Homophilic binding of PTP mu, a receptor-type protein tyrosine phosphatase, can mediate cell-cell aggregation

The receptor-like protein tyrosine phosphatase, PTPmu, displays structural similarity to cell-cell adhesion molecules of the immunoglobulin superfamily. We have investigated the ability of human PTPmu to function in such a capacity. Expression of PTPmu, with or without the PTPase domains, by recombinant baculovirus infection of Sf9 cells induced their aggregation. However, neither a chimeric form of PTPmu, containing the extracellular and transmembrane segments of the EGF receptor and the intracellular segment of PTPmu, nor the intracellular segment of PTPmu expressed as a soluble protein induced aggregation. PTPmu mediates aggregation via a homophilic mechanism, as judged by lack of incorporation of uninfected Sf9 cells into aggregates of PTPmu-expressing cells. Homophilic binding has been demonstrated between PTPmu-coated fluorescent beads (Covaspheres) and endogenously expressed PTPmu on MvLu cells. Additionally the PTPmu-coated beads specifically bound to a bacterially expressed glutathione-S-transferase fusion protein containing the extracellular segment of PTPmu (GST/PTPmu) adsorbed to petri dishes. Covaspheres coated with the GST/PTPmu fusion protein aggregated in vitro and also bound to PTPmu expressed endogenously on MvLu cells. These results suggest that the ligand for this transmembrane PTPase is another PTPmu molecule on an adjacent cell. Thus homophilic binding interactions may be an important component of the function of PTPmu in vivo

Using Synchronization for Prediction of High-Dimensional Chaotic Dynamics

We experimentally observe the nonlinear dynamics of an optoelectronic time-delayed feedback loop designed for chaotic communication using commercial fiber optic links, and we simulate the system using delay differential equations. We show that synchronization of a numerical model to experimental measurements provides a new way to assimilate data and forecast the future of this time-delayed high-dimensional system. For this system, which has a feedback time delay of 22 ns, we show that one can predict the time series for up to several delay periods, when the dynamics is about 15 dimensional.Comment: 10 pages, 4 figure

Genomic structure and alternative splicing of murine R2B receptor protein tyrosine phosphatases (PTPκ, μ, ρ and PCP-2)

BACKGROUND: Four genes designated as PTPRK (PTPκ), PTPRL/U (PCP-2), PTPRM (PTPμ) and PTPRT (PTPρ) code for a subfamily (type R2B) of receptor protein tyrosine phosphatases (RPTPs) uniquely characterized by the presence of an N-terminal MAM domain. These transmembrane molecules have been implicated in homophilic cell adhesion. In the human, the PTPRK gene is located on chromosome 6, PTPRL/U on 1, PTPRM on 18 and PTPRT on 20. In the mouse, the four genes ptprk, ptprl, ptprm and ptprt are located in syntenic regions of chromosomes 10, 4, 17 and 2, respectively. RESULTS: The genomic organization of murine R2B RPTP genes is described. The four genes varied greatly in size ranging from ~64 kb to ~1 Mb, primarily due to proportional differences in intron lengths. Although there were also minor variations in exon length, the number of exons and the phases of exon/intron junctions were highly conserved. In situ hybridization with digoxigenin-labeled cRNA probes was used to localize each of the four R2B transcripts to specific cell types within the murine central nervous system. Phylogenetic analysis of complete sequences indicated that PTPρ and PTPμ were most closely related, followed by PTPκ. The most distant family member was PCP-2. Alignment of RPTP polypeptide sequences predicted putative alternatively spliced exons. PCR experiments revealed that five of these exons were alternatively spliced, and that each of the four phosphatases incorporated them differently. The greatest variability in genomic organization and the majority of alternatively spliced exons were observed in the juxtamembrane domain, a region critical for the regulation of signal transduction. CONCLUSIONS: Comparison of the four R2B RPTP genes revealed virtually identical principles of genomic organization, despite great disparities in gene size due to variations in intron length. Although subtle differences in exon length were also observed, it is likely that functional differences among these genes arise from the specific combinations of exons generated by alternative splicing

Use of the breeding technique to estimate the structure of the analysis 'errors of the day'

A 3D-variational data assimilation scheme for a quasi-geostrophic channel model (Morss, 1998) is used to study the structure of the background error and its relationship to the corresponding bred vectors. The "true" evolution of the model atmosphere is defined by an integration of the model and "rawinsonde observations" are simulated by randomly perturbing the true state at fixed locations. Case studies using different observational densities are considered to compare the evolution of the Bred Vectors to the spatial structure of the background error. In addition, the bred vector dimension (BV-dimension), defined by Patil et al. (2001) is applied to the bred vectors. It is found that after 3-5 days the bred vectors develop well organized structures which are very similar for the two different norms (enstrophy and streamfunction) considered in this paper. When 10 surrogate bred vectors (corresponding to different days from that of the background error) are used to describe the local patterns of the background error, the explained variance is quite high, about 85-88%, indicating that the statistical average properties of the bred vectors represent well those of the background error. However, a subspace of 10 bred vectors corresponding to the time of the background error increased the percentage of explained variance to 96-98%, with the largest percentage when the background errors are large. These results suggest that a statistical basis of bred vectors collected over time can be used to create an effective constant background error covariance for data assimilation with 3D-Var. Including the "errors of the day" through the use of bred vectors corresponding to the background forecast time can bring an additional significant improvement

Weather at Sierra Negra: 7.3-year statistics and a new method to estimate the temporal fraction of cloud cover

