FieldML

FieldML is an open format for storing and exchanging models containing field information. It is able to represent a wide variety of field value types, including scalar, vector, tensor, logical, and strings. Fields are defined over domains explicitly in terms of functions. Domains may be nested to form embedding hierarchies

Plasma osteoprotegerin is related to carotid and peripheral arterial disease, but not to myocardial ischemia in type 2 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Cardiovascular disease (CVD) is frequent in type 2 diabetes mellitus patients due to accelerated atherosclerosis. Plasma osteoprotegerin (OPG) has evolved as a biomarker for CVD. We examined the relationship between plasma OPG levels and different CVD manifestations in type 2 diabetes.</p> <p>Methods</p> <p>Type 2 diabetes patients without known CVD referred consecutively to a diabetes clinic for the first time (n = 305, aged: 58.6 ± 11.3 years, diabetes duration: 4.5 ± 5.3 years) were screened for carotid arterial disease, peripheral arterial disease, and myocardial ischemia by means of carotid artery ultrasonography, peripheral ankle and toe systolic blood pressure measurements, and myocardial perfusion scintigraphy (MPS). In addition, plasma OPG concentrations and other CVD-related markers were measured.</p> <p>Results</p> <p>The prevalence of carotid arterial disease, peripheral arterial disease, and myocardial ischemia was 42%, 15%, and 30%, respectively. Plasma OPG was significantly increased in patients with carotid and peripheral arterial disease compared to patients without (p < 0.001, respectively), however, this was not the case for patients with myocardial ischemia versus those without (p = 0.71). When adjusted for age, HbA1c and U-albumin creatinine ratio in a multivariate logistic regression analysis, plasma OPG remained strongly associated with carotid arterial disease (adjusted OR: 2.12; 95% CI: 1.22-3.67; p = 0.008), but not with peripheral arterial disease or myocardial ischemia.</p> <p>Conclusions</p> <p>Increased plasma OPG concentration is associated with carotid and peripheral arterial disease in patients with type 2 diabetes, whereas no relation is observed with respect to myocardial ischemia on MPS. The reason for this discrepancy is unknown.</p> <p>Trial registration number</p> <p>at <url>http://www.clinicaltrial.gov</url>: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00298844">NCT00298844</a></p

Revision history aware repositories of computational models of biological systems

<p>Abstract</p> <p>Background</p> <p>Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model.</p> <p>One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file.</p> <p>The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems.</p> <p>Results</p> <p>We have extended the Physiome Model Repository software to be fully revision history aware, by building it on top of Mercurial, an existing DVCS. We have demonstrated the utility of this approach, when used in conjunction with the model composition facilities in CellML, to build and understand more complex models. We have also demonstrated the ability of the repository software to present version history to casual users over the web, and to highlight specific versions which are likely to be useful to users.</p> <p>Conclusions</p> <p>Providing facilities for maintaining and using revision history information is an important part of building a useful repository of computational models, as this information is useful both for understanding the source of and justification for parts of a model, and to facilitate automated processes such as merges. The availability of fully revision history aware repositories, and associated tools, will therefore be of significant benefit to the community.</p

Comparison of Short-Term Estrogenicity Tests for Identification of Hormone-Disrupting Chemicals

The aim of this study was to compare results obtained by eight different short-term assays of estrogenlike actions of chemicals conducted in 10 different laboratories in five countries. Twenty chemicals were selected to represent direct-acting estrogens, compounds with estrogenic metabolites, estrogenic antagonists, and a known cytotoxic agent. Also included in the test panel were 17β-estradiol as a positive control and ethanol as solvent control. The test compounds were coded before distribution. Test methods included direct binding to the estrogen receptor (ER), proliferation of MCF-7 cells, transient reporter gene expression in MCF-7 cells, reporter gene expression in yeast strains stably transfected with the human ER and an estrogen-responsive reporter gene, and vitellogenin production in juvenile rainbow trout. 17β-Estradiol, 17α-ethynyl estradiol, and diethylstilbestrol induced a strong estrogenic response in all test systems. Colchicine caused cytotoxicity only. Bisphenol A induced an estrogenic response in all assays. The results obtained for the remaining test compounds—tamoxifen, ICI 182.780, testosterone, bisphenol A dimethacrylate, 4-n-octylphenol, 4-n-nonylphenol, nonylphenol dodecylethoxylate, butylbenzylphthalate, dibutylphthalate, methoxychlor, o,p′-DDT, p,p′-DDE, endosulfan, chlomequat chloride, and ethanol—varied among the assays. The results demonstrate that careful standardization is necessary to obtain a reasonable degree of reproducibility. Also, similar methods vary in their sensitivity to estrogenic compounds. Thus, short-term tests are useful for screening purposes, but the methods must be further validated by additional interlaboratory and interassay comparisons to document the reliability of the methods

