Neurocognitive derivation of protein surface property from protein aggregate parameters

Current work targeted to predicate parametric relationship between aggregate and individual property of a protein. In this approach, we considered individual property of a protein as its Surface Roughness Index (SRI) which was shown to have potential to classify SCOP protein families. The bulk property was however considered as Intensity Level based Multi-fractal Dimension (ILMFD) of ordinary microscopic images of heat denatured protein aggregates which was known to have potential to serve as protein marker. The protocol used multiple ILMFD inputs obtained for a protein to produce a set of mapped outputs as possible SRI candidates. The outputs were further clustered and largest cluster centre after normalization was found to be a close approximation of expected SRI that was calculated from known PDB structure. The outcome showed that faster derivation of individual protein's surface property might be possible using its bulk form, heat denatured aggregates.     

The derivation of nerve signals from contrast flash data

This paper presents a new analysis of the contrast flash data of Alpern et al. (1970a-d). It was prompted by the criticism of Wandell (1976) who pointed out that Alpern et al., main conclusion, i.e. that the inhibitory signal N ^*() elicited by the contrast flash () takes the form , would imply an unrealistic excitatory photo response. The present analysis shows the data to be consistent with an inhibitory signal of the form .     

Visualizing 3D data obtained from microscopy on the Internet

The Internet is a powerful communication medium increasingly exploited by business and science alike, especially in structural biology and bioinformatics. The traditional presentation of static two-dimensional images of real-world objects on the limited medium of paper can now be shown interactively in three dimensions. Many facets of this new capability have already been developed, particularly in the form of VRML (virtual reality modeling language), but there is a need to extend this capability for visualizing scientific data. Here we introduce a real-time isosurfacing node for VRML, based on the marching cube approach, allowing interactive isosurfacing. A second node does three-dimensional (3D) texture-based volume-rendering for a variety of representations. The use of computers in the microscopic and structural biosciences is extensive, and many scientific file formats exist. To overcome the problem of accessing such data from VRML and other tools, we implemented extensions to SGI's IFL (image format library). IFL is a file format abstraction layer defining communication between a program and a data file. These technologies are developed in support of the BioImage project, aiming to establish a database prototype for multidimensional microscopic data with the ability to view the data within a 3D interactive environment.     

Material parameter identification of arterial wall layers from homogenised stress-strain data

Multilayer structure of the artery can have significant effects on the resulting mechanical behaviour of the artery wall. Separation of the artery into individual layers is sometimes performed to identify the layer-specific parameters of constitutive model proposed by Holzapfel, Gasser and Ogden (HGO model). Inspired by this single-layer model, a double-layer model was formulated and used for identification of material parameters from homogenised stress-strain data (of non-separated artery wall). The paper demonstrates that the layer-specific parameters of the double-layer constitutive model can be identified without the need of artery separation. The resulting double-layer model can credibly describe the homogenised stress-strain behaviour of the real artery wall including large-strain stiffening effects attributed to multilayer nature of the artery.     

Improving 3D structure prediction from chemical shift data

We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50–100 residue size range and yields reliable structures in 70 % of the cases. All structures that passed the reliability filter were accurate (<2 Å RMSD from the reference).     

Characterization of the capillary network in skeletal muscles from 3D data

In this review we present immunohistochemical methods for visualization of capillaries and muscle fibres in thick muscle sections. Special attention is paid to the procedures that preserve good morphology. Applying confocal microscopy and virtual 3D stereological grids, or tracing of capillaries in virtual reality, length of capillaries within a muscle volume or length of capillaries adjacent to a muscle fibre per fibre length, fibre surface area or fibre volume can be evaluated by an unbiased approach. Moreover, 3D models of capillaries and muscle fibres can be produced. Comparison of the developed methods with counting capillary profiles from 2D sections is discussed and the reader is warned that counting capillary profiles from 2D sections can underestimate the capillary length by as much as 75 percent. Application of the described 3D methodology is illustrated by the anatomical remodelling of capillarity during acute denervation and early reinnervation in the rat soleus and extensor digitorum longus muscles.     

