Good Learning and Implicit Model Enumeration

MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a toolneutral,computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation

Mechanism of lipoxygenase inactivation by the linoleic acid analogue octadeca-9,12-diynoic acid

During the irreversible inactivation of soybean Fe(III)-lipoxygenase [Fe(III)-LOX] by octadeca-9,12-diynoic acid (ODYA), significant quantities of 11-oxooctadeca-9,12-diynoic acid (11-oxo-ODYA) are formed [Nieuwenhuizen, W. F., et al. (1995) Biochemistry 34, 10538-10545]. To elucidate the inactivation mechanism, a quantitative study into the relationship between the inactivation and 11-oxo-ODYA formation was carried out. The following observations were made. (1) LOX (0.84 mu M) was completely inactivated by 10 to 80 mu M ODYA. However, at ODYA concentrations greater than mu 100 M, LOX was only partially inactivated, and there was no inactivation at all at ODYA concentrations above 750 mu M. The average number of turnovers in which 11-oxo-ODYA was formed increased from 1.2 to 12 when the ODYA concentration increased from 1 to 50 mu M and then decreased again to 1.2 at 1000 mu M ODYA. (2) The enzyme that was not irreversibly inactivated by ODYA was in the Fe(III) form at ODYA concentrations below 10 mu M but in the Fe(II) form at ODYA concentrations greater than 100 mu M. (3) In the presence of 750 mu M ODYA and 25 mu M 13(S)-hydroperoxy-9Z,11E-octadecadienoic acid, all of the enzyme was inactivated. On the basis of these results, it is proposed that the dioxygenation product of ODYA is 11-hydroperoxyoctadeca-9,12-diynoic acid (11-HP-ODYA), which can convert Fe(II)-LOX into its Fe(III) form. However, 11-HP-ODYA is converted into 11-oxo-ODYA, which cannot perform the oxidation. It is proposed that the inactivating agent is either 11-HP-ODYA or the 11-peroxy-octadeca-9,12-diynoic acid radical (11-peroxy-ODYA radical), formed from the ODYA radical and O2. The oxidation of Fe(II)-LOX into its Fe(III) form as well as the inactivation of Fe(III)-LOX is competitively inhibited by ODYA

Effect of Nonionic Detergents on Lipoxygenase Catalysis

“The original publication is available at www.springerlink.com”. Copyright Springer. DOI: 10.1007/BF02536325 [Full text of this article is not available in the UHRA]In many studies on lipoxygenase catalysis, nonionic detergents are used to obtain an optically transparent solution of the fatty acid substrate. In order to resolve some controversies that exist with regard to the interpretation of kinetic data obtained with solutions containing nonionic detergents, a systematic investigation was undertaken into the effects of Lubrol, Tween-20 and Triton X-100 (0–0.8 g/L) on the kinetics of linoleate (2.5–110 μM) dioxygenation, catalyzed by lipoxygenase-1 or lipoxygenase-2 from soybean, at pH 9 or 10, at 25°C. Under most conditions, it was found that the detergents slowed down the reaction. However, at high linoleate concentrations, where substrate inhibition of lipoxygenase is significant, small amounts of detergent increased the dioxygenation rate. In a quantitative analysis of the results, a kinetic model in which the incorporation of linoleate in the detergent micelles is formulated as a simple reversible equilibrium, and in which both lipoxygenase-1 and-2 interact with free linoleate, but not with linoleate incorporated in the micelles, appeared to be sufficient to predict experimental results over a wide range of experimental conditions. According to this model, the changes in the dioxygenation kinetics caused by the presence of nonionic detergents are similar (but not equal) to those caused by competitive inhibitors. The conclusions that monomeric, nonmicellar linoleate is the preferred substrate for lipoxygenase and that the observed inhibition and stimulation are solely due to changes in the effective linoleate concentration strongly corroborate the earlier observations by Galpin and Allen [Biochim. Biophys. Acta 488 (1977), 392–401].Peer reviewe

A prospective cohort study on radiation-induced hypothyroidism: development of an NTCP model

Purpose: To establish a multivariate normal tissue complication probability (NTCP) model for radiation-induced hypothyroidism. Methods and Materials: The thyroid-stimulating hormone (TSH) level of 105 patients treated with (chemo-) radiation therapy for head-and-neck cancer was prospectively measured during a median follow-up of 2.5 years. Hypothyroidism was defined as elevated serum TSH with decreased or normal free thyroxin (T4). A multivariate logistic regression model with bootstrapping was used to determine the most important prognostic variables for radiation-induced hypothyroidism. Results: Thirty-five patients (33%) developed primary hypothyroidism within 2 years after radiation therapy. An NTCP model based on 2 variables, including the mean thyroid gland dose and the thyroid gland volume, was most predictive for radiation-induced hypothyroidism. NTCP values increased with higher mean thyroid gland dose (odds ratio [OR]: 1.064/Gy) and decreased with higher thyroid gland volume (OR: 0.826/cm(3)). Model performance was good with an area under the curve (AUC) of 0.85. Conclusions: This is the first prospective study resulting in an NTCP model for radiation-induced hypothyroidism. The probability of hypothyroidism rises with increasing dose to the thyroid gland, whereas it reduces with increasing thyroid gland volume. (C) 2012 Elsevier Inc