Stochastic model of transcription factor-regulated gene expression

We consider a stochastic model of transcription factor (TF)-regulated gene expression. The model describes two genes: Gene A and Gene B which synthesize the TFs and the target gene proteins respectively. We show through analytic calculations that the TF fluctuations have a significant effect on the distribution of the target gene protein levels when the mean TF level falls in the highest sensitive region of the dose-response curve. We further study the effect of reducing the copy number of Gene A from two to one. The enhanced TF fluctuations yield results different from those in the deterministic case. The probability that the target gene protein level exceeds a threshold value is calculated with a knowledge of the probability density functions associated with the TF and target gene protein levels. Numerical simulation results for a more detailed stochastic model are shown to be in agreement with those obtained through analytic calculations. The relevance of these results in the context of the genetic disorder haploinsufficiency is pointed out. Some experimental observations on the haploinsufficiency of the tumour suppressor gene, Nkx3.1, are explained with the help of the stochastic model of TF-regulated gene expression.Comment: 17 pages, 11 figures. Accepted for publication in Physical Biolog

Bulk Flow and Shear Moments of the SFI++ Survey

We find the nine bulk--flow and shear moments from the SFI++ survey, as well as for subsamples of group and field galaxies. We constrain the velocity power spectrum shape parameter $\Gamma$ in linear theory using these moments. A likelihood function for $\Gamma$ was found after marginalizing over the power spectrum amplitude $\sigma_8\Omega_m^{0.6}$ using constraints obtained from comparisons between redshift surveys and peculiar velocity data. We have estimated the velocity noise $\sigma_*$ from the data since without it our results may be biased. We also performed a statistical analysis of the difference between the field and group catalogues and found that the results from each reflect the same underlying large scale flows. We found that we can constrain the power spectrum shape parameter to be $\Gamma=0.15^{+0.18}_{-0.08}$ for the groups catalogue and $\Gamma=0.09^{+0.04}_{-0.04}$ for the field galaxy catalogue in fair agreement with the value from WMAP

Crystallization of the C-terminal domain of the mouse brain cytosolic long-chain acyl-CoA thioesterase

The mammalian long-chain acyl-CoA thioesterase, the enzyme that catalyses the hydrolysis of acyl-CoAs to free fatty acids, contains two fused 4HBT (4-hydroxybenzoyl-CoA thioesterase) motifs. The C-terminal domain of the mouse long-chain acyl-CoA thioesterase (Acot7) has been expressed in bacteria and crystallized. The crystals were obtained by vapour diffusion using PEG 2000 MME as precipitant at pH 7.0 and 290 K. The crystals have the symmetry of space group R32 ( unit-cell parameters a = b = 136.83, c = 99.82 angstrom, gamma = 120 degrees). Two molecules are expected in the asymmetric unit. The crystals diffract to 2.4 angstrom resolution using the laboratory X-ray source and are suitable for crystal structure determination

Colour Relations in Form

The orthodox monadic determination thesis holds that we represent colour relations by virtue of representing colours. Against this orthodoxy, I argue that it is possible to represent colour relations without representing any colours. I present a model of iconic perceptual content that allows for such primitive relational colour representation, and provide four empirical arguments in its support. I close by surveying alternative views of the relationship between monadic and relational colour representation

Ras-mediated phosphorylation of a conserved threonine residue enhances the transactivation activities of c-Ets1 and c-Ets2

The Ras oncogene products regulate the expression of genes in transformed cells, and members of the Ets family of transcription factors have been implicated in this process. To determine which Ets factors are the targets of Ras signaling pathways, the abilities of several Ets factors to activate Ras-responsive enhancer (RRE) reporters in the presence of oncogenic Ras were examined. In transient transfection assay, reporters containing RREs composed of Ets-AP-1 binding sites could be activated 30-fold in NIH 3T3 fibroblasts and 80-fold in the macrophage-like line RAW264 by the combination of Ets1 or Ets2 and Ras but not by several other Ets factors that were tested in the assay. Ets2 and Ras also superactivated an RRE composed of Ets-Ets binding sites, but the Ets-responsive promoter of the c-fms gene was not superactivated. Mutation of a threonine residue to alanine in the conserved amino-terminal regions of Ets1 and Ets2 (threonine 38 and threonine 72, respectively) abrogated the ability of each of these proteins to superactivate reporter gene expression. Phosphoamino acid analysis of radiolabeled Ets2 revealed that Ras induced normally absent threonine-specific phosphorylation of the protein. The Ras-dependent increase in threonine phosphorylation was not observed in Ets2 proteins that had the conserved threonine 72 residue mutated to alanine or serine. These data indicate that Ets1 and Ets2 are specific nuclear targets of Ras signaling events and that phosphorylation of a conserved threonine residue is a necessary molecular component of Ras-mediated activation of these transcription factors