On the potentialities of 3D–1D coupled models in hemodynamics simulations

This work comprises a step towards the quantitative and qualitative analysis of coupled local and global hemodynamics phenomena in the arterial system. The aim of this work is to present some numerical examples to put in evidence the importance of the use of 3D–1D coupled models in hemodynamics problems when carrying out simulations of rather complex situations. Accordingly, some cases for which classical modeling cannot be applied are identified and solved. The results obtained here allow us to assess some interrelations between local pointwise quantities (defined at the level of the 3D model) and global mean quantities (defined at the level of the 1D model).     

Adjoint multi-start-based estimation of cardiac hyperelastic material parameters using shear data

Cardiac muscle tissue during relaxation is commonly modeled as a hyperelastic material with strongly nonlinear and anisotropic stress response. Adapting the behavior of such a model to experimental or patient data gives rise to a parameter estimation problem which involves a significant number of parameters. Gradient-based optimization algorithms provide a way to solve such nonlinear parameter estimation problems with relatively few iterations, but require the gradient of the objective functional with respect to the model parameters. This gradient has traditionally been obtained using finite differences, the calculation of which scales linearly with the number of model parameters, and introduces a differencing error. By using an automatically derived adjoint equation, we are able to calculate this gradient more efficiently, and with minimal implementation effort. We test this adjoint framework on a least squares fitting problem involving data from simple shear tests on cardiac tissue samples. A second challenge which arises in gradient-based optimization is the dependency of the algorithm on a suitable initial guess. We show how a multi-start procedure can alleviate this dependency. Finally, we provide estimates for the material parameters of the Holzapfel and Ogden strain energy law using finite element models together with experimental shear data.     

Thermodynamic parameters for the helix-coil thermal transition of ribonuclease-S-peptide and derivatives from 1H-NMR data

Values for the thermodynamic quantities, ΔH° = 11.8 ± 2.0 Kcal/mole and ΔS° = 43.6 ± 6.0 e.u., of the 3-13 helix–coil equilibrium of isolated S-peptide (19 residue N-terminal fragment of ribonuclease A) in aqueous solution (3 m M, 1M NaCl, pD 5.4) have been determined from a joint analysis of the Thr 3γ, Ala 6β, Phe 8meta, and Phe 8para ¹H chemical shift vs temperature curves (?7 to 80°C) in several aqueous–trifluorethanol mixtures. Chemical shifts in the coil and in the helix have been determined for up to 16 protons belonging to the 3-13 fragment. Thermodynamic parameters have also been determined for C-peptide (13 residue fragment) and a number of S-peptide derivatives. From the variation of the values of the thermodynamic parameters at pD 2.5, 5.4, and 8.0, a quantitation of the two helix-stabilizing side-chain interactions can be made: (1) Δ(ΔH°) ? 5 Kcal/mole and Δ(ΔS°) ? 18 e.u. for the salt bridge Glu 2^? … Arg 10⁺ and (2) Δ(ΔH°) ? 3 Kcal/mole and Δ(ΔS°) = 9 e.u. for the one in which the His 12⁺ imidazolium group is involved, presumably a partial stacking with the Phe 8 side chain.     

Estimation of growth parameters from multiple-recapture data

This article develops a method for analysis of growth data with multiple recaptures when the initial ages for all individuals are unknown. The existing approaches either impute the initial ages or model them as random effects. Assumptions about the initial age are not verifiable because all the initial ages are unknown. We present an alternative approach that treats all the lengths including the length at first capture as correlated repeated measures for each individual. Optimal estimating equations are developed using the generalized estimating equations approach that only requires the first two moment assumptions. Explicit expressions for estimation of both mean growth parameters and variance components are given to minimize the computational complexity. Simulation studies indicate that the proposed method works well. Two real data sets are analyzed for illustration, one from whelks (Dicathais aegaota) and the other from southern rock lobster (Jasus edwardsii) in South Australia.     

