Pub Date : 2013-02-28DOI: 10.4172/2169-0111.1000106
Ping-Yang Chen, Xiuquan Zhang
Perinatal growth phenotype is largely determined by genes, nutrient supply, placental transport function, environment, and growth hormones. Recently, gene mutation and expression have been reported to play an important role in perinatal growth and development. Perinatal growth epigenetics, a new concept in growth phenotype, has been accepted in fetal programming. This paper outlines the findings of perinatal phenotype in several studies and summarizes fetal growth restriction, birth defects, angiotensinogen gene mutation and pathological phenotypes of placenta, and the occurrence of other pregnancy complications. We review genetic approaches to IUGR, especially those related to growth factor genes, gene mutations and epigenetics with abnormal perinatal characterizations. We also discuss gene study directions, which should be valuable in elucidating mechanisms employed by the fetus and prevent the development of abnormal perinatal outcomes.
{"title":"Gene Determinants and Perinatal Growth Phenotype","authors":"Ping-Yang Chen, Xiuquan Zhang","doi":"10.4172/2169-0111.1000106","DOIUrl":"https://doi.org/10.4172/2169-0111.1000106","url":null,"abstract":"Perinatal growth phenotype is largely determined by genes, nutrient supply, placental transport function, environment, and growth hormones. Recently, gene mutation and expression have been reported to play an important role in perinatal growth and development. Perinatal growth epigenetics, a new concept in growth phenotype, has been accepted in fetal programming. This paper outlines the findings of perinatal phenotype in several studies and summarizes fetal growth restriction, birth defects, angiotensinogen gene mutation and pathological phenotypes of placenta, and the occurrence of other pregnancy complications. We review genetic approaches to IUGR, especially those related to growth factor genes, gene mutations and epigenetics with abnormal perinatal characterizations. We also discuss gene study directions, which should be valuable in elucidating mechanisms employed by the fetus and prevent the development of abnormal perinatal outcomes.","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"2 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2013-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2169-0111.1000106","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70874161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-30DOI: 10.4172/2169-0111.1000105
Jian-feng Pan, Chang‐an Guo, Teng Fei, Wenshuai Fan, Jia Liu, Shuo Li, Zuoqin Yan
Injectable hydrogels have emerged as a great candidate in tissue engineering for they can be delivered via a minimally invasive manner. Here, we report an in situ forming hydrogel composited of oxidized dextran (Odex) and modified gelatin. The dynamic gelling process was measured through rheological measurements. The effect of the ratio of Odex and gelatin on gelling time, microstructure, swelling ratio and in vitro degradation of the composite hydrogels were examined. Biological assess was performed through WST-1 Assay by using Synovium-derived Mesenchymal Cells (SMSCs). According to the results, adjustable physicochemical properties can be obtained through simply altering the ratio of Odex and gelatin. Moreover, with the increase of incorporated gelatin, better biocompatibility was shown in the composite hydrogels, which exhibited its potentially high application prospect in the field of cartilage tissue engineering.
{"title":"Preparation and Characterization of a Novel Injectable Hydrogel","authors":"Jian-feng Pan, Chang‐an Guo, Teng Fei, Wenshuai Fan, Jia Liu, Shuo Li, Zuoqin Yan","doi":"10.4172/2169-0111.1000105","DOIUrl":"https://doi.org/10.4172/2169-0111.1000105","url":null,"abstract":"Injectable hydrogels have emerged as a great candidate in tissue engineering for they can be delivered via a minimally invasive manner. Here, we report an in situ forming hydrogel composited of oxidized dextran (Odex) and modified gelatin. The dynamic gelling process was measured through rheological measurements. The effect of the ratio of Odex and gelatin on gelling time, microstructure, swelling ratio and in vitro degradation of the composite hydrogels were examined. Biological assess was performed through WST-1 Assay by using Synovium-derived Mesenchymal Cells (SMSCs). According to the results, adjustable physicochemical properties can be obtained through simply altering the ratio of Odex and gelatin. Moreover, with the increase of incorporated gelatin, better biocompatibility was shown in the composite hydrogels, which exhibited its potentially high application prospect in the field of cartilage tissue engineering.","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"135 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2013-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2169-0111.1000105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70874109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-15DOI: 10.4172/2169-0111.1000103
M. Conese
Respiratory diseases represent the major cause of morbidity and mortality worldwide, and for them a definitive cure is not included in the pharmacopeia. For example, despite improvements in mechanical ventilation, acute lung injury and its severe form, acute respiratory distress syndrome, are the leading cause of death in critical care, with mortality rates of 40 to 60%. In the field of chronic lung diseases, treatment with antibiotics and other medicals has prolonged the life span of individuals with cystic fibrosis, the most lethal diseases of the Caucasian population with autosomal recessive inheritance, but this is still limited to 40 years. There is urgent and desperate need of novel effective therapies for these patients.
