Neural cross-correlation and signal decorrelation: insights into coding of auditory space

The auditory systems of humans and many other species use the difference in the time of arrival of acoustic signals at the two ears to compute the lateral position of sound sources. This computation is assumed to initially occur in an assembly of neurons organized along a frequency-by-delay surface. Mathematically, the computations are equivalent to a two-dimensional cross-correlation of the input signals at the two ears, with the position of the peak activity along this surface designating the position of the source in space. In this study, partially correlated signals to the two ears are used to probe the mechanisms for encoding spatial cues in stationary or dynamic (moving) signals. It is demonstrated that a cross-correlation model of the auditory periphery coupled with statistical decision theory can predict the patterns of performance by human subjects for both stationary and motion stimuli as a function of stimulus decorrelation. Implications of these findings for the existence of a unique cortical motion system are discussed.     

The evolution of the human mind and logic--mathematics structures

The evolution of the human mind is discussed based on: (i) the fact that living beings interchange matter, energy and information with their environment, (ii) an ontological interpretation of the "reality" of the quantum world, of which logic-mathematics structures are considered constitutive parts, (iii) recent theories according to which living beings are considered as dynamic complex systems organized by information, and (iv) the fact that the evolution of living beings is guided by information about the environment and by intrinsic information on living systems (auto-organization). Assuming the evolution of vision as a model we observe that the driving forces that directed the evolution of the eyes, as dynamic complex systems, are the information about the environment supplied by sunlight and the intrinsic information-gaining mechanism of living organisms. Thus, there exists a convergence toward a visual system with the greatest ability to obtain light information, like the human eye, and also a divergence that leads to the development of specific qualities in some species. As in the case of vision the evolution of the human mind-brain cannot be a consequence of factors unrelated to the object of its own functioning. The human mind was structured for the acquisition from reality of the logic-mathematics structures that underlie the whole universe and consequently of an internal representation of the external world and of its own self. Thus, these structures are, together with the intrinsic capacity for auto-organization of the human brain, the predominant driving force of the human mind evolution. Both factors are complementary.     

Spatial models of virus-immune dynamics

To date, the majority of theoretical models describing the dynamics of infectious diseases in vivo are based on the assumption of well-mixed virus and cell populations. Because many infections take place in solid tissues, spatially structured models represent an important step forward in understanding what happens when the assumption of well-mixed populations is relaxed. Here, we explore models of virus and virus-immune dynamics where dispersal of virus and immune effector cells was constrained to occur locally. The stability properties of our spatial virus-immune dynamics models remained robust under almost all biologically plausible dispersal schemes, regardless of their complexity. The various spatial dynamics were compared to the basic non-spatial dynamics and important differences were identified: When space was assumed to be homogeneous, the dynamics generated by non-spatial and spatially structured models differed substantially at the peak of the infection. Thus, non-spatial models may lead to systematic errors in the estimates of parameters underlying acute infection dynamics. When space was assumed to be heterogeneous, spatial coupling not only changed the equilibrium properties of the uncoupled populations but also equalized the dynamics and thereby reduced the likelihood of dynamic elimination of the infection. In line with experimental and clinical observations, long-lasting oscillation periods were virtually absent. When source-sink dynamics were considered, the long-term outcome of the infection depended critically on the degree of spatial coupling. The infection collapsed when emigration from source sites became too large. Finally, we discuss the implications of spatially structured models on medical treatment of infectious diseases, and note that a huge gap exists in data accurately describing infection dynamics in solid tissues.     

Crystal structure of a carbohydrate induced homodimer of phospholipase A2 from Bungarus caeruleus at 2.1A resolution

This is the first crystal structure of a carbohydrate induced dimer of phospholipase A(2) (PLA(2)). This is an endogenous complex formed between two PLA(2) molecules and two mannoses. It was isolated from Krait venom (Bungarus caeruleus) and crystallized as such. The complete amino acid sequence of PLA(2) was determined using cDNA method. Three-dimensional structure of the complex has been solved with molecular replacement method and refined to a final R-factor of 0.192 for all the data in the resolution range 20.0-2.1A. The presence of mannose molecules in the protein crystals was confirmed using dinitrosalicylic acid test and the molecular weight of the dimer was verified with MALDI-TOF. As indicated by dynamic light scattering and analytical ultracentrifugation the dimer was also stable in solution. The good quality non-protein electron density at the interface of two PLA(2) molecules enabled us to model two mannoses. The mannoses are involved extensively in interactions with protein atoms of both PLA(2) molecules. Some of the critical amino acid residues such as Asp 49 and Tyr 31, which are part of the substrate-binding site, are found facing the interface and interacting with mannoses. The structure of the complex clearly shows that the dimerization is caused by mannoses and it results in the loss of enzymatic activity.     

Chromatographic analysis and sequencing approach of heparin oligosaccharides using cetyltrimethylammonium dynamically coated stationary phases

C(18) and C(8) bonded stationary phases dynamically coated with cetyltrimethylammonium (CTA) and strong anion exchange (SAX) were developed to obtain separations of oligosaccharide mixtures resulting from chemical or enzymatic depolymerization of heparin. With this method, the retention of sulfated oligosaccharides is directly adjustable depending on the amount of CTA adsorbed into the column. Oligosaccharides containing up to 20 sulfates were separated with a resolving power superior to that of conventional SAX analysis. The stability of the column coating enables hundreds of injections. Using ammonium methane sulfonate aqueous solutions as ultraviolet transparent mobile phases, it was possible to set up double detection, including selective detection of acetylated oligosaccharides. Analytical gel permeation chromatography was directly coupled to CTA-SAX, obtaining a two-dimensional profile of analyzed oligosaccharidic mixtures. A sequencing method of heparin oligosaccharides using partial depolymerization by heparinases according to their size and sulfation pattern and digest analysis by CTA-SAX was developed. A direct application of this method to the analysis of oligosaccharide mixtures obtained by complete digestion of heparins by heparinases I, II, and III was done. It allowed a reliable quantification of heparin building blocks. We also focused our attention on di- and tetrasaccharidic species containing the 3-O-sulfated glucosamines taken as markers of the active sites for antithrombin III. The method was also applied to more complex mixtures resulting from porcine heparin partially depolymerized with heparinase I. The specificity of the reaction was studied up to decasaccharidic fractions.     

Modeling of homogeneous cloned enzyme donor immunoassay

One of the most widely used analytical techniques for sensitive detection of biologically and clinically significant analytes is the immunoassay. In recent years direct immunoprobes allowing label-free detection of the interaction between the antibody and the target analyte have proved their capabilities as fast, simple, and nevertheless highly sensitive methods. Cloned enzyme donor immunoassay (CEDIA) homogeneous assay is based on the bacterial enzyme beta-galactosidase, which has been genetically engineered into two inactive fragments, enzyme donor and enzyme acceptor. Reassociation of the fragments in the assay forms active enzyme, which acts on substrate to generate a colored product. A comprehensive kinetic model of CEDIA is developed to aid in understanding this method and to facilitate development of a truly homogeneous version, potentially applicable to a dipstick-type multianalyte point of care analytical device (ChemChip). Although the standard assay involves a two-step process, we also chose to model a single-combined process, which would be simpler to apply in a ChemChip device. From the modeling simulation, we obtain the time courses of the amounts of product and active enzyme, from which the dynamic ranges can be obtained as 10(-6)-10(-7) and 10(-5)-10(-7)M analyte concentration for two-step and single-combined processes under the conditions of the assumed parameters, respectively. A simple one-step immunoassay has the merit of reducing time and cost and has an improved dynamic range.     

The relationship between salinity, suspended particulate matter and water clarity in aquatic systems

This work presents and recommends 1) an empirically based new model quantifying the relationship between salinity, suspended particulate matter (SPM) and water clarity (as given by the Secchi depth) and (2) an empirical model for oxygen saturation in the deep-water zone for coastal areas (O₂Sat in %). This paper also discusses the many and important roles that SPM plays in aquatic ecosystems and presents comparisons between SPM concentrations in lakes, rivers and coastal areas. Such comparative studies are very informative but not so common. The empirical O₂Sat model explains (statistically) 80% of the variability in mean O₂Sat values among 23 Baltic coastal areas. The model is based on data on sedimentation of SPM, the percentage of ET areas (areas where erosion and transportation of fine sediments occur), the theoretical deep-water retention time and the mean coastal depth. These two new models have been incorporated into an existing dynamic model for SPM in coastal areas that quantifies all important fluxes of SPM into, within and from coastal areas, such as river inflow, primary production, resuspension, sedimentation, mixing, mineralisation and the SPM exchange between the given coastal area and the sea (or adjacent coastal areas). The modified dynamic SPM model with these two new sub-models has been validated (blind tested) with very good results; the model predictions for Secchi depth, O₂Sat and sedimentation are within the uncertainty bands of the empirical data.