PubMed · 14114698
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H M TEPPERMAN, J TEPPERMAN. ADAPTIVE HYPERLIPOGENESIS.. https://pubmed.ncbi.nlm.nih.gov/14114698/
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Flux blance analysis (FBA) has been shown to be a very effective tool to interpret and predict the metabolism of various microorganisms when the set of available measurements is not sufficient to determine the fluxes within the cell. In this methodology, an underdetermined stoichiometric model is solved using a linear programming (LP) approach. The predictions of FBA models can be improved if noisy measurements are checked for consistency, and these in turn are used to estimate model parameters. In this work, a formal methodology for data reconciliation and parameter estimation with underdetermined stoichiometric models is developed and assessed. The procedure is formulated as a nonlinear optimization problem, where the LP is transformed into a set of nonlinear constraints. However, some of these constraints violate standard regularity conditions, making the direct numerical solution very difficult. Hence, a barrier formulation is used to represent these constraints, and an iterative procedure is defined that allows solving the problem to the desired degree of convergence. This methodology is assessed using a stoichiometric yeast model. The procedure is used for data reconciliation where more reliable estimations of noisy measurements are computed. On the other hand, assuming unknown biomass composition, the procedure is applied for simultaneous data reconciliation and biomass composition estimation. In both cases it is verified that the f measurements required to get unbiased and reliable estimations is reduced if the LP approach is included as additional constraints in the optimization.
Chloroacetic acids (monochloroacetic acid [MCA], dichloroacetic acid [DCA], and trichloroacetic acid [TCA]) and trihalomethanes (THMs: chloroform [CHCl(3)], bromodichloromethane [BDCM], dibromochloromethane [DBCM], and bromoform [TBM]) are common by-products of the chlorination of drinking water. The purpose of this study was to evaluate the influence of chloroacetic acids on the pharmacokinetics of trihalomethanes in the male Sprague-Dawley rat. In the first series of studies, groups of 5 animals were given, by intravenous injections, a single dose of 0.125 mmol/kg of one of the four THMs. Additional groups received a binary mixture containing 0.125 mmol/kg of a THM plus 0.125 mmol/kg of a chloroacetic acid. The venous blood concentrations of unchanged THMs were measured by headspace gas chromatography from 5 min to 6 h postadministration. The areas under the blood concentration versus time curves (AUCs) of CHCl(3), BDCM, and DBCM were increased by a factor of 3.5, 1.6, and 2, respectively, by coadministration of TCA. DCA coadministration resulted in an increase in the AUC of DBCM (x2.5) and TBM (x1.3), whereas MCA modified the Cmax (x1.5) and AUC (x1.8) of BDCM and the AUC of DBCM (x2.5). In the second series of experiments, animals received either a single dose of 0.03125 mmol/kg of one of the four THMs, a mixture containing 0.03125 mmol/kg of each of the four THMs (total dose = 0.125 mmol/kg), or a mixture containing 0.03125 mmol/kg of each of the four THMs plus 0.125 mmol/kg of either TCA or DCA. Results indicated that the AUCs of CHCl(3), BDCM, DBCM, and TBM were increased during coadministration compared to single administrations (+2.5-fold). Combined administration of the four THMs with TCA, and not DCA, resulted in an increase of the AUCs of THMs (CHCl(3): x11.7; BDCM, DBCM, and TBM: x3.9) and an increase in the Cmax of CHCl(3) (x1.9). Overall, these results indicate that, at the dose levels tested in this study, TCA alters the blood concentration profiles of THMs.
Transport of lactate, pyruvate and the ketone bodies acetoacetate and beta-hydroxybutyrate, is mediated in most mammalian cells by members of the monocarboxylate transporter family (SLC16). A conserved signature sequence has been identified in this family, which is located in the loop between helix 4 and helix 5 and extends into helix 5. We have mutated residues in this signature sequence in the rat monocarboxylate transporter (MCT1) to elucidate the significance of this region for monocarboxylate transport. Mutation of R143 and G153 resulted in complete inactivation of the transporter. For the MCT1(G153V) mutant this was explained by a failure to reach the plasma membrane. The lack of transport activity of MCT1(R143Q) could be partially rescued by the conservative exchange R143H. The resulting mutant transporter displayed reduced stability, a decreased V (max) of lactate transport but not of acetate transport, and an increased stereoselectivity. Mutation of K137, K141 and K142 indicated that only K142 played a significant role in the transport mechanism. Mutation of K142 to glutamine resulted in an increase of the K (m) for lactate from 5 mM to 12 mM. In contrast with MCT1(R143H), MCT1(K142Q) was less stereoselective than the wild-type. A mechanism is proposed that includes all critical residues.