A rule-based model of insulin signalling pathway

BACKGROUND: The insulin signalling pathway (ISP) is an important biochemical pathway, which regulates some fundamental biological functions such as glucose and lipid metabolism, protein synthesis, cell proliferation, cell differentiation and apoptosis. In the last years, different mathematical models based on ordinary differential equations have been proposed in the literature to describe specific features of the ISP, thus providing a description of the behaviour of the system and its emerging properties. However, protein-protein interactions potentially generate a multiplicity of distinct chemical species, an issue referred to as “combinatorial complexity”, which results in defining a high number of state variables equal to the number of possible protein modifications. This often leads to complex, error prone and difficult to handle model definitions. RESULTS: In this work, we present a comprehensive model of the ISP, which integrates three models previously available in the literature by using the rule-based modelling (RBM) approach. RBM allows for a simple description of a number of signalling pathway characteristics, such as the phosphorylation of signalling proteins at multiple sites with different effects, the simultaneous interaction of many molecules of the signalling pathways with several binding partners, and the information about subcellular localization where reactions take place. Thanks to its modularity, it also allows an easy integration of different pathways. After RBM specification, we simulated the dynamic behaviour of the ISP model and validated it using experimental data. We the examined the predicted profiles of all the active species and clustered them in four clusters according to their dynamic behaviour. Finally, we used parametric sensitivity analysis to show the role of negative feedback loops in controlling the robustness of the system. CONCLUSIONS: The presented ISP model is a powerful tool for data simulation and can be used in combination with experimental approaches to guide the experimental design. The model is available at http://sysbiobig.dei.unipd.it/ was submitted to Biomodels Database (https://www.ebi.ac.uk/biomodels-main/# MODEL 1604100005). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0281-4) contains supplementary material, which is available to authorized users

TMS-evoked long-lasting artefacts: A new adaptive algorithm for EEG signal correction

OBJECTIVE: During EEG the discharge of TMS generates a long-lasting decay artefact (DA) that makes the analysis of TMS-evoked potentials (TEPs) difficult. Our aim was twofold: (1) to describe how the DA affects the recorded EEG and (2) to develop a new adaptive detrend algorithm (ADA) able to correct the DA. METHODS: We performed two experiments testing 50 healthy volunteers. In experiment 1, we tested the efficacy of ADA by comparing it with two commonly-used independent component analysis (ICA) algorithms. In experiment 2, we further investigated the efficiency of ADA and the impact of the DA evoked from TMS over frontal, motor and parietal areas. RESULTS: Our results demonstrated that (1) the DA affected the EEG signal in the spatiotemporal domain; (2) ADA was able to completely remove the DA without affecting the TEP waveforms; (3). ICA corrections produced significant changes in peak-to-peak TEP amplitude. CONCLUSIONS: ADA is a reliable solution for the DA correction, especially considering that (1) it does not affect physiological responses; (2) it is completely data-driven and (3) its effectiveness does not depend on the characteristics of the artefact and on the number of recording electrodes. SIGNIFICANCE: We proposed a new reliable algorithm of correction for long-lasting TMS-EEG artifacts

Significance analysis of microarray transcript levels in time series experiments

Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over time, a first necessary step is to select differentially expressed transcripts. A variety of methods have been proposed to this purpose; however, these methods are seldom applicable in practice since they require a large number of replicates, often available only for a limited number of samples. In this data-poor context, we evaluate the performance of three selection methods, using synthetic data, over a range of experimental conditions. Application to real data is also discussed. Results: Three methods are considered, to assess differentially expressed genes in data-poor conditions. Method 1 uses a threshold on individual samples based on a model of the experimental error. Method 2 calculates the area of the region bounded by the time series expression profiles, and considers the gene differentially expressed if the area exceeds a threshold based on a model of the experimental error. These two methods are compared to Method 3, recently proposed in the literature, which exploits splines fit to compare time series profiles. Application of the three methods to synthetic data indicates that Method 2 outperforms the other two both in Precision and Recall when short time series are analyzed, while Method 3 outperforms the other two for long time series. Conclusion: These results help to address the choice of the algorithm to be used in data-poor time series expression study, depending on the length of the time series

A quantization method based on threshold optimization for microarray short time series

BACKGROUND: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often very limited compared to the number of genes, thus the use of discrete data may help reducing the probability of finding random associations between genes. RESULTS: A quantization method, based on a model of the experimental error and on a significance level able to compromise between false positive and false negative classifications, is presented, which can be used as a preliminary step in discrete reverse engineering methods. The method is tested on continuous synthetic data with two discrete reverse engineering methods: Reveal and Dynamic Bayesian Networks. CONCLUSION: The quantization method, evaluated in comparison with two standard methods, 5% threshold based on experimental error and rank sorting, improves the ability of Reveal and Dynamic Bayesian Networks to identify relations among genes

