Long noncoding intronic RNAs are differentially expressed in primary and metastatic pancreatic cancer

<p>Abstract</p> <p>Background</p> <p>Pancreatic ductal adenocarcinoma (PDAC) is known by its aggressiveness and lack of effective therapeutic options. Thus, improvement in current knowledge of molecular changes associated with pancreatic cancer is urgently needed to explore novel venues of diagnostics and treatment of this dismal disease. While there is mounting evidence that long noncoding RNAs (lncRNAs) transcribed from intronic and intergenic regions of the human genome may play different roles in the regulation of gene expression in normal and cancer cells, their expression pattern and biological relevance in pancreatic cancer is currently unknown. In the present work we investigated the relative abundance of a collection of lncRNAs in patients' pancreatic tissue samples aiming at identifying gene expression profiles correlated to pancreatic cancer and metastasis.</p> <p>Methods</p> <p>Custom 3,355-element spotted cDNA microarray interrogating protein-coding genes and putative lncRNA were used to obtain expression profiles from 38 clinical samples of tumor and non-tumor pancreatic tissues. Bioinformatics analyses were performed to characterize structure and conservation of lncRNAs expressed in pancreatic tissues, as well as to identify expression signatures correlated to tissue histology. Strand-specific reverse transcription followed by PCR and qRT-PCR were employed to determine strandedness of lncRNAs and to validate microarray results, respectively.</p> <p>Results</p> <p>We show that subsets of intronic/intergenic lncRNAs are expressed across tumor and non-tumor pancreatic tissue samples. Enrichment of promoter-associated chromatin marks and over-representation of conserved DNA elements and stable secondary structure predictions suggest that these transcripts are generated from independent transcriptional units and that at least a fraction is under evolutionary selection, and thus potentially functional.</p> <p>Statistically significant expression signatures comprising protein-coding mRNAs and lncRNAs that correlate to PDAC or to pancreatic cancer metastasis were identified. Interestingly, <it>loci </it>harboring intronic lncRNAs differentially expressed in PDAC metastases were enriched in genes associated to the MAPK pathway. Orientation-specific RT-PCR documented that intronic transcripts are expressed in sense, antisense or both orientations relative to protein-coding mRNAs. Differential expression of a subset of intronic lncRNAs (<it>PPP3CB</it>, <it>MAP3K14 </it>and <it>DAPK1 loci</it>) in metastatic samples was confirmed by Real-Time PCR.</p> <p>Conclusion</p> <p>Our findings reveal sets of intronic lncRNAs expressed in pancreatic tissues whose abundance is correlated to PDAC or metastasis, thus pointing to the potential relevance of this class of transcripts in biological processes related to malignant transformation and metastasis in pancreatic cancer.</p

Prevalence of and risk factors for fatty liver in the general population of Northern Italy: The Bagnacavallo Study

Background: The estimation of the burden of disease attributable to fatty liver requires studies performed in the general population. Methods: The Bagnacavallo Study was performed between October 2005 and March 2009. All the citizens of Bagnacavallo (Ravenna, Italy) aged 30 to 60 years as of January 2005 were eligible. Altered liver enzymes were defined as alanine transaminase &gt; 40 U/l and/or aspartate transaminase &gt; 37 U/l. Results: Four thousand and thirty-three (58%) out of 6920 eligible citizens agreed to participate and 3933 (98%) had complete data. 393 (10%) of the latter had altered liver enzymes and 3540 had not. After exclusion of subjects with HBV or HCV infection, liver ultrasonography was available for 93% of subjects with altered liber enzymes and 52% of those with normal liver enzymes. The prevalence of fatty liver, non-alcoholic fatty liver disease (NAFLD) and alcoholic fatty liver disease (AFLD) was 0.74 (95%CI 0.70 to 0.79) vs. 0.35 (0.33 to 0.37), 0.46 (0.41 to 0.51) vs. 0.22 (0.21 to 0.24) and 0.28 (0.24 to 0.33) vs. 0.13 (0.11 to 0.14) in citizens with than in those without altered liver enzymes. Ethanol intake was not associated and all the components of the metabolic syndrome (MS) were associated with fatty liver. All potential risk factors were associated with a lower odds of normal liver vs. NAFLD while they were unable to discriminate AFLD from NAFLD. Conclusions: Fatty liver as a whole was highly prevalent in Bagnacavallo in 2005/9 and was more common among citizens with altered liver enzymes

External validation of surrogate indices of fatty liver in the general population: The Bagnacavallo study

We externally validated the fatty liver index (FLI), the lipid accumulation product (LAP), the hepatic steatosis index (HSI), and the Zhejiang University index (ZJU) for the diagnosis of fatty liver (FL) and non-alcoholic fatty liver disease (NAFLD) in the general population. The validation was performed on 2159 citizens of the town of Bagnacavallo (Ravenna, Italy). Calibration was evaluated by calculating the calibration slope and intercept and by inspecting calibration plots; discrimination was evaluated using the c-statistic. The average calibration slope was 1 and the average intercept was 0 for all combinations of outcomes and indices. For the diagnosis of FL, the c-statistic was 0.85 for FLI, 0.83 for ZJU, 0.82 for HSI, and 0.80 for LAP; for the diagnosis of NAFLD, the c-statistic was 0.77 for FLI, 0.76 for ZJU, 0.75 for HSI, and 0.74 for LAP. All indices were strongly correlated with each other. In conclusion, FLI, LAP, HSI, and ZJU perform similarly well to diagnose FL and NAFLD in the Bagnacavallo population, even if FLI has a small advantage as discrimination is concerned

Muscle atrophy in advanced cirrhosis: a negleted factor in the evaluation of regional hemodinamycs

In this dissertation, the characteristics of the backflow cell model for flow systems of various holdup and mixing distributions were obtained. These include steady state and transient responses for reactor systems in which the resulting equations are nonlinear due to the reaction rate expression. The primary state variables are concentration, temperature, and coolant temperature which are dependent upon axial position. The Newton-Raphson technique of iteration is shown to be a fast and convenient method of obtaining the solution of the resulting mass and energy balance equations. Also, the frequency response characteristics for small deviations in the state variables around or about the steady state values are obtained by a direct matrix method. Certain transient and frequency responses are compared with experimental data. In all cases, very favorable comparisons are obtained for the responses. The maximum principle of Pontryagin is used in the optimization studies. The temperature profile to maximize the yield of an intermediate product of a chain reaction in a steady state reactor system with axial dispersion is obtained. The state variables for this type of system are described by a two-point boundary value system of differential equations in position. The adjoint variables resulting from the application of the maximum principle to this problem are also defined by a two-point boundary value system. Optimal control specifications for dynamic reactor systems are obtained through the application of the maximum principle and the utilization of gradient methods of convergence to the optimal trajectories. A step-by-step procedure is presented for the use of these equations. The optimization specifications are a single variable type. Also, the possibility of an internal feedback control loop on a second variable is considered. Some examples are presented to illustrate the techniques and the responses that can be expected. The techniques which are presented can be used on a relatively small computer and are fast enough to make on-line dynamic optimization of the control trajectories possible

Muscle atrophy in advanced cirrhosis: a negleted factor in the evaluation of regional hemodinamycs

none7noneP. Caraceni; F. Dazzani; E. Salizzoni; M. Domenicali; A. Zambruni; F. Trevisani; M. BernardiP. Caraceni; F. Dazzani; E. Salizzoni; M. Domenicali; A. Zambruni; F. Trevisani; M. Bernard