Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

The visual recognition of complex movements and actions is crucial for communication and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and the dorsal pathway. The model makes specific predictions that motivate new experiments.

Bifurcation analysis of a model for biological control

In this paper we study the Lyapunov stability and Hopf bifurcation in a biological system which models the biological control of parasites of orange plantations. (c) 2007 Elsevier Ltd. All rights reserved.

Sensitivity of the BEAM4 fisheries bioeconomic model to the main biological input parameters

Several runs of the BEAM4 model were carried out, combining several sets of input parameters from von Bertalanffy's growth curve (Lt = L-x[1 - e(-k(-to))]) and the natural mortality (M), with sets or parameters from the length-weight relationship (W=aL(b)). Further simulations were made with variations of +/- 20%, in the input parameters: recruitment (R), catchability coefficient (q), and the lengths at which 50 and 75% of the fishes are retained by the net (L-50%, and L-75%). The data used were those of the pair trawl fisheries for corvina Micropogonias furnieri, off southeastern Brazil. Results showed variations in the output (landed weight) ranging from - 62 to 147% associated with the diverse sets of VBGF and LWR parameters, and lower variations associated with the other input parameters tested. (C) 2001 Elsevier B.V. B.V. All rights reserved.

Chemometric analysis of Hymenoptera toxins and defensins: A model for predicting the biological activity of novel peptides from venoms and hemolymph

When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The trial and error approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. © 2011 Elsevier Inc.

Molecular model for hydrated biological tissues

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Biological evaluation of the bone healing process after application of two potentially osteogenic proteins: an animal experimental model

doi: 10.1111/j.1741-2358.2011.00526.x Biological evaluation of the bone healing process after application of two potentially osteogenic proteins: an animal experimental model Objective: The aim of this work was to analyse qualitatively and quantitatively the newly formed bone after insertion of rhBMP-2 and protein extracted from Hevea brasiliensis (P-1), associated or not with a carrier in critical bone defects created in Wistar rat calvarial bone, using histological and histomorphometrical analyses. Materials and methods: Eighty-four male Wistar rats were used, divided into two groups, according to the period of time until the sacrifice (2 and 6 weeks). Each one of these groups was subdivided into six groups with seven animals each, according to the treatments: (1) 5 mu g of pure rhBMP-2, (2) 5 mu g of rhBMP-2/monoolein gel, (3) pure monoolein gel, (4) 5 mu g of pure P-1, (5) 5 mu g of P-1/monoolein gel and (6) critical bone defect controls. The animals were euthanised and the calvarial bone tissue removed for histological and histomorphometrical analyses. Result and conclusion: The results showed an improvement in the bone healing process using the rhBMP-2 protein, associated or not with a material carrier in relation to the other groups, and this process demonstrated to be time dependent.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Parameter estimation in a growth model for a biological population

The motivating problem concerns the estimation of the growth curve of solitary corals that follow the nonlinear Von Bertalanffy Growth Function (VBGF). The most common parameterization of the VBGF for corals is based on two parameters: the ultimate length L∞ and the growth rate k. One aim was to find a more reliable method for estimating these parameters, which can capture the influence of environmental covariates. The main issue with current methods is that they force the linearization of VBGF and neglect intra-individual variability. The idea was to use the hierarchical nonlinear model which has the appealing features of taking into account the influence of collection sites, possible intra-site measurement correlation and variance heterogeneity, and that can handle the influence of environmental factors and all the reliable information that might influence coral growth. This method was used on two databases of different solitary corals i.e. Balanophyllia europaea and Leptopsammia pruvoti, collected in six different sites in different environmental conditions, which introduced a decisive improvement in the results. Nevertheless, the theory of the energy balance in growth ascertains the linear correlation of the two parameters and the independence of the ultimate length L∞ from the influence of environmental covariates, so a further aim of the thesis was to propose a new parameterization based on the ultimate length and parameter c which explicitly describes the part of growth ascribable to site-specific conditions such as environmental factors. We explored the possibility of estimating these parameters characterizing the VBGF new parameterization via the nonlinear hierarchical model. Again there was a general improvement with respect to traditional methods. The results of the two parameterizations were similar, although a very slight improvement was observed in the new one. This is, nevertheless, more suitable from a theoretical point of view when considering environmental covariates.

Transport of nanoparticles into polymersomes : a minimal model system of particles passage through biological membranes