{"title":"Towards a Combined Gene and Cell Therapy for Lung Diseases: The Case of Induced Pluripotent Stem Cells","authors":"M. Conese","doi":"10.4172/2169-0111.1000103","DOIUrl":"https://doi.org/10.4172/2169-0111.1000103","url":null,"abstract":"Respiratory diseases represent the major cause of morbidity and mortality worldwide, and for them a definitive cure is not included in the pharmacopeia. For example, despite improvements in mechanical \u0000ventilation, acute lung injury and its severe form, acute respiratory distress syndrome, are the leading cause of death in critical care, with mortality rates of 40 to 60%. In the field of chronic lung diseases, treatment with antibiotics and other medicals has prolonged the life span of individuals with cystic fibrosis, the most lethal diseases of the Caucasian population with autosomal recessive inheritance, but this is still limited to 40 years. There is urgent and desperate need of novel effective therapies for these patients.","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"1 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70874389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-02-09DOI: 10.4172/2169-0111.1000102
Ji-Gang Zhang, Jian Li, Wenlong Tang, H. Deng
It is usually observed that among genes there exist strong statistical interactions associated with diseases of public health importance. Gene interactions can potentially contribute to the improvement of disease classification accuracy. Especially when gene expression differs across different classes are not great enough, it is more important to take use of gene interactions for disease classification analyses. However, most gene selection algorithms in classification analyses merely focus on genes whose expression levels show differences across classes, and ignore the discriminatory information from gene interactions. In this study, we develop a two-stage algorithm that can take gene interaction into account during a gene selection procedure. Its biggest advantage is that it can take advantage of discriminatory information from gene interactions as well as gene expression differences, by using "Bayes error" as a gene selection criterion. Using simulated and real microarray data sets, we demonstrate the ability of gene interactions for classification accuracy improvement, and present that the proposed algorithm can yield small informative sets of genes while leading to highly accurate classification results. Thus our study may give a novel sight for future gene selection algorithms of human diseases discrimination.
{"title":"Fusing Gene Interaction to Improve Disease Discrimination on Classification Analysis.","authors":"Ji-Gang Zhang, Jian Li, Wenlong Tang, H. Deng","doi":"10.4172/2169-0111.1000102","DOIUrl":"https://doi.org/10.4172/2169-0111.1000102","url":null,"abstract":"It is usually observed that among genes there exist strong statistical interactions associated with diseases of public health importance. Gene interactions can potentially contribute to the improvement of disease classification accuracy. Especially when gene expression differs across different classes are not great enough, it is more important to take use of gene interactions for disease classification analyses. However, most gene selection algorithms in classification analyses merely focus on genes whose expression levels show differences across classes, and ignore the discriminatory information from gene interactions. In this study, we develop a two-stage algorithm that can take gene interaction into account during a gene selection procedure. Its biggest advantage is that it can take advantage of discriminatory information from gene interactions as well as gene expression differences, by using \"Bayes error\" as a gene selection criterion. Using simulated and real microarray data sets, we demonstrate the ability of gene interactions for classification accuracy improvement, and present that the proposed algorithm can yield small informative sets of genes while leading to highly accurate classification results. Thus our study may give a novel sight for future gene selection algorithms of human diseases discrimination.","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"1 1 1","pages":"1000102"},"PeriodicalIF":0.0,"publicationDate":"2012-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2169-0111.1000102","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70874505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ji-Gang Zhang, Jian Li, Wenlong Tang, Hong-Wen Deng
It is usually observed that among genes there exist strong statistical interactions associated with diseases of public health importance. Gene interactions can potentially contribute to the improvement of disease classification accuracy. Especially when gene expression differs across different classes are not great enough, it is more important to take use of gene interactions for disease classification analyses. However, most gene selection algorithms in classification analyses merely focus on genes whose expression levels show differences across classes, and ignore the discriminatory information from gene interactions. In this study, we develop a two-stage algorithm that can take gene interaction into account during a gene selection procedure. Its biggest advantage is that it can take advantage of discriminatory information from gene interactions as well as gene expression differences, by using "Bayes error" as a gene selection criterion. Using simulated and real microarray data sets, we demonstrate the ability of gene interactions for classification accuracy improvement, and present that the proposed algorithm can yield small informative sets of genes while leading to highly accurate classification results. Thus our study may give a novel sight for future gene selection algorithms of human diseases discrimination.
