A simple and rapid method for identifying and semi-quantifying peptide hormones in isolated pancreatic islets by direct-tissue matrix-assisted laser desorption ionization time-of-flight mass spectrometry

We describe a new, simple, robust and efficient method based on direct‐tissue matrix‐assisted laser desorption ionization time‐of‐flight (MALDI‐TOF) mass spectrometry that enables consistent semi‐quantitation of peptide hormones in isolated pancreatic islets from normal and diabetic rodents. Prominent signals were measured that corresponded to all the main peptide hormones present in islet‐endocrine cells: (α‐cells) glucagon, glicentin‐related polypeptide/GRPP; (β‐cells) insulin I, insulin II, C‐peptide I, C‐peptide II, amylin; (δ‐cells) somatostatin‐14; and (PP‐cells), and pancreatic polypeptide. The signal ratios coincided with known relative hormone abundances. The method demonstrated that severe insulin deficiency is accompanied by elevated levels of all non‐β‐cell‐hormones in diabetic rat islets, consistent with alleviation of paracrine suppression of hormone production by non‐β‐cells. It was also effective in characterizing hormonal phenotype in hemizygous human‐amylin transgenic mice that express human and mouse amylin in approx. equimolar quantities. Finally, the method demonstrated utility in basic peptide‐hormone discovery by identifying a prominent new Gcg‐gene‐derived peptide (theoretical monoisotopic molecular weight 3263.5 Da), closely related to but distinct from GRPP, in diabetic islets. This peptide, whose sequence is HAPQDTEENARSFPASQTEPLEDPNQINE in Rattus norvegicus, could be a peptide hormone whose roles in physiology and metabolic disease warrant further investigation. This method provides a powerful new approach that could provide important new insights into the physiology and regulation of peptide hormones in islets and other endocrine tissues. It has potentially wide‐ranging applications that encompass endocrinology, pharmacology, phenotypic analysis in genetic models of metabolic disease, and hormone discovery, and could also effectively limit the numbers of animals required for such studies. Copyright © 2011 John Wiley & Sons, Ltd.     

Some Exact Solutions of Two Fifth Order KdV-type Nonlinear Partial Differential Equations

We consider the generalized integrable fifth order nonlinear Korteweg-de Vries (fKdV) equation. The extended Tanh method has been used rigorously, by computational program MAPLE, for solving this fifth order nonlinear partial differential equation. The general solutions of the fKdV equation are formed considering an ansatz of the solution in terms of tanh. Then, in particular, some exact solutions are found for the two fifth order KdV-type equations given by the Caudrey-Dodd-Gibbon equation and the another fifth order equation. The obtained solutions include solitary wave solution for both the two equations.     

Torsional vibrations of wet clutches: influence of mechanical parameters

Using a small scale test-rig a number of experiments were performed in which the imposed disk velocity v _disk, the different mechanical parameters of the test-rig (damping c and tangential stiffness k), and normal load were varied independently.     

The Catline for Deep Regression

Motivated by the notion of regression depth (Rousseeuw and Hubert, 1996) we introduce thecatline, a new method for simple linear regression. At any bivariate data setZ_n={(x_i, y_i);i=1, …, n} its regression depth is at leastn/3. This lower bound is attained for data lying on a convex or concave curve, whereas for perfectly linear data the catline attains a depth ofn. We construct anO(n log n) algorithm for the catline, so it can be computed fast in practice. The catline is Fisher-consistent at any linear modely=βx+α+ein which the error distribution satisfies med(e | x)=0, which encompasses skewed and/or heteroscedastic errors. The breakdown value of the catline is 1/3, and its influence function is bounded. At the bivariate gaussian distribution its asymptotic relative efficiency compared to theL¹line is 79.3% for the slope, and 88.9% for the intercept. The finite-sample relative efficiencies are in close agreement with these values. This combination of properties makes the catline an attractive fitting method.     

Structures in solutions from joint experimental-computational analysis: applications to cyclic molecules and studies of noncovalent interactions

The potential of an approach combining nuclear magnetic resonance (NMR) spectroscopy, molecular dynamics (MD) simulations, and quantum mechanical (QM) calculations for full structural characterizations in solution is assessed using cyclic organic compounds, namely, benzazocinone derivatives 1-3 with fused five- and eight-membered aliphatic rings, camphoric anhydride 4, and bullvalene 5. Various MD simulations were considered, using force field and semiempirical QM treatments, implicit and explicit solvation, and high-temperature MD calculations for selecting plausible molecular geometries for subsequent QM geometry optimizations using mainly B3LYP, M062X, and MP2 methods. The QM-predicted values of NMR parameters were compared to their experimental values for verification of the final structures derived from the MD/QM analysis. From these comparisons, initial estimates of quality thresholds (calculated as rms deviations) were 0.7-0.9 Hz for (3)J(HH) couplings, 0.07-0.11 ? for interproton distances, 0.05-0.08 ppm for (1)H chemical shifts, and 1.0-2.1 ppm for (13)C chemical shifts. The obtained results suggest that the accuracy of the MD analysis in predicting geometries and relative conformational energies is not critical and that the final geometry refinements of the structures selected from the MD simulations using QM methods are sufficient for correcting for the expected inaccuracy of the MD analysis. A unique example of C(sp(3))-H···N(sp(3)) intramolecular noncovalent interaction is also identified using the NMR/MD/QM and the natural bond orbital analyses. As the NMR/MD/QM approach relies on the final QM geometry optimization, comparisons of geometric characteristics predicted by different QM methods and those from X-ray and neutron diffraction measurements were undertaken using rigid and flexible cyclic systems. The joint analysis shows that intermolecular noncovalent interactions present in the solid state alter molecular geometries significantly compared to the geometries of isolated molecules from QM calculations.     