A Bayesian Search for Transcriptional Motifs

Identifying transcription factor (TF) binding sites (TFBSs) is an important step towards understanding transcriptional regulation. A common approach is to use gaplessly aligned, experimentally supported TFBSs for a particular TF, and algorithmically search for more occurrences of the same TFBSs. The largest publicly available databases of TF binding specificities contain models which are represented as position weight matrices (PWM). There are other methods using more sophisticated representations, but these have more limited databases, or aren't publicly available. Therefore, this paper focuses on methods that search using one PWM per TF. An algorithm, MATCHTM, for identifying TFBSs corresponding to a particular PWM is available, but is not based on a rigorous statistical model of TF binding, making it difficult to interpret or adjust the parameters and output of the algorithm. Furthermore, there is no public description of the algorithm sufficient to exactly reproduce it. Another algorithm, MAST, computes a p-value for the presence of a TFBS using true probabilities of finding each base at each offset from that position. We developed a statistical model, BaSeTraM, for the binding of TFs to TFBSs, taking into account random variation in the base present at each position within a TFBS. Treating the counts in the matrices and the sequences of sites as random variables, we combine this TFBS composition model with a background model to obtain a Bayesian classifier. We implemented our classifier in a package (SBaSeTraM). We tested SBaSeTraM against a MATCHTM implementation by searching all probes used in an experimental Saccharomyces cerevisiae TF binding dataset, and comparing our predictions to the data. We found no statistically significant differences in sensitivity between the algorithms (at fixed selectivity), indicating that SBaSeTraM's performance is at least comparable to the leading currently available algorithm. Our software is freely available at: http://wiki.github.com/A1kmm/sbasetram/building-the-tools

