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1.
Chin J Physiol ; 60(1): 62-72, 2017 Feb 28.
Artigo em Inglês | MEDLINE | ID: mdl-28052647

RESUMO

Diabetes (one of non-communicable diseases) is serious due to its complications, such like, cardiovascular ailments, neuropathy, nephropathy, retinopathy, wound gangrene and sexual impotence. Diabetes and associated chronic conditions are rapidly emerging as major health problems. In clinical, there were different drugs for diabetes treatment on different mechanisms. However, there were limited studies on the efficacy of electric stimulations on diabetes therapeutic application. In current study, we try to evaluate the effect of microcurrent electrical nerve stimulator (MENS) on diabetes modulation as an alternative medicine. A total of 36 male ICR mice of 6 weeks old were randomly divided into 4 groups [1] Control, [2] MENS only, [3] DM, [4] DM with MENS. During 8 weeks treatments, the diabetes-associated assessments included body weight, diet utilization, blood glucose measurement, other biochemistries and histopathological observations. The diabetes animal model induced by STZ had 180 mg/dl fasting blood glucose (GLU-AC) before MENS intervention. After 3 and 6 weeks administration, the GLU-AC of DM+MENS group significantly decreased 31.97% and 50.82% (P < 0.0001), respectively, as compared to DM group and the OGTT also demonstrated the similar significant results. The diabetic syndromes of polydipsia and polyphagia were also significantly ameliorated by MENS intervention. In other biochemical indexes, the glycated hemoglobin (HbA1c), hyperinsulinemia, liver functions (AST & ALT) and kidneys function (BUN & Creatinine) were also significantly mitigated by MENS under diabetes model. The histological observation also showed the MENS administration improved the diabetes-related pathological characteristics in liver, kidney and pancreas tissues. Our results suggest that administration of MENS could significantly improve diabetes animal model on blood sugar homeostasis, diabetic polydipsia, biochemistries, and tissue damage. In the health conditions, the MENS didn't exist obvious side effects on assessments. Therefore, the MENS could be potential on alternative medicine or supportive applications to future DM therapeutics.


Assuntos
Diabetes Mellitus Experimental/terapia , Terapia por Estimulação Elétrica , Animais , Teste de Tolerância a Glucose , Camundongos Endogâmicos ICR , Distribuição Aleatória
2.
J Bioinform Comput Biol ; 11(5): 1342005, 2013 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-24131054

RESUMO

Phylogenetic analysis has to overcome the grant challenge of inferring accurate species trees from evolutionary histories of gene families (gene trees) that are discordant with the species tree along whose branches they have evolved. Two well studied approaches to cope with this challenge are to solve either biologically informed gene tree parsimony (GTP) problems under gene duplication, gene loss, and deep coalescence, or the classic RF supertree problem that does not rely on any biological model. Despite the potential of these problems to infer credible species trees, they are NP-hard. Therefore, these problems are addressed by heuristics that typically lack any provable accuracy and precision. We describe fast dynamic programming algorithms that solve the GTP problems and the RF supertree problem exactly, and demonstrate that our algorithms can solve instances with data sets consisting of as many as 22 taxa. Extensions of our algorithms can also report the number of all optimal species trees, as well as the trees themselves. To better asses the quality of the resulting species trees that best fit the given gene trees, we also compute the worst case species trees, their numbers, and optimization score for each of the computational problems. Finally, we demonstrate the performance of our exact algorithms using empirical and simulated data sets, and analyze the quality of heuristic solutions for the studied problems by contrasting them with our exact solutions.


Assuntos
Modelos Genéticos , Família Multigênica , Filogenia , Algoritmos , Animais , Biologia Computacional , Simulação por Computador , Bases de Dados Genéticas , Evolução Molecular , Deleção de Genes , Duplicação Gênica , Modelos Estatísticos , Especificidade da Espécie
3.
BMC Bioinformatics ; 13 Suppl 10: S16, 2012 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-22759421

RESUMO

BACKGROUND: Biological networks provide fundamental insights into the functional characterization of genes and their products, the characterization of DNA-protein interactions, the identification of regulatory mechanisms, and other biological tasks. Due to the experimental and biological complexity, their computational exploitation faces many algorithmic challenges. RESULTS: We introduce novel weighted quasi-biclique problems to identify functional modules in biological networks when represented by bipartite graphs. In difference to previous quasi-biclique problems, we include biological interaction levels by using edge-weighted quasi-bicliques. While we prove that our problems are NP-hard, we also describe IP formulations to compute exact solutions for moderately sized networks. CONCLUSIONS: We verify the effectiveness of our IP solutions using both simulation and empirical data. The simulation shows high quasi-biclique recall rates, and the empirical data corroborate the abilities of our weighted quasi-bicliques in extracting features and recovering missing interactions from biological networks.