Flow injection spectrophotometric determination of N-acetyl-L-cysteine as a complex with palladium(II)

We describe a new method using flow-injection analysis with spectro-photometric detection, suitable for the determination of N-acetyl-L-cysteine (NAC). The proposed method is appropriate for the determination of NAC in reaction with Pd(2+) ions in the concentration range from 1.0 × 10(-5) mol L(-1) to 6.0 × 10(-5) mol L(-1). The detection limit NAC was 5.84 × 10(-6) mol L(-1) and the recorded relative standard deviation of the method is in the range from 1.67 to 4.11%. NAC and Pd(2+) form complexes of Pd(2+):NAC molar ratios of 1:1 and 1:2, depending on the ratio of their analytical concentrations. The cumulative conditional stability constant for the Pd(NAC)(2)(2+) complex is β(12)' = 2.69 × 10(9) L(2) mol(-2). The proposed method was compared with the classic spectrophotometric determination of NAC, using the same reagent, PdCl(2), and had shown certain advantages: a) shorter analysis time; b) the use of smaller volumes of sample and reagents, which make the proposed method cheaper and faster for NAC determination in real samples without sample pretreatment.     

From water clustering to osmotic coefficients

Water activity is an important macroscopic property of aerosol particles and droplets in the atmosphere as well as aqueous solutions in many other fields of physical chemistry. This study focuses on relating water activity, described using osmotic coefficients, to the microscopic water structure in systems of atmospheric relevance, namely, aqueous solutions of each of the four electrolytes: NaCl, (NH(4))(2)SO(4), NH(4)Cl, and Na(2)SO(4). The osmotic coefficients of these compounds, as reported in literature based on thermodynamic measurements, decrease as a function of molality for dilute solutions and increase as a function of molality for concentrated solutions. At an intermediate molality, a minimum value of the osmotic coefficient is observed. We explain this behavior by describing osmotic coefficients as the product of two concentration-dependent effects: incomplete electrolyte dissociation and variations in the microphysical water structure. The degree of dissociation in electrolyte solutions can be obtained directly from literature or derived from reported pK values, and in this work the water structure is quantified using low-wavenumber Raman spectroscopy. We use the band at 180 cm(-1) in Raman spectra of aqueous electrolyte solutions, which has been assigned to the displacement of the central oxygen atom in a tetrahedral hydrogen bonding environment composed of five H(2)O units. The abundance of such translationally restricted water molecules is essential in describing the local microphysical structure of water, and the height of the band is used to estimate the amount of such translationally restricted water molecules in solution. We were able to qualitatively reproduce and explain literature values of osmotic coefficients for the four studied electrolytes. Our results indicate that the effect of electrolyte dissociation, which decreases as a function of molality, dominates in dilute solutions, whereas changes in water structure are more significant at higher concentrations.     

The computation of stability boundaries in state space for a class of biochemical engineering systems

The stability of a class of biochemical processes defined by a set of m biochemical reactions involving n components is analysed. The processes operate in a continuous mode and possess at least two stable equilibrium states: the normal operating point and a biological wash out state. Using a canonical state representation of the process dynamics the geometric structure of the operating point's stability boundary is characterized. Numerical algorithms are developed to evaluate this boundary and to visualize its extent in state space. The proposed technique is illustrated with a representative engineering example.     

Automated On-Line GPC-GC-FPD Involving Co-Solvent Trapping and the On-Column Interface for the Determination of Organophosphorus Pesticides in Olive Oils

The robustness of an automated on-line GPC-GC-FPD method for the determination of Organophosphorus (OP) Pesticides in olive oil has been significantly improved, now allowing a routine operation. The original GPC-GC transfer technique employed a loop type interface with an early vapor exit and co-solvent trapping. Shooting, caused by boiling delay and malfunctioning of the solvent vapor exit during the transfer of the 3 mL solvent fraction to the retention gap, resulted in insufficient focusing of the OP-pesticides. In this interfacing concept, the GPC fraction is introduced directly into the carrier gas stream during a certain time interval using the Dualchrom pressure- and flow regulation, resulting in a very stable transfer. The interface now basically corresponds to an on-column interface with flow regulation. Via a Pyrex glass door behind the GC-oven door it can be seen that the liquid flow is broken up into alternating gas-liquid segments by the carrier gas flow during transfer. This avoids shooting in the retention gap and broadens the temperature range for successful transfer. By using a smaller sized GPC column the solvent fraction transferred was reduced to 1.3 mL. Methyl acetate/cyclopentane and the co-solvent n-nonane were selected for their lower boiling points. The modified method is very robust and has been applied to the analysis of 28 different OP-pesticides in olive oil with an overall detection limit of 0.002 mg/kg. Routinely 24 h of unattended operation is possible with a cycle time of 75 min.     

Crack identification method in beam-like structures using changes in experimentally measured frequencies and Particle Swarm Optimization

In this paper, a technique is presented for the detection and localization of an open crack in beam-like structures using experimentally measured natural frequencies and the Particle Swarm Optimization (PSO) method. The technique considers the variation in local flexibility near the crack. The natural frequencies of a cracked beam are determined experimentally and numerically using the Finite Element Method (FEM). The optimization algorithm is programmed in MATLAB. The algorithm is used to estimate the location and severity of a crack by minimizing the differences between measured and calculated frequencies. The method is verified using experimentally measured data on a cantilever steel beam. The Fourier transform is adopted to improve the frequency resolution. The results demonstrate the good accuracy of the proposed technique.