Do more fat cells make for better outcomes?

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nvited Speakers Abstracts

roplet associated proteins, such as perilipin 1 andomparative gene identification-58, in a series ofolecular interactions to match lipolytic flux toetabolic needs. In this presentation, evidence

rom human studies and genetically modified miceill describe the importance of ATGL in regu-

ating metabolism in health and disease. Furtheriscussion will focus on the recent identificationnd functional characterisation of novel regulatoryhosphorylation sites in ATGL.

oi:10.1016/j.orcp.2011.08.068

o more fat cells make for better outcomes?

on Whitehead

Mater Medical Research Institute, Brisbane,ustralia

It is now widely recognised that obesity repre-ents a state of chronic low grade inflammationnd a large body of evidence suggests that it ishis that underpins the association between obe-ity and the increased prevalence and severity ofetabolic disease. However, a proportion of obeseeople are metabolically healthy demonstratinghat obesity per se does not automatically leado compromised metabolism. One potential expla-ation for this apparent paradox is that ‘fit fat’eople have a greater capacity for adipogenesishan their unhealthy counterparts. Higher ratesf adipogenesis facilitate adipose tissue expansiony increasing adipocyte cell number (hyperplasia)ather than increasing adipocyte cell size (hypertro-hy). The generation of new ‘fit fat cells’ preventshe excessive hypertrophy of existing fat cells,hich otherwise become inflamed due to cellular

tress (e.g. hypoxia), resulting in increased pro-uction of pro-inflammatory adipokines (e.g. TNF�,L-6, and MCP-1). Recent gene expression studies inumans support such a model and raise the intrigu-ng possibility that one way to combat obesityelated diseases may be to promote adipogenesis.

oi:10.1016/j.orcp.2011.08.069

euroendocrine regulation of energy balanceuring pregnancy and its implications in obesity

ave Grattan

Centre for Neuroendocrinology and Departmentf Anatomy and Structural Biology, University oftago, Dunedin, New Zealand

Appetite and food intake are increased duringregnancy, an adaptive response that facili-ates energy storage in preparation for the high

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etabolic demands of pregnancy and subsequentactation. To maintain the increased energy intaken the face of increased adiposity and rising lep-in levels, pregnant females become resistanto the central anorectic actions of leptin. Inats, pregnancy-induced leptin resistance is char-cterised by elevated NPY and reduced POMCxpression in the arcuate nucleus, reduced lep-in receptor (LepRb) mRNA levels and suppressionf leptin-induced pSTAT3 in the ventromedialypothalamic nucleus, and a loss of anorecticesponses to both leptin and aMSH. Our recentata suggest that this leptin-resistance is alsoikely to cause central insulin resistance andltered peripheral glucose homeostasis during preg-ancy. Our studies show complex hormone-induceddaptations in the hypothalamic pathways regu-ating bodyweight and glucose homeostasis duringregnancy. These studies provide important under-tanding of bodyweight regulation in pregnantomen, but also provide insights into mechanisms

hat might perturb normal bodyweight homeostasisn obesity.

oi:10.1016/j.orcp.2011.08.070

romoting physical activity to children: Modelingipple effects in time use

im S. Olds ∗, K. Ferrar, S. Gomersall, J. Walters,. Maher

Health and Use of Time (HUT) Group, Sansomnstitute for Health Research, University of Southustralia, Adelaide, Australia

When children increase physical activity, therere ‘‘ripple effects’’ in the time committed tother activities, such as sleep, screen time, socialnd cognitive behaviours. These activities all haveealth implications, and implications for weightanagement. Ripple effects are almost never mod-

led. Using a large national dataset, we haveuantified ripple effects, a procedure which, cou-led with energy balance models, allows us toimulate likely effects on overall activity andeight loss of various behavioural interventions on

he population as a whole, and on various socio-emographic subsets.

Different interventions have strikingly differentffects. A 30 min increase in sport, for example,ncreases overall physical activity by 24 min, andeduces screen time by 15 min, with only a small5 min) reduction in sleep. A 30 min reduction in