Computational Modelling of Cardiac Trabecula Mechanics

Cardiac trabeculae are thin strips of muscle within the ventricles that can be readily excised and used to investigate contractile mechanics of cardiac muscle. Recently, the Auckland Bioengineering Institute has developed a novel cardiac myometer that simultaneously measures force, length and shape of actively contracting isolated cardiac trabeculae. Here we have developed a muscle-specific computational model based on optical coherence tomography geometric surface data that replicates passive mechanics of trabecula. We hypothesised that the muscle's surface geometry data, in addition to force-length data, would improve the fit between the model simulated mechanics and the experimental data. The trabecula model was optimised using two different objective functions (muscle length or shape) driven by a pressure boundary condition. For both objective functions, there was a region of optimal parameters the optimiser tended towards but, due to the coupling between parameters, the ability to find the true optimal parameters was hindered. Due to the limitations of the data, we found that the addition of surface data did not improve parameter estimation and that using only the force-length data provided sufficient information to produce an optimal fit. References A. Anderson. The Cardiac Myometer: Measuring Matters of the Heart. PhD thesis, University of Auckland, 2016. K. F. Augenstein, Brett R. Cowan, Ian J. LeGrice, Poul M. F. Nielsen, and Alistair A. Young. Method and apparatus for soft tissue material parameter estimation using tissue tagged Magnetic Resonance Imaging. Journal of Biomechanical Engineering, 127(1):148&ndash;157, February 2005. C. Bradley, Andy Bowery, Randall Britten, Vincent Budelmann, Oscar Camara, Richard Christie, Andrew Cookson, Alejandro F. Frangi, Thiranja Babarenda Gamage, Thomas Heidlauf, Sebastian Krittian, David Ladd, Caton Little, Kumar Mithraratne, Martyn Nash, David Nickerson, Poul Nielsen, Oyvind Nordbo, Stig Omholt, Ali Pashaei, David Paterson, Vijayaraghavan Rajagopal, Adam Reeve, Oliver Rohrle, Soroush Safaei, Rafael Sebastian, Martin Steghofer, Tim Wu, Ting Yu, Heye Zhang, and Peter Hunter. OpenCMISS: A multi-physics and multi-scale computational infrastructure for the VPH/Physiome project. Progress in Biophysics and Molecular Biology, 107(1):32&ndash;47, October 2011. doi:http://dx.doi.org/10.1016/j.pbiomolbio.2011.06.015 M. L. Cheuk, A. J. Anderson, J. C. Han, N. Lippok, F. Vanholsbeeck, B. P. Ruddy, D. S. Loiselle, P. M. F. Nielsen, and A. J. Taberner. Four-Dimensional Imaging of Cardiac Trabeculae Contracting In Vitro Using Gated OCT. IEEE Transactions on Biomedical Engineering, 64(1):218&ndash;224, January 2017. doi:http://dx.doi.org/10.1109/TBME.2016.2553154 M. L. Cheuk, N. Lippok, A. W. Dixon, B. P. Ruddy, F. Vanholsbeeck, P. M. F. Nielsen, and A. J. Taberner. Optical coherence tomography imaging of cardiac trabeculae. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pages 182&ndash;185, August 2014. doi:http://dx.doi.org/10.1109/EMBC.2014.6943559 J. M Guccione, Andrew D McCulloch, and LK Waldman. Passive material properties of intact ventricular myocardium determined from a cylindrical model. J Biomech Eng, 113(1):42&ndash;55, 1991. J. C. Han, Andrew J. Taberner, Robert S. Kirton, Poul M. Nielsen, Nicholas P. Smith, and Denis S. Loiselle. A unique micromechanocalorimeter for simultaneous measurement of heat rate and force production of cardiac trabeculae carneae. Journal of Applied Physiology, 107(3):946&ndash;951, September 2009. doi:http://dx.doi.org/10.1152/japplphysiol.00549.2009 M. P. Nash and P. J. Hunter. Regional mechanics of the beating heart. In Cardiac Perfusion and Pumping Engineering, volume Volume 1 of Clinically-Oriented Biomedical Engineering, pages 83&ndash;127. WORLD SCIENTIFIC, July 2007. doi:http://dx.doi.org/10.1142/9789812775597_0004 J. H. Omens, D. A. MacKenna, and A. D. McCulloch. Measurement of strain and analysis of stress in resting rat left ventricular myocardium. Journal of Biomechanics, 26(6):665&ndash;676, June 1993. doi:http://dx.doi.org/10.1016/0021-9290(93)90030-I V. Y. Wang, H. I. Lam, Daniel B. Ennis, Brett R. Cowan, Alistair A. Young, and Martyn P. Nash. Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function. Medical Image Analysis, 13(5):773&ndash;784, October 2009. doi:http://dx.doi.org/10.1016/j.media.2009.07.00

Comparison of shor-term estrogenicity tests for identification of hormone-disrupting chemicals

The aim of this study was to compare results obtained by eight different short-term assays of estrogenlike actions of chemicals conducted in 10 different laboratories in five countries. Twenty chemicals were selected to represent direct-acting estrogens, compounds with estrogenic metabolites, estrogenic antagonists, and a known cytotoxic agent. Also included in the test panel were 17β-estradiol as a positive control and ethanol as solvent control. The test compounds were coded before distribution. Test methods included direct binding to the estrogen receptor (ER), proliferation of MCF-7 cells, transient reporter gene expression in MCF-7 cells, reporter gene expression in yeast strains stably transfected with the human ER and an estrogen-responsive reporter gene, and vitellogenin production in juvenile rainbow trout. 17β-Estradiol, 17α-ethynyl estradiol, and diethylstilbestrol induced a strong estrogenic response in all test systems. Colchicine caused cytotoxicity only. Bisphenol A induced an estrogenic response in all assays. The results obtained for the remaining test compounds—tamoxifen, ICI 182.780, testosterone, bisphenol A dimethacrylate, 4-n-octylphenol, 4-n-nonylphenol, nonylphenol dodecylethoxylate, butylbenzylphthalate, dibutylphthalate, methoxychlor, o,p′-DDT, p,p′-DDE, endosulfan, chlomequat chloride, and ethanol—varied among the assays. The results demonstrate that careful standardization is necessary to obtain a reasonable degree of reproducibility. Also, similar methods vary in their sensitivity to estrogenic compounds. Thus, short-term tests are useful for screening purposes, but the methods must be further validated by additional interlaboratory and interassay comparisons to document the reliability of the methods.This study was supported by grants from the European Commission (Biomedicine and Health Research and Technological Programme, BMH4-CT96-03 14), the Danish Environmental Research Programme (96.01.015.16), and the Danish Medical Research Council (9401656)