Modular cis-regulatory organization of Endo16, a gut-specific gene of the sea urchin embryo

The Endo16 gene of Strongylocentrotus purpuratus is expressed at the blastula stage of embryogenesis throughout the vegetal plate, at the gastrula stage in the whole of the archenteron and in postgastrular stages only in the midgut. We showed earlier that a 2300 bp upstream sequence suffices to faithfully recreate this pattern of expression when fused to a CAT reporter gene. Here we define the functional organization of this cis-regulatory domain, which includes over thirty high specificity binding sites, serviced by at least thirteen different putative transcription factors, in addition to >20 sites for a factor commonly found in the regulatory sequences of other sea urchin genes as well (SpGCF1). The Endo16 cis-regulatory domain consists of several different functional elements, or modules, each containing one or two unique DNA-binding factor target sites, plus sites for factors binding in other modules as well. Modular regulatory function was defined in experiments in which regions of the cis-regulatory DNA containing specific clusters of sites were tested in isolation, combined with one another, or by selective deletion, and the effects on expression of the CAT reporter were determined by whole-mount in situ hybridization or CAT enzyme activity measurements. The most proximal module (A) is mainly responsible for early embryonic expression, and module A alone suffices to locate expression in the vegetal plate and archenteron. The adjacent module (B) is responsible for a steep postgastrular rise in expression, when the gene is transcribed only in the midgut and, prior to this module B alone also suffices to promote expression in the vegetal plate and archenteron. The most distal module, G, acts as a booster for either A or B modules. However, no combination of A, B and G modules generates vegetal plate or gut expression exclusively. Ectopic expression of A-, B- and G-CAT fusion constructs occurs in the adjacent (veg1-derived) ectoderm and in skeletogenic mesenchyme cells. For expression to be confined to endoderm requires negative regulatory functions mediated by modules E, F and DC. Modules E and F each repress ectopic expression specifically in veg1 ectoderm. Module DC represses ectopic expression specifically in skeletogenic mesenchyme. Expression of some Endo16 constructs is dramatically increased by treatment with LiCl, which expands the territory in which the endogenous Endo16 gene is expressed at the expense of veg1 ectoderm. The same modules that act to repress ectopic expression in untreated embryos are required for enhanced expression of constructs after LiC1 treatment. Furthermore, both the negative spatial control functions and response to LiC1 require the presence of module A. The total regulatory requirements of the Endo16 gene during embryogenesis can be expressed in terms of the positive and negative functions of the individual modules and the interactions between modules that are identified in this study

Cis-regulatory logic in the endo16 gene: switching from a specification to a differentiation mode of control

The endo16 gene of Strongylocentrotus purpuratus encodes a secreted protein of the embryonic and larval midgut. The overall functional organization of the spatial and temporal control system of this gene are relatively well known from a series of earlier cis-regulatory studies. Our recent computational model for the logic operations of the proximal region of the endo16 control system (Module A) specifies the function of interactions at each transcription factor target site of Module A. Here, we extend sequence level functional analysis to the adjacent cis-regulatory region, Module B. The computational logic model is broadened to include B/A interactions as well as other Module B functions. Module B drives expression later in development and its major activator is responsible for a sharp, gut-specific increase in transcription after gastrulation. As shown earlier, Module B output undergoes a synergistic amplification that requires interactions within Module A. The interactions within Module B that are required to generate and transmit its output to Module A are identified. Logic considerations predicted an internal cis-regulatory switch by which spatial control of endo16 expression is shifted from Module A (early) to Module B (later). This prediction was confirmed experimentally and a distinct set of interactions in Module B that mediate the switch function was demonstrated. The endo16 computational model now provides a detailed explanation of the information processing functions executed by the cis-regulatory system of this gene throughout embryogenesis. Early in development the gene participates in the specification events that define the endomesoderm; later it functions as a gut-specific differentiation gene. The cis-regulatory switch mediates this functional change

Quantitative functional interrelations within the cis-regulatory system of the S. purpuratus Endo16 gene

Embryonic expression of the Endo16 gene of Strongylocentrotus purpuratus is controlled by interactions with at least 13 different DNA-binding factors. These interactions occur within a cis-regulatory domain that extends about 2300 bp upstream from the transcription start site. A recent functional characterization of this domain reveals six different subregions, or cis-regulatory modules, each of which displays a specific regulatory subfunction when linked with the basal promoter and in some cases various other modules (C.-H. Yuh and E. Davidson (1996) Development 122, 1069-1082). In the present work, we analyzed quantitative time-course measurements of the CAT enzyme output of embryos bearing expression constructs controlled by various Endo16 regulatory modules, either singly or in combination. Three of these modules function positively in that, in isolation, each is capable of promoting expression in vegetal plate and adjacent cell lineages, though with different temporal profiles of activity. Models for the mode of interaction of the three positive modules with one another were tested by assuming mathematical relations that would generate, from the measured single module time courses, the experimentally observed profiles of activity obtained when the relevant modules are physically linked in the same construct. The generated and observed time functions were compared, and the differences were minimized by least squares adjustment of a scale parameter. When the modules were tested in context of the endogenous promoter region, one of the positive modules (A) was found to increase the output of the others (B and G), by a constant factor. In contrast, a solution in which the time-course data of modules A and B are multiplied by one another was required for the interrelations of the positive modules when a minimal SV40 promoter was used. One interpretation is that, in this construct, each module independently stimulates the basal transcription complex. We used a similar approach to analyze the repressive activity of the three Endo16 cis-regulatory modules that act negatively in controlling spatial expression. The evidence obtained confirms that the repressive modules act only by affecting the output of module A (C.-H. Yuh and E. Davidson (1996) Development 122, 1069-1082). A new hierarchical model of the cis-regulatory system was formulated in which module A plays a central integrating role, and which also implies specific functions for certain DNA-binding sites within the basal promoter fragment of the gene. Additional kinetic experiments were then carried out, and key aspects of the model were confirmed

