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Fourteen Ganoderma lucidum strains from different geographic regions were identified using ITS region sequencing. Based on the sequences obtained, the genomic relationship between the analyzed strains was determined. All G. lucidum strains were also genetically characterized using the AFLP technique. G. lucidum strains included in the analysis displayed an AFLP profile similarity level in the range from 9.6 to 33.9%. Biolog FF MicroPlates were applied to obtain data on utilization of 95 carbon sources and mitochondrial activity. The analysis allowed comparison of functional diversity of the fungal strains. The substrate utilization profiles for the isolates tested revealed a broad variability within the analyzed G. lucidum species and proved to be a good profiling technology for studying the diversity in fungi. Significant differences have been demonstrated in substrate richness values. Interestingly, the analysis of growth and biomass production also differentiated the strains based on the growth rate on the agar and sawdust substrate. In general, the mycelial growth on the sawdust substrate was more balanced and the fastest fungal growth was observed for GRE3 and FCL192. [ABSTRACT FROM AUTHOR]

Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data. [ABSTRACT FROM AUTHOR]

Nicotinamide N-methyltransferase (NNMT) catalyzes the methylation of nicotinamide. Our previous works indicate that NNMT is involved in the body mass index and energy metabolism, and recently the association between a SNP (rs694539) of NNMT and a variety of cardiovascular diseases was reported. At present, more than 200 NNMT single nucleotide polymorphisms (SNPs) have been identified in the databases of the human genome projects; however, the association between rs694539 variation and hyperlipidemia has not been reported yet, and whether there are any SNPs in NNMT significantly associated with hyperlipidemia is still unclear. In this paper, we selected 19 SNPs in NNMT as the tagSNPs using Haploview software (Haploview 4.2) first and then performed a case-control study to observe the association between these tagSNPs and hyperlipidemia and finally applied physiological approaches to explore the possible mechanisms through which the NNMT polymorphism induces hyperlipidemia. The results show that a SNP (rs1941404) in NNMT is significantly associated with hyperlipidemia, and the influence of rs1941404 variation on the resting energy expenditure may be the possible mechanism for rs1941404 variation to induce hyperlipidemia. [ABSTRACT FROM AUTHOR]

The present study was designed to evaluate the dynamic expression of lncRNA NORAD in fracture healing of patients with brittle fractures and explore the function and mechanism of NORAD in regulating osteoblastic proliferation, differentiation, and apoptosis. The expression level of NORAD was detected by quantitative real-time PCR. The proliferation, differentiation, and apoptosis of osteoblasts were analyzed by MTT assay, ELISA, and flow cytometry. Luciferase report analysis was used to confirm the interaction between NORAD and its target ceRNA miR-26a. This study showed no significant differences in serum NORAD expression on the 7th day during fracture healing in patients, but increased expression of NORAD was certified on the 14, 21, and 28 days after fixation. Overexpression of NORAD promoted the proliferation and differentiation of osteoblasts and suppressed the apoptosis of osteoblasts. miR-26a proved to be the target gene of NORAD and was inhibited by overexpression of NORAD in osteoblasts. The enhanced expression of miR-26a was negatively linked to the lessened expression of NORAD. NORAD could accelerate the proliferation and differentiation of osteoblasts and inhibit apoptosis, thereby promoting fracture healing. [ABSTRACT FROM AUTHOR]

Lung cancer is the primary reason for death due to cancer worldwide, and non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer. Most patients die from complications of NSCLC due to poor diagnosis. In this paper, we aimed to predict gene biomarkers that may be of use for diagnosis of NSCLC by integrating differential gene expression analysis with functional association network analysis. We first constructed an NSCLC-specific functional association network by combining gene expression correlation with functional association. Then, we applied a network partition algorithm to divide the network into gene modules and identify the most NSCLC-specific gene modules based on their differential expression pattern in between normal and NSCLC samples. Finally, from these modules, we identified genes that exhibited the most impact on the expression of their functionally associated genes in between normal and NSCLC samples and predicted them as NSCLC biomarkers. Literature review of the top predicted gene biomarkers suggested that most of them were already considered critical for development of NSCLC. [ABSTRACT FROM AUTHOR]

Autism spectrum disorders (ASDs) are a group of mental illnesses highly correlated with gut microbiota. Recent studies have shown that some abnormal aromatic metabolites in autism patients are presumably derived from overgrown Clostridium species in gut, which may be used for diagnostic purposes. In this paper, a GC/MS based metabolomic approach was utilized to seek similar biomarkers by analyzing the urinary information in 62 ASDs patients compared with 62 non-ASDs controls in China, aged 1.5–7. Three compounds identified as 3-(3-hydroxyphenyl)-3-hydroxypropionic acid (HPHPA), 3-hydroxyphenylacetic acid (3HPA), and 3-hydroxyhippuric acid (3HHA) were found in higher concentrations in autistic children than in the controls (p<0.001). After oral vancomycin treatment, urinary excretion of HPHPA (p<0.001), 3HPA (p<0.005), and 3HHA (p<0.001) decreased markedly, which indicated that these compounds may also be from gut Clostridium species. The sensitivity and specificity of HPHPA, 3HPA, and 3HHA were evaluated by receiver-operating characteristic (ROC) analysis. The specificity of each compound for ASDs was very high (>96%). After two-regression analysis, the optimal area under the curve (AUC, 0.962), sensitivity (90.3%), and specificity (98.4%) were obtained by ROC curve of Prediction probability based on the three metabolites. These findings demonstrate that the measurements of the three compounds are strong predictors of ASDs and support the potential clinical utility for identifying a subgroup of ASDs subjects. [ABSTRACT FROM AUTHOR]

