Optimizing dynamical network structure for pinning control

Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights

A rare presentation of late right coronary artery spasm following aortic valve replacement

BACKGROUND: Coronary artery spasm (CAS) is defined as a reversible, sudden epicardial coronary artery stenosis that causes vessel occlusion or near occlusion. CASE REPORT: In this article, we present a clinical case of CAS in a 48-year-old woman undergoing elective aortic valve replacement surgery for aortic stenosis. On the 3rd post-operative day, the patient suffered from chest pain and dyspnea. Emergent coronary angiography demonstrated a significant spasm of the ostium portion of the right coronary artery. CONCLUSION: This case shows that delayed coronary spasm should be considered as a cause of hemodynamic instability after valvular surgery. © 2015, Isfahan University of Medical Sciences(IUMS). All rights reserved

Mechanism Underlying Defective Interferon Gamma-Induced IDO Expression in Non-obese Diabetic Mouse Fibroblasts

Indoleamine 2,3-dioxygenase (IDO) can locally suppress T cell-mediated immune responses. It has been shown that defective self-tolerance in early prediabetic female non-obese diabetic (NOD) mice can be attributed to the impaired interferon-gamma (IFN-γ)- induced IDO expression in dendritic cells of these animals. As IFN-γ can induce IDO in both dendritic cells and fibroblasts, we asked the question of whether there exists a similar defect in IFN-γ-induced IDO expression in NOD mice dermal fibroblasts. To this end, we examined the effect of IFN-γ on expression of IDO and its enzymatic activity in NOD dermal fibroblasts. The results showed that fibroblasts from either prediabetic (8 wks of age) female or male, and diabetic female or male (12 and 24 wks of age respectively) NOD mice failed to express IDO in response to IFN-γ treatment. To find underlying mechanisms, we scrutinized the IFN- γ signaling pathway and investigated expression of other IFN-γ-modulated factors including major histocompatibility complex class I (MHC-I) and type I collagen (COL-I). The findings revealed a defect of signal transducer and activator of transcription 1 (STAT1) phosphorylation in NOD cells relative to that of controls. Furthermore, we found an increase in MHC-I and suppression of COL-I expression in fibroblasts from both NOD and control mice following IFN-γ treatment; indicating that the impaired response to IFN-γ in NOD fibroblasts is specific to IDO gene. Finally, we showed that an IFN-γ-independent IDO expression pathway i.e. lipopolysaccharide (LPS)-mediated-c-Jun kinase is operative in NOD mice fibroblast. In conclusion, the findings of this study for the first time indicate that IFN-γ fails to induce IDO expression in NOD dermal fibroblasts; this may partially be due to defective STAT1 phosphorylation in IFN-γ-induced-IDO signaling pathway

Study of measuring Tilapia (Oreochromis niloticus) freshness using quality index method (QIM)

Fish freshness by using QIM and according to scoring to all of parts variable (positive and negative) was by sensory method and finally become the parameters of quantitative and qualitative with statistical analysis is based, tables used in volatility score of 0 to 23, with a score of 0 to 3 respectively, for their excellent quality, 3 to 7good, from 7 to 10 and from 10 to above average evaluation is unacceptable. In this study to measure the freshness of fish species Nile Tilapia (Oreochromis niloticus), black and red in 4 treatments, whole fish and empty stomach is considered and the objective of this study was to calculate the survival rate of fish in ice cover practically immediately after harvest to measure qualitative factors (sensory evaluation, chemical and microbiological).For this study 50 pieces of red and 50 pieces black Tilapia after weighed, washed and then selection 25 pieces for each treatment in unlit, ratio of 3 to 1 (ice - fish) was covered .The mean (± SD) change in temperature the fish flesh during study were between 0.2 ±0.07 a to 0.3 ±0.1a degrees Celsius, that need to raise the quality temperature is maintained at 0 degrees Celsius in unlit center. Fish covered with ice keep at ambient temperature, and after measuring the change free nitrogen, pH and microbial tests, the results showed maximum shelf life of whole fish in ice cover 9 and for empty stomach fish was7 days .And also statistical analysis (Duncan test) of data between treatments (Whole and empty fish covered in ice ) was significant (P<0.05)

Bacterial flora-typing with targeted, chip-based Pyrosequencing

<p>Abstract</p> <p>Background</p> <p>The metagenomic analysis of microbial communities holds the potential to improve our understanding of the role of microbes in clinical conditions. Recent, dramatic improvements in DNA sequencing throughput and cost will enable such analyses on individuals. However, such advances in throughput generally come at the cost of shorter read-lengths, limiting the discriminatory power of each read. In particular, classifying the microbial content of samples by sequencing the < 1,600 bp 16S rRNA gene will be affected by such limitations.</p> <p>Results</p> <p>We describe a method for identifying the phylogenetic content of bacterial samples using high-throughput Pyrosequencing targeted at the 16S rRNA gene. Our analysis is adapted to the shorter read-lengths of such technology and uses a database of 16S rDNA to determine the most specific phylogenetic classification for reads, resulting in a weighted phylogenetic tree characterizing the content of the sample. We present results for six samples obtained from the human vagina during pregnancy that corroborates previous studies using conventional techniques.</p> <p>Next, we analyze the power of our method to classify reads at each level of the phylogeny using simulation experiments. We assess the impacts of read-length and database completeness on our method, and predict how we do as technology improves and more bacteria are sequenced. Finally, we study the utility of targeting specific 16S variable regions and show that such an approach considerably improves results for certain types of microbial samples. Using simulation, our method can be used to determine the most informative variable region.</p> <p>Conclusion</p> <p>This study provides positive validation of the effectiveness of targeting 16S metagenomes using short-read sequencing technology. Our methodology allows us to infer the most specific assignment of the sequence reads within the phylogeny, and to identify the most discriminative variable region to target. The analysis of high-throughput Pyrosequencing on human flora samples will accelerate the study of the relationship between the microbial world and ourselves.</p

Explorative visual analytics on interval-based genomic data and their metadata

Background: With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. Results: This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. Conclusions: GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSEunder GPLv3 open-source license