Nucleosome Structure Incorporated Histone Acetylation Site Prediction in \u3ci\u3eArabidopsis thaliana\u3c/i\u3e

BackgroundAcetylation is a crucial post-translational modification for histones, and plays a key role in gene expression regulation. Due to limited data and lack of a clear acetylation consensus sequence, a few researches have focused on prediction of lysine acetylation sites. Several systematic prediction studies have been conducted for human and yeast, but less for Arabidopsis thaliana. ResultsConcerning the insufficient observation on acetylation site, we analyzed contributions of the peptide-alignment-based distance definition and 3D structure factors in acetylation prediction. We found that traditional structure contributes little to acetylation site prediction. Identified acetylation sites of histones in Arabidopsis thaliana are conserved and cross predictable with that of human by peptide based methods. However, the predicted specificity is overestimated, because of the existence of non-observed acetylable site. Here, by performing a complete exploration on the factors that affect the acetylability of lysines in histones, we focused on the relative position of lysine at nucleosome level, and defined a new structure feature to promote the performance in predicting the acetylability of all the histone lysines in A. thaliana. ConclusionWe found a new spacial correlated acetylation factor, and defined a ε-N spacial location based feature, which contains five core spacial ellipsoid wired areas. By incorporating the new feature, the performance of predicting the acetylability of all the histone lysines in A. Thaliana was promoted, in which the previous mispredicted acetylable lysines were corrected by comparing to the peptide-based prediction

Nucleosome Structure Incorporated Histone Acetylation Site Prediction in \u3ci\u3eArabidopsis thaliana\u3c/i\u3e

Background Acetylation is a crucial post-translational modification for histones, and plays a key role in gene expression regulation. Due to limited data and lack of a clear acetylation consensus sequence, a few researches have focused on prediction of lysine acetylation sites. Several systematic prediction studies have been conducted for human and yeast, but less for Arabidopsis thaliana. Results Concerning the insufficient observation on acetylation site, we analyzed contributions of the peptide-alignment-based distance definition and 3D structure factors in acetylation prediction. We found that traditional structure contributes little to acetylation site prediction. Identified acetylation sites of histones in Arabidopsis thaliana are conserved and cross predictable with that of human by peptide based methods. However, the predicted specificity is overestimated, because of the existence of non-observed acetylable site. Here, by performing a complete exploration on the factors that affect the acetylability of lysines in histones, we focused on the relative position of lysine at nucleosome level, and defined a new structure feature to promote the performance in predicting the acetylability of all the histone lysines in A. thaliana. Conclusion We found a new spacial correlated acetylation factor, and defined a ε-N spacial location based feature, which contains five core spacial ellipsoid wired areas. By incorporating the new feature, the performance of predicting the acetylability of all the histone lysines in A. Thaliana was promoted, in which the previous mispredicted acetylable lysines were corrected by comparing to the peptide-based prediction

Exploring virus relationships based on virus-host protein-protein interaction network

<p>Abstract</p> <p>Background</p> <p>Currently, several systems have been proposed to classify viruses and indicate the relationships between different ones, though each system has its limitations because of the complexity of viral origins and their rapid evolution rate. We hereby propose a new method to explore the relationships between different viruses.</p> <p>Method</p> <p>A new method, which is based on the virus-host protein-protein interaction network, is proposed in this paper to categorize viruses. The distances between 114 human viruses, including 48 HIV-1 and HIV-2 viruses, are estimated according to the protein-protein interaction network between these viruses and humans.</p> <p>Conclusions/significance</p> <p>The results demonstrated that our method can disclose not only relationships consistent with the taxonomic results of currently used systems of classification but also the potential relationships that the current virus classification systems have not revealed. Moreover, the method points to a new direction where the functional relationships between viruses and hosts can be used to explore the virus relationships on a systematic level.</p

Carnitine metabolites and cognitive improvement in patients with schizophrenia treated with olanzapine: a prospective longitudinal study

Objective: Cognitive impairment is one of the core symptoms of schizophrenia, which is stable and lifelong. L-carnitine has been shown to improve cognitive function and decrease the rate of cognitive deterioration in patients with Alzheimer’s disease. However, it remains unclear regarding the role of L-carnitine and its metabolites in cognitive functions in schizophrenia after treatment with olanzapine. The purpose of this study was to evaluate the relationship between changes in plasma levels of L-carnitine metabolites and cognitive improvement after olanzapine treatment.Methods: This was a prospective longitudinal study. In this study, we recruited 25 female patients with first episode schizophrenia (FES) who were drug naïve at baseline and received 4 weeks of olanzapine monotherapy. Cognitive function was assessed at baseline and 4-week follow-up using the RBANS. Plasma L-carnitine metabolite levels were determined by a metabolomics technology based on untargeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS).Results: We found that the immediate memory index, delayed memory index and RBANS composite score were significantly increased at the 4-week follow-up after treatment. A total of 7 differential L-carnitine metabolites were identified in FES patients after olanzapine monotherapy. In addition, we found that changes in butyrylcarnitine were positively correlated with improvements in language index and RBANS composite score. Further regression analyses confirmed the association between reduced butyrylcarnitine levels and cognitive improvement after olanzapine monotherapy in FES patients.Conclusion: Our study shows that cognitive improvement after olanzapine treatment was associated with changes in L-carnitine metabolite levels in patients with FES, suggesting a key role of L-carnitine in cognition in schizophrenia

Global Protein Interactome Exploration Through Mining Genome-Scale Data in \u3ci\u3eArabidopsis thaliana\u3c/i\u3e

