Inhomogeneous distribution of flux pinning strength and its effecton irreversibility line and vortex glass-liquid transition line in Bi-2212 tapes

The irreversibility line and the vortex glass-liquid transition line under a magnetic field parallel to the c-axis are investigated for silver-sheathed and dip-coated Bi-2212 tape wires. It is found that the two characteristic lines for silver-sheathed tape is well explained by the flux creep-flow model assuming the distribution of pinning strength with a single peak. On the other hand, general agreements are obtained for these characteristic lines and the critical current density between experiments and theory only when two peaks are assumed in the distribution of flux pinning strength for the dip-coated tape. The causative structure in the dip-coated tape for the peak at small strength in the distribution is discusse

Hybrid dynamic/static method for large-scale simulation of metabolism

BACKGROUND: Many computer studies have employed either dynamic simulation or metabolic flux analysis (MFA) to predict the behaviour of biochemical pathways. Dynamic simulation determines the time evolution of pathway properties in response to environmental changes, whereas MFA provides only a snapshot of pathway properties within a particular set of environmental conditions. However, owing to the large amount of kinetic data required for dynamic simulation, MFA, which requires less information, has been used to manipulate large-scale pathways to determine metabolic outcomes. RESULTS: Here we describe a simulation method based on cooperation between kinetics-based dynamic models and MFA-based static models. This hybrid method enables quasi-dynamic simulations of large-scale metabolic pathways, while drastically reducing the number of kinetics assays needed for dynamic simulations. The dynamic behaviour of metabolic pathways predicted by our method is almost identical to that determined by dynamic kinetic simulation. CONCLUSION: The discrepancies between the dynamic and the hybrid models were sufficiently small to prove that an MFA-based static module is capable of performing dynamic simulations as accurately as kinetic models. Our hybrid method reduces the number of biochemical experiments required for dynamic models of large-scale metabolic pathways by replacing suitable enzyme reactions with a static module

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles

BACKGROUND: In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. RESULTS: The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. CONCLUSION: The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles

A microarray data-based semi-kinetic method for predicting quantitative dynamics of genetic networks

BACKGROUND: Elucidating the dynamic behaviour of genetic regulatory networks is one of the most significant challenges in systems biology. However, conventional quantitative predictions have been limited to small networks because publicly available transcriptome data has not been extensively applied to dynamic simulation. RESULTS: We present a microarray data-based semi-kinetic (MASK) method which facilitates the prediction of regulatory dynamics of genetic networks composed of recurrently appearing network motifs with reasonable accuracy. The MASK method allows the determination of model parameters representing the contribution of regulators to transcription rate from time-series microarray data. Using a virtual regulatory network and a Saccharomyces cerevisiae ribosomal protein gene module, we confirmed that a MASK model can predict expression profiles for various conditions as accurately as a conventional kinetic model. CONCLUSION: We have demonstrated the MASK method for the construction of dynamic simulation models of genetic networks from time-series microarray data, initial mRNA copy number and first-order degradation constants of mRNA. The quantitative accuracy of the MASK models has been confirmed, and the results indicated that this method enables the prediction of quantitative dynamics in genetic networks composed of commonly used network motifs, which cover considerable fraction of the whole network

Distinguishing enzymes using metabolome data for the hybrid dynamic/static method

BACKGROUND: In the process of constructing a dynamic model of a metabolic pathway, a large number of parameters such as kinetic constants and initial metabolite concentrations are required. However, in many cases, experimental determination of these parameters is time-consuming. Therefore, for large-scale modelling, it is essential to develop a method that requires few experimental parameters. The hybrid dynamic/static (HDS) method is a combination of the conventional kinetic representation and metabolic flux analysis (MFA). Since no kinetic information is required in the static module, which consists of MFA, the HDS method may dramatically reduce the number of required parameters. However, no adequate method for developing a hybrid model from experimental data has been proposed. RESULTS: In this study, we develop a method for constructing hybrid models based on metabolome data. The method discriminates enzymes into static modules and dynamic modules using metabolite concentration time series data. Enzyme reaction rate time series were estimated from the metabolite concentration time series data and used to distinguish enzymes optimally for the dynamic and static modules. The method was applied to build hybrid models of two microbial central-carbon metabolism systems using simulation results from their dynamic models. CONCLUSION: A protocol to build a hybrid model using metabolome data and a minimal number of kinetic parameters has been developed. The proposed method was successfully applied to the strictly regulated central-carbon metabolism system, demonstrating the practical use of the HDS method, which is designed for computer modelling of metabolic systems

