A new lower-limb prosthetic developed at Vanderbilt University allows amputees to walk without the leg-dragging gait characteristic of conventional artificial legs.
Source: Vanderbilt University - Discipline: Technology www.labspaces.net
People with a known, high risk for Alzheimer's disease develop abnormal brain function even before the appearance of telltale amyloid plaques that are characteristic of the disease, according to a new study www.sciencecentric.com
A priori selection of models for use in phylogeny estimation from molecular sequence data is increasingly important as the number and complexity of available models increases. The Bayesian information criterion (BIC) and the derivative decision-theoretic (DT) approaches rely on a conservative approximation to estimate the posterior probability of a given model. Here, we extended the DT method by using reversible jump Markov chain Monte Carlo approaches to directly estimate model probabilities for an extended candidate pool of all 406 special cases of the general time reversible + family. We analyzed 250 diverse data sets in order to evaluate the effectiveness of the BIC approximation for model selection under the BIC and DT approaches. Model choice under DT differed between the BIC approximation and direct estimation methods for 45% of the data sets (113/250), and differing model choice resulted in significantly different sets of trees in the posterior distributions for 26% of the data sets (64/250). The model with the lowest BIC score differed from the model with the highest posterior probability in 30% of the data sets (76/250). When the data indicate a clear model preference, the BIC approximation works well enough to result in the same model selection as with directly estimated model probabilities, but a substantial proportion of biological data sets lack this characteristic, which leads to selection of underparametrized models. mbe.oxfordjournals.org
Unlike the growth factor dependence of normal cells, cancer cells can maintain growth factor–independent glycolysis and survival through expression of oncogenic kinases, such as BCR-Abl. Although targeted kinase inhibition can promote cancer cell death, therapeutic resistance develops frequently, and further mechanistic understanding is needed. Cell metabolism may be central to this cell death pathway, as we have shown that growth factor deprivation leads to decreased glycolysis that promotes apoptosis via p53 activation and induction of the proapoptotic protein Puma. Here, we extend these findings to show that elevated glucose metabolism, characteristic of cancer cells, can suppress protein kinase C (PKC)–dependent p53 activation to maintain cell survival after growth factor withdrawal. In contrast, DNA damage–induced p53 activation was PKC independent and was not metabolically sensitive. Both stresses required p53 Ser18 phosphorylation for maximal activity but led to unique patterns of p53 target gene expression, showing distinct activation and response pathways for p53 that were differentially regulated by metabolism. Consistent with oncogenic kinases acting to replace growth factors, treatment of BCR-Abl–expressing cells with the kinase inhibitor imatinib led to reduced metabolism and p53- and Puma-dependent cell death. Accordingly, maintenance of glucose uptake inhibited p53 activation and promoted imatinib resistance. Furthermore, inhibition of glycolysis enhanced imatinib sensitivity in BCR-Abl–expressing cells with wild-type p53 but had little effect on p53-null cells. These data show that distinct pathways regulate p53 after DNA damage and metabolic stress and that inhibiting glucose metabolism may enhance the efficacy of and overcome resistance to targeted molecular cancer therapies. Cancer Res; 70(20); 8066–76. 2010 AACR. cancerres.aacrjournals.org
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