The epidthelial sodium channel ENaC and its regulators in the epidermal permeability barrier function

The highly amiloride-sensitive epithelial sodium channel ENaC is well known to be involved in controlling whole body sodium homeostasis and lung liquid clearance. ENaC expression has also been detected in the skin of amphibians and mammals. Mice lacking ENaC expression lose rapidly weight associated with an epidermal barrier defect that develops following birth. This dehydration is accompanied with a highly abnormal lipid matrix composition and an impaired skin surface acidification. This strongly suggests a role of ENaC in the maturation of barrier function rather than in the prenatal generation of the barrier, and may be as such an important modulator for skin hydration. In parallel, gene targeting experiments of regulators of ENaC activity, membrane serine proteases, also termed channel activating proteases, like CAP1/Prss8 and matriptase/MT-SP1 by themselves have been shown to be crucial for the epidermal barrier function. In our review, we mainly focus on the role of ENaC and its regulators in the skin and discuss their importance in the epidermal permeability barrier function.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

1D.03: Inactive matrix GLA protein is associated with renal resistive index in a population-based study

OBJECTIVE: Renal resistive index (RRI) varies directly with renal vascular stiffness and pulse pressure. RRI correlates positively with arteriolosclerosis in damaged kidneys and predicts progressive renal dysfunction. Matrix Gla-protein (MGP) is a vascular calcification inhibitor that needs vitamin K to be activated. Inactive MGP, known as desphospho-uncarboxylated MGP (dp-ucMGP), can be measured in plasma and has been associated with various cardiovascular (CV) markers, CV outcomes and mortality. In this study we hypothesize that increased RRI is associated with high levels of dp-ucMGP. DESIGN AND METHOD: We recruited participants via a multi-center family-based cross-sectional study in Switzerland exploring the role of genes and kidney hemodynamics in blood pressure regulation. Dp-ucMGP was quantified in plasma samples by sandwich ELISA. Renal doppler sonography was performed using a standardized protocol to measure RRIs on 3 segmental arteries in each kidney. The mean of the 6 measures was reported. Multiple regression analysis was performed to estimate associations between RRI and dp-ucMGP adjusting for sex, age, pulse pressure, mean pressure, renal function and other CV risk factors. RESULTS: We included 1035 participants in our analyses. Mean values were 0.64 ± 0.06 for RRI and 0.44 ± 0.21 (nmol/L) for dp-ucMGP. RRI was positively associated with dp-ucMGP both before and after adjustment for sex, age, body mass index, pulse pressure, mean pressure, heart rate, renal function, low and high density lipoprotein, smoking status, diabetes, blood pressure and cholesterol lowering drugs, and history of CV disease (P < 0.001). CONCLUSIONS: RRI is independently and positively associated with high levels of dp-ucMGP after adjustment for pulse pressure and common CV risk factors. Further studies are needed to determine if vitamin K supplementation can have a positive effect on renal vascular stiffness and kidney function.

Inactive Matrix Gla-Protein is associated with arterial stiffness in an adult population-based study

Increased pulse wave velocity (PWV) is a marker of aortic stiffness and an independent predictor of mortality. Matrix Gla-protein (MGP) is a vascular calcification inhibitor that needs vitamin K to be activated. Inactive MGP, known as desphospho-uncarboxylated MGP (dp-ucMGP), can be measured in plasma and has been associated with various cardiovascular markers, cardiovascular outcomes, and mortality. In this study, we hypothesized that high levels of dp-ucMGP are associated with increased PWV. We recruited participants via a multicenter family-based cross-sectional study in Switzerland. Dp-ucMGP was quantified in plasma by sandwich ELISA. Aortic PWV was determined by applanation tonometry using carotid and femoral pulse waveforms. Multiple regression analysis was performed to estimate associations between PWV and dp-ucMGP adjusting for age, renal function, and other cardiovascular risk factors. We included 1001 participants in our analyses (475 men and 526 women). Mean values were 7.87±2.10 m/s for PWV and 0.43±0.20 nmol/L for dp-ucMGP. PWV was positively associated with dp-ucMGP both before and after adjustment for sex, age, body mass index, height, systolic and diastolic blood pressure (BP), heart rate, renal function, low- and high-density lipoprotein, glucose, smoking status, diabetes mellitus, BP and cholesterol lowering drugs, and history of cardiovascular disease (P≤0.01). In conclusion, high levels of dp-ucMGP are independently and positively associated with arterial stiffness after adjustment for common cardiovascular risk factors, renal function, and age. Experimental studies are needed to determine whether vitamin K supplementation slows arterial stiffening by increasing MGP carboxylation.

