Strange Baryon Production in Heavy Ion Collisions

The rapidity distribution of $\Lambda$ and $\bar{\Lambda}$ produced in nucleus-nucleus collisions at CERN energies is studied in the framework of an independent string model - with quark-antiquark as well as diquark-antidiquark pairs in the nucleon sea. It is shown that, besides the $\Lambda$-$\bar{\Lambda}$ pair production resulting from the fragmentation of sea diquarks, final state interactions of co-moving secondaries $\pi + N \to K + \Lambda$ and $\pi + \bar{N} \to K + \bar{\Lambda}$ are needed in order to reproduce the data. Predictions for $Pb$-$Pb$ collisions are presented.Comment: Plain TeX + epsf, 40 pages; 1 Postscript-table and 7 Postscript figures (uuencoded

A generalization of the Wiener rational basis functions on infinite intervals: Part I-derivation and properties

We formulate and derive a generalization of an orthogonal rational-function basis for spectral expansions over the infinite or semi-infinite interval. The original functions, first presented by Wiener, are a mapping and weighting of the Fourier basis to the infinite interval. By identifying the Fourier series as a biorthogonal composition of Jacobi polynomials/functions, we are able to define generalized Fourier series which, when appropriately mapped to the whole real line and weighted, generalize Wiener's basis functions. It is known that the original Wiener rational functions inherit sparse Galerkin matrices for differentiation, and can utilize the fast Fourier transform (FFT) for computation of the expansion coefficients. We show that the generalized basis sets also have a sparse differentiation matrix and we discuss connection problems, which are necessary theoretical developments for application of the FFT

Point Mutations in the 90-kDa Heat Shock Protein Binding Region of the Glucocorticoid Receptor Affect the Functional Characteristics of the Receptor a

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72162/1/j.1749-6632.1995.tb31403.x.pd

Influence of Material Parameter Variability on the Predicted Coronary Artery Biomechanical Environment via Uncertainty Quantification

Central to the clinical adoption of patient-specific modeling strategies is demonstrating that simulation results are reliable and safe. Simulation frameworks must be robust to uncertainty in model input(s), and levels of confidence should accompany results. In this study we applied a coupled uncertainty quantification-finite element (FE) framework to understand the impact of uncertainty in vascular material properties on variability in predicted stresses. Univariate probability distributions were fit to material parameters derived from layer-specific mechanical behavior testing of human coronary tissue. Parameters were assumed to be probabilistically independent, allowing for efficient parameter ensemble sampling. In an idealized coronary artery geometry, a forward FE model for each parameter ensemble was created to predict tissue stresses under physiologic loading. An emulator was constructed within the UncertainSCI software using polynomial chaos techniques, and statistics and sensitivities were directly computed. Results demonstrated that material parameter uncertainty propagates to variability in predicted stresses across the vessel wall, with the largest dispersions in stress within the adventitial layer. Variability in stress was most sensitive to uncertainties in the anisotropic component of the strain energy function. Unary and binary interactions within the adventitial layer were the main contributors to stress variance, and the leading factor in stress variability was uncertainty in the stress-like material parameter summarizing contribution of the embedded fibers to the overall artery stiffness. Results from a patient-specific coronary model confirmed many of these findings. Collectively, this highlights the impact of material property variation on predicted artery stresses and presents a pipeline to explore and characterize uncertainty in computational biomechanics.Comment: To appear: Biomechanics and Modeling in Mechanobiolog

Key Residues Defining the Μ-Opioid Receptor Binding Pocket: A Site-Directed Mutagenesis Study

Structural elements of the rat Μ-opioid receptor important in ligand receptor binding and selectivity were examined using a site-directed mutagenesis approach. Five single amino acid mutations were made, three that altered conserved residues in the Μ, Δ, and Κ receptors (Asn 150 to Ala, His 297 to Ala, and Tyr 326 to Phe) and two designed to test for Μ/Δ selectivity (Ile 198 to Val and Val 202 to Ile). Mutation of His 297 in transmembrane domain 6 (TM6) resulted in no detectable binding with [ 3 H]DAMGO ( 3 H-labeled d-Ala 2 , N -Me-Phe 4 ,Gly-ol 5 -enkephalin), [ 3 H]bremazocine, or [ 3 H]ethylketocyclazocine. Mutation of Asn 150 in TM3 produces a three- to 20-fold increase in affinity for the opioid agonists morphine, DAMGO, fentanyl, Β-endorphin 1–31 , JOM-13, deltorphin II, dynorphin 1–13 , and U50,488, with no change in the binding of antagonists such as naloxone, naltrexone, naltrindole, and nor-binaltorphamine. In contrast, the Tyr 326 mutation in TM7 resulted in a decreased affinity for a wide spectrum of Μ, Δ, and Κ agonists and antagonists. Altering Val 202 to Ile in TM4 produced no change on ligand affinity, but Ile 198 to Val resulted in a four- to fivefold decreased affinity for the Μ agonists morphine and DAMGO, with no change in the binding affinities of Κ and Δ ligands.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65474/1/j.1471-4159.1997.68010344.x.pd

Evaluation of Affymetrix Gene Chip sensitivity in rat hippocampal tissue using SAGE analysis *

DNA microarrays are a powerful tool for monitoring thousands of transcript levels simultaneously. However, the use of DNA microarrays in studying the central nervous system faces several challenges. These include the detection of low-abundance transcripts in highly complex tissue as well as estimating relatively low-magnitude changes in transcript levels in response to experimental manipulation. Many transcripts important to brain function have low expression levels or are expressed in relatively few cells, making them difficult to detect in the complex background of brain tissue. The aim of the present study is to evaluate the sensitivity of Gene Chip detection of transcripts in brain by using results from serial analysis of gene expression (SAGE) studies. The results of this comparison indicate that Affymetrix Gene Chips, like SAGE, only reliably detect medium- to high-abundance transcripts and that detection of low-abundance transcripts, many of which have great relevance to biological function in brain, is inconsistent. Specifically, we estimate that Gene Chips reliably detect no more than 30% of the hippocampal transcriptome when using a gross hippocampal dissection as the source tissue. This report provides the first broad evaluation of Affymetrix Gene Chip sensitivity relevant to studying the brain.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75717/1/j.1460-9568.2002.02097.x.pd

The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line

Molecular basis for dynorphin A selectivity: A chimeric study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31194/1/0000096.pd

Cloning of potential candidates for guinea pig opioid receptors

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31190/1/0000092.pd