Inhibition of L-type amino acid transport with non-physiological amino acids in the Pahenu2 mouse model of phenylketonuria

Phenylketonuria, an autosomal recessive Mendelian disorder, is one of the most common inborn errors of metabolism. Although currently treated by diet, many suboptimal outcomes occur for patients. Neuropathological outcomes include cognitive loss, white matter abnormalities, and hypo- or demyelination, resulting from high concentrations and/or fluctuating levels of phenylalanine. High phenylalanine can also result in competitive exclusion of other large neutral amino acids from the brain, including tyrosine and tryptophan (essential precursors of dopamine and serotonin). This competition occurs at the blood brain barrier, where the L-type amino acid transporter, LAT1, selectively facilitates entry of large neutral amino acids. The hypothesis of these studies is that certain non-physiological amino acids (NPAA; DL-norleucine (NL), 2-aminonorbornane (NB; 2-aminobicyclo-(2,1,1)-heptane-2-carboxylic acid), α-aminoisobutyrate (AIB), and α-methyl-aminoisobutyrate (MAIB)) would competitively inhibit LAT1 transport of phenylalanine (Phe) at the blood-brain barrier interface. To test this hypothesis, Pah-/- mice (n=5, mixed gender; Pah+/-(n=5) as controls) were fed either 5% NL, 0.5% NB, 5% AIB or 3% MAIB (w/w 18% protein mouse chow) for 3 weeks. Outcome measurements included food intake, body weight, brain LNAAs, and brain monoamines measured via LCMS/MS or HPLC. Brain Phe values at sacrifice were significantly reduced for NL, NB, and MAIB, verifying the hypothesis that these NPAAs could inhibit Phe trafficking into the brain. However, concomitant reductions in tyrosine and methionine occurred at the concentrations employed. Blood Phe levels were not altered indicating no effect of NPAA competitors in the gut. Brain NL and NB levels, measured with HPLC, verified both uptake and transport of NPAAs. Although believed predominantly unmetabolized, NL feeding significantly increased blood urea nitrogen. Pah-/-disturbances of monoamine metabolism were exacerbated by NPAA intervention, primarily with NB (the prototypical LAT inhibitor). To achieve the overarching goal of using NPAAs to stabilize Phe transport levels into the brain, a specific Phe-reducing combination and concentration of NPAAs must be found. Our studies represent the first in vivo use of NL, NB and MAIB in Pah-/- mice, and provide proof-of-principle for further characterization of these LAT inhibitors. Our data is the first to document an effect of MAIB, a specific system A transport inhibitor, on large neutral amino acid transport.

STUDY OF A DIRECT SAMPLING METHOD FOR THE INVERSE MEDIUM SCATTERING PROBLEM

Direct sampling methods are increasingly being used to solve the inverse medium scattering problem to estimate the shape of the scattering object. A simple direct method using one incident wave and multiple measurements was proposed by Ito, Jin and Zou. In this report, we performed some analytic and numerical studies of the direct sampling method. The method was found to be effective in general. However, there are a few exceptions exposed in the investigation. Analytic solutions in different situations were studied to verify the viability of the method while numerical tests were used to validate the effectiveness of the method.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.