Previous studies suggest that metformin may exert a protective effect on cisplatin-induced cytotoxicity in cancer cells, and this finding has led to a caution for considering metformin use in the treatment of cancer patients. However, in this paper we provide the first demonstration that metformin synergistically augments cisplatin cytotoxicity in the esophageal squamous cancer cell line, ECA109, under glucose-deprivation conditions, which may be more representative of the microenvironment within solid tumors; this effect is very different from the previously reported cytoprotective effect of metformin against cisplatin in commonly used high glucose incubation medium. The potential mechanisms underlying the synergistic effect of metformin on cisplatin-induced cytotoxicity under glucose-deprivation conditions may include enhancement of metformin-associated cytotoxicity, marked reduction in the cellular ATP levels, deregulation of the AKT and AMPK signaling pathways, and impaired DNA repair function. [ABSTRACT FROM AUTHOR]

Low back pain (LBP) is a very prevalent disease and degenerative disc diseases (DDDs) usually account for the LBP. However, the pathogenesis of DDDs is complicated and difficult to elucidate. Alternative splicing is a sophisticated regulatory process which greatly increases cellular complexity and phenotypic diversity of eukaryotic organisms. In addition, the cartilage endplate-derived stem cells have been discovered and identified by our research group. In this paper, we continue to investigate gene expression profiling and alternative splicing events during chondrogenic differentiation of cartilage endplate-derived stem cells. We adopted Affymetrix Human Transcriptome Array 2.0 (HTA 2.0) to compare the transcriptional and splicing changes between the control and differentiated samples. RT-PCR and quantitative PCR are used to validate the microarray results. The GO and KEGG pathway analysis was also performed. After bioinformatics analysis of the data, we detected 1953 differentially expressed genes. In terms of alternative splicing, the Splicing Index algorithm was used to select alternatively spliced genes. We detected 4411 alternatively spliced genes. GO and KEGG pathway analysis also revealed several functionally involved biological processes and signaling pathways. To our knowledge, this is the first study to investigate the alternative splicing mechanisms in chondrogenic differentiation of stem cells on a genome-wide scale. [ABSTRACT FROM AUTHOR]

Mouse models have provided an essential platform to investigate facets of human diseases, from etiology, diagnosis, and prognosis, to potential treatments. Muscular dystrophy (MD) is the most common human genetic disease occurring in approximately 1 in 2500 births. The mdx mouse, which is dystrophin-deficient, has long been used to model this disease. However, this mouse strain displays a rather mild disease course compared to human patients. The mdx mice have been bred to additional genetically engineered mice to worsen the disease. Alternatively, other genes which cause human MD have been genetically disrupted in mice. We are now comparing disease progression from one of these alternative gene disruptions, the γ-sarcoglycan null mouse Sgcg−/− on the DBA2/J background, to the mdx mouse line. This paper aims to assess the time-course severity of the disease in the mouse models and determine which is best for MD research. The Sgcg−/− mice have a more severe phenotype than the mdx mice. Muscle function was assessed by plethysmography and echocardiography. Histologically the Sgcg−/− mice displayed increased fibrosis and variable fiber size. By quantitative Evan’s blue dye uptake and hydroxyproline content two key disease determinants, membrane permeability and fibrosis respectively, were also proven worse in the Sgcg−/− mice. [ABSTRACT FROM AUTHOR]

In order to understand disease pathogenesis, improve medical diagnosis, or discover effective drug targets, it is important to identify significant genes deeply involved in human disease. For this purpose, many earlier approaches attempted to prioritize candidate genes using gene expression profiles or SNP genotype data, but they often suffer from producing many false-positive results. To address this issue, in this paper, we propose a meta-analysis strategy for gene prioritization that employs three different genetic resources—gene expression data, single nucleotide polymorphism (SNP) genotype data, and expression quantitative trait loci (eQTL) data—in an integrative manner. For integration, we utilized an improved technique for the order of preference by similarity to ideal solution (TOPSIS) to combine scores from distinct resources. This method was evaluated on two publicly available datasets regarding prostate cancer and lung cancer to identify disease-related genes. Consequently, our proposed strategy for gene prioritization showed its superiority to conventional methods in discovering significant disease-related genes with several types of genetic resources, while making good use of potential complementarities among available resources. [ABSTRACT FROM AUTHOR]

Introduction. Diversion colitis is a significant health problem due to its high incidence in patients with diverting enterostomy. This mucosal inflammation presents characteristic histopathological features allowing for the differentiation of this entity from other inflammatory bowel diseases. The pathophysiology of this disease remains ill-defined, in part due to the lack of appropriate animal models. The present study was performed in order to develop and characterize a murine model of diversion colitis. Methods. A diverting loop colostomy was performed in C57BL/6 mice either in the ascending colon or in the transverse colon. Animals were assessed for clinical and histopathological parameters during short-term and long-term survival. Results. Animals with a colostomy in the transverse colon showed a good long-term survival and developed a mild colitis in the bypassed bowel closely resembling the human pathology on a histopathological level. Conclusion. This model is a promising tool to further elucidate the pathomechanism leading to impaired mucosal homeostasis in bypassed colonic segments. Moreover, the establishment of the model in the C57BL/6 background allows the combination of this colitis model with various transgenic mouse strains to investigate the effect of locally deregulated mucosal immunity on systemic immune homeostasis and to develop specific therapeutic strategies. [ABSTRACT FROM AUTHOR]