Hyperfine Coherence in the Presence of Spontaneous Photon Scattering

The coherence of a hyperfine-state superposition of a trapped $^{9}$Be$^+$ ion in the presence of off-resonant light is experimentally studied. It is shown that Rayleigh elastic scattering of photons that does not change state populations also does not affect coherence. Coherence times exceeding the average scattering time of 19 photons are observed. This result implies that, with sufficient control over its parameters, laser light can be used to manipulate hyperfine-state superpositions with very little decoherence.Comment: Letter, 4 figure

Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype phenotype correlations

We have generated a mouse carrying the human G551D mutation in the cystic fibrosis transmembrane conductance regulator gene (CFTR) by a one-step gene targeting procedure. These mutant mice show cystic fibrosis pathology but have a reduced risk of fatal intestinal blockage compared with 'null' mutants, in keeping with the reduced incidence of meconium ileus in G551D patients. The G551D mutant mice show greatly reduced CFTR-related chloride transport, displaying activity intermediate between that of cftr(mlUNC) replacement ('null') and cftr(mlHGU) insertional (residual activity) mutants and equivalent to approximately 4% of wild-type CFTR activity. The long-term survival of these animals should provide an excellent model with which to study cystic fibrosis, and they illustrate the value of mouse models carrying relevant mutations for examining genotype-phenotype correlations

An Automated Process for 2D and 3D Finite Element Overclosure and Gap Adjustment using Radial Basis Function Networks

In biomechanics, geometries representing complicated organic structures are consistently segmented from sparse volumetric data or morphed from template geometries resulting in initial overclosure between adjacent geometries. In FEA, these overclosures result in numerical instability and inaccuracy as part of contact analysis. Several techniques exist to fix overclosures, but most suffer from several drawbacks. This work introduces a novel automated algorithm in an iterative process to remove overclosure and create a desired minimum gap for 2D and 3D finite element models. The RBF Network algorithm was introduced by its four major steps to remove the initial overclosure. Additionally, the algorithm was validated using two test cases against conventional nodal adjustment. The first case compared the ability of each algorithm to remove differing levels of overclosure between two deformable muscles and the effects on mesh quality. The second case used a non-deformable femur and deformable distal femoral cartilage geometry with initial overclosure to test both algorithms and observe the effects on the resulting contact FEA. The RBF Network in the first case study was successfully able to remove all overclosures. In the second case, the nodal adjustment method failed to create a usable FEA model, while the RBF Network had no such issue. This work proposed an algorithm to remove initial overclosures prior to FEA that has improved performance over conventional nodal adjustment, especially in complicated situations and those involving 3D elements. The work can be included in existing FEA modeling workflows to improve FEA results in situations involving sparse volumetric segmentation and mesh morphing. This algorithm has been implemented in MATLAB, and the source code is publicly available to download at the following GitHub repository: https://github.com/thor-andreassen/femorsComment: 26 Pages, 5 Figures, 2 Table

Integration of Neural Architecture within a Finite Element Framework for Improved Neuromusculoskeletal Modeling

Neuromusculoskeletal (NMS) models can aid in studying the impacts of the nervous and musculoskeletal systems on one another. These computational models facilitate studies investigating mechanisms and treatment of musculoskeletal and neurodegenerative conditions. In this study, we present a predictive NMS model that uses an embedded neural architecture within a finite element (FE) framework to simulate muscle activation. A previously developed neuromuscular model of a motor neuron was embedded into a simple FE musculoskeletal model. Input stimulation profiles from literature were simulated in the FE NMS model to verify effective integration of the software platforms. Motor unit recruitment and rate coding capabilities of the model were evaluated. The integrated model reproduced previously published output muscle forces with an average error of 0.0435 N. The integrated model effectively demonstrated motor unit recruitment and rate coding in the physiological range based upon motor unit discharge rates and muscle force output. The combined capability of a predictive NMS model within a FE framework can aid in improving our understanding of how the nervous and musculoskeletal systems work together. While this study focused on a simple FE application, the framework presented here easily accommodates increased complexity in the neuromuscular model, the FE simulation, or both