An Optimized Data Structure for High Throughput 3D Proteomics Data: mzRTree

As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available in standard XML-based portable formats. The structures that are currently employed to manage these data can be highly inefficient, especially when dealing with high-throughput profile data. LC-MS datasets are usually accessed through 2D range queries. Optimizing this type of operation could dramatically reduce the complexity of data analysis. We propose a novel data structure for LC-MS datasets, called mzRTree, which embodies a scalable index based on the R-tree data structure. mzRTree can be efficiently created from the XML-based data formats and it is suitable for handling very large datasets. We experimentally show that, on all range queries, mzRTree outperforms other known structures used for LC-MS data, even on those queries these structures are optimized for. Besides, mzRTree is also more space efficient. As a result, mzRTree reduces data analysis computational costs for very large profile datasets.Comment: Paper details: 10 pages, 7 figures, 2 tables. To be published in Journal of Proteomics. Source code available at http://www.dei.unipd.it/mzrtre

Prediction of Postprandial Glycemic Exposure Utility of fasting and 2-h glucose measurements alone and in combination with assessment of body composition, fitness, and strength

OBJECTIVE —To determine the best predictors of total postprandial glycemic exposure and peak glucose concentrations in nondiabetic humans. RESEARCH DESIGN AND METHODS —Data from 203 nondiabetic volunteers who ingested a carbohydrate-containing mixed meal were analyzed. RESULTS —Fasting glucose and insulin concentrations were poor predictors of postprandial glucose area above basal ( R 2 = ∼0.07, P < 0.001). The correlation was stronger for 2-h glucose concentration ( R 2 = 0.55, P < 0.001) and improved slightly but significantly ( P < 0.001) with the addition of fasting glucose, insulin, age, sex, and body weight to the model ( r 2 = 0.58). The 2-h glucose concentration also predicted the peak glucose concentration ( R 2 = 0.37, P < 0.001) with strength of the prediction increasing ( P < 0.001) modestly with the addition of fasting glucose, insulin, age, sex, and body weight to the model ( R 2 = 0.48, P < 0.001). On the other hand, addition of measures of body function and composition did not improve prediction of total glycemic exposure or peak glucose concentration. CONCLUSIONS —Isolated measures of fasting or 2-h glucose concentrations alone or in combination with more complex measures of body composition and function are poor predictors of postprandial glycemic exposure or peak glucose concentration. This may explain, at least in part, the weak and at times inconsistent relationship between these parameters and cardiovascular risk

Surfactant disaturated-phosphatidylcholine kinetics in acute respiratory distress syndrome by stable isotopes and a two compartment model

BACKGROUND: In patients with acute respiratory distress syndrome (ARDS), it is well known that only part of the lungs is aerated and surfactant function is impaired, but the extent of lung damage and changes in surfactant turnover remain unclear. The objective of the study was to evaluate surfactant disaturated-phosphatidylcholine turnover in patients with ARDS using stable isotopes. METHODS: We studied 12 patients with ARDS and 7 subjects with normal lungs. After the tracheal instillation of a trace dose of (13)C-dipalmitoyl-phosphatidylcholine, we measured the (13)C enrichment over time of palmitate residues of disaturated-phosphatidylcholine isolated from tracheal aspirates. Data were interpreted using a model with two compartments, alveoli and lung tissue, and kinetic parameters were derived assuming that, in controls, alveolar macrophages may degrade between 5 and 50% of disaturated-phosphatidylcholine, the rest being lost from tissue. In ARDS we assumed that 5–100% of disaturated-phosphatidylcholine is degraded in the alveolar space, due to release of hydrolytic enzymes. Some of the kinetic parameters were uniquely determined, while others were identified as lower and upper bounds. RESULTS: In ARDS, the alveolar pool of disaturated-phosphatidylcholine was significantly lower than in controls (0.16 ± 0.04 vs. 1.31 ± 0.40 mg/kg, p < 0.05). Fluxes between tissue and alveoli and de novo synthesis of disaturated-phosphatidylcholine were also significantly lower, while mean resident time in lung tissue was significantly higher in ARDS than in controls. Recycling was 16.2 ± 3.5 in ARDS and 31.9 ± 7.3 in controls (p = 0.08). CONCLUSION: In ARDS the alveolar pool of surfactant is reduced and disaturated-phosphatidylcholine turnover is altered

Surfactant disaturated-phosphatidylcholine kinetics in acute respiratory distress syndrome by stable isotopes and a two compartment model