Sierra Negra, one of the highest peaks in central Mexico, is the site of the Large Millimeter Telescope. We describe the first results of a comprehensive analysis of the weather data measured in situ from October 2000 to February 2008 to be used as a reference for future activity in the site. We compare the data from two different stations at the summit considering the accuracy of both instruments. We analysed the diurnal, seasonal and annual cycles for all the parameters. The thermal stability is remarkably good, crucial for a good performance of the telescopes. From the solar radiation data we developed a new method to estimate the fraction of time when the sky is clear of clouds. We show that our measurements are consistent with a warm standard atmosphere model. The conditions at the site are benign and stable given its altitude, showing that Sierra Negra is a extremely good site for millimeter and high energy observations.Comment: Accepted, MNRAS, 17 pages, 26 figure file

Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics

A 24-member ensemble of 1-h high-resolution forecasts over the Southern United Kingdom is used to study short-range forecast error statistics. The initial conditions are found from perturbations from an ensemble transform Kalman filter. Forecasts from this system are assumed to lie within the bounds of forecast error of an operational forecast system. Although noisy, this system is capable of producing physically reasonable statistics which are analysed and compared to statistics implied from a variational assimilation system. The variances for temperature errors for instance show structures that reflect convective activity. Some variables, notably potential temperature and specific humidity perturbations, have autocorrelation functions that deviate from 3-D isotropy at the convective-scale (horizontal scales less than 10 km). Other variables, notably the velocity potential for horizontal divergence perturbations, maintain 3-D isotropy at all scales. Geostrophic and hydrostatic balances are studied by examining correlations between terms in the divergence and vertical momentum equations respectively. Both balances are found to decay as the horizontal scale decreases. It is estimated that geostrophic balance becomes less important at scales smaller than 75 km, and hydrostatic balance becomes less important at scales smaller than 35 km, although more work is required to validate these findings. The implications of these results for high-resolution data assimilation are discussed

Protein tyrosine phosphatases: the problems of a growing family

Protein tyrosine phosphorylation is now recognized as an important component of the control of many fundamental aspects of cellular function, including growth and differentiation, cell cycle and cytoskeletal integrity. In vivo, the net level of phosphorylation of tyrosyl residues in a target substrate reflects the balance between the competing action of kinases and phosphatases. We are examining physiological roles for protein tyrosine phosphorylation, pursuing the problem from the perspective of the enzymes that catalyze the dephosphorylation reaction, the protein tyrosine phosphatases (PTPases). The PTPases have, until recently, been somewhat neglected relative to the protein tyrosine kinases (PTKs). However, considerable progress has been made in identifying new members of the PTPase family, and it appears that they constitute a novel class of signal transducing molecules that rival the PTKs in their structural diversity and complexity. One of the principal reasons that the study of PTPases has lagged behind that of the..

Nonparametric Data Assimilation Scheme for Land Hydrological Applications

Data assimilation, which relies on explicit knowledge of dynamical models, is a well-known approach that addresses models' limitations due to various reasons, such as errors in input and forcing data sets. This approach, however, requires intensive computational efforts, especially for high-dimensional systems such as distributed hydrological models. Alternatively, data-driven methods offer comparable solutions when the physics underlying the models are unknown. For the first time in a hydrological context, a nonparametric framework is implemented here to improve model estimates using available observations. This method uses Takens delay coordinate method to reconstruct the dynamics of the system within a Kalman filtering framework, called the Kalman-Takens filter. A synthetic experiment is undertaken to fully investigate the capability of the proposed method by comparing its performance with that of a standard assimilation framework based on an adaptive unscented Kalman filter (AUKF). Furthermore, using terrestrial water storage (TWS) estimates obtained from the Gravity Recovery And Climate Experiment mission, both filters are applied to a real case scenario to update different water storages over Australia. In situ groundwater and soil moisture measurements within Australia are used to further evaluate the results. The Kalman-Takens filter successfully improves the estimated water storages at levels comparable to the AUKF results, with an average root-mean-square error reduction of 37.30% for groundwater and 12.11% for soil moisture estimates. Additionally, the Kalman-Takens filter, while reducing estimation complexities, requires a fraction of the computational time, that is, ~8 times faster compared to the AUKF approach

Statistical and dynamical properties of covariant lyapunov vectors in a coupled atmosphere-ocean model—multiscale effects, geometric degeneracy, and error dynamics

We study a simplified coupled atmosphere-ocean model using the formalism of covariant Lyapunov vectors (CLVs), which link physically-based directions of perturbations to growth/decay rates. The model is obtained via a severe truncation of quasi-geostrophic equations for the two fluids, and includes a simple yet physically meaningful representation of their dynamical/thermodynamical coupling. The model has 36 degrees of freedom, and the parameters are chosen so that a chaotic behaviour is observed. There are two positive Lyapunov exponents (LEs), sixteen negative LEs, and eighteen near-zero LEs. The presence of many near-zero LEs results from the vast time-scale separation between the characteristic time scales of the two fluids, and leads to nontrivial error growth properties in the tangent space spanned by the corresponding CLVs, which are geometrically very degenerate. Such CLVs correspond to two different classes of ocean/atmosphere coupled modes. The tangent space spanned by the CLVs corresponding to the positive and negative LEs has, instead, a non-pathological behaviour, and one can construct robust large deviations laws for the finite time LEs, thus providing a universal model for assessing predictability on long to ultra-long scales along such directions. Interestingly, the tangent space of the unstable manifold has substantial projection on both atmospheric and oceanic components. The results show the difficulties in using hyperbolicity as a conceptual framework for multiscale chaotic dynamical systems, whereas the framework of partial hyperbolicity seems better suited, possibly indicating an alternative definition for the chaotic hypothesis. They also suggest the need for an accurate analysis of error dynamics on different time scales and domains and for a careful set-up of assimilation schemes when looking at coupled atmosphere-ocean models