最明显。shTCAB1-C慢病毒能明显抑制Cal27细胞增殖能力,也能降低其侵袭能力,穿过人工基底膜的平均细胞数明显低于空白对照组及非特异性对照组,侵袭抑制率高达67.5%（P〈0.05）。结论：成功构建并包装了端粒酶新蛋白TCAB1靶向的RNAi慢病毒,该病毒可高效感染人口腔鳞状细胞癌细胞,产生特异性的基因沉默效应。