Molecular interactions of STAC proteins with skeletal muscle dihydropyridine receptor and excitation‐contraction coupling

Excitation‐contraction coupling (ECC) is the physiological process in which an electrical signal originating from the central nervous system is converted into muscle contraction. In skeletal muscle tissue, the key step in the molecular mechanism of ECC initiated by the muscle action potential is the cooperation between two Ca²⁺ channels, dihydropyridine receptor (DHPR; voltage‐dependent L‐type calcium channel) and ryanodine receptor 1 (RyR1). These two channels were originally postulated to communicate with each other via direct mechanical interactions; however, the molecular details of this cooperation have remained ambiguous. Recently, it has been proposed that one or more supporting proteins are in fact required for communication of DHPR with RyR1 during the ECC process. One such protein that is increasingly believed to play a role in this interaction is the SH3 and cysteine‐rich domain‐containing protein 3 (STAC3), which has been proposed to bind a cytosolic portion of the DHPR α_1S subunit known as the II–III loop. In this work, we present direct evidence for an interaction between a small peptide sequence of the II–III loop and several residues within the SH3 domains of STAC3 as well as the neuronal isoform STAC2. Differences in this interaction between STAC3 and STAC2 suggest that STAC3 possesses distinct biophysical features that are potentially important for its physiological interactions with the II–III loop. Therefore, this work demonstrates an isoform‐specific interaction between STAC3 and the II–III loop of DHPR and provides novel insights into a putative molecular mechanism behind this association in the skeletal muscle ECC process.     

The elementary mass action rate constants of P-gp transport for a confluent monolayer of MDCKII-hMDR1 cells

The human multi-drug resistance membrane transporter, P-glycoprotein, or P-gp, has been extensively studied due to its importance to human health and disease. Thus far, the kinetic analysis of P-gp transport has been limited to steady-state Michaelis-Menten approaches or to compartmental models, neither of which can prove molecular mechanisms. Determination of the elementary kinetic rate constants of transport will be essential to understanding how P-gp works. The experimental system we use is a confluent monolayer of MDCKII-hMDR1 cells that overexpress P-gp. It is a physiologically relevant model system, and transport is measured without biochemical manipulations of P-gp. The Michaelis-Menten mass action reaction is used to model P-gp transport. Without imposing the steady-state assumptions, this reaction depends upon several parameters that must be simultaneously fitted. An exhaustive fitting of transport data to find all possible parameter vectors that best fit the data was accomplished with a reasonable computation time using a hierarchical algorithm. For three P-gp substrates (amprenavir, loperamide, and quinidine), we have successfully fitted the elementary rate constants, i.e., drug association to P-gp from the apical membrane inner monolayer, drug dissociation back into the apical membrane inner monolayer, and drug efflux from P-gp into the apical chamber, as well as the density of efflux active P-gp. All three drugs had overlapping ranges for the efflux active P-gp, which was a benchmark for the validity of the fitting process. One novel finding was that the association to P-gp appears to be rate-limited solely by drug lateral diffusion within the inner monolayer of the plasma membrane for all three drugs. This would be expected if P-gp structure were open to the lipids of the apical membrane inner monolayer, as has been suggested by recent structural studies. The fitted kinetic parameters show how P-gp efflux of a wide range of xenobiotics has been maximized.     

Biaxial elastic material properties of porcine coronary media and adventitia

The importance of mechanical stresses and strains has become well recognized in vascular physiology and pathology. To compute the stress and strain on the various components of the vessel wall, we must know the constitutive equations for the different layers of the vessel wall. The objective of the present study is to determine the constitutive equation of the coronary artery treated as a two-layer composite: intima-media and adventitial layers. Twelve hearts were obtained from a local slaughterhouse, and the right coronary artery and left anterior descending artery were dissected free from the myocardium. The vessel wall was initially mechanically tested biaxially (inflation and axial extension) as a whole (intact wall) and subsequently as intima-media or adventitial layer. A Fung-type exponential strain energy function was used to curve fit the experimental data for the intact wall and individual layers for the right coronary artery and left anterior descending artery. Two methods were used for the determination of material constants, including the Marquardt-Levenberg nonlinear least squares method and the genetic algorithm method. Our results show that there were no statistically significant differences in the material constants obtained from the two methods and that either set of elastic constants results in good fit of the data. Furthermore, at an in vivo value of axial stretch ratio, we find that the stiffness is as follows: intima-media > intact > adventitia. These results underscore the composite nature of coronary arteries with different material properties in each layer. The present results are necessary for analysis of coronary artery mechanics and to provide a fundamental understanding of vessel physiology.     

