Normal hypertrophy accompanied by phosphoryation and activation of AMP-activated protein kinase α1 following overload in LKB1 knockout mice

The activation of the AMP-activated protein kinase (AMPK) and inhibition of the mammalian target of rapamycin complex 1 (mTORC1) is hypothesized to underlie the fact that muscle growth following resistance exercise is decreased by concurrent endurance exercise. To directly test this hypothesis, the capacity for muscle growth was determined in mice lacking the primary upstream kinase for AMPK in skeletal muscle, LKB1. Following either 1 or 4 weeks of overload, there was no difference in muscle growth between the wild type (wt) and LKB1−/− mice (1 week: wt, 38.8 ± 7.75%; LKB1−/−, 27.8 ± 12.98%; 4 week: wt, 75.8 ± 15.2%; LKB1−/−, 85.0 ± 22.6%). In spite of the fact that the LKB1 had been knocked out in skeletal muscle, the phosphorylation and activity of the α1 isoform of AMPK were markedly increased in both the wt and the LKB1−/− mice. To identify the upstream kinase(s) responsible, we studied potential upstream kinases other than LKB1. The activity of both Ca2+–calmodulin-dependent protein kinase kinase α(CaMKKα) (5.05 ± 0.86-fold) and CaMKKβ (10.1 ± 2.59-fold) increased in the overloaded muscles, and this correlated with their increased expression. Phosphorylation of TAK-1 also increased 10-fold following overload in both the wt and LKB1 mice. Even though the α1 isoform of AMPK was activated by overload, there were no increases in expression of mitochondrial proteins or GLUT4, indicating that the α1 isoform is not involved in these metabolic adaptations. The phosphorylation of TSC2, an upstream regulator of the TORC1 pathway, at the AMPK site (Ser1345) was increased in response to overload, and this was not affected by LKB1 deficiency. Taken together, these data suggest that the α1 isoform of AMPK is preferentially activated in skeletal muscle following overload in the absence of metabolic adaptations, suggesting that this isoform might be important in the regulation of growth but not metabolism.

Mouse B7-H3 induces antitumor immunity

Members of the B7 family costimulate the proliferation of lymphocytes during the initiation and maintenance of antigen-specific humoral and cell-mediated immune responses. While B7-1 and -2 are restricted to lymphoid tissues, and activate naïve T cells, recently identified members including B7-H2 and -H3 are widely expressed on nonlymphoid tissues, and regulate effector lymphocytes in the periphery. B7-H3 has properties that suggested it may display antitumor activity, including the ability to stimulate Th1 and cytotoxic T-cell responses. Here, we test this notion by determining whether intratumoral injection of an expression plasmid encoding a newly described mouse homologue of B7-H3 is able to eradicate EL-4 lymphomas. Intratumoral injection of a mouse B7-H3 pcDNA3 expression plasmid led to complete regression of 50% tumors, or otherwise significantly slowed tumor growth. Mice whose tumors completely regressed resisted a challenge with parental tumor cells, indicating systemic immunity had been generated. B7-H3-mediated antitumor immunity was mediated by CD8(+) T and NK cells, with no apparent contribution from CD4(+) T cells. In summary, the results indicate that B7-H3 interactions may play a role in regulating cell-mediated immune responses against cancer, and that B7-H3 is a potential therapeutic tool.

Molecular physiology of water balance in the Spinifex hopping mouse

Many animals live in the deserts of Australia and survive without drinking water. This research examined desert adaptations in the Spinifex hopping mouse (Notomys alexis), and is the first study to demonstrate how many genes and exzymes in the kidney are controlled to maintain water balance in the absence of drinking water.

Conservation genetics of the New Holland mouse Pseudomys novaehollandiae, Waterhouse, 1843 (Rodentia: Muridae) : an analysis of mitochondrial DNA control region variation

An investigation of the genetic diversity of New Holland mouse populations using DNA. Ten distinct restriction enzyme fragment patterns or haplotypes were detected. From the fragment patterns, estimates of genetic divergence between the haplotypes revealed a degree of genetic structuring within New Holland mouse with four population assemblages apparent.

An examination of conditional asset pricing models in the Australian equities market

This article examines the link between macroeconomic variables and equity returns in Australia by testing conditional asset pricing models. We find that conditioning the Fama-French model with a series of macroeconomic variables does not considerably improve its performance. However, we do find that the Fama-French factors, SMB and HML, retain their ability to explain equity returns even after the model is conditioned on macroeconomic variables. Our findings suggest that investors do not adjust their risk premiums according to the changes in the macroeconomic variables we employ.

Human action categorization using conditional random field

Automatic human action recognition has been a challenging issue in the field of machine vision. Some high-level features such as SIFT, although with promising performance for action recognition, are computationally complex to some extent. To deal with this problem, we construct the features based on the Distance Transform of body contours, which is relatively simple and computationally efficient, to represent human action in the video. After extracting the features from videos, we adopt the Conditional Random Field for modeling the temporal action sequences. The proposed method is tested with an available standard dataset. We also testify the robustness of our method on various realistic conditions, such as body occlusion or intersection.

Hierarchical semi-markov conditional random fields for recursive sequential data

Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov chains to model complex hierarchical, nested Markov processes. It is parameterised in a discriminative framework and has polynomial time algorithms for learning and inference. Importantly, we develop efficient algorithms for learning and constrained inference in a partially-supervised setting, which is important issue in practice where labels can only be obtained sparsely. We demonstrate the HSCRF in two applications: (i) recognising human activities of daily living (ADLs) from indoor surveillance cameras, and (ii) noun-phrase chunking. We show that the HSCRF is capable of learning rich hierarchical models with reasonable accuracy in both fully and partially observed data cases.