Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

<p>Abstract</p> <p>Background</p> <p>Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences.</p> <p>Results</p> <p>The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes.</p> <p>Conclusions</p> <p>The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at <url>http://biomine.ece.ualberta.ca/MODAS/</url>.</p

G = MAT: Linking Transcription Factor Expression and DNA Binding Data

Transcription factors are proteins that bind to motifs on the DNA and thus affect gene expression regulation. The qualitative description of the corresponding processes is therefore important for a better understanding of essential biological mechanisms. However, wet lab experiments targeted at the discovery of the regulatory interplay between transcription factors and binding sites are expensive. We propose a new, purely computational method for finding putative associations between transcription factors and motifs. This method is based on a linear model that combines sequence information with expression data. We present various methods for model parameter estimation and show, via experiments on simulated data, that these methods are reliable. Finally, we examine the performance of this model on biological data and conclude that it can indeed be used to discover meaningful associations. The developed software is available as a web tool and Scilab source code at http://biit.cs.ut.ee/gmat/

Prevalence of the metabolic syndrome in Pudong New Area of Shanghai using three proposed definitions among Chinese adults

<p>Abstract</p> <p>Background</p> <p>The prevalence of metabolic syndrome (MS) has been increasing in China in recent years. The aim of this study is to estimate and compare the prevalence of MS among Chinese adults in Shanghai, one of the most economic developed areas in China, using definitions proposed by World Health Organization (WHO), National Cholesterol Education Program Adult Treatment Panel (modified ATP III) and International Diabetes Federation (IDF).</p> <p>Methods</p> <p>This cross-sectional study included 5,584 adults at age 20-79 randomly selected from Pudong New Area of Shanghai, China, through a three-stage sampling. All participants were interviewed in-person between April and July of 2008 to collect information on demographic and lifestyle characteristics. At the interview, anthropometry and blood pressure were measured and bio-specimens were collected.</p> <p>Results</p> <p>The prevalence estimates for the MS increased with age for each definition in men and women, but the estimates varied greatly between the definitions and by sex. The prevalence of the MS was higher in men (20.2%) than in women (18.7%) using WHO definition but this sex difference was reversed when using the modified ATP III (28.4% for men vs. 35.1% for women) and the IDF (15.9% for men vs. 26.7% for women) criteria. The most common metabolic disorder in this population was dyslipidaemia, regardless of the definition used. Substantial agreement, estimated using the kappa statistic, was found between the modified ATP III and IDF definition, whereas the lowest agreement was observed between the WHO and ATP III criteria.</p> <p>Conclusions</p> <p>The MS is highly prevalent among Chinese adults in Pudong New Area of Shanghai and the most prevalent component was dyslipidemia. These findings underscore the importance of prevention and control efforts for the MS in this area and the need for a unified predictive definition for the syndrome for use by clinical practitioners and public health agencies.</p

Multicenter double blind trial of autologous bone marrow mononuclear cell transplantation through intracoronary injection post acute myocardium infarction – MiHeart/AMI study

Background: Myocardial infarction remains as a major cause of mortality worldwide and a high rate of survivors develop heart failure as a sequel, resulting in a high morbidity and elevated expenditures for health system resources. We have designed a multicenter trial to test for the efficacy of autologous bone marrow (ABM) mononuclear cell (MC) transplantation in this subgroup of patients. The main hypothesis to be tested is that treated patients will have a significantly higher ejection fraction (EF) improvement after 6 months than controls. Methods: A sample of 300 patients admitted with ST elevation acute myocardial infarction (STEMI) and left ventricle (LV) systolic dysfunction, and submitted to successful mechanical or chemical recanalization of the infarct-related coronary artery will be selected for inclusion and randomized to either treated or control group in a double blind manner. The former group will receive 100 x 106 MC suspended in saline with 5% autologous serum in the culprit vessel, while the latter will receive placebo (saline with 5% autologous serum). Implications: Many phase I/II clinical trials using cell therapy for STEMI have been reported, demonstrating that cell transplantation is safe and may lead to better preserved LV function. Patients with high risk to develop systolic dysfunction have the potential to benefit more. Larger randomized, double blind and controlled trials to test for the efficacy of cell therapies in patients with high risk for developing heart failure are required.Brazilian Ministry of Science and Technology (MCT)/The Financing Agency for Studies and Projects (FINEP

Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Identification of Yeasts Is Contingent on Robust Reference Spectra

BACKGROUND: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for yeast identification is limited by the requirement for protein extraction and for robust reference spectra across yeast species in databases. We evaluated its ability to identify a range of yeasts in comparison with phenotypic methods. METHODS: MALDI-TOF MS was performed on 30 reference and 167 clinical isolates followed by prospective examination of 67 clinical strains in parallel with biochemical testing (total n = 264). Discordant/unreliable identifications were resolved by sequencing of the internal transcribed spacer region of the rRNA gene cluster. PRINCIPAL FINDINGS: Twenty (67%; 16 species), and 24 (80%) of 30 reference strains were identified to species, (spectral score ≥2.0) and genus (score ≥1.70)-level, respectively. Of clinical isolates, 140/167 (84%) strains were correctly identified with scores of ≥2.0 and 160/167 (96%) with scores of ≥1.70; amongst Candida spp. (n = 148), correct species assignment at scores of ≥2.0, and ≥1.70 was obtained for 86% and 96% isolates, respectively (vs. 76.4% by biochemical methods). Prospectively, species-level identification was achieved for 79% of isolates, whilst 91% and 94% of strains yielded scores of ≥1.90 and ≥1.70, respectively (100% isolates identified by biochemical methods). All test scores of 1.70-1.90 provided correct species assignment despite being identified to "genus-level". MALDI-TOF MS identified uncommon Candida spp., differentiated Candida parapsilosis from C. orthopsilosis and C. metapsilosis and distinguished between C. glabrata, C. nivariensis and C. bracarensis. Yeasts with scores of <1.70 were rare species such as C. nivariensis (3/10 strains) and C. bracarensis (n = 1) but included 4/12 Cryptococcus neoformans. There were no misidentifications. Four novel species-specific spectra were obtained. Protein extraction was essential for reliable results. CONCLUSIONS: MALDI-TOF MS enabled rapid, reliable identification of clinically-important yeasts. The addition of spectra to databases and reduction in identification scores required for species-level identification may improve its utility

Process account of curiosity and interest: a reward-learning perspective

Previous studies suggested roles for curiosity and interest in knowledge acquisition and exploration, but there has been a long-standing debate about how to define these concepts and whether they are related or different. In this paper, we address the definition issue by arguing that there is inherent difficulty in defining curiosity and interest, because both curiosity and interest are naïve concepts, which are not supposed to have a priori scientific definitions. We present a reward-learning framework of autonomous knowledge acquisition and use this framework to illustrate the importance of process account as an alternative to advance our understanding of curiosity and interest without being troubled by their definitions. The framework centers on the role of rewarding experience associated with knowledge acquisition and learning and posits that the acquisition of new knowledge strengthens the value of further information. Critically, we argue that curiosity and interest are the concepts that they subjectively construe through this knowledge-acquisition process. Finally, we discuss the implications of the reward-learning framework for education and empirical research in educational psychology

A New Model for Raf Kinase Inhibitory Protein Induced Chemotherapeutic Resistance

Therapeutic resistance remains the most challenging aspect of treating cancer. Raf kinase inhibitory protein (RKIP) emerged as a molecule capable of sensitizing cancerous cells to radio- and chemotherapy. Moreover, this small evolutionary conserved molecule, endows significant resistance to cancer therapy when its expression is reduced or lost. RKIP has been shown to inhibit the Raf-MEK-ERK, NFκB, GRK and activate the GSK3β signaling pathways. Inhibition of Raf-MEK-ERK and NFκB remains the most prominent pathways implicated in the sensitization of cells to therapeutic drugs. Our purpose was to identify a possible link between RKIP-KEAP 1-NRF2 and drug resistance. To that end, RKIP-KEAP 1 association was tested in human colorectal cancer tissues using immunohistochemistry. RKIP miRNA silencing and its inducible overexpression were employed in HEK-293 immortalized cells, HT29 and HCT116 colon cancer cell lines to further investigate our aim. We show that RKIP enhanced Kelch-like ECH-associated protein1 (KEAP 1) stability in colorectal cancer tissues and HT29 CRC cell line. RKIP silencing in immortalized HEK-293 cells (termed HEK-499) correlated significantly with KEAP 1 protein degradation and subsequent NRF2 addiction in these cells. Moreover, RKIP depletion in HEK-499, compared to control cells, bestowed resistance to supra physiological levels of H2O2 and Cisplatin possibly by upregulating NF-E2-related nuclear factor 2 (NRF2) responsive genes. Similarly, we observed a direct correlation between the extent of apoptosis, after treatment with Adriamycin, and the expression levels of RKIP/KEAP 1 in HT29 but not in HCT116 CRC cells. Our data illuminate, for the first time, the NRF2-KEAP 1 pathway as a possible target for personalized therapeutic intervention in RKIP depleted cancers

