Excessive Dpp signaling induces cardial apoptosis through dTAK1 and dJNK during late embryogenesis of Drosophila

<p>Abstract</p> <p>Background</p> <p>To identify genes involved in the heart development of <it>Drosophila</it>, we found that embryos lacking <it>raw </it>function exhibited cardial phenotypes. <it>raw </it>was initially identified as a dorsal open group gene. The dorsal open phenotype was demonstrated to be resulted from the aberrant expression of <it>decapentaplegic </it>(<it>dpp</it>), a member of the tumor growth factor beta (TGF-β), signaling pathway. Despite the role of <it>dpp </it>in pattering cardioblasts during early embryogenesis of <it>Drosophila </it>have been demonstrated, how mutation in <it>raw </it>and/or excessive <it>dpp </it>signaling involves in the differentiating heart of <it>Drosophila </it>has not been fully elaborated at late stages.</p> <p>Results</p> <p>We show that <it>raw </it>mutation produced a mild overspecification of cardial cells at stage 14, but these overproduced cells were mostly eliminated in late mutant embryos due to apoptosis. Aberrant <it>dpp </it>signaling is likely to contribute to the cardial phenotype found in <it>raw </it>mutants, because expression of <it>dpp </it>or constitutively activated <it>thickven </it>(<it>tkv^CA</it>), the type I receptor of Dpp, induced a <it>raw</it>-like phenotype. Additionally, we show that <it>dpp </it>induced non-autonomous apoptosis through TGFβ activated kinase 1 (<it>TAK1</it>), because mis-expression of a dominant negative form of <it>Drosophila TAK1 </it>(<it>dTAK1^DN</it>) was able to suppress cell death in <it>raw </it>mutants or embryos overexpressing <it>dpp</it>. Importantly, we demonstrated that <it>dpp </it>induce its own expression through <it>dTAK1</it>, which also leads to the hyperactivation of <it>Drosophila </it>JNK (DJNK). The hyperactivated DJNK was attributed to be the cause of Dpp/DTAK1-induced apoptosis because overexpression of a dominant negative DJNK, <it>basket </it>(<it>bsk^DN</it>), suppressed cell death induced by Dpp or DTAK1. Moreover, targeted overexpression of the anti-apoptotic P35 protein, or a dominant negative proapoptotic P53 (P53^DN) protein blocked Dpp/DTAK1-induced apoptosis, and rescued heart cells under the <it>raw </it>mutation background.</p> <p>Conclusions</p> <p>We find that ectopic Dpp led to DJNK-dependent cardial apoptosis through the non-canonical TGF-β pathway during late embryogenesis of <it>Drosophila</it>. This certainly will increase our understanding of the pathogenesis of cardiomyopathy, because haemodynamic overload can up-regulate TGF-β and death of cardiomyocytes is observed in virtually every myocardial disease. Thus, our study may provide possible medical intervention for human cardiomyopathy.</p

IDENTIFYING GAIT ASYMMETRY USING DIGITAL SENSORS

The purpose of this study was to determine which phases and kinematics were easier to identify gait asymmetry by using digital sensors. Sixteen participants were recruited in this study. The participants were requested to walk naturally under two conditions (with or without asymmetrical load). Four digital sensor sets were attached on 4 limbs to collect kinematics data. The results showed that only the AS1 of Medial-Later acceleration of upper limb on the stance phase significantly different between unloading and loading conditions; on the lower limb were AS1 of Superior-Inferior acceleration and Flex/Extension angular velocity on the swing phase. The digital sensors that attach on upper and lower limbs both can detect gait asymmetry, but the asymmetrical phase and kinematics are different on upper and lower limbs

Geographically weighted temporally correlated logistic regression model.

Detecting the temporally and spatially varying correlations is important to understand the biological and disease systems. Here we proposed a geographically weighted temporally correlated logistic regression (GWTCLR) model to identify such dynamic correlation of predictors on binomial outcome data, by incorporating spatial and temporal information for joint inference. The local likelihood method is adopted to estimate the spatial relationship, while the smoothing method is employed to estimate the temporal variation. We present the construction and implementation of GWTCLR and the study of the asymptotic properties of the proposed estimator. Simulation studies were conducted to evaluate the robustness of the proposed model. GWTCLR was applied on real epidemiologic data to study the climatic determinants of human seasonal influenza epidemics. Our method obtained results largely consistent with previous studies but also revealed certain spatial and temporal varying patterns that were unobservable by previous models and methods

Order picking optimization with order assignment and multiple workstations in KIVA warehouses

We consider the problem of allocating orders and racks to multiple stations and sequencing their interlinked processing flows at each station in the robot-assisted KIVA warehouse. The various decisions involved in the problem, which are closely associated and must be solved in real time, are often tackled separately for ease of treatment. However, exploiting the synergy between order assignment and picking station scheduling benefits picking efficiency. We develop a comprehensive mathematical model that takes the synergy into consideration to minimize the total number of rack visits. To solve this intractable problem, we develop an efficient algorithm based on simulated annealing and dynamic programming. Computational studies show that the proposed approach outperforms the rule-based policies used in practice in terms of solution quality. Moreover, the results reveal that ignoring the order assignment policy leads to considerable optimality gaps for real-world-sized instances

A vorticity dynamics based model for the turbulent dissipation: Model development and validation

A new model dissipation rate equation is proposed based on the dynamic equation of the mean-square vorticity fluctuation for large Reynolds number turbulence. The advantage of working with the vorticity fluctuation equation is that the physical meanings of the terms in this equation are more clear than those in the dissipation rate equation. Hence, the model development based on the vorticity fluctuation equation is more straightforward. The resulting form of the model equation is consistent with the spectral energy cascade analysis introduced by Lumley. The proposed model dissipation rate equation is numerically well behaved and can be applied to any level of turbulence modeling. It is applied to a realizable eddy viscosity model. Flows that are examined include: rotating homogeneous shear flows; free shear flows; a channel flow and flat plate boundary layers with and without pressure gradients; and backward facing step separated flows. In most cases, the present model predictions show considerable improvement over the standard kappa-epsilon model