Identification of novel components of NAD-utilizing metabolic pathways and prediction of their biochemical functions

Nicotinamide adenine dinucleotide (NAD) is a ubiquitous cofactor participating in numerous redox reactions. It is also a substrate for regulatory modifications of proteins and nucleic acids via the addition of ADP-ribose moieties or removal of acyl groups by transfer to ADP-ribose. In this study, we use in-depth sequence, structure and genomic context analysis to uncover new enzymes and substrate-binding proteins in NAD-utilizing metabolic and macromolecular modification systems. We predict that Escherichia coli YbiA and related families of domains from diverse bacteria, eukaryotes, large DNA viruses and single strand RNA viruses are previously unrecognized components of NAD-utilizing pathways that probably operate on ADP-ribose derivatives. Using contextual analysis we show that some of these proteins potentially act in RNA repair, where NAD is used to remove 2'-3' cyclic phosphodiester linkages. Likewise, we predict that another family of YbiA-related enzymes is likely to comprise a novel NAD-dependent ADP-ribosylation system for proteins, in conjunction with a previously unrecognized ADP-ribosyltransferase. A similar ADP-ribosyltransferase is also coupled with MACRO or ADP-ribosylglycohydrolase domain proteins in other related systems, suggesting that all these novel systems are likely to comprise pairs of ADP-ribosylation and ribosylglycohydrolase enzymes analogous to the DraG-DraT system, and a novel group of bacterial polymorphic toxins. We present evidence that some of these coupled ADP-ribosyltransferases/ribosylglycohydrolases are likely to regulate certain restriction modification enzymes in bacteria. The ADP-ribosyltransferases found in these, the bacterial polymorphic toxin and host-directed toxin systems of bacteria such as Waddlia also throw light on the evolution of this fold and the origin of eukaryotic polyADP-ribosyltransferases and NEURL4-like ARTs, which might be involved in centrosomal assembly. We also infer a novel biosynthetic pathway that might be involved in the synthesis of a nicotinate-derived compound in conjunction with an asparagine synthetase and AMPylating peptide ligase. We use the data derived from this analysis to understand the origin and early evolutionary trajectories of key NAD-utilizing enzymes and present targets for future biochemical investigations.

Metalloporphyrins as cytochrome P450 models for chlorhexidine metabolite prediction

The catalytic oxidation of chlorhexidine (CHX, a strong microbicidal agent) mediated by ironporphyrins has been investigated by using hydrogen peroxide, mCPBA, tBuOOH, or NaOCl as oxidant. All of these oxygen donors yielded p-chloroaniline (pCA) as the main product. The higher pCA yields amounted to 71% in the following conditions: catalyst/oxidant/substrate molar ratio of 1:150:50, aqueous medium, FeTMPyP as catalyst. The medium pH also had a strong effect on the pCA yields; in physiological pH, formation of this product was specially favored in the presence of the catalysts, with yields 58% higher than those achieved in control reactions. This provided strong evidence that CHX is metabolized to pCA upon ingestion. (c) 2012 Elsevier B.V. All rights reserved.

Estimating total body fat using a skinfold prediction equation in Brazilian children

Background: The double burden of obesity and underweight is increasing in developing countries and simple methods for the assessment of fat mass in children are needed. Aim: To develop and validate a new anthropometric predication equation for assessment of fat mass in children. Subjects and methods: Body composition was assessed in 145 children aged 9.8 +/- 1.3 (SD) years from Sao Paulo, Brazil using dual energy X-ray absorptiometry (DEXA) and skinfold measurements. The study sample was divided into development and validation sub-sets to develop a new prediction equation for FM (PE). Results: Using multiple linear regression analyses, the best equation for predicting FM (R-2 - 0.77) included body weight, triceps skinfold, height, gender and age as independent variables. When cross-validated, the new PE was valid in this sample (R-2 = 0.80), while previously published equations were not. Conclusion: The PE was more valid for Brazilian children that existing equations, but further studies are needed to assess the validity of this PE in other populations.

Ground-level ozone prediction using a neural network model based on meteorological variables and applied to the metropolitan area of Sao Paulo

A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was developed, based on average values of meteorological variables in the morning (8:00-12:00 hr) and afternoon (13:00-17: 00 hr) periods. Outputs are the maximum and average ozone concentrations in the afternoon (12:00-17:00 hr). The correlation coefficient between computed and measured values was 0.82 and 0.88 for the maximum and average ozone concentration, respectively. The model presented good performance as a prediction tool for the maximum ozone concentration. For prediction periods from 1 to 5 days 0 to 23% failures (95% confidence) were obtained.

New Equation for Prediction of Reverse Remodeling after Cardiac Resynchronization Therapy

Objectives: To integrate data from two-dimensional echocardiography (2D ECHO), three-dimensional echocardiography (3D ECHO), and tissue Doppler imaging (TDI) for prediction of left ventricular (LV) reverse remodeling (LVRR) after cardiac resynchronization therapy (CRT). It was also compared the evaluation of cardiac dyssynchrony by TDI and 3D ECHO. Methods: Twenty-four consecutive patients with heart failure, sinus rhythm, QRS = 120 msec, functional class III or IV and LV ejection fraction (LVEF) = 0.35 underwent CRT. 2D ECHO, 3D ECHO with systolic dyssynchrony index (SDI) analysis, and TDI were performed before, 3 and 6 months after CRT. Cardiac dyssynchrony analyses by TDI and SDI were compared with the Pearson's correlation test. Before CRT, a univariate analysis of baseline characteristics was performed for the construction of a logistic regression model to identify the best predictors of LVRR. Results: After 3 months of CRT, there was a moderate correlation between TDI and SDI (r = 0.52). At other time points, there was no strong correlation. Nine of twenty-four (38%) patients presented with LVRR 6 months after CRT. After logistic regression analysis, SDI (SDI > 11%) was the only independent factor in the prediction of LVRR 6 months of CRT (sensitivity = 0.89 and specificity = 0.73). After construction of receiver operator characteristic (ROC) curves, an equation was established to predict LVRR: LVRR =-0.4LVDD (mm) + 0.5LVEF (%) + 1.1SDI (%), with responders presenting values >0 (sensitivity = 0.67 and specificity = 0.87). Conclusions: In this study, there was no strong correlation between TDI and SDI. An equation is proposed for the prediction of LVRR after CRT. Although larger trials are needed to validate these findings, this equation may be useful to candidates for CRT. (Echocardiography 2012;29:678-687)

An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

Prediction and probability of neonatal outcome in isolated congenital diaphragmatic hernia using multiple ultrasound parameters

Objectives To evaluate the accuracy and probabilities of different fetal ultrasound parameters to predict neonatal outcome in isolated congenital diaphragmatic hernia (CDH). Methods Between January 2004 and December 2010, we evaluated prospectively 108 fetuses with isolated CDH (82 left-sided and 26 right-sided). The following parameters were evaluated: gestational age at diagnosis, side of the diaphragmatic defect, presence of polyhydramnios, presence of liver herniated into the fetal thorax (liver-up), lung-to-head ratio (LHR) and observed/expected LHR (o/e-LHR), observed/expected contralateral and total fetal lung volume (o/e-ContFLV and o/e-TotFLV) ratios, ultrasonographic fetal lung volume/fetal weight ratio (US-FLW), observed/expected contralateral and main pulmonary artery diameter (o/e-ContPA and o/eMPA) ratios and the contralateral vascularization index (Cont-VI). The outcomes were neonatal death and severe postnatal pulmonary arterial hypertension (PAH). Results Neonatal mortality was 64.8% (70/108). Severe PAH was diagnosed in 68 (63.0%) cases, of which 63 died neonatally (92.6%) (P < 0.001). Gestational age at diagnosis, side of the defect and polyhydramnios were not associated with poor outcome (P > 0.05). LHR, o/eLHR, liver-up, o/e-ContFLV, o/e-TotFLV, US-FLW, o/eContPA, o/e-MPA and Cont-VI were associated with both neonatal death and severe postnatal PAH (P < 0.001). Receiver-operating characteristics curves indicated that measuring total lung volumes (o/e-TotFLV and US-FLW) was more accurate than was considering only the contralateral lung sizes (LHR, o/e-LHR and o/e-ContFLV; P < 0.05), and Cont-VI was the most accurate ultrasound parameter to predict neonatal death and severe PAH (P < 0.001). Conclusions Evaluating total lung volumes is more accurate than is measuring only the contralateral lung size. Evaluating pulmonary vascularization (Cont-VI) is the most accurate predictor of neonatal outcome. Estimating the probability of survival and severe PAH allows classification of cases according to prognosis. Copyright (C) 2011 ISUOG. Published by John Wiley & Sons, Ltd.

Prediction of enzymatic infarct size in ST-segment elevation myocardial infarction

Objectives Predictors of adverse outcomes following myocardial infarction (MI) are well established; however, little is known about what predicts enzymatically estimated infarct size in patients with acute ST-elevation MI. The Complement And Reduction of INfarct size after Angioplasty or Lytics trials of pexelizumab used creatine kinase (CK)-MB area under the curve to determine infarct size in patients treated with primary percutaneous coronary intervention (PCI) or fibrinolysis. Methods Prediction of infarct size was carried out by measuring CK-MB area under the curve in patients with ST-segment elevation MI treated with reperfusion therapy from January 2000 to April 2002. Infarct size was calculated in 1622 patients (PCI=817; fibrinolysis=805). Logistic regression was used to examine the relationship between baseline demographics, total ST-segment elevation, index angiographic findings (PCI group), and binary outcome of CK-MB area under the curve greater than 3000 ng/ml. Results Large infarcts occurred in 63% (515) of the PCI group and 69% (554) of the fibrinolysis group. Independent predictors of large infarcts differed depending on mode of reperfusion. In PCI, male sex, no prior coronary revascularization and diabetes, decreased systolic blood pressure, sum of ST-segment elevation, total (angiographic) occlusion, and nonright coronary artery culprit artery were independent predictors of larger infarcts (C index=0.73). In fibrinolysis, younger age, decreased heart rate, white race, no history of arrhythmia, increased time to fibrinolytic therapy in patients treated up to 2 h after symptom onset, and sum of ST-segment elevation were independently associated with a larger infarct size (C index=0.68). Conclusion Clinical and patient data can be used to predict larger infarcts on the basis of CK-MB quantification. These models may be helpful in designing future trials and in guiding the use of novel pharmacotherapies aimed at limiting infarct size in clinical practice. Coron Artery Dis 23:118-125 (C) 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.

A fragment-based approach for the in silico prediction of blood-brain barrier permeation

Blood-brain barrier (BBB) permeation is an essential property for drugs that act in the central nervous system (CNS) for the treatment of human diseases, such as epilepsy, depression, Alzheimer's disease, Parkinson disease, schizophrenia, among others. In the present work, quantitative structure-property relationship (QSPR) studies were conducted for the development and validation of in silico models for the prediction of BBB permeation. The data set used has substantial chemical diversity and a relatively wide distribution of property values. The generated QSPR models showed good statistical parameters and were successfully employed for the prediction of a test set containing 48 compounds. The predictive models presented herein are useful in the identification, selection and design of new drug candidates having improved pharmacokinetic properties.

Prediction of the temperature distribution of partially submersed umbilical cables

The objective of this work is to predict the temperature distribution of partially submersed umbilical cables under different operating and environmental conditions. The commercial code Fluent® was used to simulate the heat transfer and the air fluid flow of part of a vertical umbilical cable near the air-water interface. A free-convective three-dimensional turbulent flow in open-ended vertical annuli was solved. The influence of parameters such as the heat dissipating rate, wind velocity, air temperature and solar radiation was analyzed. The influence of the presence of a radiation shield consisting of a partially submersed cylindrical steel tube was also considered. The air flow and the buoyancydriven convective heat transfer in the annular region between the steel tube and the umbilical cable were calculated using the standard k-ε turbulence model. The radiative heat transfer between the umbilical external surface and the radiation shield was calculated using the Discrete Ordinates model. The results indicate that the influence of a hot environment and intense solar radiation may affect the umbilical cable performance in its dry portion.

Link prediction using a probabilistic description logic

Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.

Prediction of sediments toxicity using consensus-based sediment quality guidelines and benthic foraminifera in the Ria de Aveiro(Portugal)

Ria de Aveiro is a large and shallow lagoon on the west coast of Portugal (40º38’N, 8º45´W), characterized by a complex geometry. It includes large areas of intertidal flats and a network of narrow channels which are connected to the Atlantic by an artificial inlet. Tides are the main forcing of the hydrology and physical processes of the lagoon. The deeper areas near the inlet are characterized by strong marine influence through tidal inflow, with high values of current velocity (>1m/s) and tidal range (2–3 m at spring tides), while in remote shallow areas, the circulation and the sea water inflow are reduced. These remote areas are more influenced by fresh waters received from several rivers and several small streams. The Aveiro lagoon is a very important ecosystem but as been used as recipient for various kinds of anthropogenic wastes resulting from the high population density, urban activities and industrial development. One of the most important Portuguese industrial centre is located in the lagoon margins. Ria de Aveiro is a coastal lagoon under huge direct antropization. This system also suffers strong diffuse antropization. This work is related with diffuse antropization linked with chemical pollution which may lead to biological stress and collapse.