This thesis focuses on the design and characterization of a novel, artificial minimal model membrane system with chosen physical parameters to mimic a nanoparticle uptake process driven exclusively by adhesion and softness of the bilayer. The realization is based on polymersomes composed of poly(dimethylsiloxane)-b-poly(2-methyloxazoline) (PMDS-b-PMOXA) and nanoscopic colloidal particles (polystyrene, silica), and the utilization of powerful characterization techniques. rnPDMS-b-PMOXA polymersomes with a radius, Rh ~100 nm, a size polydispersity, PD = 1.1 and a membrane thickness, h = 16 nm, were prepared using the film rehydratation method. Due to the suitable mechanical properties (Young’s modulus of ~17 MPa and a bending modulus of ~7⋅10-8 J) along with the long-term stability and the modifiability, these kind of polymersomes can be used as model membranes to study physical and physicochemical aspects of transmembrane transport of nanoparticles. A combination of photon (PCS) and fluorescence (FCS) correlation spectroscopies optimizes species selectivity, necessary for a unique internalization study encompassing two main efforts. rnFor the proof of concepts, the first effort focused on the interaction of nanoparticles (Rh NP SiO2 = 14 nm, Rh NP PS = 16 nm; cNP = 0.1 gL-1) and polymersomes (Rh P = 112 nm; cP = 0.045 gL-1) with fixed size and concentration. Identification of a modified form factor of the polymersome entities, selectively seen in the PCS experiment, enabled a precise monitor and quantitative description of the incorporation process. Combining PCS and FCS led to the estimation of the incorporated particles per polymersome (about 8 in the examined system) and the development of an appropriate methodology for the kinetics and dynamics of the internalization process. rnThe second effort aimed at the establishment of the necessary phenomenology to facilitate comparison with theories. The size and concentration of the nanoparticles were chosen as the most important system variables (Rh NP = 14 - 57 nm; cNP = 0.05 - 0.2 gL-1). It was revealed that the incorporation process could be controlled to a significant extent by changing the nanoparticles size and concentration. Average number of 7 up to 11 NPs with Rh NP = 14 nm and 3 up to 6 NPs with Rh NP = 25 nm can be internalized into the present polymersomes by changing initial nanoparticles concentration in the range 0.1- 0.2 gL-1. Rapid internalization of the particles by polymersomes is observed only above a critical threshold particles concentration, dependent on the nanoparticle size. rnWith regard possible pathways for the particle uptake, cryogenic transmission electron microscopy (cryo-TEM) has revealed two different incorporation mechanisms depending on the size of the involved nanoparticles: cooperative incorporation of nanoparticles groups or single nanoparticles incorporation. Conditions for nanoparticle uptake and controlled filling of polymersomes were presented. rnIn the framework of this thesis, the experimental observation of transmembrane transport of spherical PS and SiO2 NPs into polymersomes via an internalization process was reported and examined quantitatively for the first time. rnIn a summary the work performed in frames of this thesis might have significant impact on cell model systems’ development and thus improved understanding of transmembrane transport processes. The present experimental findings help create the missing phenomenology necessary for a detailed understanding of a phenomenon with great relevance in transmembrane transport. The fact that transmembrane transport of nanoparticles can be performed by artificial model system without any additional stimuli has a fundamental impact on the understanding, not only of the nanoparticle invagination process but also of the interaction of nanoparticles with biological as well as polymeric membranes. rn

On the effects of circulation, sediment resuspension and biological incorporation by diatoms in an ocean model of aluminium, link to model data

The distribution of dissolved aluminium in the West Atlantic Ocean shows a mirror image with that of dissolved silicic acid, hinting at intricate interactions between the ocean cycling of Al and Si. The marine biogeochemistry of Al is of interest because of its potential impact on diatom opal remineralisation, hence Si availability. Furthermore, the dissolved Al concentration at the surface ocean has been used as a tracer for dust input, dust being the most important source of the bio-essential trace element iron to the ocean. Previously, the dissolved concentration of Al was simulated reasonably well with only a dust source, and scavenging by adsorption on settling biogenic debris as the only removal process. Here we explore the impacts of (i) a sediment source of Al in the Northern Hemisphere (especially north of ~ 40° N), (ii) the imposed velocity field, and (iii) biological incorporation of Al on the modelled Al distribution in the ocean. The sediment source clearly improves the model results, and using a different velocity field shows the importance of advection on the simulated Al distribution. Biological incorporation appears to be a potentially important removal process. However, conclusive independent data to constrain the Al / Si incorporation ratio by growing diatoms are missing. Therefore, this study does not provide a definitive answer to the question of the relative importance of Al removal by incorporation compared to removal by adsorptive scavenging.

Dynamical principles in biological processes: A model of charge migration in proteins and DNA

The generalized master equations (GMEs) that contain multiple time scales have been derived quantum mechanically. The GME method has then been applied to a model of charge migration in proteins that invokes the hole hopping between local amino acid sites driven by the torsional motions of the floppy backbones. This model is then applied to analyze the experimental results for sequence-dependent long-range hole transport in DNA reported by Meggers et al. [Meggers, E., Michel-Beyerle, M. E., & Giese, B. (1998) J. Am. Chem. Soc. 120, 12950–12955]. The model has also been applied to analyze the experimental results of femtosecond dynamics of DNA-mediated electron transfer reported by Zewail and co-workers [Wan, C., Fiebig, T., Kelley, S. O., Treadway, C. R., Barton, J. K. & Zewail, A. H. (1999) Proc. Natl. Acad. Sci. USA 96, 6014–6019]. The initial events in the dynamics of protein folding have begun to attract attention. The GME obtained in this paper will be applicable to this problem.

Biological impact on mineral dissolution: Application of the lichen model to understanding mineral weathering in the rhizosphere

Microorganisms modify rates and mechanisms of chemical and physical weathering and clay growth, thus playing fundamental roles in soil and sediment formation. Because processes in soils are inherently complex and difficult to study, we employ a model based on the lichen–mineral system to identify the fundamental interactions. Fixed carbon released by the photosynthetic symbiont stimulates growth of fungi and other microorganisms. These microorganisms directly or indirectly induce mineral disaggregation, hydration, dissolution, and secondary mineral formation. Model polysaccharides were used to investigate direct mediation of mineral surface reactions by extracellular polymers. Polysaccharides can suppress or enhance rates of chemical weathering by up to three orders of magnitude, depending on the pH, mineral surface structure and composition, and organic functional groups. Mg, Mn, Fe, Al, and Si are redistributed into clays that strongly adsorb ions. Microbes contribute to dissolution of insoluble secondary phosphates, possibly via release of organic acids. These reactions significantly impact soil fertility. Below fungi–mineral interfaces, mineral surfaces are exposed to dissolved metabolic byproducts. Through this indirect process, microorganisms can accelerate mineral dissolution, leading to enhanced porosity and permeability and colonization by microbial communities.