The Early Nutritional Environment of Mice Determines the Capacity for Adipose Tissue Expansion by Modulating Genes of Caveolae Structure

While the phenomenon linking the early nutritional environment to disease susceptibility exists in many mammalian species, the underlying mechanisms are unknown. We hypothesized that nutritional programming is a variable quantitative state of gene expression, fixed by the state of energy balance in the neonate, that waxes and wanes in the adult animal in response to changes in energy balance. We tested this hypothesis with an experiment, based upon global gene expression, to identify networks of genes in which expression patterns in inguinal fat of mice have been altered by the nutritional environment during early post-natal development. The effects of over- and under-nutrition on adiposity and gene expression phenotypes were assessed at 5, 10, 21 days of age and in adult C57Bl/6J mice fed chow followed by high fat diet for 8 weeks. Under-nutrition severely suppressed plasma insulin and leptin during lactation and diet-induced obesity in adult mice, whereas over-nourished mice were phenotypically indistinguishable from those on a control diet. Food intake was not affected by under- or over-nutrition. Microarray gene expression data revealed a major class of genes encoding proteins of the caveolae and cytoskeleton, including Cav1, Cav2, Ptrf (Cavin1), Ldlr, Vldlr and Mest, that were highly associated with adipose tissue expansion in 10 day-old mice during the dynamic phase of inguinal fat development and in adult animals exposed to an obesogenic environment. In conclusion gene expression profiles, fat mass and adipocyte size in 10 day old mice predicted similar phenotypes in adult mice with variable diet-induced obesity. These results are supported by phenotypes of KO mice and suggest that when an animal enters a state of positive energy balance adipose tissue expansion is initiated by coordinate changes in mRNA levels for proteins required for modulating the structure of the caveolae to maximize the capacity of the adipocyte for lipid storage

CD1b-restricted GEM T cell responses are modulated by Mycobacterium tuberculosis mycolic acid meromycolate chains

Tuberculosis, caused by Mycobacterium tuberculosis, remains a major human pandemic. Germline-encoded mycolyl lipid-reactive (GEM) T cells are donor-unrestricted and recognize CD1b-presented mycobacterial mycolates. However, the molecular requirements governing mycolate antigenicity for the GEM T cell receptor (TCR) remain poorly understood. Here, we demonstrate CD1b expression in tuberculosis granulomas and reveal a central role for meromycolate chains in influencing GEM-TCR activity. Meromycolate fine structure influences T cell responses in TB-exposed individuals, and meromycolate alterations modulate functional responses by GEM-TCRs. Computational simulations suggest that meromycolate chain dynamics regulate mycolate head group movement, thereby modulating GEM-TCR activity. Our findings have significant implications for the design of future vaccines that target GEM T cells

An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports

This paper puts forward an integrated optimisation model that combines three distinct problems, namely berth allocation, quay crane assignment, and quay crane scheduling that arise in container ports. Each one of these problems is difficult to solve in its own right. However, solving them individually leads almost surely to sub-optimal solutions. Hence, it is desirable to solve them in a combined form. The model is of the mixed-integer programming type with the objective being to minimize the tardiness of vessels and reduce the cost of berthing. Experimental results show that relatively small instances of the proposed model can be solved exactly using CPLEX. Large scale instances, however, can only be solved in reasonable times using heuristics. Here, an implementation of the genetic algorithm is considered. The effectiveness of this implementation is tested against CPLEX on small to medium size instances of the combined model. Larger size instances were also solved with the genetic algorithm, showing that this approach is capable of finding the optimal or near optimal solutions in realistic times

Different Transcriptional Control of Metabolism and Extracellular Matrix in Visceral and Subcutaneous Fat of Obese and Rimonabant Treated Mice

