DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
The proliferative response of T-cells to autolo-gous non-T-cells is referred to as the autologous mixed lymphocyte reaction (AMLR). Recent studies have suggested that AMLR represents a mechanism of immune regulation i...The proliferative response of T-cells to autolo-gous non-T-cells is referred to as the autologous mixed lymphocyte reaction (AMLR). Recent studies have suggested that AMLR represents a mechanism of immune regulation in vivo. We investigated AMLR in patients with acute- and chronic myeloid leukemia (AML and CML). AMLR was found to be significantly depressed (P<0.001) in AML patients (n=17, cpm=532±95) and CML patients (n=13, cpm=688±99) when compared with that of their healthy HLA-identical siblings serving as controls (n=17, cpm=4152±619 and n=13 cpm=4086±421, respectively). In order to understand the cellular basis of the defective AMLR in patients with AML end CML, we performed mitogen-treated T-cell cultures analysis of T-cell subsets and HLA-Ⅱ antigen detection on monocytes. The results indicated that the defect of AMLR in patients resided at the stimulator monocyte level rather than at the responder T-cell level. Enumeration of monocytes reactive with monoclonal antibody Tu22, which recognizes determinants of HLA-DQ, demonstrated that ML patients had a significantly decreased (P<0.091) number of circulating Tu22+ monocytes when compared with normal controls. These studies suggest that a deficiency of HLA-DQ+ monocytes contributes to the depression of AMLR in ML and possibly underlies the abnormalities of immune response present in this disease.展开更多
Based on the complex effective conductivity method, a closed-form expression for the internal impedance of mixed carbon nanotube （CNT） bundles, in which the number of CNTs for a given diameter follows a Gaussian dis...Based on the complex effective conductivity method, a closed-form expression for the internal impedance of mixed carbon nanotube （CNT） bundles, in which the number of CNTs for a given diameter follows a Gaussian distribution, is proposed in this paper. It can appropriately capture the skin effect as well as the temperature effect of mixed CNT bundles. The results of the closed-form expression and the numerical calculation are compared with various mean diameters, standard deviations, and temperatures. It is shown that the proposed model has very high accuracy in the whole frequency range considered, with maximum errors of 1% and 2.3% for the resistance and the internal inductance, respectively. Moreover, by using the proposed model, the high-frequency electrical characteristics of mixed CNT bundles are deeply analyzed to provide helpful design guidelines for their application in future high-performance three-dimensional integrated circuits.展开更多
Microarray has become increasingly popular biotechnology in biological and medical researches, and has been widely applied in classification of treatment subtypes using expression patterns of biomarkers. We developed ...Microarray has become increasingly popular biotechnology in biological and medical researches, and has been widely applied in classification of treatment subtypes using expression patterns of biomarkers. We developed a statistical procedure to identify expression biomarkers for treatment subtype classification by constructing an F-statistic based on Henderson method Ⅲ. Monte Carlo simulations were conducted to examine the robustness and efficiency of the proposed method. Simulation results showed that our method could provide satisfying power of identifying differentially expressed genes （DEGs） with false discovery rate （FDR） lower than the given type I error rate. In addition, we analyzed a leukemia dataset collected from 38 leukemia patients with 27 samples diagnosed as acute lymphoblastic leukemia （ALL） and 11 samples as acute myeloid leukemia （AML）. We compared our results with those from the methods of significance analysis of microarray （SAM） and microarray analysis of variance （MAANOVA）. Among these three methods, only expression biomarkers identified by our method can precisely identify the three human acute leukemia subtypes.展开更多
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
文摘The proliferative response of T-cells to autolo-gous non-T-cells is referred to as the autologous mixed lymphocyte reaction (AMLR). Recent studies have suggested that AMLR represents a mechanism of immune regulation in vivo. We investigated AMLR in patients with acute- and chronic myeloid leukemia (AML and CML). AMLR was found to be significantly depressed (P<0.001) in AML patients (n=17, cpm=532±95) and CML patients (n=13, cpm=688±99) when compared with that of their healthy HLA-identical siblings serving as controls (n=17, cpm=4152±619 and n=13 cpm=4086±421, respectively). In order to understand the cellular basis of the defective AMLR in patients with AML end CML, we performed mitogen-treated T-cell cultures analysis of T-cell subsets and HLA-Ⅱ antigen detection on monocytes. The results indicated that the defect of AMLR in patients resided at the stimulator monocyte level rather than at the responder T-cell level. Enumeration of monocytes reactive with monoclonal antibody Tu22, which recognizes determinants of HLA-DQ, demonstrated that ML patients had a significantly decreased (P<0.091) number of circulating Tu22+ monocytes when compared with normal controls. These studies suggest that a deficiency of HLA-DQ+ monocytes contributes to the depression of AMLR in ML and possibly underlies the abnormalities of immune response present in this disease.
基金Project supported by the National Science and Technology Major Project of China(Grant No.2015ZX03001004)the National Natural Science Foundation of China(Grant Nos.61604113,61625403,61334003,61376039,61574104,and 61474088)
文摘Based on the complex effective conductivity method, a closed-form expression for the internal impedance of mixed carbon nanotube （CNT） bundles, in which the number of CNTs for a given diameter follows a Gaussian distribution, is proposed in this paper. It can appropriately capture the skin effect as well as the temperature effect of mixed CNT bundles. The results of the closed-form expression and the numerical calculation are compared with various mean diameters, standard deviations, and temperatures. It is shown that the proposed model has very high accuracy in the whole frequency range considered, with maximum errors of 1% and 2.3% for the resistance and the internal inductance, respectively. Moreover, by using the proposed model, the high-frequency electrical characteristics of mixed CNT bundles are deeply analyzed to provide helpful design guidelines for their application in future high-performance three-dimensional integrated circuits.
基金Project partly supported by the National Basic Research Program(973) of China (No. 2004CB117306) and the National Natural Sci-ence Foundation of China (No. 2002AA234031)
文摘Microarray has become increasingly popular biotechnology in biological and medical researches, and has been widely applied in classification of treatment subtypes using expression patterns of biomarkers. We developed a statistical procedure to identify expression biomarkers for treatment subtype classification by constructing an F-statistic based on Henderson method Ⅲ. Monte Carlo simulations were conducted to examine the robustness and efficiency of the proposed method. Simulation results showed that our method could provide satisfying power of identifying differentially expressed genes （DEGs） with false discovery rate （FDR） lower than the given type I error rate. In addition, we analyzed a leukemia dataset collected from 38 leukemia patients with 27 samples diagnosed as acute lymphoblastic leukemia （ALL） and 11 samples as acute myeloid leukemia （AML）. We compared our results with those from the methods of significance analysis of microarray （SAM） and microarray analysis of variance （MAANOVA）. Among these three methods, only expression biomarkers identified by our method can precisely identify the three human acute leukemia subtypes.
