Immunolocalization of a PIGR-like Protein in Tetrahymena thermophila

Netrins are pleiotropic signaling molecules which guide axonal development and help regulate processes such as angiogenesis. Netrins can act as chemorepellents for developing axons, and our previous work has shown that several netrins, including netrin-1, netrin-3, and netrin-4, are chemorepellents in Tetrahymena thermophila. In vertebrates, netrin-1 signals through several receptors, including those in the UNC-5 family. UNC-5 family proteins often signal through the src family of tyrosine kinases. We have previously characterized UNC-5 and src-like proteins in Tetrahymena, by immunolocalization and Western blotting. Sequencing of our src-like proteins gave a number of homologous sequences, including the sequence for polymeric immunoglobulin-like receptor (PIGR). With all of these findings in mind, we hypothesized that Tetrahymena might possess a receptor similar to PIGR, which would localize either to the plasma membrane or cilia of Tetrahymena

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions

Biochemical Evidence for Netrin-Signaling Homologues in Tetrahymena thermophila

Netrins are pleiotropic guidance proteins that are involved in developmental signaling of branched structures within vertebrates. However, like many developmental pathways, dysregulation of the netrin pathway has been implicated in cancer progression and metastasis. Since Tetrahymena respond to guidance proteins, showing chemoattractant and chemorepellent behavior, we hypothesized that we could use these organisms as a model system for cancer signaling. We have previously found that netrin-1-peptided, netrin-3-peptide, and recombinant netrin-4 are all chemorepellents in this organism. Since netrin-1-peptide signals through a tyrosine kinase in Tetrahymena, we hypothesized that Tetrahymena might possess tyrosine kinases as well as a receptor homologous to UNC-5, a netrin receptor which relays signals via tyrosine kinases in vertebrates. Using immunoprecipitation with a polyclonal anti-UNC-5-B antibody, we purified a 250 kD protein from Tetrahymena whole cell extract. Similarly, we immunoprecipitated several proteins, including a 60 kD protein and a 75 kD protein using a polyclonal anti-src-antibody. Our purified samples were sent out for identification by mass spectroscopy. Mass spectroscopy indicated that we have purified a number of novel peptides not currently found in the Tetrahymena Genome Database. Our data indicate that the proteome database in this organism is incomplete, and that there are additional proteins waiting to be discovered in this organism

Human Systems Integration in the Federal Government

Human Systems Integration principles and methods can be used to help integrate people, technology, and organizations in an effective and efficient manner. Over the past decade, a wide range of tools, techniques, and technologies have been developed by federal agencies to achieve significant cost and performance benefits. In this discussion, we will explore trends in military human systems integration and learn about the critical role being played by human performance and effectiveness research. We will also examine case studies on the planning and design of future human space flight vehicles, the national air space system and the first nuclear reactors to be built in the United States in over 30 years. And with an eye toward sustaining the discipline s principles and methods, we ll take a look at educating and training the next generation of human systems integration practitioners

Mapping between dissipative and Hamiltonian systems

Theoretical studies of nonequilibrium systems are complicated by the lack of a general framework. In this work we first show that a transformation introduced by Ao recently (J. Phys. A {\bf 37}, L25 (2004)) is related to previous works of Graham (Z. Physik B {\bf 26}, 397 (1977)) and Eyink {\it et al.} (J. Stat. Phys. {\bf 83}, 385 (1996)), which can also be viewed as the generalized application of the Helmholtz theorem in vector calculus. We then show that systems described by ordinary stochastic differential equations with white noise can be mapped to thermostated Hamiltonian systems. A steady-state of a dissipative system corresponds to the equilibrium state of the corresponding Hamiltonian system. These results provides a solid theoretical ground for corresponding studies on nonequilibrium dynamics, especially on nonequilibrium steady state. The mapping permits the application of established techniques and results for Hamiltonian systems to dissipative non-Hamiltonian systems, those for thermodynamic equilibrium states to nonequilibrium steady states. We discuss several implications of the present work.Comment: 18 pages, no figure. final version for publication on J. Phys. A: Math & Theo

Macroscopic fluctuation theory

Stationary non-equilibrium states describe steady flows through macroscopic systems. Although they represent the simplest generalization of equilibrium states, they exhibit a variety of new phenomena. Within a statistical mechanics approach, these states have been the subject of several theoretical investigations, both analytic and numerical. The macroscopic fluctuation theory, based on a formula for the probability of joint space-time fluctuations of thermodynamic variables and currents, provides a unified macroscopic treatment of such states for driven diffusive systems. We give a detailed review of this theory including its main predictions and most relevant applications.Comment: Review article. Revised extended versio

Joint-action coordination in transferring objects

Here we report a study of joint-action coordination in transferring objects. Fourteen dyads were asked to repeatedly reposition a cylinder in a shared workspace without using dialogue. Variations in task constraints concerned the size of the two target regions in which the cylinder had to be (re)positioned and the size and weight of the transferred cylinder. Movements of the wrist, index finger and thumb of both actors were recorded by means of a 3D motion-tracking system. Data analyses focused on the interpersonal transfer of lifting-height and movement-speed variations. Whereas the analyses of variance did not reveal any interpersonal transfer effects targeted data comparisons demonstrated that the actor who fetched the cylinder from where the other actor had put it was systematically less surprised by cylinder-weight changes than the actor who was first confronted with such changes. In addition, a moderate, accuracy-constraint independent adaptation to each other’s movement speed was found. The current findings suggest that motor resonance plays only a moderate role in collaborative motor control and confirm the independency between sensorimotor and cognitive processing of action-related information

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio