ABSTRACT
UNLABELLED: Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms. AVAILABILITY AND IMPLEMENTATION: http://ci.smu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Data Mining/methods , Gene Regulatory Networks , Genes , Software , Cluster Analysis , Humans , Internet , MEDLINEABSTRACT
BACKGROUND: Biomedical researchers often want to explore pathogenesis and pathways regulated by abnormally expressed genes, such as those identified by microarray analyses. Literature mining is an important way to assist in this task. Many literature mining tools are now available. However, few of them allows the user to make manual adjustments to zero in on what he/she wants to know in particular. RESULTS: We present our software program, GenCLiP (Gene Cluster with Literature Profiles), which is based on the methods presented by Chaussabel and Sher (Genome Biol 2002, 3(10):RESEARCH0055) that search gene lists to identify functional clusters of genes based on up-to-date literature profiling. Four features were added to this previously described method: the ability to 1) manually curate keywords extracted from the literature, 2) search genes and gene co-occurrence networks related to custom keywords, 3) compare analyzed gene results with negative and positive controls generated by GenCLiP, and 4) calculate probabilities that the resulting genes and gene networks are randomly related. In this paper, we show with a set of differentially expressed genes between keloids and normal control, how implementation of functions in GenCLiP successfully identified keywords related to the pathogenesis of keloids and unknown gene pathways involved in the pathogenesis of keloids. CONCLUSION: With regard to the identification of disease-susceptibility genes, GenCLiP allows one to quickly acquire a primary pathogenesis profile and identify pathways involving abnormally expressed genes not previously associated with the disease.
Subject(s)
Gene Expression Profiling/methods , Multigene Family , Natural Language Processing , User-Computer Interface , Vocabulary, Controlled , Cluster Analysis , Databases, Bibliographic , Gene Regulatory Networks , Genetic Predisposition to Disease , Humans , Keloid/genetics , Keloid/physiopathology , Oligonucleotide Array Sequence Analysis , Predictive Value of Tests , Publications , SoftwareABSTRACT
A 23-year-old male patient, who was stabbed in the left chest at the fourth intercostal space leaving a 4-cm wound, was in agonal state with blood pressure of 0/0 kPa when admitted. The patient underwent emergency room thoractomy on stretcher through the left fourth intercostal anterior lateral incision 16 min after injury. The exploration revealed 2 500 ml blood in the plural cavity, 4-cm wound in the pericardium, 2-cm wound in the right ventricle of the heart without asystole, and 5-cm wound in the left upper lobe of the lung. Within 4 min the wound in the heart was sutured with the pericardium as the backing. The patient was discharged with full recovery 8 d after injury.
Subject(s)
Emergency Service, Hospital , Heart Injuries/surgery , Shock, Hemorrhagic/surgery , Wounds, Stab/surgery , Adult , Cardiopulmonary Resuscitation/methods , Humans , Male , Thoracotomy , Treatment OutcomeABSTRACT
BACKGROUND: Oxygen and glucose are two important nutrients for mammalian cell function. In this study, the effect of glucose and oxygen concentrations on C2C12 cellular metabolism was characterized with an emphasis on detecting whether cells show oxygen conformance (OC) in response to hypoxia. METHODS: After C2C12 cells being cultured in the levels of glucose at 0.6 mM (LG), 5.6 mM (MG), or 23.3 mM(HG) under normoxic or hypoxic (1% oxygen) condition, cellular oxygen consumption, glucose consumption, lactate production, and metabolic status were determined. Short-term oxygen consumption was measured with a novel oxygen biosensor technique. Longer-term measurements were performed with standard glucose, lactate, and cell metabolism assays. RESULTS: It was found that oxygen depletion in normoxia is dependent on the glucose concentration in the medium. Cellular glucose uptake and lactate production increased significantly in hypoxia than those in normoxia. In hypoxia the cellular response to the level of glucose was different to that in normoxia. The metabolic activities decreased while glucose concentration increased in normoxia, while in hypoxia, metabolic activity was reduced in LG and MG, but unchanged in HG condition. The OC phenomenon was not observed in the present study. CONCLUSIONS: Our findings suggested that a combination of low oxygen and low glucose damages the viability of C2C12 cells more seriously than low oxygen alone. In addition, when there is sufficient glucose, C2C12 cells will respond to hypoxia by upregulating anaerobic respiration, as shown by lactate production.
Subject(s)
Cell Hypoxia/genetics , Glucose/metabolism , Myoblasts/metabolism , Oxygen/metabolism , Anaerobiosis , Animals , Biosensing Techniques , Cell Hypoxia/physiology , Cell Survival , Glucose/isolation & purification , Mice , Myoblasts/cytology , Oxygen/isolation & purification , Oxygen ConsumptionABSTRACT
OBJECTIVE: To investigate the differentially expressed genes in keloids in comparison with normal skin using cDNA microarray. METHODS: The cDNA microarray consisting of 8064 clones of human genes was employed to detect and screen the differentially expressed genes in keloid and normal skin tissues. Semi-quantitative RT-PCR was applied to verify the results of gene microarray. RESULTS: Totally 277 differentially expressed genes were identified in keloids in comparison with normal skin tissue, including 163 up-regulated genes and 114 down-regulated ones according to the designed data filter criteria. These differentially expressed genes belonged to 26 different functional gene families involving different biological processes. RT-PCR yielded results were consistent with those of microarray study. CONCLUSION: A variety of genes are involved in the formation of keloids. The 277 differentially expressed genes comprise the differential gene expression profile of keloids and describe the general changes in the gene expressions in keloid at transcriptional level. Further analysis of the identified genes might help reveal the molecular mechanism of abnormal scarring.