Human brown adipose tissue (BAT) presence, metabolic activity and estimated mass are typically measured by imaging [18F]fluorodeoxyglucose (FDG) uptake in response to cold exposure in regions of the body expected to contain BAT, using positron emission tomography combined with x-ray computed tomography (FDG-PET/CT). Efforts to describe the epidemiology and biology of human BAT are hampered by diverse experimental practices, making it difficult to directly compare results among laboratories. An expert panel was assembled by the National Institute of Diabetes and Digestive and Kidney Diseases on November 4, 2014 to discuss minimal requirements for conducting FDG-PET/CT experiments of human BAT, data analysis, and publication of results. This resulted in Brown Adipose Reporting Criteria in Imaging STudies (BARCIST 1.0). Since there are no fully-validated best practices at this time, panel recommendations are meant to enhance comparability across experiments, but not to constrain experimental design or the questions that can be asked.

Brown adipose tissue (BAT) dissipates energy and its activity correlates with leanness in human adults. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography coupled with computer tomography (PET/CT) is still the standard for measuring BAT activity, but exposes subjects to ionizing radiation. To study BAT function in large human cohorts, novel diagnostic tools are needed. Here we show that brown adipocytes release exosomes and that BAT activation increases exosome release. Profiling miRNAs in exosomes released from brown adipocytes, and in exosomes isolated from mouse serum, we show that levels of miRNAs change after BAT activation in vitro and in vivo. One of these exosomal miRNAs, miR-92a, is also present in human serum exosomes. Importantly, serum concentrations of exosomal miR-92a inversely correlate with human BAT activity measured by 18F-FDG PET/CT in two unique and independent cohorts comprising 41 healthy individuals. Thus, exosomal miR-92a represents a potential serum biomarker for BAT activity in mice and humans.

Energy consumption of residential buildings and o ces adds up to about 30% of total carbon dioxide emissions; and occupant behaviour contributes to 80% of the variation in energy consumption 1 . Indoor climate regulations are based on an empirical thermal comfort model that was developed in the 1960s (ref. 2). Standard values for one of its primary variables-metabolic rate-are based on an average male, and may overestimate female metabolic rate by up to 35% (ref. 3). This may cause buildings to be intrinsically nonenergy-e cient in providing comfort to females. Therefore, we make a case to use actual metabolic rates. Moreover, with a biophysical analysis we illustrate the e ect of miscalculating metabolic rate on female thermal demand. The approach is fundamentally di erent from current empirical thermal comfort models and builds up predictions from the physical and physiological constraints, rather than statistical association to thermal comfort. It provides a substantiation of the thermal comfort standard on the population level and adds flexibility to predict thermal demand of subpopulations and individuals. Ultimately, an accurate representation of thermal demand of all occupants leads to actual energy consumption predictions and real energy savings of buildings that are designed and operated by the buildings services community.As the built environment is focusing more on design of energyefficient buildings (for example, near-zero-energy buildings), we argue that indoor climate standards should accurately represent the thermal demand of all occupants. Otherwise there is a great risk that occupants will adapt their behaviour to optimize personal comfort, which may in turn nullify the effects of supposed energy-efficient designs. Furthermore, various fields in commerce, science and policymaking depend on accurate predictions of building energy consumption. For instance, commercial incentives for building renovations premised on energy-saving predictions; scientific climate change simulations require building energy consumption predictions to account for warming effects in winter 4 ; and policymaking for resource management requires integrated resource assessments including energy consumption by buildings 5 .The total variation in building energy consumption that is explained by occupant behaviour includes operating the thermostat, windows or air conditioning system 1 . In general, females prefer a higher room temperature than males in home and office situations, and mean values may differ as much as 3 K (males: 22 • C versus females: 25 • C; refs 6,7). Despite this discrepancy in preferred room temperature, no significant gender effect is found with respect to the mean skin temperature range that is associated with thermal comfort (males: 32.8-33.8 • C versus females: 32.4-33.6 • C; ref. 8).Indoor thermal environment design is primarily based on PMV/PPD (predicted mean vote/percentage people dissatisfied) criteria. The PMV is expressed on the ASHRAE 7-point Thermal Sensation Scale ranging from cold (−3) to hot ...

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