STEM CELL GROWTH AND DIFFERENTIATION IN HYDRA ATTENUATA

The differentiation of nerve cells and nematocytes from interstitial stem cells in Hydra has been investigated under conditions of changing stem cell density. Interstitial stem cells were cultured in a feeder layer system consisting of aggregates of nitrogen mustard-inactivated tissue. The aggregates were seeded with varying numbers of stem cells from 10 to 400 per aggregate; between 4 and 7 days later the rates of nerve and nematocyte differentiation were measured. Nerve differentiation was scored by labelling the stem cell population with [3H]-thymidine and counting nests of 4 proliferating nematoblasts. In both cases the numbers of differentiating cells were normalized to the size of the stem cell population. The results indicate that the rate of nematocyte differentiation increases as the concentration of stem cells increases in aggregates; under the same conditions the rate of nerve differentiation remains essentially constant. To calculate the numbers of stem cells entering each pathway per generation, a computer was programmed to simulate the growth and differentiation of interstitial stem cells. Standard curves were prepared from the simulations relating the rates of nerve and nematocyte differentiation to the fraction of stem cells committed to each pathway per generation. The rates of nerve and nematocyte commitment were then estimated from the experimentally observed rates of differentiation using the standard curves. The results indicate that nerve commitment remains constant at about 0.13 stem cells per generation over a wide range of stem cell concentration. Nematocyte commitment, by comparison, increases from 0.15 to 0.21 stem cells per generation as stem cell concentration increases in aggregates. The fact that the ratio of nerve to nematocyte commitment changes under our conditions suggests that stem cell commitment is not a stochastic process but subject to control by environmental stimuli

Ubiquity of synonymity: almost all large binary trees are not uniquely identified by their spectra or their immanantal polynomials

There are several common ways to encode a tree as a matrix, such as the adjacency matrix, the Laplacian matrix (that is, the infinitesimal generator of the natural random walk), and the matrix of pairwise distances between leaves. Such representations involve a specific labeling of the vertices or at least the leaves, and so it is natural to attempt to identify trees by some feature of the associated matrices that is invariant under relabeling. An obvious candidate is the spectrum of eigenvalues (or, equivalently, the characteristic polynomial). We show for any of these choices of matrix that the fraction of binary trees with a unique spectrum goes to zero as the number of leaves goes to infinity. We investigate the rate of convergence of the above fraction to zero using numerical methods. For the adjacency and Laplacian matrices, we show that that the {\em a priori} more informative immanantal polynomials have no greater power to distinguish between trees

The Yield Curve Slope and Monetary Policy Innovations

We separate changes of the federal funds rate into two components; one reflects the Fed's superior forecasts about the state of the economy and the other component reflects the Fed's reaction to the public's forecast about the state of the economy. Romer and Romer (2000) found that the Fed reveals information about inflation when it tightens monetary policy. Their research has implications for measuring monetary policy as well. When the Fed raises short-term interest rates it leads to some combination of increased inflationary expectations and an increased real rate. In this paper we estimate a structural VAR that allows us to separate out (identify) components of federal funds changes that are due to inflationary expectations (thus neutral) and that part which is contractionary. Our measure of monetary policy is the part of federal funds changes that exclude the Fed's revelation of its asymmetric information about future inflation.Monetary policy, Yield curve, Inflation, Price puzzle

Earth orbital teleoperator visual system evaluation program

Visual system parameters and stereoptic television component geometries were evaluated for optimum viewing. The accuracy of operator range estimation using a Fresnell stereo television system with a three dimensional cursor was examined. An operator's ability to align three dimensional targets using vidicon tube and solid state television cameras as part of a Fresnell stereoptic system was evaluated. An operator's ability to discriminate between varied color samples viewed with a color television system was determined

Predicting B Cell Receptor Substitution Profiles Using Public Repertoire Data

B cells develop high affinity receptors during the course of affinity maturation, a cyclic process of mutation and selection. At the end of affinity maturation, a number of cells sharing the same ancestor (i.e. in the same "clonal family") are released from the germinal center, their amino acid frequency profile reflects the allowed and disallowed substitutions at each position. These clonal-family-specific frequency profiles, called "substitution profiles", are useful for studying the course of affinity maturation as well as for antibody engineering purposes. However, most often only a single sequence is recovered from each clonal family in a sequencing experiment, making it impossible to construct a clonal-family-specific substitution profile. Given the public release of many high-quality large B cell receptor datasets, one may ask whether it is possible to use such data in a prediction model for clonal-family-specific substitution profiles. In this paper, we present the method "Substitution Profiles Using Related Families" (SPURF), a penalized tensor regression framework that integrates information from a rich assemblage of datasets to predict the clonal-family-specific substitution profile for any single input sequence. Using this framework, we show that substitution profiles from similar clonal families can be leveraged together with simulated substitution profiles and germline gene sequence information to improve prediction. We fit this model on a large public dataset and validate the robustness of our approach on an external dataset. Furthermore, we provide a command-line tool in an open-source software package (https://github.com/krdav/SPURF) implementing these ideas and providing easy prediction using our pre-fit models.Comment: 23 page

A Bayesian phylogenetic hidden Markov model for B cell receptor sequence analysis.

The human body generates a diverse set of high affinity antibodies, the soluble form of B cell receptors (BCRs), that bind to and neutralize invading pathogens. The natural development of BCRs must be understood in order to design vaccines for highly mutable pathogens such as influenza and HIV. BCR diversity is induced by naturally occurring combinatorial "V(D)J" rearrangement, mutation, and selection processes. Most current methods for BCR sequence analysis focus on separately modeling the above processes. Statistical phylogenetic methods are often used to model the mutational dynamics of BCR sequence data, but these techniques do not consider all the complexities associated with B cell diversification such as the V(D)J rearrangement process. In particular, standard phylogenetic approaches assume the DNA bases of the progenitor (or "naive") sequence arise independently and according to the same distribution, ignoring the complexities of V(D)J rearrangement. In this paper, we introduce a novel approach to Bayesian phylogenetic inference for BCR sequences that is based on a phylogenetic hidden Markov model (phylo-HMM). This technique not only integrates a naive rearrangement model with a phylogenetic model for BCR sequence evolution but also naturally accounts for uncertainty in all unobserved variables, including the phylogenetic tree, via posterior distribution sampling

Data acquisition and path selection decision making for an autonomous roving vehicle

Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data

Venetian Song

https://digitalcommons.library.umaine.edu/mmb-ps/3110/thumbnail.jp