Multiple sites in the N-terminal half of simian immunodeficiency virus capsid protein contribute to evasion from rhesus monkey TRIM5α-mediated restriction

<p>Abstract</p> <p>Background</p> <p>We previously reported that cynomolgus monkey (CM) TRIM5α could restrict human immunodeficiency virus type 2 (HIV-2) strains carrying a proline at the 120^thposition of the capsid protein (CA), but it failed to restrict those with a glutamine or an alanine. In contrast, rhesus monkey (Rh) TRIM5α could restrict all HIV-2 strains tested but not simian immunodeficiency virus isolated from macaque (SIVmac), despite its genetic similarity to HIV-2.</p> <p>Results</p> <p>We attempted to identify the viral determinant of SIVmac evasion from Rh TRIM5α-mediated restriction using chimeric viruses formed between SIVmac239 and HIV-2 GH123 strains. Consistent with a previous study, chimeric viruses carrying the loop between α-helices 4 and 5 (L4/5) (from the 82^ndto 99^thamino acid residues) of HIV-2 CA were efficiently restricted by Rh TRIM5α. However, the corresponding loop of SIVmac239 CA alone (from the 81^stto 97^thamino acid residues) was not sufficient to evade Rh TRIM5α restriction in the HIV-2 background. A single glutamine-to-proline substitution at the 118^thamino acid of SIVmac239 CA, corresponding to the 120^thamino acid of HIV-2 GH123, also increased susceptibility to Rh TRIM5α, indicating that glutamine at the 118^thof SIVmac239 CA is necessary to evade Rh TRIM5α. In addition, the N-terminal portion (from the 5^thto 12^thamino acid residues) and the 107^thand 109^thamino acid residues in α-helix 6 of SIVmac CA are necessary for complete evasion from Rh TRIM5α-mediated restriction. A three-dimensional model of hexameric GH123 CA showed that these multiple regions are located on the CA surface, suggesting their direct interaction with TRIM5α.</p> <p>Conclusion</p> <p>We found that multiple regions of the SIVmac CA are necessary for complete evasion from Rh TRIM5α restriction.</p

Bone Marrow Allograft Rejection Mediated by a Novel Murine NK Receptor, NKG2I

Natural killer (NK) cells mediate bone marrow allograft rejection. However, the molecular mechanisms underlying such a rejection remain elusive. In previous analyses, it has been shown that NK cells recognize allogeneic target cells through Ly-49s and CD94/NKG2 heterodimers. Here, we describe identification and characterization of a novel murine NK receptor, NKG2I, belonging to the NKG2 family. NKG2I, which was composed of 226 amino acids, showed ∼40% homology to the murine NKG2D and CD94 in the C-type lectin domain. Flow cytometric analysis with anti-NKG2I monoclonal antibody (mAb) revealed that expression of NKG2I was largely confined to NK and NKT cells, but was not seen in T cells. Furthermore, anti-NKG2I mAb inhibited NK cell–mediated cytotoxicity, whereas cross-linking of NKG2I enhanced interleukin 2– and interleukin 12–dependent interferon-γ production. Similarly, the injection of anti-NKG2I mAb before the allogeneic bone marrow transfer in vivo impinged on the function of NKG2I, resulting in the enhanced colony formation in the spleen. NKG2I is a novel activating receptor mediating recognition and rejection of allogeneic target cells