Response of the Thermal Conductivity as a Function of Water Content of a Burnt Mediterranean Loam Soil

The purpose of this research is to explore the variability on the soil thermal conductivity -λ- after a prescribe fire, and to assess the effects of the ashes on the heat transfer once it"s were incorporated into the soil matrix. Sampling plot was located in the Montgrí Massif (NE of Spain). A set of 42 soil samples between surface and 5 cm depth was collected before and after the fire. To characterize the soil chemical and physical variables were analyzed. To determine the vari-ability on the soil λ a dry-out curve per scenario (before and after fire) was determined. SoilRho® method based on ASTM D-5334-08 which was validated by LabFerrer was used. Soil thermal conductivity has shown changes in their values. Indeed, in all moisture scenarios the values of soil λ decreased after soil was burnt. The critical point in the rela-tionship ϴ (λ) for the soil after fire which always was stronger than soil before to be burnt. Soil with"white" ashes showed a high thermal conductivity. An X-Ray diffractometry analysis allowed to clarify and to verify these results. To sum up, we could say that thermal conductivity presents changes when the scenario changes, i.e. before and after to be burnt. On the other hand, the volume of ashes incorporated on the soil increased the differences between no burnt and burnt soil, showing even some improvements on the heat transfer when water content started to govern the process.

Planarians as a model to assess in vivo the role of matrix metalloproteinase genes during homeostasis and regeneration

Matrix metalloproteinases (MMPs) are major executors of extracellular matrix remodeling and, consequently, play key roles in the response of cells to their microenvironment. The experimentally accessible stem cell population and the robust regenerative capabilities of planarians offer an ideal model to study how modulation of the proteolytic system in the extracellular environment affects cell behavior in vivo. Genome-wide identification of Schmidtea mediterranea MMPs reveals that planarians possess four mmp-like genes. Two of them (mmp1 and mmp2) are strongly expressed in a subset of secretory cells and encode putative matrilysins. The other genes (mt-mmpA and mt-mmpB) are widely expressed in postmitotic cells and appear structurally related to membrane-type MMPs. These genes are conserved in the planarian Dugesia japonica. Here we explore the role of the planarian mmp genes by RNA interference (RNAi) during tissue homeostasis and regeneration. Our analyses identify essential functions for two of them. Following inhibition of mmp1 planarians display dramatic disruption of tissues architecture and significant decrease in cell death. These results suggest that mmp1 controls tissue turnover, modulating survival of postmitotic cells. Unexpectedly, the ability to regenerate is unaffected by mmp1(RNAi). Silencing of mt-mmpA alters tissue integrity and delays blastema growth, without affecting proliferation of stem cells. Our data support the possibility that the activity of this protease modulates cell migration and regulates anoikis, with a consequent pivotal role in tissue homeostasis and regeneration. Our data provide evidence of the involvement of specific MMPs in tissue homeostasis and regeneration and demonstrate that the behavior of planarian stem cells is critically dependent on the microenvironment surrounding these cells. Studying MMPs function in the planarian model provides evidence on how individual proteases work in vivo in adult tissues. These results have high potential to generate significant information for development of regenerative and anti cancer therapies.

Analytical Dirac-Hartree-Fock-Slater screening function for atoms (Z=1-92)

An analytical approximation, depending on five parameters, for the atomic screening function is proposed. The corresponding electrostatic potential takes a simple analytical form (superposition of three Yukawa potentials) well suited to most practical applications. Parameters in the screening function, determined by an analytical fitting procedure to Dirac-Hartree-Fock-Slater (DHFS) self-consistent data, are given for Z=1¿92. The reliability of this analytical approach is demonstrated by showing that (a) Born cross sections for elastic scattering of fast charged particles by the present analytical field and by the DHFS field practically coincide and (b) one-electron binding energies computed from the independent-particle model with our analytical field (corrected for exchange and electrostatic self-interaction) agree closely with the DHFS energy eigenvalues.

