LncRNA DANCR aggravates the progression of ovarian cancer by downregulating UPF1.

OBJECTIVE: To uncover the role of long non-coding RNA (lncRNA) DANCR in aggravating the progression of ovarian cancer (OC) by downregulating UPF1 level. PATIENTS AND METHODS: DANCR level in OC tissues and matched adjacent normal ones was determined by quantitative real-time polymerase chain reaction (qRT-PCR). Its expression level in OC patients with different tumor node metastasis (TNM) staging and either with metastasis, or not, was examined as well. Receiver operating characteristic (ROC) curves were introduced for assessing the prognostic value of DANCR in OC. Subsequently, regulatory effects of DANCR on proliferative and migratory abilities of HO8910 and HEY cells were evaluated. Subcellular distribution of DANCR in OC cells was analyzed. Furthermore, the interaction between DANCR and UPF1 was explored by RNA immunoprecipitation (RIP) and Pearson correlation analysis. Finally, rescue experiments were conducted to clarify the role of DANCR/UPF1 axis in the progression of OC. RESULTS: DANCR was upregulated in OC tissues and cell lines. Its level was higher in OC patients with worse tumor stage and accompanied by metastatic loci. DANCR exerted the potential to serve as a prognostic marker for OC. Overexpression of DANCR accelerated HO8910 and HEY cells to proliferate and migrate. UPF1 was found to be downregulated in OC tissues and negatively correlated to DANCR. DANCR was mainly distributed in the cytoplasm and interacted with UPF1. Overexpression of UPF1 in OC cells partially reversed the promotive effect of DANCR on proliferative and migratory rates. CONCLUSIONS: LncRNA DANCR accelerates the proliferative and migratory abilities of OC cells through negatively regulating UPF1 level, thus aggravating the progression of OC.

Mining topological structures of protein-protein interaction networks for human brain-specific genes.

Compared to other placental mammals, humans have unique thinking and cognitive abilities because of their developed cerebral cortex composed of billions of neurons and synaptic connections. As the primary effectors of the mechanisms of life, proteins and their interactions form the basis of cellular and molecular functions in the living body. In this paper, we developed a pipeline for mining topological structures, identifying functional modules, and analyzing their functions from publically available datasets. A human brain-specific protein-protein interaction network with 1482 nodes and 3105 edges was built using a MapReduce based shortest path algorithm. Within this, 7 functional cliques were identified using a network clustering method, 98 hub proteins were obtained by the calculation of betweenness and connectivity, and 5 closest relationship to clique connector proteins were recognized by the combination scores of topological distance and gene ontology similarity. Furthermore, we discovered functional modules interacting with TP53 protein, which involves several fragmented research study conclusions and might be an important clue for further in vivo or in silico experiments to confirm these associations.

Serum S100A4 levels as a novel biomarker for detection of acute myocardial infarction.

OBJECTIVE: Myocardial infarction causes significant mortality and morbidity. Timely diagnosis allows clinicians to risk stratify their patients and select appropriate treatment. Biomarkers have been used to assist with timely diagnosis, while an increasing number of novel markers have been identified to predict outcome following an acute myocardial infarction or acute coronary syndrome. The objective of this study was to determine S100A4 expression in AMI and determine whether S100A4 could be a biomarker for detection of acute myocardial infarction (AMI). PATIENTS AND METHODS: We measured circulating S100A4 levels in 173 patients (median age 58.3 years) who presented with first-time AMI 8 hours after the incident. The circulating S100A4 levels in 173 healthy volunteers (median age 57.3 years) was also measured. S100A4 was detected using enzyme immunoassay in both groups. RESULTS: Serum S100A4 levels were significantly higher in patients with AMI [89.6 (4.3-214.6) pg/ml] compared to controls [11.8 (0-41.5) pg/ml] (p < 0.001). We found that a S100A4 level > 41.5 pg/ml had a Sensitivity 76.3% and specificity 87.5% for predicting AMI. S100A4 revealed the higher sensitivity for diagnosing AMI. CONCLUSIONS: Elevated S100A4 in plasma may be a novel biomarker for early detection of AMI.

Effect of dizocilpine maleate on monoamines and their metabolites in rat brain.

Systemic (ip) injection of dizocilpine maleate (DM, 0.1 and 0.5 mg.kg-1) increased the levels of 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid but did not bring about any noticeable change in the dopamine (DA) level in the striatum and limbic area. DM also increased the levels of norepinephrine in the limbic area and 5-hydroxyindoleacetic acid in the hippocampus. Amphetamine increased DA level and reduced DOPAC level in the striatum and limbic area. The behavioral manifestations revealed that DM predominantly evoked circling behavior and ataxia. The results indicate that the mechanism of the behavioral effect of DM may be different from that of amphetamine.