General Rotorcraft Aeromechanical Stability Program (GRASP) version 1.03: User's manual

The Rotorcraft Dynamics Division, Aeroflightdynamics Directorate, U.S. Army Aviation Research and Technology Activity has developed the General Rotorcraft Aeromechanical Stability Program (GRASP) to perform calculations that will assess the stability of rotorcraft in hovering flight and ground contact conditions. The program is designed to be state-of-the-art, hybrid, finite-element/multibody code that can be applied to all existing and future helicopter configurations. While GRASP was specifically designed to solve rotorcraft stability problems, its innovative structure and formulation allow for application to a wide range of structures. This manual describes the preparation of the input file required by Version 1.03 of GRASP, the procedures used to invoke GRASP on the NASA Ames Research Center CRAY X-MP 48 computer, and the interpretation of the output produced by GRASP. The parameters used by the input file are defined, and summaries of the input file and the job control language are included

Analytical modeling of helicopter static and dynamic induced velocity in GRASP

The methodology used by the General Rotorcraft Aeromechanical Stability Program (GRASP) to model the characteristics of the flow through a helicopter rotor in hovering or axial flight is described. Since the induced flow plays a significant role in determining the aeroelastic properties of rotorcraft, the computation of the induced flow is an important aspect of the program. Because of the combined finite-element/multibody methodology used as the basis for GRASP, the implementation of induced velocity calculations presented an unusual challenge to the developers. To preserve the modelling flexibility and generality of the code, it was necessary to depart from the traditional methods of computing the induced velocity. This is accomplished by calculating the actuator disc contributions to the rotor loads in a separate element called the air mass element, and then performing the calculations of the aerodynamic forces on individual blade elements within the aeroelastic beam element

A point collocation method for geometrically nonlinear membranes

AbstractThis paper describes the development of a numerical model for geometrically nonlinear membranes and evaluates its performance for membranes at static equilibrium. The scheme has several features not commonly seen in structural finite element analysis: the point collocation method, group formulation, and a staggered mesh. In the point collocation finite element method, the partial differential equations are solved at each node instead of by integrating over elements. The group formulation simplifies the handling of nonlinearities by interpolating the nonlinear products of variables, as opposed to seeking the product of independently interpolated variables. The domain is discretized with a staggered mesh of linear triangles and associated polygons. Two sequential gradient recovery operations are performed: first the gradients of the linear triangles are calculated and converted to stresses; then, polygon derivative shape functions derived in this paper are used to determine the internal forces from the stress gradients. The resulting system of nonlinear equations is solved with a Jacobian-free Newton–Krylov solver. The code is first verified using the patch test and the method of manufactured solutions. Then the results are validated using experimental data and benchmark code results in the literature for the Hencky problem (a circular membrane with a fixed perimeter and uniform inflation pressure). The observed rates of convergence for both displacement and radial strain were two. For the configurations and grids used in this investigation, the scheme was suitable for accurately predicting sub-hyperelastic deformations

General Rotorcraft Aeromechanical Stability Program (GRASP): Theory manual

The general rotorcraft aeromechanical stability program (GRASP) was developed to calculate aeroelastic stability for rotorcraft in hovering flight, vertical flight, and ground contact conditions. GRASP is described in terms of its capabilities and its philosophy of modeling. The equations of motion that govern the physical system are described, as well as the analytical approximations used to derive them. The equations include the kinematical equation, the element equations, and the constraint equations. In addition, the solution procedures used by GRASP are described. GRASP is capable of treating the nonlinear static and linearized dynamic behavior of structures represented by arbitrary collections of rigid-body and beam elements. These elements may be connected in an arbitrary fashion, and are permitted to have large relative motions. The main limitation of this analysis is that periodic coefficient effects are not treated, restricting rotorcraft flight conditions to hover, axial flight, and ground contact. Instead of following the methods employed in other rotorcraft programs. GRASP is designed to be a hybrid of the finite-element method and the multibody methods used in spacecraft analysis. GRASP differs from traditional finite-element programs by allowing multiple levels of substructure in which the substructures can move and/or rotate relative to others with no small-angle approximations. This capability facilitates the modeling of rotorcraft structures, including the rotating/nonrotating interface and the details of the blade/root kinematics for various types. GRASP differs from traditional multibody programs by considering aeroelastic effects, including inflow dynamics (simple unsteady aerodynamics) and nonlinear aerodynamic coefficients

A Heterogeneous In Vitro Three Dimensional Model of Tumour-Stroma Interactions Regulating Sprouting Angiogenesis

Angiogenesis, the formation of new blood vessels, is an essential process for tumour progression and is an area of significant therapeutic interest. Different in vitro systems and more complex in vivo systems have been described for the study of tumour angiogenesis. However, there are few human 3D in vitro systems described to date which mimic the cellular heterogeneity and complexity of angiogenesis within the tumour microenvironment. In this study we describe the Minitumour model – a 3 dimensional human spheroid-based system consisting of endothelial cells and fibroblasts in co-culture with the breast cancer cell line MDA-MB-231, for the study of tumour angiogenesis in vitro. After implantation in collagen-I gels, Minitumour spheroids form quantifiable endothelial capillary-like structures. The endothelial cell pre-capillary sprouts are supported by the fibroblasts, which act as mural cells, and their growth is increased by the presence of cancer cells. Characterisation of the Minitumour model using small molecule inhibitors and inhibitory antibodies show that endothelial sprout formation is dependent on growth factors and cytokines known to be important for tumour angiogenesis. The model also shows a response to anti-angiogenic agents similar to previously described in vivo data. We demonstrate that independent manipulation of the different cell types is possible, using common molecular techniques, before incorporation into the model. This aspect of Minitumour spheroid analysis makes this model ideal for high content studies of gene function in individual cell types, allowing for the dissection of their roles in cell-cell interactions. Finally, using this technique, we were able to show the requirement of the metalloproteinase MT1-MMP in endothelial cells and fibroblasts, but not cancer cells, for sprouting angiogenesis

Tissue Specific Profiling of Females of Schistosoma japonicum by Integrated Laser Microdissection Microscopy and Microarray Analysis

Schistosomes are parasitic worms responsible for important human diseases in tropical and developing nations. There is urgent need to develop new drugs and vaccines to augment current treatments for this disease. In recent years, concerted efforts by many laboratories have led to extensive genetic sequencing of the parasites, and the publication of genome sequence for two agents of schistosomiasis appears imminent. This genetic information has revealed many molecules expressed by the schistosome parasites for which no functional information is available. This lack of information extends to ignorance of where in the complex multicellular schistosome parasites the genes are expressed. We integrated two molecular and cellular techniques to address these knowledge gaps. We used laser microdissection microscopy to dissect small but highly important tissues involved in nutrition and reproduction from sections of female Schistosoma japonicum. From these dissected tissues we then used a broad molecular biology method to identify the multiple genes active in these tissues. Our approach has allowed us to formulate the basis of a “gene atlas” for schistosome parasites, defining the expression repertoire of specific tissues. The better understanding of the roles of tissues in parasite biology, especially in development, reproduction and interactions with its human hosts, should promote future investigations into pathogenesis and control of these significant parasites

Multizone Paper Platform for 3D Cell Cultures

In vitro 3D culture is an important model for tissues in vivo. Cells in different locations of 3D tissues are physiologically different, because they are exposed to different concentrations of oxygen, nutrients, and signaling molecules, and to other environmental factors (temperature, mechanical stress, etc). The majority of high-throughput assays based on 3D cultures, however, can only detect the average behavior of cells in the whole 3D construct. Isolation of cells from specific regions of 3D cultures is possible, but relies on low-throughput techniques such as tissue sectioning and micromanipulation. Based on a procedure reported previously (“cells-in-gels-in-paper” or CiGiP), this paper describes a simple method for culture of arrays of thin planar sections of tissues, either alone or stacked to create more complex 3D tissue structures. This procedure starts with sheets of paper patterned with hydrophobic regions that form 96 hydrophilic zones. Serial spotting of cells suspended in extracellular matrix (ECM) gel onto the patterned paper creates an array of 200 micron-thick slabs of ECM gel (supported mechanically by cellulose fibers) containing cells. Stacking the sheets with zones aligned on top of one another assembles 96 3D multilayer constructs. De-stacking the layers of the 3D culture, by peeling apart the sheets of paper, “sections” all 96 cultures at once. It is, thus, simple to isolate 200-micron-thick cell-containing slabs from each 3D culture in the 96-zone array. Because the 3D cultures are assembled from multiple layers, the number of cells plated initially in each layer determines the spatial distribution of cells in the stacked 3D cultures. This capability made it possible to compare the growth of 3D tumor models of different spatial composition, and to examine the migration of cells in these structures

Eukaryotic Protein Kinases (ePKs) of the Helminth Parasite Schistosoma mansoni

<p>Abstract</p> <p>Background</p> <p>Schistosomiasis remains an important parasitic disease and a major economic problem in many countries. The <it>Schistosoma mansoni </it>genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the <it>S. mansoni </it>predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets.</p> <p>Results</p> <p>We have identified 252 ePKs, which corresponds to 1.9% of the <it>S. mansoni </it>predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that <it>S. mansoni </it>has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in <it>S. mansoni </it>or belong to an expanded family in this parasite. Only 16 <it>S. mansoni </it>ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite.</p> <p>Conclusions</p> <p>Our approach has improved the functional annotation of 40% of <it>S. mansoni </it>ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of <it>S. mansoni </it>in response to diverse environments during the parasite development, vector interaction, and host infection.</p

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice