Thermodynamically consistent model calibration in chemical kinetics

<p>Abstract</p> <p>Background</p> <p>The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function.</p> <p>Results</p> <p>We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an <it>open </it>biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from <url>http://www.cis.jhu.edu/~goutsias/CSS lab/software.html</url>. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database.</p> <p>Conclusions</p> <p>TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting.</p

METHODS FOR COMPUTATION AND ANALYSIS OF MARKOVIAN DYNAMICS ON COMPLEX NETWORKS

A problem central to many scientific and engineering disciplines is how to deal with noisy dynamic processes that take place on networks. Examples include the ebb and flow of biochemical concentrations within cells, the firing patterns of neurons in the brain, and the spread of disease on social networks. In this thesis, we present a general formalism capable of representing many such problems by means of a master equation. Our study begins by synthesizing the literature to provide a toolkit of known mathematical and computational analysis techniques for dealing with this equation. Subsequently a novel exact numerical solution technique is developed, which can be orders of magnitude faster than the state-of-the-art numerical solver. However, numerical solutions are only applicable to a small subset of processes on networks. Thus, many approximate solution techniques exist in the literature to deal with this problem. Unfortunately, no practical tools exist to quantitatively evaluate the quality of an approximate solution in a given system. Therefore, a statistical tool that is capable of evaluating any analytical or Monte Carlo based approximation to the master equation is developed herein. Finally, we note that larger networks with more complex dynamical phenomena suffer from the same curse of dimensionality as the classical mechanics of a gas. We therefore propose that thermodynamic analysis techniques, adapted from statistical mechanics, may provide a new way forward in analyzing such systems. The investigation focuses on a behavior known as avalanching—complex bursting patterns with fractal properties. By developing thermodynamic analysis techniques along with a potential energy landscape perspective, we are able to demonstrate that increasing intrinsic noise causes a phase transition that results in avalanching. This novel result is utilized to characterize avalanching in an epidemiological model for the first time and to explain avalanching in biological neural networks, in which the cause has been falsely attributed to specific neural architectures. This thesis contributes to the existing literature by providing a novel solution technique, enhances existing and future literature by providing a general method for statistical evaluation of approximative solution techniques, and paves the way towards a promising approach to the thermodynamic analysis of large complex processes on networks

1-(1-Carboxy­methyl-1,4-anhydro-2,3-O-isopropyl­idene-α-d-erythrofuranos­yl)thymine

X-Ray crystallography unequivocally determined the stereochemistry of the thymine base in the title compound, C14H18N2O7. The absolute stereochemistry was determined from the use of d-ribose as the starting material. There are two independent mol­ecules in the asymmetric unit (Z′ = 2) which exist as N—H⋯O hydrogen-bonded pairs in the crystal structure

The impact of body mass index on disease progression in ankylosing spondylitis

Publisher Copyright: © 2018 De Gruyter Open Ltd. All rights reserved.Obesity can be a factor that affects the course of chronic systemic inflammatory arthritis. The objective of this study was to characterise patients with ankylosing spondylitis (AS) according to an evaluation of their body mass index (BMI) and by exploring the link between the overweightness and obesity with routinely measured disease-specific variables, including disease activity (Bath Ankylosing Spondylitis Disease Activity Index BASDAI; Ankylosing Spondylitis Disease Activity Score, using CRP, ASDAScrp), spinal mobility (Bath Ankylosing Spondylitis Metrology Index, BASMI), functional capacity (BASFI), extraspinal manifestations like fatigue, uveitis, and peripheral arthritis present during the course of the disease. A total of 107 patients were included in the cross-sectional study fulfilling the modified New York criteria for AS. Patients were divided into three groups: with the evaluation of BMI 30.0 (obesity). The mean BMI was 25.13 (SD 4.07). 33% of patients were overweight and 15% were obese. The mean values of age, duration of AS, ASDAScrp, BASDAI, Bath Ankylosing Spondylitis Functional Index (BASFI), BASMI, pain in spine, and fatigue in the group with BMI < 24.9 were lower than in the other groups (p < 0.05). There was no difference between groups in age of AS onset, uveitis and peripheral arthritis. AS patients who were overweight or obese had a higher level of the disease activity, pain, fatigue, functional disability and spinal mobility impairment with worse values in the case of obesity.publishersversionPeer reviewe

Cardiovascular training improves fitness in patients with ankylosing spondylitis

Objective: Several studies suggest that patients with ankylosing spondylitis (AS) have an increased risk of cardiovascular disease. This study aimed to evaluate the effects of a 12-week individually heart rate-monitored, moderately intensive cardiovascular training on cardiovascular fitness and perceived disease activity in AS patients. Methods: Patients diagnosed with AS according to modified New York criteria were to either 'cardiovascular training' or 'attention control'. The training group performed three cardiovascular trainings per week. All participants attended one weekly usual care flexibility training. Attention control contained regular discussion groups on coping strategies. Adherence was self-monitored. Assessments were performed at baseline and after the intervention period of 3 months. Physical fitness was the primary endpoint, measured in watts using a submaximal bicycle test following the PWC75% protocol. All analyses controlled for gender, age, body mass index, baseline fitness and physical activity levels, and BASDAI. Results: Of 106 AS patients enrolled, 40% were women, mean age was 49 (SD +/-12) years. 76.5% of the training group reported exercising at least three times a week. At 3 month follow-up, fitness level in the training group was significantly higher than in the control group (90.32 (SD 4.52) vs.109.84 (SD 4.72) respectively, p=0.001), independent of other covariates. Average BASDAI total score was 0.31 points lower (p = 0.31) in the training group, reaching significance for the 'peripheral pain' subscore (1.19; p=0.01), but not for 'back pain' or 'fatigue'. Conclusions: Cardiovascular training, in addition to flexibility exercise, increased fitness in AS patients and reduced their peripheral pain

SeekFusion - A Clinically Validated Fusion Transcript Detection Pipeline for PCR-Based Next-Generation Sequencing of RNA

Detecting gene fusions involving driver oncogenes is pivotal in clinical diagnosis and treatment of cancer patients. Recent developments in next-generation sequencing (NGS) technologies have enabled improved assays for bioinformatics-based gene fusions detection. In clinical applications, where a small number of fusions are clinically actionable, targeted polymerase chain reaction (PCR)-based NGS chemistries, such as the QIAseq RNAscan assay, aim to improve accuracy compared to standard RNA sequencing. Existing informatics methods for gene fusion detection in NGS-based RNA sequencing assays traditionally use a transcriptome-based spliced alignment approach or a de-novo assembly approach. Transcriptome-based spliced alignment methods face challenges with short read mapping yielding low quality alignments. De-novo assembly-based methods yield longer contigs from short reads that can be more sensitive for genomic rearrangements, but face performance and scalability challenges. Consequently, there exists a need for a method to efficiently and accurately detect fusions in targeted PCR-based NGS chemistries. We describe SeekFusion, a highly accurate and computationally efficient pipeline enabling identification of gene fusions from PCR-based NGS chemistries. Utilizing biological samples processed with the QIAseq RNAscan assay and in-silico simulated data we demonstrate that SeekFusion gene fusion detection accuracy outperforms popular existing methods such as STAR-Fusion, TOPHAT-Fusion and JAFFA-hybrid. We also present results from 4,484 patient samples tested for neurological tumors and sarcoma, encompassing details on some novel fusions identified

Numerical Integration of the Master Equation in Some Models of Stochastic Epidemiology

The processes by which disease spreads in a population of individuals are inherently stochastic. The master equation has proven to be a useful tool for modeling such processes. Unfortunately, solving the master equation analytically is possible only in limited cases (e.g., when the model is linear), and thus numerical procedures or approximation methods must be employed. Available approximation methods, such as the system size expansion method of van Kampen, may fail to provide reliable solutions, whereas current numerical approaches can induce appreciable computational cost. In this paper, we propose a new numerical technique for solving the master equation. Our method is based on a more informative stochastic process than the population process commonly used in the literature. By exploiting the structure of the master equation governing this process, we develop a novel technique for calculating the exact solution of the master equation – up to a desired precision – in certain models of stochastic epidemiology. We demonstrate the potential of our method by solving the master equation associated with the stochastic SIR epidemic model. MATLAB software that implements the methods discussed in this paper is freely available as Supporting Information S1

Safety and Clinical Responses in Ankylosing Spondylitis after Three Months of Etanercept Therapy

We aimed to evaluate the safety and clinical responses in Korean ankylosing spondylitis (AS) patients after three months of etanercept therapy. AS patients satisfying the Modified New York Criteria were enrolled. They were assessed for safety and clinical responses at enrollment and after three months of etanercept therapy. A total of 124 patients completed the study. After three months, the rate of ASsessment in AS International Working Group 20% improvement (ASAS 20) response was 79.8%. The rates of ASAS 40 and ASAS 5/6 responses were 58.5 and 62.8%, respectively. Significant improvement of Korean version of Bath AS Disease Activity Index (KBASDAI) (p<0.0001), Bath AS Functional Activity Index (BASFI) (p<0.0001), and Bath AS Metrology Index (BASMI) (p=0.0009) were achieved after three months. Quality of life was also significantly improved after three months, as demonstrated by scores for SF-36 (p<0.0001) and EQ-5D (p<0.0001). Erythrocyte sedimentation rate and C-reactive protein were significantly decreased (p<0.0001, p<0.0001, respectively). None of the patients developed tuberculosis and there were no serious adverse event. AS patients with inadequate response to conventional therapy showed significant clinical improvement without serious adverse events after three months of etanercept therapy