An architecture for biological information extraction and representation

Motivations: Technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. There is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data. RESULTS: In this paper, we present a general architecture, called ALFA, for information extraction and representation from diverse biological data. The ALFA architecture consists of: (i) a networked, hierarchical, hyper-graph object model for representing information from heterogeneous data sources in a standardized, structured format; and (ii) a suite of integrated, interactive software tools for information extraction and representation from diverse biological data sources. As part of our research efforts to explore this space, we have currently prototyped the ALFA object model and a set of interactive software tools for searching, filtering, and extracting information from scientific text. In particular, we describe BioFerret, a meta-search tool for searching and filtering relevant information from the web, and ALFA Text Viewer, an interactive tool for user-guided extraction, disambiguation, and representation of information from scientific text. We further demonstrate the potential of our tools in integrating the extracted information with experimental data and diagrammatic biological models via the common underlying ALFA representation. CONTACT: aditya_vailaya@agilent.com.     

Assessment of NIR spectroscopy for nondestructive analysis of physical and chemical attributes of sulfamethazine bolus dosage forms

The goal of this study was to assess the utility of near infrared (NIR) spectroscopy for the determination of content uniformity, tablet crushing strength (tablet hardness), and dissolution rate in sulfamethazine veterinary bolus dosage forms. A formulation containing sulfamethazine, corn starch, and magnesium stearate was employed. The formulations were wet granulated with a 10% (wt/vol) starch paste in a high shear granulator and dried at 60°C in a convection tray dryer. The tablets were compressed on a Stokes B2 rotary tablet press running at 30 rpm. Each sample was scanned in reflectance mode in the wavelengths of the NIR region. Principal component analysis (PCA) of the NIR tablet spectra and the neat raw materials indicated that the scores of the first 2 principal components were highly correlated with the chemical and physical attributes. Based on the PCA model, the significant wavelengths for sulfamethazine are 1514, (1660–1694), 2000, 2050, 2150, 2175, 2225, and 2275 nm; for corn starch are 1974, 2100, and 2325 nm; and for magnesium stearate are 2325 and 2375 nm. In addition, the loadings show large negative peaks around the water band regions (≈1420 and 1940 nm), indicating that the partial least squares (PLS) models could be affected by product water content. A simple linear regression model was able to predict content uniformity with a correlation coefficient of 0.986 at 1656 nm; the use of a PLS regression model, with 3 factors, had anr ² of 0.9496 and a sandard error of calibration of 0.0316. The PLS validation set had anr ² of 0.9662 and a standard error of 0.0354. PLS calibration models, based on tablet absorbance data, could successfully predict tablet crushing strength and dissolution in spite of varying active pharmaceutical ingredient (API) levels. Prediction plots based on these PLS models yielded correlation coefficients of 0.84 and 0.92 on independent validation sets for crushing strength and Q₁₂₀ (percentage dissolved in 120 minutes), respectively. Published: September 20, 2005 The opinions expressed in this paper are of the authors' personal views. They do not necessarily reflect the views or policies of the FDA.     

Quantifying crystal form content in physical mixtures of (±)-tartaric acid and (+)-tartaric acid using near infrared reflectance spectroscopy

The objective of this study was to use diffuse reflectance near infrared spectroscopy (NIRS) to determine racemic compound content in physical mixtures composed primarily of the enantiomorph and to assess the error, instrument reproducibility and limits of detection (LOD) and quantification (LOQ) of the method. Physical mixtures ranging from 0 to 25% (±)-tartaric acid in (+)-tartaric acid were prepared and spectra of the powder samples contained in glass vials were obtained using a Foss NIRSystems Model 5000 monochrometer equipped with a Rapid Content Analyzer scanning from 1100 to 2500 nm. A calibration curve was constructed by plotting (±)-tartaric acid weight percent against the 2^nd derivative values of log (1/R) vs λ at a single wavelength, normalized with a denominator wavelength (1480 nm/1280 nm). Excellent linearity was observed (R²=0.9999). The standard error of calibration (SEC) was 0.07 and the standard error of prediction (SEP) for the validation set was 0.11. Instrument and method errors for samples in the 2% composition range ((±)-tartaric acid in (+)-tartaric acid) were less than 1% RSD and 3% RSD, respectively. The practical LOD and LOQ were 0.1% and 0.5%, respectively, and comparable to the calculated LOD and LOQ. These studies show that NIRS can be used as a rapid and sensitive quantitative method for determining racemate content in the presence of the enatiomerically pure crystal in the solid-state. Published: October 6, 2005