Role of PheE15 gate in ligand entry and nitric oxide detoxification function of Mycobacterium tuberculosis truncated hemoglobin N

The truncated hemoglobin N, HbN, of Mycobacterium tuberculosis is endowed with a potent nitric oxide dioxygenase (NOD) activity that allows it to relieve nitrosative stress and enhance in vivo survival of its host. Despite its small size, the protein matrix of HbN hosts a two-branched tunnel, consisting of orthogonal short and long channels, that connects the heme active site to the protein surface. A novel dual-path mechanism has been suggested to drive migration of O(2) and NO to the distal heme cavity. While oxygen migrates mainly by the short path, a ligand-induced conformational change regulates opening of the long tunnel branch for NO, via a phenylalanine (PheE15) residue that acts as a gate. Site-directed mutagenesis and molecular simulations have been used to examine the gating role played by PheE15 in modulating the NOD function of HbN. Mutants carrying replacement of PheE15 with alanine, isoleucine, tyrosine and tryptophan have similar O(2)/CO association kinetics, but display significant reduction in their NOD function. Molecular simulations substantiated that mutation at the PheE15 gate confers significant changes in the long tunnel, and therefore may affect the migration of ligands. These results support the pivotal role of PheE15 gate in modulating the diffusion of NO via the long tunnel branch in the oxygenated protein, and hence the NOD function of HbN.

New approximation to the third-order density : application to the calculation of correlated multicenter indices

In this work we present the formulas for the calculation of exact three-center electron sharing indices (3c-ESI) and introduce two new approximate expressions for correlated wave functions. The 3c-ESI uses the third-order density, the diagonal of the third-order reduced density matrix, but the approximations suggested in this work only involve natural orbitals and occupancies. In addition, the first calculations of 3c-ESI using Valdemoro's, Nakatsuji's and Mazziotti's approximation for the third-order reduced density matrix are also presented for comparison. Our results on a test set of molecules, including 32 3c-ESI values, prove that the new approximation based on the cubic root of natural occupancies performs the best, yielding absolute errors below 0.07 and an average absolute error of 0.015. Furthemore, this approximation seems to be rather insensitive to the amount of electron correlation present in the system. This newly developed methodology provides a computational inexpensive method to calculate 3c-ESI from correlated wave functions and opens new avenues to approximate high-order reduced density matrices in other contexts, such as the contracted Schrödinger equation and the anti-Hermitian contracted Schrödinger equation

Nuclear Matrix in Apoptotic Cell Death and Cell Proliferation. The role of Nuclear Mitotic Apparatus (NuMA) Protein

The nucleus is a membrane enclosed organelle containing most of the genetic information of the cell in the form of chromatin. The nucleus, which can be divided into many sub-organelles such as the nucleoli, the Cajal bodies and the nuclear lamina, is the site for several essential cellular functions such as the DNA replication and its regulation and most of the RNA synthesis and processing. The nucleus is often affected in disease: the size and the shape of the nucleus, the chromatin distribution and the size of the nucleoli have remained the basis for the grading of several cancers. The maintenance of the vertebrate body shape depends on the skeleton. Similarly, in a smaller context, the shape of the cell and the nucleus are mainly regulated by the cytoskeletal and nucleoskeletal elements. The nuclear matrix, which by definition is a detergent, DNase and salt resistant proteinaceous nuclear structure, has been suggested to form the nucleoskeleton responsible for the nuclear integrity. Nuclear mitotic apparatus protein, NuMA, a component of the nuclear matrix, is better known for its mitotic spindle organizing function. NuMA is one of the nuclear matrix proteins suggested to participate in the maintenance of the nuclear integrity during interphase but its interphase function has not been solved to date. This thesis study concentrated on the role of NuMA and the nuclear matrix as structural and functional components of the interphase nucleus. The first two studies clarified the essential role of caspase-3 in the disintegration of the nuclear structures during apoptosis. The second study also showed NuMA and chromatin to co-elute from cells in significant amounts and the apoptotic cleavage of NuMA was clarified to have an important role in the dissociation of NuMA from the chromatin. The third study concentrated on the interphase function of NuMA showing NuMA depletion to result in cell cycle arrest and the cytoplasmic relocalization of NuMA interaction partner GAS41. We suggest that the relocalization of the transcription factor GAS41 may mediate the cell cycle arrest. Thus, this study has given new aspects in the interactions of NuMA, chromatin and the nuclear matrix.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

The regulation and function of collagenase-3 (MMP-13) in cutaneous wound healing and squamous cell carcinoma