{"title":"Fusing Gene Interaction to Improve Disease Discrimination on Classification Analysis.","authors":"Ji-Gang Zhang, Jian Li, Wenlong Tang, Hong-Wen Deng","doi":"10.4172/AGE.1000102","DOIUrl":"https://doi.org/10.4172/AGE.1000102","url":null,"abstract":"<p><p>It is usually observed that among genes there exist strong statistical interactions associated with diseases of public health importance. Gene interactions can potentially contribute to the improvement of disease classification accuracy. Especially when gene expression differs across different classes are not great enough, it is more important to take use of gene interactions for disease classification analyses. However, most gene selection algorithms in classification analyses merely focus on genes whose expression levels show differences across classes, and ignore the discriminatory information from gene interactions. In this study, we develop a two-stage algorithm that can take gene interaction into account during a gene selection procedure. Its biggest advantage is that it can take advantage of discriminatory information from gene interactions as well as gene expression differences, by using \"Bayes error\" as a gene selection criterion. Using simulated and real microarray data sets, we demonstrate the ability of gene interactions for classification accuracy improvement, and present that the proposed algorithm can yield small informative sets of genes while leading to highly accurate classification results. Thus our study may give a novel sight for future gene selection algorithms of human diseases discrimination.</p>","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"1 1","pages":"1000102"},"PeriodicalIF":0.0,"publicationDate":"2012-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694734/pdf/nihms458589.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31545726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-01-16DOI: 10.4172/2169-0111.1000E101
Yue Zhang
How would you like to stay 25 forever?To some extent, it might be not a dream in the future to reverse the aging and agingrelated diseases. Certainly, aging was thus far programmed by natural selection during evolution so eventually inevitable [1-2]. However, performance can come from a cost. Through systematical modifications of the Genome Regulatory Network (GRN) and/or proteome, human cell and tissue engineering could couple with such inevitability by means of cellular reprogramming, genome editing [3] and tissue regenerative engineering. Many reviews previously speculated that the exhaustion of adult stem cell promotes the ageing and degenerative diseases, shortening the longevity [4]. Indeed, one of latest exciting investigations shows us the case of age reversal: implanting young stem cells to rejuvenate aging stem cells. Interestingly, the research team injected the stem like /progenitor cells into the abdomens of 17-day-old progeria mice, which generally have a lifespan of 21 to 28 days, some of them have a robust health and a life span up to 66 days [5]. Progeria is a disease that causes abnormally accelerated aging, such as loss of muscle mass,mesodermal/mesenchymal defects, accelerated atherosclerosis, neurodegeneration, osteoporosis, and trembling. It has been genetically shown that the deficiency of Lamina A (also the components of its embedded Mi-2/Nucelosome Remodeling and histone Deacetylation, i.e. NuRD complex) causes the chromatin old and leads thus to ageing [4,6]. After receiving the injection of stem cells, the mice recipients showed new blood vessel growth in the brain and muscle, improvement of health and increase of longevity. The injections of stem cells also delayed the onset of the majority of aging-related symptomsin a less acute model of accelerated aging. Intriguingly, the “labelled” injected cells went all over the place rather than home in on muscle or one kind of tissue.It raised the suspicion that the cells were secreting something that was kick-start regenerative capacity in whole organisms but effectively staving off aging [5]. This somehow mimics the kick-start of OSKM reprogramming of the cell pluripotency in cellular engineering [3,7], namely, to hit one node in the network, then spread to the whole system. We can view it with system biology: as on one balloon, to touch one starting point, the pressure reshapes the whole balloon.