BACKGROUND: In patients with acute respiratory distress syndrome (ARDS), it is well known that only part of the lungs is aerated and surfactant function is impaired, but the extent of lung damage and changes in surfactant turnover remain unclear. The objective of the study was to evaluate surfactant disaturated-phosphatidylcholine turnover in patients with ARDS using stable isotopes. METHODS: We studied 12 patients with ARDS and 7 subjects with normal lungs. After the tracheal instillation of a trace dose of (13)C-dipalmitoyl-phosphatidylcholine, we measured the (13)C enrichment over time of palmitate residues of disaturated-phosphatidylcholine isolated from tracheal aspirates. Data were interpreted using a model with two compartments, alveoli and lung tissue, and kinetic parameters were derived assuming that, in controls, alveolar macrophages may degrade between 5 and 50% of disaturated-phosphatidylcholine, the rest being lost from tissue. In ARDS we assumed that 5–100% of disaturated-phosphatidylcholine is degraded in the alveolar space, due to release of hydrolytic enzymes. Some of the kinetic parameters were uniquely determined, while others were identified as lower and upper bounds. RESULTS: In ARDS, the alveolar pool of disaturated-phosphatidylcholine was significantly lower than in controls (0.16 ± 0.04 vs. 1.31 ± 0.40 mg/kg, p < 0.05). Fluxes between tissue and alveoli and de novo synthesis of disaturated-phosphatidylcholine were also significantly lower, while mean resident time in lung tissue was significantly higher in ARDS than in controls. Recycling was 16.2 ± 3.5 in ARDS and 31.9 ± 7.3 in controls (p = 0.08). CONCLUSION: In ARDS the alveolar pool of surfactant is reduced and disaturated-phosphatidylcholine turnover is altered

Decreased VLDL-Apo B 100 fractional synthesis rate despite hypertriglyceridemia in subjects with type 2 diabetes and nephropathy

Subjects with Type 2 Diabetes Mellitus (T2DM) and diabetic nephropathy (DN) often exhibit hypertriglyceridemia. The mechanism(s) of such an increase are poorly known. OBJECTIVE: We investigated VLDL-Apo B 100 kinetics in T2DM subjects with and without DN, and in healthy controls. DESIGN: Stable isotope 13C-leucine infusion, and modelling analysis of tracer-to-tracee ratio dynamics in the protein product pool in the 6-8 hr period following tracer infusion, were employed. SETTING: Male subjects affected by T2DM, either with (n=9) or without (n=5) DN, and healthy male controls (n=6), were studied under spontaneous glycemic levels in the post-absorptive state. RESULTS: In the T2DM patients with DN, plasma triglyceride (TG) (2.2\ub10.8 mmol/L, Mean\ub1SD) and VLDL-Apo B 100 (17.4\ub110.4 mg/dl) concentrations, and VLDL-Apo B 100 pool (0.56\ub10.29 g), were 3e60-80% greater (p<0.05 or less) than those of the T2DM subjects without DN (TG: 1.4\ub10.5 mmol/L; VLDL-Apo B 100: 9.9\ub12.5 mg/dl; VLDL-Apo B 100 pool: 0.36\ub10.09 g), and 3e80-110% greater (p<0.04 or less) than those of nondiabetic controls (TG: 1.2\ub10.4 mmol/L; VLDL-Apo B 100: 8.2\ub11.7 mg/dl; VLDL-Apo B 100: 0.32\ub10.09 g). In sharp contrast however, in the subjects with T2DM and DN, VLDL-Apo B 100 FSR was 6550% lower (4.8\ub12.2 pools/day) than that of either the T2DM subjects without DN (9.9\ub14.3 pools/day, p<0.025) or the control subjects (12.5\ub19.1 pools/day, p<0.04). CONCLUSIONS: The hypertriglyceridemia of T2DM patients with DN is not due to hepatic VLDL-Apo B 100 overproduction, which is decreased, but it should be attributed to decreased apolipoprotein removal

Ongoing β-Cell Turnover in Adult Nonhuman Primates Is Not Adaptively Increased in Streptozotocin-Induced Diabetes

OBJECTIVE: \u3b2-Cell turnover and its potential to permit \u3b2-cell regeneration in adult primates are unknown. Our aims were 1) to measure \u3b2-cell turnover in adult nonhuman primates; 2) to establish the relative contribution of \u3b2-cell replication and formation of new \u3b2-cells from other precursors (defined thus as \u3b2-cell neogenesis); and 3) to establish whether there is an adaptive increase in \u3b2-cell formation (attempted regeneration) in streptozotocin (STZ)-induced diabetes in adult nonhuman primates. RESEARCH DESIGN AND METHODS: Adult (aged 7 years) vervet monkeys were administered STZ (45-55 mg/kg, n = 7) or saline (n = 9). Pancreas was obtained from each animal twice, first by open surgical biopsy and then by euthanasia. \u3b2-Cell turnover was evaluated by applying a mathematic model to measured replication and apoptosis rates. RESULTS: \u3b2-Cell turnover is present in adult nonhuman primates (3.3 \ub1 0.9 mg/month), mostly (~80%) derived from \u3b2-cell neogenesis. \u3b2-Cell formation was minimal in STZ-induced diabetes. Despite marked hyperglycemia, \u3b2-cell apoptosis was not increased in monkeys administered STZ. CONCLUSIONS: There is ongoing \u3b2-cell turnover in adult nonhuman primates that cannot be accounted for by \u3b2-cell replication. There is no evidence of \u3b2-cell regeneration in monkeys administered STZ. Hyperglycemia does not induce \u3b2-cell apoptosis in nonhuman primates in vivo