Assuntos
Algoritmos , Biologia Computacional/métodos , Biologia de Sistemas/métodos , Simulação por Computador , Mineração de Dados , Redes Reguladoras de Genes , Redes e Vias Metabólicas , Modelos Teóricos
4.
BMC Bioinformatics ; 12 Suppl 1: S14, 2011 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-21342543

RESUMO

BACKGROUND: The gene duplication (GD) problem seeks a species tree that implies the fewest gene duplication events across a given collection of gene trees. Solving this problem makes it possible to use large gene families with complex histories of duplication and loss to infer phylogenetic trees. However, the GD problem is NP-hard, and therefore, most analyses use heuristics that lack any performance guarantee. RESULTS: We describe the first integer linear programming (ILP) formulation to solve instances of the gene duplication problem exactly. With simulations, we demonstrate that the ILP solution can solve problem instances with up to 14 taxa. Furthermore, we apply the new ILP solution to solve the gene duplication problem for the seed plant phylogeny using a 12-taxon, 6,084-gene data set. The unique, optimal solution, which places Gnetales sister to the conifers, represents a new, large-scale genomic perspective on one of the most puzzling questions in plant systematics. CONCLUSIONS: Although the GD problem is NP-hard, our novel ILP solution for it can solve instances with data sets consisting of as many as 14 taxa and 1,000 genes in a few hours. These are the largest instances that have been solved to optimally to date. Thus, this work can provide large-scale genomic perspectives on phylogenetic questions that previously could only be addressed by heuristic estimates.


Assuntos
Duplicação Gênica , Filogenia , Plantas/genética , Programação Linear , Algoritmos , Simulação por Computador , Genoma de Planta , Genômica/métodos
5.
BMC Bioinformatics ; 6: 44, 2005 Mar 07.
Artigo em Inglês | MEDLINE | ID: mdl-15748298

RESUMO

BACKGROUND: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. RESULTS: In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory function, we would deduce the upstream regulatory genes with their regulatory abilities and activation delays, and then link up a regulatory pathway. Iteratively, these regulatory genes are considered as target genes to trace back their upstream regulatory genes. Then we could construct the regulatory pathway (or network) to the genome wide. In short, we can infer the genetic regulatory pathways from gene-expression profiles quantitatively, which can confirm some doubted paths or seek some unknown paths in a regulatory pathway (network). Finally, the proposed approach is validated by randomly reshuffling the time order of microarray data. CONCLUSION: We focus our algorithm on the inference of regulatory abilities of the identified causal genes, and how much delay before they regulate the downstream genes. With this information, a regulatory pathway would be built up using microarray data. In the present study, two signaling pathways, i.e. circadian regulatory pathway in Arabidopsis thaliana and metabolic shift pathway from fermentation to respiration in yeast Saccharomyces cerevisiae, are reconstructed using microarray data to evaluate the performance of our proposed method. In the circadian regulatory pathway, we identified mainly the interactions between the biological clock and the photoperiodic genes consistent with the known regulatory mechanisms. We also discovered the now less-known regulations between crytochrome and phytochrome. In the metabolic shift pathway, the casual relationship of enzymatic genes could be detected properly.


Assuntos
Biologia Computacional/métodos , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Mapeamento de Interação de Proteínas/métodos , Algoritmos , Arabidopsis/metabolismo , Ritmo Circadiano , Biologia Computacional/instrumentação , Simulação por Computador , Proteínas de Ligação a DNA , Fermentação , Perfilação da Expressão Gênica , Regulação da Expressão Gênica , Regulação Fúngica da Expressão Gênica , Genes Fúngicos , Genes de Plantas , Genoma Fúngico , Funções Verossimilhança , Modelos Biológicos , Modelos Estatísticos , Ligação Proteica , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/química , Transdução de Sinais , Fatores de Transcrição
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