c-Myc induced changes in higher order rDNA structure accompany growth factor stimulation of quiescent cells

Human c-Myc is believed to be a high level coordinator of protein synthesis capacity and cell growth rate, capable of activating transcription by all three nuclear RNA Polymerases. Direct activation of rDNA transcription by c-Myc is functionally conserved in rat cells, despite high divergence in non-coding rDNA sequences, suggesting that this coordinating role is likely to be a general within mammals. Upon re-feeding of starved cells, c-Myc activity enhances the efficiency of RNA Polymerase I and SL1/TIF-1B recruitment to the rDNA and rapidly induces higher order gene loop structures in rDNA chromatin that juxtapose upstream and downstream rDNA sequences. Furthermore c-Myc induced gene-loop formation in rDNA genes occurs independently of rDNA transcription, implying that it may be an early step in the re-programming of quiescent cells as they enter the growth cycle

Variability and uncertainty in empirical ground-motion prediction for probabilistic hazard and risk analyses

© The Author(s) 2015.The terms aleatory variability and epistemic uncertainty mean different things to people who routinely use them within the fields of seismic hazard and risk analysis. This state is not helped by the repetition of loosely framed generic definitions that actually inaccurate. The present paper takes a closer look at the components of total uncertainty that contribute to ground-motion modelling in hazard and risk applications. The sources and nature of uncertainty are discussed and it is shown that the common approach to deciding what should be included within hazard and risk integrals and what should be pushed into logic tree formulations warrants reconsideration. In addition, it is shown that current approaches to the generation of random fields of ground motions for spatial risk analyses are incorrect and a more appropriate framework is presented

A Positioning Scheme Combining Location Tracking with Vision Assisting for Wireless Sensor Networks

This paper presents the performance of an adaptive location-estimation technique combining Kalman filtering (KF)with vision assisting for wireless sensor networks. For improving the accuracy of a location estimator, a KF procedureis employed at a mobile terminal to filter variations of the location estimate. Furthermore, using a vision-assistedcalibration technique, the proposed approach based on the normalized cross-correlation scheme is an accuracyenhancement procedure that effectively removes system errors causing uncertainty in real dynamic environments.Namely, according to the vision-assisted approach to extract the locations of the reference nodes as landmarks, a KFbasedapproach with the landmark information can calibrate the location estimation and reduce the corner effect of alocation-estimation system. In terms of the location accuracy estimated from the proposed approach, the experimentalresults demonstrate that more than 60 percent of the location estimates have error distances less than 1.4 meters in aZigBee positioning platform. As compared with the non-tracking algorithm and non-vision-assisted approach, theproposed algorithm can achieve reasonably good performance

Foldy-Wouthuysen transformation for a Dirac-Pauli dyon and the Thomas-Bargmann-Michel-Telegdi equation

The classical dynamics for a charged point particle with intrinsic spin is governed by a relativistic Hamiltonian for the orbital motion and by the Thomas-Bargmann-Michel-Telegdi equation for the precession of the spin. It is natural to ask whether the classical Hamiltonian (with both the orbital and spin parts) is consistent with that in the relativistic quantum theory for a spin-1/2 charged particle, which is described by the Dirac equation. In the low-energy limit, up to terms of the 7th order in $1/E_g$ ($E_g=2mc^2$ and $m$ is the particle mass), we investigate the Foldy-Wouthuysen (FW) transformation of the Dirac Hamiltonian in the presence of homogeneous and static electromagnetic fields and show that it is indeed in agreement with the classical Hamiltonian with the gyromagnetic ratio being equal to 2. Through electromagnetic duality, this result can be generalized for a spin-1/2 dyon, which has both electric and magnetic charges and thus possesses both intrinsic electric and magnetic dipole moments. Furthermore, the relativistic quantum theory for a spin-1/2 dyon with arbitrary values of the gyromagnetic and gyroelectric ratios can be described by the Dirac-Pauli equation, which is the Dirac equation with augmentation for the anomalous electric and anomalous magnetic dipole moments. The FW transformation of the Dirac-Pauli Hamiltonian is shown, up to the 7th order again, to be also in accord with the classical Hamiltonian.Comment: 18 page

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR)