Turgor Regulation via Cell Wall Adjustment in White Spruce1

Turgor regulation at reduced water contents was closely associated with changes in the elastic quality of the cell walls of individual needles and shoots of naturally drought-resistant seedlings of white spruce (Picea glauca [Moench] Voss.) and of seedlings of intermediate resistance that had been pretreated with paclobutrazol, a stress-protecting, synthetic plant-growth regulator. Paclobutrazol-treated seedlings showed marked increases in drought resistance, and pressure-volume analysis combined with Chardakov measurements confirmed observations that water stress was ameliorated during prolonged drought. Turgor was maintained in the paclobutrazol-treated and in the naturally resistant drought-stressed seedlings despite water contents near or below the turgor-loss volumes of well-watered controls. The maintenance of turgor in these seedlings was in large part a function of the dynamic process of cell wall adjustment, as reflected by marked reductions in both the saturated and turgor-loss volumes and by large increases in the elastic coefficients of the tissues. Shear and Young's moduli, calculated from pressure-volume curves and the radii and wall thicknesses of mesophyll cells, also confirmed observed changes in the elastic qualities of the cell walls. Elastic coefficients of well-watered, paclobutrazol-treated seedlings were consistently larger than those in well-watered controls and several times larger than the values in untreated plants, which succumbed rapidly to drought. In contrast, untreated seedlings that withstood prolonged drought without wilting displayed elastic coefficients similar to those in seedlings that had been treated with paclobutrazol but that had not been exposed to drought.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Uncovering BRCA1-regulated signalling pathways by microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has dramatically changed the way in which we now address basic biomedical questions. Expression profiling using microarrays facilitates an experimental approach where alterations in the transcript level of entire transcriptomes can be simultaneously assayed in response to defined stimuli. We have used microarray analysis to identify downstream transcriptional targets of the BRCA1 (Breast Cancer 1) tumour-suppressor gene as a means of defining its function. BRCA1 has been implicated in the predisposition to early onset breast and ovarian cancer and while its exact function remains to be defined, roles in DNA repair, cell-cycle control and transcriptional regulation have been implied. In the current study we have generated cell lines with tetracycline-regulated, inducible expression of BRCA1 as a tool to identify genes, which might represent important effectors of BRCA1 function. Oligonucleotide array-based expression profiling identified a number of genes that were upregulated at various times following inducible expression of BRCA1 including the DNA damage-responsive gene GADD45 (Growth Arrest after DNA Damage). Identified targets were confirmed by Northern blot analysis and their functional significance as BRCA1 targets examined.

Uncovering functionally relevant signaling pathways using microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has fundamentally altered the way in which we now address basic biomedical questions. Microarrays technology facilitates a more complete and inclusive experimental approach where alterations in the transcript level of entire genomes can be simultaneously assayed in response to a variety of stimuli. Conceptually different approaches to the development of microarray technology have resulted in the generation of two different array formats: oligonucleotide arrays and cDNA arrays. The application of microarray and related technologies to identify specific targets of defined genes that have clearly been implicated in cancer progression requires a specific experimental approach. The objective of tiffs approach is to define changes in transcriptional profile that occur in response to modulating the expression level of the gene to be studied. The resulting altered expression profile can then be viewed as a blueprint by which that gene effects its cellular function. We have used oligonucleotide array-based expression profiling in collaboration with Affymetrix to identify downstream transcriptional targets of the BRCA1 tumor-suppressor gene as a means of defining its function. BRCA1 has been implicated in at least three functional pathways, namely, mediating the cellular response to DNA damage, as a cell cycle checkpoint protein and in the regulation of transcription. The physiological significance of these properties and their implications for the function of BRCA1 as a tumor-suppressor gene remain to be defined.

The influence of various seat design parameters: a computational analysis

Nowadays, low back pain becomes a common healthcare problem. Poor or unsuitable seat design is related to the discomfort and other healthcare problems of users. The aim of this study is to investigate the influence of seat design variables on the compressive loadings of lumbar joints. A basis that includes a musculoskeletal human body model and a chair model has been developed using LifeMOD Biomechanics Modeller. Inverse and forward dynamic simulations have been performed for various seat design parameters. The results show that the inclination of backrest and seat pan may or may not decrease the compressive spinal joint forces, depending on other conditions. The medium-level height and depth of seat pan and the medium-level and high-level height of backrest are found to cause the minimum compressive loads on lumbar joints. This work contributes to a better understanding of sitting biomechanics and provides some useful guidelines for seat design.

Conifer defence against insects: microarray gene expression profiling of Sitka spruce (Picea sitchensis) induced by mechanical wounding or feeding by spruce budworms (Choristoneura occidentalis) or white pine weevils (Pissodes strobi) reveals large

Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant defence. Refined expression analysis using gene-specific primers and real-time PCR for selected transcripts was in agreement with microarray results for most genes tested. This study provides the first large-scale survey of insect-induced defence transcripts in a gymnosperm and provides a platform for functional investigation of plant-insect interactions in spruce. Induction of spruce genes of octadecanoid and ethylene signalling, terpenoid biosynthesis, and phenolic secondary metabolism are discussed in more detail.

Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis

Systems-level identification and analysis of cellular circuits in the brain will require the development of whole-brain imaging with single-cell resolution. To this end, we performed comprehensive chemical screening to develop a whole-brain clearing and imaging method, termed CUBIC (clear, unobstructed brain imaging cocktails and computational analysis). CUBIC is a simple and efficient method involving the immersion of brain samples in chemical mixtures containing aminoalcohols, which enables rapid whole-brain imaging with single-photon excitation microscopy. CUBIC is applicable to multicolor imaging of fluorescent proteins or immunostained samples in adult brains and is scalable from a primate brain to subcellular structures. We also developed a whole-brain cell-nuclear counterstaining protocol and a computational image analysis pipeline that, together with CUBIC reagents, enable the visualization and quantification of neural activities induced by environmental stimulation. CUBIC enables time-course expression profiling of whole adult brains with single-cell resolution.

Computational analysis of proteome of H5N1 avian influenza virus to define T cell epitopes with vaccine potential

The existing vaccines against influenza are based on the generation of neutralizing antibody primarily directed against surface proteins-hernagglutinin and neuraminidase. In this work, we have computationally defined conserved T cell epitopes of proteins of influenza virus H5N1 to help in the design of a vaccine with haplotype specificity for a target population. The peptides from the proteome of H5NI irus which are predicted to bind to different HLAs, do not show similarity with peptides of human proteorne and are also identified to be generated by proteolytic cleavage. These peptides could be made use of in the design of either a DNA vaccine or a subunit vaccine against V influenza. (c) 2007 Elsevier Ltd. All rights reserved.

RNA expression analysis from formalin fixed paraffin embedded tissues

Formalin fixation and paraffin embedding (FFPE) is the most commonly used method worldwide for tissue storage. This method preserves the tissue integrity but causes extensive damage to nucleic acids stored within the tissue. As methods for measuring gene expression such as RT-PCR and microarray are adopted into clinical practice there is an increasing necessity to access the wealth of information locked in the Formalin fixation and paraffin embedding archives. This paper reviews the progress in this field and discusses the unique opportunities that exist for the application of these techniques in the development of personalized medicine.

Structural studies of prephenate dehydratase from Mycobacterium tuberculosis H37Rv by SAXS, ultracentrifugation, and computational analysis