Age-dependent alterations in the inflammatory response to pulmonary challenge

The aging lung is increasingly susceptible to infectious disease. Changes in pulmonary physiology and function are common in older populations, and in those older than 60 years, pneumonia is the major cause of infectious death. Understanding age-related changes in the innate and adaptive immune systems, and how they affect both pulmonary and systemic responses to pulmonary challenge are critical to the development of novel therapeutic strategies for the treatment of the elderly patient. In this observational study, we examined age-associated differences in inflammatory responses to pulmonary challenge with cell wall components from Gram-positive bacteria. Thus, male Sprague-Dawley rats, aged 6 months or greater than 18 months (approximating humans of 20 and 55-65 years), were challenged, intratracheally, with lipoteichoic acid and peptidoglycan. Cellular and cytokine evaluations were performed on both bronchoalveolar lavage fluid (BAL) and plasma, 24 h post-challenge. The plasma concentration of free thyroxine, a marker of severity in non-thyroidal illness, was also evaluated. The older animals had an increased chemotactic gradient in favor of the airspaces, which was associated with a greater accumulation of neutrophils and protein. Furthermore, macrophage migration inhibitory factor (MIF), an inflammatory mediator and putative biomarker in acute lung injury, was increased in both the plasma and BAL of the older, but not young animals. Conversely, plasma free thyroxine, a natural inhibitor of MIF, was decreased in the older animals. These findings identify age-associated inflammatory/metabolic changes following pulmonary challenge that it may be possible to manipulate to improve outcome in the older, critically ill patient

Evaluation of Poly-Mechanistic Antiangiogenic Combinations to Enhance Cytotoxic Therapy Response in Pancreatic Cancer

Gemcitabine (Gem) has limited clinical benefits in pancreatic ductal adenocarcinoma (PDAC). The present study investigated combinations of gemcitabine with antiangiogenic agents of various mechanisms for PDAC, including bevacizumab (Bev), sunitinib (Su) and EMAP II. Cell proliferation and protein expression were analyzed by WST-1 assay and Western blotting. In vivo experiments were performed via murine xenografts. Inhibition of in vitro proliferation of AsPC-1 PDAC cells by gemcitabine (10 µM), bevacizumab (1 mg/ml), sunitinib (10 µM) and EMAP (10 µM) was 35, 22, 81 and 6 percent; combination of gemcitabine with bevacizumab, sunitinib or EMAP had no additive effects. In endothelial HUVECs, gemcitabine, bevacizumab, sunitinib and EMAP caused 70, 41, 86 and 67 percent inhibition, while combination of gemcitabine with bevacizumab, sunitinib or EMAP had additive effects. In WI-38 fibroblasts, gemcitabine, bevacizumab, sunitinib and EMAP caused 79, 58, 80 and 29 percent inhibition, with additive effects in combination as well. Net in vivo tumor growth inhibition in gemcitabine, bevacizumab, sunitinib and EMAP monotherapy was 43, 38, 94 and 46 percent; dual combinations of Gem+Bev, Gem+Su and Gem+EMAP led to 69, 99 and 64 percent inhibition. Combinations of more than one antiangiogenic agent with gemcitabine were generally more effective but not superior to Gem+Su. Intratumoral proliferation, apoptosis and microvessel density findings correlated with tumor growth inhibition data. Median animal survival was increased by gemcitabine (26 days) but not by bevacizumab, sunitinib or EMAP monotherapy compared to controls (19 days). Gemcitabine combinations with bevacizumab, sunitinib or EMAP improved survival to similar extent (36 or 37 days). Combinations of gemcitabine with Bev+EMAP (43 days) or with Bev+Su+EMAP (46 days) led to the maximum survival benefit observed. Combination of antiangiogenic agents improves gemcitabine response, with sunitinib inducing the strongest effect. These findings demonstrate advantages of combining multi-targeting agents with standard gemcitabine therapy for PDAC