Multi-epoch analysis of the X-ray spectrum of the active galactic nucleus in NGC 5506

We present a multi-epoch X-ray spectroscopy analysis of the nearby narrow-line Seyfert I galaxy NGC 5506. For the first time, spectra taken by Chandra, XMM-Newton, Suzaku, and NuSTAR - covering the 2000-2014 time span - are analyzed simultaneously, using state-of-the-art models to describe reprocessing of the primary continuum by optical thick matter in the AGN environment. The main goal of our study is determining the spin of the supermassive black hole (SMBH). The nuclear X-ray spectrum is photoelectrically absorbed by matter with column density $\simeq 3 \times 10^{22}$ cm$^{-2}$. A soft excess is present at energies lower than the photoelectric cut-off. Both photo-ionized and collisionally ionized components are required to fit it. This component is constant over the time-scales probed by our data. The spectrum at energies higher than 2 keV is variable. We propose that its evolution could be driven by flux-dependent changes in the geometry of the innermost regions of the accretion disk. The black hole spin in NGC 5506 is constrained to be 0.93$\pm _{ 0.04 }^{0.04}$ at 90% confidence level for one interesting parameter.Comment: 13 pages, 9 figures. v2: refereed versio

A Novel microRNA and transcription factor mediated regulatory network in schizophrenia

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is a complex brain disorder with molecular mechanisms that have yet to be elucidated. Previous studies have suggested that changes in gene expression may play an important role in the etiology of schizophrenia, and that microRNAs (miRNAs) and transcription factors (TFs) are primary regulators of this gene expression. So far, several miRNA-TF mediated regulatory modules have been verified. We hypothesized that miRNAs and TFs might play combinatory regulatory roles for schizophrenia genes and, thus, explored miRNA-TF regulatory networks in schizophrenia.</p> <p>Results</p> <p>We identified 32 feed-forward loops (FFLs) among our compiled schizophrenia-related miRNAs, TFs and genes. Our evaluation revealed that these observed FFLs were significantly enriched in schizophrenia genes. By converging the FFLs and mutual feedback loops, we constructed a novel miRNA-TF regulatory network for schizophrenia. Our analysis revealed EGR3 and hsa-miR-195 were core regulators in this regulatory network. We next proposed a model highlighting EGR3 and miRNAs involved in signaling pathways and regulatory networks in the nervous system. Finally, we suggested several single nucleotide polymorphisms (SNPs) located on miRNAs, their target sites, and TFBSs, which may have an effect in schizophrenia gene regulation.</p> <p>Conclusions</p> <p>This study provides many insights on the regulatory mechanisms of genes involved in schizophrenia. It represents the first investigation of a miRNA-TF regulatory network for a complex disease, as demonstrated in schizophrenia.</p

RNA-Seq analysis implicates dysregulation of the immune system in schizophrenia

Background While genome-wide association studies identified some promising candidates for schizophrenia, the majority of risk genes remained unknown. We were interested in testing whether integration gene expression and other functional information could facilitate the identification of susceptibility genes and related biological pathways. Results We conducted high throughput sequencing analyses to evaluate mRNA expression in blood samples isolated from 3 schizophrenia patients and 3 healthy controls. We also conducted pooled sequencing of 10 schizophrenic patients and matched controls. Differentially expressed genes were identified by t-test. In the individually sequenced dataset, we identified 198 genes differentially expressed between cases and controls, of them 19 had been verified by the pooled sequencing dataset and 21 reached nominal significance in gene-based association analyses of a genome wide association dataset. Pathway analysis of these differentially expressed genes revealed that they were highly enriched in the immune related pathways. Two genes, S100A8 and TYROBP, had consistent changes in expression in both individual and pooled sequencing datasets and were nominally significant in gene-based association analysis. Conclusions Integration of gene expression and pathway analyses with genome-wide association may be an efficient approach to identify risk genes for schizophrenia

InPrePPI: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes

Background Although many genomic features have been used in the prediction of protein-protein interactions (PPIs), frequently only one is used in a computational method. After realizing the limited power in the prediction using only one genomic feature, investigators are now moving toward integration. So far, there have been few integration studies for PPI prediction; one failed to yield appreciable improvement of prediction and the others did not conduct performance comparison. It remains unclear whether an integration of multiple genomic features can improve the PPI prediction and, if it can, how to integrate these features. Results In this study, we first performed a systematic evaluation on the PPI prediction in Escherichia coli (E. coli) by four genomic context based methods: the phylogenetic profile method, the gene cluster method, the gene fusion method, and the gene neighbor method. The number of predicted PPIs and the average degree in the predicted PPI networks varied greatly among the four methods. Further, no method outperformed the others when we tested using three well-defined positive datasets from the KEGG, EcoCyc, and DIP databases. Based on these comparisons, we developed a novel integrated method, named InPrePPI. InPrePPI first normalizes the AC value (an integrated value of the accuracy and coverage) of each method using three positive datasets, then calculates a weight for each method, and finally uses the weight to calculate an integrated score for each protein pair predicted by the four genomic context based methods. We demonstrate that InPrePPI outperforms each of the four individual methods and, in general, the other two existing integrated methods: the joint observation method and the integrated prediction method in STRING. These four methods and InPrePPI are implemented in a user-friendly web interface. Conclusion This study evaluated the PPI prediction by four genomic context based methods, and presents an integrated evaluation method that shows better performance in E. coli

Analysis of the variation of in situ seafloor sediments acoustic characteristics with porosity based EDFM

Numerous factors influence the acoustic characteristics of seafloor sediments, necessitating a comprehensive study that combines theoretical analysis, laboratory measurements and in situ measurements to support acoustic prediction and inversion. In this study, a porosity-based effective density fluid model (P-EDFM) is established to analyze the variation of acoustic properties with the porosity of seafloor sediments. On the biases of P-EDFM, the attribute of measured sound velocity and acoustic attenuation coefficient of seafloor sediment in Series 9B of the SAX99 was well interpreted within the frequency range of 25-100 kHz. The in situ measured sound velocity ratio was well predicated by the P-EDFM in the East China Sea and Yellow Sea. It reveals that the in situ sound velocity ratio decreases with increasing bulk porosity and with decreasing bulk density. The scattering and differences in the acoustic attenuation coefficient measured in situ in seafloor sediments are found to be greater than those observed for sound velocity. After considering the influence of temperature in the P-EDFM, the prediction of in situ sound velocity aligns well with the measured dataset. While, the acoustic attenuation coefficient exhibits an inflection point, increasing initially and then decreasing with changes in porosity, similar to the observed pattern in Hamilton’s observation and estimation. By incorporating temperature and frequency influences, the in situ measurements of sound velocity of seafloor sediments are corrected into laboratory sound velocities by using the P-EDFM. The result reveals the sediment samples’ sampling and transmitting process has a much greater impact on the sound velocity of sandy sediment in the East China Sea compared to muddy sediment. Overall, P-EDFM can predict the in situ sound velocity and sound attenuation coefficient under different temperatures and frequencies, with a lower prediction error for sound velocity compared to sound attenuation coefficient

Characterization of schizophrenia adverse drug interactions through a network approach and drug classification

Antipsychotic drugs are medications commonly for schizophrenia (SCZ) treatment, which include two groups: typical and atypical. SCZ patients have multiple comorbidities, and the coadministration of drugs is quite common. This may result in adverse drug-drug interactions, which are events that occur when the effect of a drug is altered by the coadministration of another drug. Therefore, it is important to provide a comprehensive view of these interactions for further coadministration improvement. Here, we extracted SCZ drugs and their adverse drug interactions from the DrugBank and compiled a SCZ-specific adverse drug interaction network. This network included 28 SCZ drugs, 241 non-SCZs, and 991 interactions. By integrating the Anatomical Therapeutic Chemical (ATC) classification with the network analysis, we characterized those interactions. Our results indicated that SCZ drugs tended to have more adverse drug interactions than other drugs. Furthermore, SCZ typical drugs had significant interactions with drugs of the &quot;alimentary tract and metabolism&quot; category while SCZ atypical drugs had significant interactions with drugs of the categories &quot;nervous system&quot; and &quot;antiinfectives for systemic uses. &quot; This study is the first to characterize the adverse drug interactions in the course of SCZ treatment and might provide useful information for the future SCZ treatment

Comparative Phospho- and Acetyl Proteomics Analysis of Posttranslational Modifications Regulating Intestine Regeneration in Sea Cucumbers

Sea cucumbers exposed to stressful circumstances eviscerate most internal organs, and then regenerate them rapidly under favorable environments. Reversible protein phosphorylation and acetylation are major modifications regulating protein function. Herein, for the first time, we perform quantitative phospho- and acetyl proteomics analyses of intestine regeneration in a sea cucumber species Apostichopus japonicus. We identified 1,862 phosphorylation sites in 1,169 proteins, and 712 acetylation sites in 470 proteins. Of the 147 and 251 proteins differentially modified by phosphorylation and acetylation, respectively, most were related to cytoskeleton biogenesis, protein synthesis and modification, signal recognition and transduction, energy production and conversion, or substance transport and metabolism. Phosphorylation appears to play a more important role in signal recognition and transduction than acetylation, while acetylation is of greater importance in posttranslational modification, protein turnover, chaperones; energy production and conversion; amino acid and lipid transport and metabolism. These results expanded our understanding of the regulatory mechanisms of posttranslational modifications in intestine regeneration of sea cucumbers after evisceration