{"title":"New Frontiers of Aging Reversal and Aging-Related Diseases Reprogramming","authors":"Yue Zhang","doi":"10.4172/2169-0111.1000E101","DOIUrl":"https://doi.org/10.4172/2169-0111.1000E101","url":null,"abstract":"How would you like to stay 25 forever?To some extent, it might be not a dream in the future to reverse the aging and agingrelated diseases. Certainly, aging was thus far programmed by natural selection during evolution so eventually inevitable [1-2]. However, performance can come from a cost. Through systematical modifications of the Genome Regulatory Network (GRN) and/or proteome, human cell and tissue engineering could couple with such inevitability by means of cellular reprogramming, genome editing [3] and tissue regenerative engineering. Many reviews previously speculated that the exhaustion of adult stem cell promotes the ageing and degenerative diseases, shortening the longevity [4]. Indeed, one of latest exciting investigations shows us the case of age reversal: implanting young stem cells to rejuvenate aging stem cells. Interestingly, the research team injected the stem like /progenitor cells into the abdomens of 17-day-old progeria mice, which generally have a lifespan of 21 to 28 days, some of them have a robust health and a life span up to 66 days [5]. Progeria is a disease that causes abnormally accelerated aging, such as loss of muscle mass,mesodermal/mesenchymal defects, accelerated atherosclerosis, neurodegeneration, osteoporosis, and trembling. It has been genetically shown that the deficiency of Lamina A (also the components of its embedded Mi-2/Nucelosome Remodeling and histone Deacetylation, i.e. NuRD complex) causes the chromatin old and leads thus to ageing [4,6]. After receiving the injection of stem cells, the mice recipients showed new blood vessel growth in the brain and muscle, improvement of health and increase of longevity. The injections of stem cells also delayed the onset of the majority of aging-related symptomsin a less acute model of accelerated aging. Intriguingly, the “labelled” injected cells went all over the place rather than home in on muscle or one kind of tissue.It raised the suspicion that the cells were secreting something that was kick-start regenerative capacity in whole organisms but effectively staving off aging [5]. This somehow mimics the kick-start of OSKM reprogramming of the cell pluripotency in cellular engineering [3,7], namely, to hit one node in the network, then spread to the whole system. We can view it with system biology: as on one balloon, to touch one starting point, the pressure reshapes the whole balloon.","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"1 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2012-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70877188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is realized that a combined analysis of different types of genomic measurements tends to give more reliable classification results. However, how to efficiently combine data with different resolutions is challenging. We propose a novel compressed sensing based approach for the combined analysis of gene expression and copy number variants data for the purpose of subtyping six types of Gliomas. Experimental results show that the proposed combined approach can substantially improve the classification accuracy compared to that of using either of individual data type. The proposed approach can be applicable to many other types of genomic data.
{"title":"Subtyping of Gliomaby Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach.","authors":"Wenlong Tang, Hongbao Cao, Ji-Gang Zhang, Junbo Duan, Dongdong Lin, Yu-Ping Wang","doi":"10.4172/2169-0111.1000101","DOIUrl":"https://doi.org/10.4172/2169-0111.1000101","url":null,"abstract":"<p><p>It is realized that a combined analysis of different types of genomic measurements tends to give more reliable classification results. However, how to efficiently combine data with different resolutions is challenging. We propose a novel compressed sensing based approach for the combined analysis of gene expression and copy number variants data for the purpose of subtyping six types of Gliomas. Experimental results show that the proposed combined approach can substantially improve the classification accuracy compared to that of using either of individual data type. The proposed approach can be applicable to many other types of genomic data.</p>","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"1 ","pages":"101"},"PeriodicalIF":0.0,"publicationDate":"2012-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2169-0111.1000101","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32705757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4172/2169-0111.1000104
A. Chhabra
T cell immunity is critical for protection against infectious agents as well as cancer. T cell immune response is a well orchestrated process that involves three key components. CD8+ T cells that harbor cytolytic machinery and can target and kill the tumor cells in an antigen specific manner, CD4+ T cells that can either “help” the generation of a productive CD8+ T cell or “regulate/suppress” it, and the Antigen Presenting Cells (APC) that can efficiently process the antigens and present them to the effector T cells in small fragments, termed as the antigenic epitopes. The specificity and efficacy of T cell immune response is evident by the remarkable success of vaccines against infectious agents. However, attempts to develop similar approaches against cancer have not resulted in similar success. The main reason for this is the fact that, most human cancers arise from within and self-reactive immune repertoire is eliminated during developmental process to prevent autoimmunity.
{"title":"Engineering Anti-Tumor T Cell Immunity","authors":"A. Chhabra","doi":"10.4172/2169-0111.1000104","DOIUrl":"https://doi.org/10.4172/2169-0111.1000104","url":null,"abstract":"T cell immunity is critical for protection against infectious agents as well as cancer. T cell immune response is a well orchestrated process that involves three key components. CD8+ T cells that harbor cytolytic machinery and can target and kill the tumor cells in an antigen specific manner, CD4+ T cells that can either “help” the generation of a productive CD8+ T cell or “regulate/suppress” it, and the Antigen Presenting Cells (APC) that can efficiently process the antigens and present them to the effector T cells in small fragments, termed as the antigenic epitopes. The specificity and efficacy of T cell immune response is evident by the remarkable success of vaccines against infectious agents. However, attempts to develop similar approaches against cancer have not resulted in similar success. The main reason for this is the fact that, most human cancers arise from within and self-reactive immune repertoire is eliminated during developmental process to prevent autoimmunity.","PeriodicalId":89733,"journal":{"name":"Advancements in genetic engineering","volume":"2 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2169-0111.1000104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70874087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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