Metabolism of Maillard reaction products by the human gut microbiota - implications for health

The human colonic microbiota imparts metabolic versatility on the colon, interacts at many levels in healthy intestinal and systemic metabolism, and plays protective roles in chronic disease and acute infection. Colonic bacterial metabolism is largely dependant on dietary residues from the upper gut. Carbohydrates, resistant to digestion, drive colonic bacterial fermentation and the resulting end products are considered beneficial. Many colonic species ferment proteins but the end products are not always beneficial and include toxic compounds, such as amines and phenols. Most components of a typical Western diet are heat processed. The Maillard reaction, involving food protein and sugar, is a complex network of reactions occurring during thermal processing. The resultant modified protein resists digestion in the small intestine but is available for colonic bacterial fermentation. Little is known about the fate of the modified protein but some Maillard reaction products (MRP) are biologically active by, e.g. altering bacterial population levels within the colon or, upon absorption, interacting with human disease mechanisms by induction of inflammatory responses. This review presents current understanding of the interactions between MRP and intestinal bacteria. Recent scientific advances offering the possibility of elucidating the consequences of microbe-MRP interactions within the gut are discussed.

Application of semiquantitative proteomics techniques to the Maillard reaction

Proteomic tools-in particular, mass spectrometry (MS)-have advanced significantly in recent years, and the identification of proteins within complex mixtures is now a routine procedure. Quantitative methods of analysis are less well advanced and continue to develop. These include the use of stable isotope ratio approaches, isotopically labeled peptide standards, and nonlabeling methods. This paper summarizes the use of MS as a proteomics tool to identify and semiquantify proteins and their modified forms by using examples of relevance to the Maillard reaction. Finally, some challenges for the future are presented.

Novel approaches to the analysis of the Maillard reaction of proteins

The Maillard reaction comprises a complex network of reactions which has proven to be of great importance in both food science and medicine. The majority of methods developed for studying the Maillard reaction in food have focused on model systems containing amino acids and monosaccharides. In this study, a number of electrophoretic techniques, including two-dimensional gel electrophoresis and capillary electrophoresis, are presented. These have been developed specifically for the analysis of the Maillard reaction of food proteins, and are giving important insights into this complex process.

The application of a Trous wave filtering and Monte Carlo analysis on secis 2001 solar eclipse observations

Eight thousand images of the solar corona were captured during the June 2001 total solar eclipse. New software for the alignment of the images and an automated technique for detecting intensity oscillations using multi-scale wavelet analysis were developed. Large areas of the images covered by the Moon and the upper corona were scanned for oscillations and the statistical properties of the atmospheric effects were determined. The a Trous wavelet transform was used for noise reduction and Monte Carlo analysis as a significance test of the detections. The effectiveness of those techniques is discussed in detail.

Atomic ordering in nano-layered FePt: Multiscale Monte Carlo simulation

Nano- and meso-scale simulation of chemical ordering kinetics in nano-layered L1(0)-AB binary intermetallics was performed. In the nano- (atomistic) scale Monte Carlo (MC) technique with vacancy mechanism of atomic migration implemented with diverse models for the system energetics was used. The meso-scale microstructure evolution was, in turn, simulated by means of a MC procedure applied to a system built of meso-scale voxels ordered in particular L1(0) variants. The voxels were free to change the L1(0) variant and interacted with antiphase-boundary energies evaluated within the nano-scale simulations. The study addressed FePt thin layers considered as a material for ultra-high-density magnetic storage media and revealed metastability of the L1(0) c-variant superstructure with monoatomic planes parallel to the (001)-oriented layer surface and off-plane easy magnetization. The layers, originally perfectly ordered in the c-variant, showed discontinuous precipitation of a- and b-L1(0)-variant domains running in parallel with homogeneous disordering (i.e. generation of antisite defects). The domains nucleated heterogeneously on the free monoatomic Fe surface of the layer, grew inwards its volume and relaxed towards an equilibrium microstructure of the system. Two

Is the pinning of ordinary dislocations in γ-TiAl intrinsic or extrinsic in nature? A combined atomistic and kinetic Monte Carlo approach

We address the question of the observed pinning of 1/2

Anisotropic seismic inversion using a multigrid Monte Carlo approach

We propose a new approach for the inversion of anisotropic P-wave data based on Monte Carlo methods combined with a multigrid approach. Simulated annealing facilitates objective minimization of the functional characterizing the misfit between observed and predicted traveltimes, as controlled by the Thomsen anisotropy parameters (epsilon, delta). Cycling between finer and coarser grids enhances the computational efficiency of the inversion process, thus accelerating the convergence of the solution while acting as a regularization technique of the inverse problem. Multigrid perturbation samples the probability density function without the requirements for the user to adjust tuning parameters. This increases the probability that the preferred global, rather than a poor local, minimum is attained. Undertaking multigrid refinement and Monte Carlo search in parallel produces more robust convergence than does the initially more intuitive approach of completing them sequentially. We demonstrate the usefulness of the new multigrid Monte Carlo (MGMC) scheme by applying it to (a) synthetic, noise-contaminated data reflecting an isotropic subsurface of constant slowness, horizontally layered geologic media and discrete subsurface anomalies; and (b) a crosshole seismic data set acquired by previous authors at the Reskajeage test site in Cornwall, UK. Inverted distributions of slowness (s) and the Thomson anisotropy parameters (epsilon, delta) compare favourably with those obtained previously using a popular matrix-based method. Reconstruction of the Thomsen epsilon parameter is particularly robust compared to that of slowness and the Thomsen delta parameter, even in the face of complex subsurface anomalies. The Thomsen epsilon and delta parameters have enhanced sensitivities to bulk-fabric and fracture-based anisotropies in the TI medium at Reskajeage. Because reconstruction of slowness (s) is intimately linked to that epsilon and delta in the MGMC scheme, inverted images of phase velocity reflect the integrated effects of these two modes of anisotropy. The new MGMC technique thus promises to facilitate rapid inversion of crosshole P-wave data for seismic slownesses and the Thomsen anisotropy parameters, with minimal user input in the inversion process.

Nonrigid Structure-From-Motion From 2-D Images Using Markov Chain Monte Carlo

In this paper we present a new method for simultaneously determining three dimensional (3-D) shape and motion of a non-rigid object from uncalibrated two dimensional (2- D) images without assuming the distribution characteristics. A non-rigid motion can be treated as a combination of a rigid rotation and a non-rigid deformation. To seek accurate recovery of deformable structures, we estimate the probability distribution function of the corresponding features through random sampling, incorporating an established probabilistic model. The fitting between the observation and the projection of the estimated 3-D structure will be evaluated using a Markov chain Monte Carlo based expectation maximisation algorithm. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results.