Matrix metalloproteinase-13 (MMP-13) is a potent proteolytic enzyme, whose expression has been previously associated with fetal bone development and postnatal bone remodeling and with adult gingival wound healing. MMP-13 is also known to be involved in the growth and invasion of various cancers including squamous cell carcinoma (SCC) of the skin. The aim of this study was to further elucidate the function and regulation of MMP-13 in wound repair and cancer. In this study, it was shown that fetal skin fibroblasts express MMP-13 in response to transforming growth factor-β in a p38 MAP kinase dependent manner. In addition, MMP-13 was found to be expressed in vivo by wound fibroblasts in human fetal skin grafted on SCID mice. Adenovirally delivered expression of MMP-13 enhanced collagen matrix contraction by fibroblasts in vitro in association with altered cytoskeletal structure, enhanced proliferation and survival. These results indicate that MMP-13 is involved in cell-mediated collagen matrix remodeling and suggest a role for MMP-13 in superior matrix remodeling and scarless healing of fetal skin wounds. Using an MMP-13 deficient mouse strain, it was shown that MMP-13 is essential for the normal development of experimental granulation tissue in mice. MMP-13 was implicated in the regulation of myofibroblast function and angiogenesis and the expression of genes involved in cellular proliferation and movement, immune response, angiogenesis and proteolysis. Finally, epidermal mitogen, keratinocyte growth factor (KGF) was shown to suppress the malignant properties of skin SCC cells by downregulating the expression of several target genes with potential cancer promoting properties, including MMP-13, and by reducing SCC cell invasion. These results provide evidence that MMP-13 potently regulates cell viability, myofibroblast function and angiogenesis associated with wound healing and cancer. In addition, fibroblasts expressing MMP-13 show high collagen reorganization capacity. Moreover, the results suggest that KGF mediates the anti-cancer effects on skin SCC

The Structure and Function of αI Domains in Collagen Receptor and Leukocyte Integrins

Integrins are heterodimeric, signaling transmembrane adhesion receptors that connect the intracellular actin microfilaments to the extracellular matrix composed of collagens and other matrix molecules. Bidirectional signaling is mediated via drastic conformational changes in integrins. These changes also occur in the integrin αI domains, which are responsible for ligand binding by collagen receptor and leukocyte specific integrins. Like intact integrins, soluble αI domains exist in the closed, low affinity form and in the open, high affinity form, and so it is possible to use isolated αI domains to study the factors and mechanisms involved in integrin activation/deactivation. Integrins are found in all mammalian tissues and cells, where they play crucial roles in growth, migration, defense mechanisms and apoptosis. Integrins are involved in many human diseases, such as inflammatory, cardiovascular and metastatic diseases, and so plenty of effort has been invested into developing integrin specific drugs. Humans have 24 different integrins, four of which are collagen receptor (α1β1, α2β1, α10β1, α11β1) and five leukocyte specific integrins (αLβ2, αMβ2, αXβ2, αDβ2, αEβ7). These two integrin groups are quite unselective having both primary and secondary ligands. This work presents the first systematic studies performed on these integrin groups to find out how integrin activation affects ligand binding and selectivity. These kinds of studies are important not only for understanding the partially overlapping functions of integrins, but also for drug development. In general, our results indicated that selectivity in ligand recognition is greatly reduced upon integrin activation. Interestingly, in some cases the ligand binding properties of integrins have been shown to be cell type specific. The reason for this is not known, but our observations suggest that cell types with a higher integrin activation state have lower ligand selectivity, and vice versa. Furthermore, we solved the three-dimensional structure for the activated form of the collagen receptor α1I domain. This structure revealed a novel intermediate conformation not previously seen with any other integrin αI domain. This is the first 3D structure for an activated collagen receptor αI domain without ligand. Based on the differences between the open and closed conformation of the αI domain we set structural criteria for a search for effective collagen receptor drugs. By docking a large number of molecules into the closed conformation of the α2I domain we discovered two polyketides, which best fulfilled the set structural criteria, and by cell adhesion studies we showed them to be specific inhibitors of the collagen receptor integrins.

Functions of the extracellular matrix and matrix degrading proteases during tumor progression

Cell interactions with extracellular matrices are important to pathological changes that occur during cell transformation and tumorigenesis. Several extracellular matrix proteins including fibronectin, thrombospondin-1, laminin, SPARC, and osteopontin have been suggested to modulate tumor phenotype by affecting cell migration, survival, or angiogenesis. Likewise, proteases including the matrix metalloproteinases (MMPs) are understood to not only facilitate migration of cells by degradation of matrices, but also to affect tumor formation and growth. We have recently demonstrated an in vivo role for the RGD-containing protein, osteopontin, during tumor progression, and found evidence for distinct functions in the host versus the tumor cells. Because of the compartmentalization and temporal regulation of MMP expression, it is likely that MMPs may also function dually in host stroma and the tumor cell. In addition, an important function of proteases appears to be not only degradation, but also cleavage of matrix proteins to generate functionally distinct fragments based on receptor binding, biological activity, or regulation of growth factors.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.