On the derivation of the Kargol's mechanistic transport equations from the Kedem-Katchalsky phenomenological equations

In the present article, it was demonstrated that--by starting from the so-called adjusted Kedem-Katchalsky (KK) phenomenological equations (Suchanek et al. 2004), i.e. the equations: Jv=LpDeltaP-LpDDeltaPi. JD=-LDpDeltaP+LDDeltaPi it is possible to derive practical transport equations (for the volume flow and the solute flow) in the form of the Kargol s mechanistic transport equations (Kargol and Kargol 2000, 2001, 2003a,b,c, 2004; Kargol 2002). On this basis, it has been found that the KK thermodynamic formalism for membrane transport (practical equations) is in general identical with the mechanistic equations for membrane transport.     

Sensitivity of stress and strain calculations to passive material parameters in cardiac mechanical models using unloaded geometries

Cardiac stress (load) and strain (stretch) are widely studied indicators of cardiac function and outcome, but are difficult or impossible to directly measure in relation to the cardiac microstructure. An alternative approach is to estimate these states using computer methods and image-based measurements, but this still requires knowledge of the tissue material properties and the unloaded state, both of which are difficult to determine. In this work, we tested the sensitivity of these two interdependent unknowns (reference geometry and material parameters) on stress and strain calculations in cardiac tissue. Our study used a finite element model of the human ventricle, with a hyperelastic passive material model, and was driven by a cell model mediated active contraction. We evaluated 21 different published parameter sets for the five parameters of the passive material model, and for each set we optimised the corresponding unloaded geometry and contractility parameter to model a single pressure-volume loop. The resulting mechanics were compared, and calculated systolic stresses were largely insensitive to the chosen parameter set when an unloading algorithm was used. Meanwhile, material strain calculations varied substantially depending on the choice of material parameters. These results indicate that determining the correct material and unloaded configuration may be highly important to understand strain driven processes, but less so for calculating stress estimates.     

Calvarial cells synthesize 1 alpha,25-dihydroxyvitamin D3 from 25-hydroxyvitamin D3

A metabolite of vitamin D has been isolated in pure form from incubation of 25-hydroxyvitamin D3 with embryonic chick calvarial cells that had been grown on Cytodex 1 microcarrier beads. The isolation involved dichloromethane extraction of the cells and incubation medium, followed by Sephadex LH-20 column chromatography and high-performance liquid chromatography of the extract. The metabolite was identified as 1 alpha,25-dihydroxyvitamin D3 by means of ultraviolet absorption spectroscopy, mass spectrometry, and sensitivity to oxidation by periodate. This metabolite was not produced by cell-free medium or by cells from embryonic chick liver, skin, or heart. In conclusion, (1) kidney cells are not unique in having 25-hydroxyvitamin D3:1 alpha-hydroxylase activity as previously believed and (2) vitamin D target tissues such as the skeleton may play a direct role in mediating the metabolism of 25-hydroxyvitamin D3 to 1 alpha,25-dihydroxyvitamin D3, a vitamin D metabolite active at those sites.     

Large-scale reconstruction of 3D structures of human chromosomes from chromosomal contact data

Chromosomes are not positioned randomly within a nucleus, but instead, they adopt preferred spatial conformations to facilitate necessary long-range gene–gene interactions and regulations. Thus, obtaining the 3D shape of chromosomes of a genome is critical for understanding how the genome folds, functions and how its genes interact and are regulated. Here, we describe a method to reconstruct preferred 3D structures of individual chromosomes of the human genome from chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. A novel parameterized objective function was designed for modeling chromosome structures, which was optimized by a gradient descent method to generate chromosomal structural models that could satisfy as many intra-chromosomal contacts as possible. We applied the objective function and the corresponding optimization method to two Hi-C chromosomal data sets of both a healthy and a cancerous human B-cell to construct 3D models of individual chromosomes at resolutions of 1 MB and 200 KB, respectively. The parameters used with the method were calibrated according to an independent fluorescence in situ hybridization experimental data. The structural models generated by our method could satisfy a high percentage of contacts (pairs of loci in interaction) and non-contacts (pairs of loci not in interaction) and were compatible with the known two-compartment organization of human chromatin structures. Furthermore, structural models generated at different resolutions and from randomly permuted data sets were consistent.