BACKGROUND: The visceral (VAT) and subcutaneous (SCAT) adipose tissues play different roles in physiology and obesity. The molecular mechanisms underlying their expansion in obesity and following body weight reduction are poorly defined. METHODOLOGY: C57Bl/6 mice fed a high fat diet (HFD) for 6 months developed low, medium, or high body weight as compared to normal chow fed mice. Mice from each groups were then treated with the cannabinoid receptor 1 antagonist rimonabant or vehicle for 24 days to normalize their body weight. Transcriptomic data for visceral and subcutaneous adipose tissues from each group of mice were obtained and analyzed to identify: i) genes regulated by HFD irrespective of body weight, ii) genes whose expression correlated with body weight, iii) the biological processes activated in each tissue using gene set enrichment analysis (GSEA), iv) the transcriptional programs affected by rimonabant. PRINCIPAL FINDINGS: In VAT, "metabolic" genes encoding enzymes for lipid and steroid biosynthesis and glucose catabolism were down-regulated irrespective of body weight whereas "structure" genes controlling cell architecture and tissue remodeling had expression levels correlated with body weight. In SCAT, the identified "metabolic" and "structure" genes were mostly different from those identified in VAT and were regulated irrespective of body weight. GSEA indicated active adipogenesis in both tissues but a more prominent involvement of tissue stroma in VAT than in SCAT. Rimonabant treatment normalized most gene expression but further reduced oxidative phosphorylation gene expression in SCAT but not in VAT. CONCLUSION: VAT and SCAT show strikingly different gene expression programs in response to high fat diet and rimonabant treatment. Our results may lead to identification of therapeutic targets acting on specific fat depots to control obesity

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050

© 2016 The Author(s). Background: Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. Methods: Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. Results: Average malaria incidence was 0.107 per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R2 = 0.825) and 17.102 % for test data (R2 = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. Conclusions: The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas

Alliances and the innovation performance of corporate and public research spin-off firms

We explore the innovation performance benefits of alliances for spin-off firms, in particular spin-offs either from other firms or from public research organizations. During the early years of the emerging combinatorial chemistry industry, the industry on which our empirical analysis focuses, spin-offs engaged in alliances with large and established partners, partners of similar type and size, and with public research organizations, often for different reasons. We seek to understand to what extent alliances of spin-offs with other firms (either large- or small- and medium-sized firms) affected their innovation performance and also how this performance may have been affected by their corporate or public research background. We find evidence that in general alliances of spin-offs with other firms, in particular alliances with large firms, increased their innovation performance. Corporate spin-offs that formed alliances with other firms outperformed public research spin-offs with such alliances. This suggests that, in terms of their innovation performance, corporate spin-offs that engaged in alliances with other firms seemed to have benefitted from their prior corporate background. Interestingly, it turns out that the negative impact of alliances on the innovation performance of public research spin-offs was largely affected by their alliances with small- and medium-sized firms

UCP1 Induction during Recruitment of Brown Adipocytes in White Adipose Tissue Is Dependent on Cyclooxygenase Activity

Background The uncoupling protein 1 (UCP1) is a hallmark of brown adipocytes and pivotal for cold- and diet-induced thermogenesis. Methodology/Principal Findings Here we report that cyclooxygenase (COX) activity and prostaglandin E2 (PGE2) are crucially involved in induction of UCP1 expression in inguinal white adipocytes, but not in classic interscapular brown adipocytes. Cold-induced expression of UCP1 in inguinal white adipocytes was repressed in COX2 knockout (KO) mice and by administration of the COX inhibitor indomethacin in wild-type mice. Indomethacin repressed β-adrenergic induction of UCP1 expression in primary inguinal adipocytes. The use of PGE2 receptor antagonists implicated EP4 as a main PGE2 receptor, and injection of the stable PGE2 analog (EP3/4 agonist) 16,16 dm PGE2 induced UCP1 expression in inguinal white adipose tissue. Inhibition of COX activity attenuated diet-induced UCP1 expression and increased energy efficiency and adipose tissue mass in obesity-resistant mice kept at thermoneutrality. Conclusions/Significance Our findings provide evidence that induction of UCP1 expression in white adipose tissue, but not in classic interscapular brown adipose tissue is dependent on cyclooxygenase activity. Our results indicate that cyclooxygenase-dependent induction of UCP1 expression in white adipose tissues is important for diet-induced thermogenesis providing support for a surprising role of COX activity in the control of energy balance and obesity development