Tuberculosis (TB) is one of the most common infectious diseases known to man and responsible for millions of human deaths in the world. The increasing incidence of TB in developing countries, the proliferation of multidrug resistant strains, and the absence of resources for treatment have highlighted the need of developing new drugs against TB. The shikimate pathway leads to the biosynthesis of chorismate, a precursor of aromatic amino acids. This pathway is absent from mammals and shown to be essential for the survival of Mycobacterium tuberculosis, the causative agent of TB. Accordingly, enzymes of aromatic amino acid biosynthesis pathway represent promising targets for structure-based drug design. The first reaction in phenylalanine biosynthesis involves the conversion of chorismate to prephenate, catalyzed by chorismate mutase. The second reaction is catalyzed by prephenate dehydratase (PDT) and involves decarboxylation and dehydratation of prephenate to form phenylpyruvate, the precursor of phenylalanine. Here, we describe utilization of different techniques to infer the structure of M. tuberculosis PDT (MtbPDT) in solution. Small angle X-ray scattering and ultracentrifugation analysis showed that the protein oligomeric state is a tetramer and MtbPDT is a flat disk protein. Bioinformatics tools were used to infer the structure of MtbPDT A molecular model for MtbPDT is presented and molecular dynamics simulations indicate that MtbPDT i.s stable. Experimental and molecular modeling results were in agreement and provide evidence for a tetrameric state of MtbPDT in solution.

Structural studies of prephenate dehydratase from Mycobacterium tuberculosis H37Rv by SAXS, ultracentrifugation, and computational analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

COMPUTATIONAL ANALYSIS OF THE AEROELASTIC DYNAMICS OF A WIND TURBINE BLADE WITH VARIABLE-SPEED STALL CONTROL

The accuracy of simulating the aerodynamics and structural properties of the blades is crucial in the wind-turbine technology. Hence the models used to implement these features need to be very precise and their level of detailing needs to be high. With the variety of blade designs being developed the models should be versatile enough to adapt to the changes required by every design. We are going to implement a combination of numerical models which are associated with the structural and the aerodynamic part of the simulation using the computational power of a parallel HPC cluster. The structural part models the heterogeneous internal structure of the beam based on a novel implementation of the Generalized Timoshenko Beam Model Technique.. Using this technique the 3-D structure of the blade is reduced into a 1-D beam which is asymptotically equivalent. This reduces the computational cost of the model without compromising its accuracy. This structural model interacts with the Flow model which is a modified version of the Blade Element Momentum Theory. The modified version of the BEM accounts for the large deflections of the blade and also considers the pre-defined structure of the blade. The coning, sweeping of the blade, tilt of the nacelle and the twist of the sections along the blade length are all computed by the model which aren’t considered in the classical BEM theory. Each of these two models provides feedback to the other and the interactive computations lead to more accurate outputs. We successfully implemented the computational models to analyze and simulate the structural and aerodynamic aspects of the blades. The interactive nature of these models and their ability to recompute data using the feedback from each other makes this code more efficient than the commercial codes available. In this thesis we start off with the verification of these models by testing it on the well-known benchmark blade for the NREL-5MW Reference Wind Turbine, an alternative fixed-speed stall-controlled blade design proposed by Delft University, and a novel alternative design that we proposed for a variable-speed stall-controlled turbine, which offers the potential for more uniform power control and improved annual energy production.. To optimize the power output of the stall-controlled blade we modify the existing designs and study their behavior using the aforementioned aero elastic model.

Asymptotic and computational analysis of mistuning effects on the dynamics of bladed disks

