How is precision regulated in maintaining trunk posture?

Precision of limb control is associated with increased joint stiffness caused by antagonistic co-activation. The aim of this study was to examine whether this strategy also applies to precision of trunk postural control. To this end, thirteen subjects performed static postural tasks, aiming at a target object with a cursor that responded to 2D trunk angles. By manipulating target dimensions, different levels of precision were imposed in the frontal and sagittal planes. Trunk angle and electromyography (EMG) of abdominal and back muscles were recorded. Repeated measures ANOVAs revealed significant effects of target dimensions on kinematic variability in both movement planes. Specifically, standard deviation (SD) of trunk angle decreased significantly when target size in the same direction decreased, regardless of the precision demands in the other direction. Thus, precision control of trunk posture was directionally specific. However, no consistent effect of precision demands was found on trunk muscle activity, when averaged over time series. Therefore, it was concluded that stiffness regulation by antagonistic co-activation was not used to meet increased precision demands in trunk postural control. Instead, results from additional analyses suggest that precision of trunk angle was controlled in a feedback mode

Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: the PLANET study

Intra-tumor heterogeneity (ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic (transcriptomic and immune) heterogeneity. Using one of the largest prospective surgical cohorts for Hepatocellular Carcinoma (HCC) with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients (331 samples). We found that while genomic ITH was rather constant across TNM stages, phenotypic ITH had a very different trajectory and quickly diversified in stage II patients. Most strikingly, 30% patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types

Suppression of TGFβ-Induced Epithelial-Mesenchymal Transition Like Phenotype by a PIAS1 Regulated Sumoylation Pathway in NMuMG Epithelial Cells

Epithelial-mesenchymal-transition (EMT) is a fundamental cellular process that is critical for normal development and tumor metastasis. The transforming growth factor beta (TGFβ) is a potent inducer of EMT like effects, but the mechanisms that regulate TGFβ-induced EMT remain incompletely understood. Using the widely employed NMuMG mammary epithelial cells as a model to study TGFβ-induced EMT, we report that TGFβ downregulates the levels of the SUMO E3 ligase PIAS1 in cells undergoing EMT. Gain and loss of function analyses indicate that PIAS1 acts in a SUMO ligase dependent manner to suppress the ability of TGFβ to induce EMT in these cells. We also find that TGFβ inhibits sumoylation of the PIAS1 substrate SnoN, a transcriptional regulator that antagonizes TGFβ-induced EMT. Accordingly, loss of function mutations of SnoN sumoylation impair the ability of SnoN to inhibit TGFβ-induced EMT in NMuMG cells. Collectively, our findings suggest that PIAS1 is a novel negative regulator of EMT and reveal that inhibition of the PIAS1-SnoN sumoylation pathway represents a key mechanism by which TGFβ induces EMT, with important implications in normal development and tumor metastasis

Micropropagation and conservation of selected endangered anticancer medicinal plants from the Western Ghats of India

Globally, cancer is a constant battle which severely affects the human population. The major limitations of the anticancer drugs are the deleterious side effects on the quality of life. Plants play a vital role in curing many diseases with minimal or no side effects. Phytocompounds derived from various medicinal plants serve as the best source of drugs to treat cancer. The global demand for phytomedicines is mostly reached by the medicinal herbs from the tropical nations of the world even though many plant species are threatened with extinction. India is one of the mega diverse countries of the world due to its ecological habitats, latitudinal variation, and diverse climatic range. Western Ghats of India is one of the most important depositories of endemic herbs. It is found along the stretch of south western part of India and constitutes rain forest with more than 4000 diverse medicinal plant species. In recent times, many of these therapeutically valued herbs have become endangered and are being included under the red-listed plant category in this region. Due to a sharp rise in the demand for plant-based products, this rich collection is diminishing at an alarming rate that eventually triggered dangerous to biodiversity. Thus, conservation of the endangered medicinal plants has become a matter of importance. The conservation by using only in situ approaches may not be sufficient enough to safeguard such a huge bio-resource of endangered medicinal plants. Hence, the use of biotechnological methods would be vital to complement the ex vitro protection programs and help to reestablish endangered plant species. In this backdrop, the key tools of biotechnology that could assist plant conservation were developed in terms of in vitro regeneration, seed banking, DNA storage, pollen storage, germplasm storage, gene bank (field gene banking), tissue bank, and cryopreservation. In this chapter, an attempt has been made to critically review major endangered medicinal plants that possess anticancer compounds and their conservation aspects by integrating various biotechnological tool

BATCH-DIST - A COMPREHENSIVE PACKAGE FOR SIMULATION, DESIGN, OPTIMIZATION AND OPTIMAL-CONTROL OF MULTICOMPONENT, MULTIFRACTION BATCH DISTILLATION-COLUMNS

BATCH-DIST is a general-purpose simulation package for the design, simulation and optimization of multicomponent, multifraction batch distillation columns operating under different modes (constant reflux, variable reflux and optimal reflux policy). The package includes simulation models of varying degrees of complexity and rigor; efficient but simplified models (based on short-cut methods) for preliminary design and rapid analysis of column behavior, and rigorous models (based on solution of transient heat and mass balance differential equations) for verification and detailed column design. Besides simulation and design, BATCH-DIST can also accomplish optimization and optimal control of columns. Coded in Fortran 77, the package is flexible and user-friendly. BATCH-DIST has been extensively tested with benchmark cases involving binary and multicomponent systems, with nonideal behavior and in columns with appreciable holdup effects. Such test cases have clearly demonstrated that predictions of the simplified models in the package compare well with those of the rigorous models. This powerful and comprehensive package is expected to be computationally more efficient than existing packages

Improved techniques for the development of quadratic perturbation models

In this paper, the quadratic model developed by Patwardhan and Madhavan (1993) using the regular perturbation approach has been further refined to produce a better estimate of second-order effects. As an alternate to the regular perturbation model, a structurally better form of the quadratic model has also been derived that does not require any of the simplifying assumptions that were used in our previous work (Patwardhan and Madhavan, 1993). The coefficients of this model are computed using the solutions of the first- and second-order sensitivity equations. A recursive form of quadratic perturbation models is also developed for the systems with a nonlinear output map. The computational advantages of the proposed quadratic models have been presented. The improved prediction capabilities of the quadratic models obtained using the proposed modifications have been demonstrated using a simulation example. The analysis of the model structure and the simulation results indicate that the quadratic model developed using the sensitivity equation approach is a better choice for approximating the local behavior of a highly nonlinear system and, consequently, for the development of an nonlinear model predictive control scheme

Nonlinear predictive control of an exothermic CSTR using recursive quadratic state space models

The possibility of using a discrete quadratic perturbation model for approximating nonlinear plant dynamics in the neighborhood of the operating point is explored in this paper. A method is evolved for computing the model coefficients using first and second order sensitivity equations. The proposed model is further used to develop a nonlinear model predictive control algorithm. The performance of the proposed control algorithm is demonstrated by simulating a benchmark CSTR control problem characterized by the change in the sign of the steady state gain in the operating region.© IEE