Background Many essential cellular processes, such as cellular metabolism, transport, cellular metabolism and most regulatory mechanisms, rely on physical interactions between proteins. Genome-wide protein interactome networks of yeast, human and several other animal organisms have already been established, but this kind of network reminds to be established in the field of plant. Results We first predicted the protein protein interaction in Arabidopsis thaliana with methods, including ortholog, SSBP, gene fusion, gene neighbor, phylogenetic profile, coexpression, protein domain, and used Naïve Bayesian approach next to integrate the results of these methods and text mining data to build a genome-wide protein interactome network. Furthermore, we adopted the data of GO enrichment analysis, pathway, published literature to validate our network, the confirmation of our network shows the feasibility of using our network to predict protein function and other usage. Conclusions Our interactome is a comprehensive genome-wide network in the organism plant Arabidopsis thaliana, and provides a rich resource for researchers in related field to study the protein function, molecular interaction and potential mechanism under different conditions

Maximum predictive power of the microarray-based models for clinical outcomes is limited by correlation between endpoint and gene expression profile

<p>Abstract</p> <p>Background</p> <p>Microarray data have been used for gene signature selection to predict clinical outcomes. Many studies have attempted to identify factors that affect models' performance with only little success. Fine-tuning of model parameters and optimizing each step of the modeling process often results in over-fitting problems without improving performance.</p> <p>Results</p> <p>We propose a quantitative measurement, termed consistency degree, to detect the correlation between disease endpoint and gene expression profile. Different endpoints were shown to have different consistency degrees to gene expression profiles. The validity of this measurement to estimate the consistency was tested with significance at a p-value less than 2.2e-16 for all of the studied endpoints. According to the consistency degree score, overall survival milestone outcome of multiple myeloma was proposed to extend from 730 days to 1561 days, which is more consistent with gene expression profile.</p> <p>Conclusion</p> <p>For various clinical endpoints, the maximum predictive powers of different microarray-based models are limited by the correlation between endpoint and gene expression profile of disease samples as indicated by the consistency degree score. In addition, previous defined clinical outcomes can also be reassessed and refined more coherent according to related disease gene expression profile. Our findings point to an entirely new direction for assessing the microarray-based predictive models and provide important information to gene signature based clinical applications.</p

Nanomechanical properties of Mg–Al intermetallic compounds produced by packed powder diffusion coating (PPDC) on the surface of AZ91E

A packed powder diffusion coating (PPDC) treatment produced two intermetallic layers on the surface of the commercial magnesium alloy AZ91E. The beta-phase (Mg17Al12) was immediately on top of the AZ91E, on top of which was the tau-phase (Mg-32(Al,Zn)(49)). Nanoindentation showed that the elastic modulus and hardness of each of the intermetallic compounds was significantly greater than that of the AZ91E substrate. Staircase displacement bursts occurred during nanoindentation of the intermetallic compounds, attributed to the combination of incipient plasticity at low loads, and the development of dislocation networks due to dislocation pile ups around the indentation at higher loads. Crystallographic analysis of beta phase orientations using EBSD showed that the nanomechanical properties of the intermetallic compound produced through PPDC treatment were isotropic. (C) 2013 Elsevier B.V. All rights reserved

Baicalin Improves Survival in a Murine Model of Polymicrobial Sepsis via Suppressing Inflammatory Response and Lymphocyte Apoptosis

BACKGROUND: An imbalance between overwhelming inflammation and lymphocyte apoptosis is the main cause of high mortality in patients with sepsis. Baicalin, the main active ingredient of the Scutellaria root, exerts anti-inflammatory, anti-apoptotic, and even antibacterial properties in inflammatory and infectious diseases. However, the therapeutic effect of baicalin on polymicrobial sepsis remains unknown. METHODOLOGY/PRINCIPAL FINDINGS: Polymicrobial sepsis was induced by cecal ligation and puncture (CLP) in C57BL/6 mice. Mice were infused with baicalin intraperitoneally at 1 h, 6 h and 12 h after CLP. Survival rates were assessed over the subsequent 8 days. Bacterial burdens in blood and peritoneal cavity were calculated to assess the bacterial clearance. Neutrophil count in peritoneal lavage fluid was also calculated. Injuries to the lung and liver were detected by hematoxylin and eosin staining. Levels of cytokines, including tumor necrosis factor (TNF)-alpha, interleukin (IL)-6, IL-10 and IL-17, in blood and peritoneum were measured by enzyme-linked immunosorbent assay. Adaptive immune function was assessed by apoptosis of lymphocytes in the thymus and counts of different cell types in the spleen. Baicalin significantly enhanced bacterial clearance and improved survival of septic mice. The number of neutrophils in peritoneal lavage fluid was reduced by baicalin. Less neutrophil infiltration of the lung and liver in baicalin-treated mice was associated with attenuated injuries to these organs. Baicalin significantly reduced the levels of proinflammatory cytokines but increased the level of anti-inflammatory cytokine in blood and peritoneum. Apoptosis of CD3(+) T cell was inhibited in the thymus. The numbers of CD4(+), CD8(+) T lymphocytes and dendritic cells (DCs) were higher, while the number of CD4(+)CD25(+) regulatory T cells was lower in the baicalin group compared with the CLP group. CONCLUSIONS/SIGNIFICANCE: Baicalin improves survival of mice with polymicrobial sepsis, and this may be attributed to its antibacterial property as well as its anti-inflammatory and anti-apoptotic effects

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049