Es bien conocido que las pequeñas imperfecciones existentes en los álabes de un rótor de turbomaquinaria (conocidas como “mistuning”) pueden causar un aumento considerable de la amplitud de vibración de la respuesta forzada y, por el contrario, tienen típicamente un efecto beneficioso en el flameo del rótor. Para entender estos efectos se pueden llevar a cabo estudios numéricos del problema aeroelástico completo. Sin embargo, el cálculo de “mistuning” usando modelos de alta resolución es una tarea difícil de realizar, ya que los modelos necesarios para describir de manera precisa el componente de turbomáquina (por ejemplo rotor) tienen, necesariamente, un número muy elevado de grados de libertad, y, además, es necesario hacer un estudio estadístico para poder explorar apropiadamente las distribuciones posibles de “mistuning”, que tienen una naturaleza aleatoria. Diferentes modelos de orden reducido han sido desarrollados en los últimos años para superar este inconveniente. Uno de estos modelos, llamado “Asymptotic Mistuning Model (AMM)”, se deriva de la formulación completa usando técnicas de perturbaciones que se basan en que el “mistuning” es pequeño. El AMM retiene sólo los modos relevantes para describir el efecto del mistuning, y permite identificar los mecanismos clave involucrados en la amplificación de la respuesta forzada y en la estabilización del flameo. En este trabajo, el AMM se usa para estudiar el efecto del “mistuning” de la estructura y de la amortiguación sobre la amplitud de la respuesta forzada. Los resultados obtenidos son validados usando modelos simplificados del rotor y también otros de alta definición. Además, en el marco del proyecto europeo FP7 "Flutter-Free Turbomachinery Blades (FUTURE)", el AMM se aplica para diseñar distribuciones de “mistuning” intencional: (i) una que anula y (ii) otra que reduce a la mitad la amplitud del flameo de un rotor inestable; y las distribuciones obtenidas se validan experimentalmente. Por último, la capacidad de AMM para predecir el comportamiento de flameo de rotores con “mistuning” se comprueba usando resultados de CFD detallados. Abstract It is well known that the small imperfections of the individual blades in a turbomachinery rotor (known as “mistuning”) can cause a substantial increase of the forced response vibration amplitude, and it also typically results in an improvement of the flutter vibration characteristics of the rotor. The understanding of these phenomena can be attempted just by performing numerical simulations of the complete aeroelastic problem. However, the computation of mistuning cases using high fidelity models is a formidable task, because a detailed model of the whole rotor has to be considered, and a statistical study has to be carried out in order to properly explore the effect of the random mistuning distributions. Many reduced order models have been developed in recent years to overcome this barrier. One of these models, called the Asymptotic Mistuning Model (AMM), is systematically derived from the complete bladed disk formulation using a consistent perturbative procedure that exploits the smallness of mistuning to simplify the problem. The AMM retains only the essential system modes that are involved in the mistuning effect, and it allows to identify the key mechanisms of the amplification of the forced response amplitude and the flutter stabilization. In this work, AMM methodolgy is used to study the effect of structural and damping mistuning on the forced response vibration amplitude. The obtained results are verified using a one degree of freedom model of a rotor, and also high fidelity models of the complete rotor. The AMM is also applied, in the frame of the European FP7 project “Flutter-Free Turbomachinery Blades (FUTURE)”, to design two intentional mistuning patterns: (i) one to complete stabilize an unstable rotor, and (ii) other to approximately reduce by half its flutter amplitude. The designed patterns are validated experimentally. Finally, the ability of AMM to predict the flutter behavior of mistuned rotors is checked against numerical, high fidelity CFD results.

Telomere length and replicative aging in human vascular tissues.

Because repeated injury of the endothelium and subsequent turnover of intimal and medial cells have been implicated in atherosclerosis, we examined telomere length, a marker of somatic cell turnover, in cells from these tissues. Telomere lengths were assessed by Southern analysis of terminal restriction fragments (TRFs) generated by HinfI/Rsa I digestion of human genomic DNA. Mean TRF length decreased as a function of population doublings in human endothelial cell cultures from umbilical veins, iliac arteries, and iliac veins. When endothelial cells were examined for mean TRF length as a function of donor age, there was a significantly greater rate of decrease for cells from iliac arteries than from iliac veins (102 bp/yr vs. 47 bp/yr, respectively, P < 0.05), consistent with higher hemodynamic stress and increased cell turnover in arteries. Moreover, the rate of telomere loss as a function of donor age was greater in the intimal DNA of iliac arteries compared to that of the internal thoracic arteries (147 bp/yr vs. 87 bp/yr, respectively, P < 0.05), a region of the arterial tree subject to less hemodynamic stress. This indicates that the effect is not tissue specific. DNA from the medial tissue of the iliac and internal thoracic arteries showed no significant difference in the rates of decrease, suggesting that chronic stress leading to cellular senescence is more pronounced in the intima than in the media. These observations extend the use of telomere size as a marker for the replicative history of cells and are consistent with a role for focal replicative senescence in cardiovascular diseases.