Beresford, Nicholas A.

Galeriu, Dan

Melintescu, Anca

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This version available at http://nora.nerc.ac.uk/508517     NERC has developed NORA to enable users to access research outputs wholly or partially funded by NERC. Copyright and other rights for material on this site are retained by the rights owners. Users should read the terms and conditions of use of this material at http://nora.nerc.ac.uk/policies.html#access           Conference or Workshop Item    Melintescu, Anca; Galeriu, Dan; Beresford, Nicholas A. 2014. Energy metabolism and transfer of 3H and 14C in mammals and birds. In: 3rd International Conference on Radioecology and Environmental Radioactivity, Barcelona, 7-12 Sept 2014.                         Contact CEH NORA team at  noraceh@ceh.ac.uk  The NERC and CEH trademarks and logos (‘the Trademarks’) are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. Energy Metabolism and Transfer of 3H and 14C in Mammals and Birds Anca Melintescu1, Dan Galeriu1, Nicholas A. Beresford21 “Horia Hulubei” National Institute for Physics and Nuclear Engineering, Department of Environmental Physics and Life, 30 Reactorului St., POB MG-6, Bucharest-Magurele, RO-077125, Romania, ancameli@ifin.nipne.ro, melianca@yahoo.com  2 NERC Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Av. Bailrigg, Lancaster LA1 4AP, United KingdomINTRODUCTIONIncreasingly nuclear facilities and other sites releasing radionuclides have to demonstrate conservation of biodiversity. Among the radionuclides of interest, tritium (3H) and radiocarbon (14C) transfer in environment needs to be modelled differently than that of other radionuclides released from nuclear facilities because hydrogen and carbon are the main components of biological tissues and enter the life cycle. The model previously developed for 3H (in both forms tritiated water (HTO) and organically bound tritium (OBT)) and 14C dynamic transfer in farm animals (Galeriu et al., 2009) has been extended for few types of wild animal (Galeriu et al., 2005; Melintescu and Galeriu, 2010; Galeriu and Melintescu, 2011). Using the limited information regarding organ specific metabolic rates (SpMR) for domestic animals, allometric relationships were established in relation to body mass and thereafter applied to wild species. The aim of the present study is the revising of the scientific basis of the previous model and the assessment of uncertainty of input parameters, in order to test the model for a larger range of mammals and birds. The present version of the model has the same compartments as the previous one (blood plasma, muscle, viscera, red blood cells, adipose tissue, and ‘residual’) excepting brain, which is considered separately in the present version. In the previous version brain was bulked in the viscera compartment together with liver, kidney, heart, stomach and the walls of gastro-intestinal tract (GIT). Part of the food energy is taken by animals and transformed for using in specific processes in order to minimize the entropy increase and defines the basal metabolic rate (BMR). The addition of brain as a specific compartment in our revised model acknowledges that brain significantly contributes to BMR for birds and mammals. The present study is based on a data base of wild mammals and birds (Navarrete et al., 2011; Daan et al., 1990) and is focused on the requirements regarding the input information for BMR, field metabolic rate (FMR), and organ mass for model application to a larger range of animals. MATERIALS AND METHODSThe BMR of the whole body is a sum over all organs metabolic rates and consequently, the organ mass and organs SpMR must be known ( , 𝐵𝑀𝑅 = ∑𝑖𝑂𝑀𝑖 ∗ 𝑆𝑝𝑀𝑅𝑖where OM is organ mass). These are well known for humans, but rarely for other species. In the present study, the first systematic approach for BMR in rat (Ratus norvegicus) is carried out, because there is a large data base for BMR and organ mass (Even et al., 2001) and information regarding the organs SpMR is available (Wang et al., 2001; Galeriu et al., 2005). Data for adult Wistar, Zucker and Sprague-Dawley rats, as well as food-restricted Wistar rats were considered to test the “healthy adult” organ SpMR. For mammals, the data base for organs mass (Navarrete et al., 2011) did not provide the muscle mass, which was derived in the present study based on an extensive literature search. In the present study, we used organ SpMR provided elsewhere (Galeriu et al., 2005). The assessment of the best estimate for BMR was obtained taking into account the influence of taxonomic order and family, habitats and body temperature on BMR. For animals in active state, the metabolic energy and its partition differ from the basal state with consequences on the dynamics of radionuclides. The present study discusses endotherm animals with constant mass for which information on the FMR and metabolisable energy intake (MEI) are needed. The energy partition in each model compartment is based on compartment contribution to basal metabolism, heat increment of feeding (HIF), need to keep the body temperature constant and need for locomotion. The brain and residual compartment have quite constant energy metabolism in active state comparable to that of the basal state. For the adipose tissue some data for domestic animals were found (Galeriu et al., 2005) and the contribution of brown adipose tissue can also be added where it is needed (e.g. small mammals in cold environments). The rest of energy is used by muscle for activity or shivering in cold conditions.  Biological half times (of 14C, HTO, OBT or enhanced 13C) can only be estimated in a dynamic situation when the activity in whole body or in an organ is measured at various times after a change in diet.  In such situations, any organ (e.g. muscle or liver) is in interaction with other organs and has a complex behaviour. An organ has at least two types of cells: functional and structural with different half times. But also, as a part of the whole body, it is subjected to recycling together with other organs. Consequently, for example, carbon dynamics have two half times in a given organ. For rat, the  14C (Galeriu et al., 2009) and 13C data (MacAvoy et al., 2006) give similar turnover times for muscle and liver. . Carbon turnover measurements were available for rodents (Mus Musculus, Peromyscus maniculatus), gerbils (Meriones unguienlatus), alpacas (Lama pacos), Japanese quail (Coturnix japonica) and zebra finch (Taeniopygia guttata). Peromiscus maniculatus has higher mass than Mus Musculus but shorter carbon half-time in muscle contrary to what may be expected. RESULTS AND CONCLUSIONSThe calculated BMR for rat is compared with the experimental data (Even et al., 2001) (Fig. 1) and demonstrates a statistically significant relationship (BMRcalc= 6.77+0.951*BMRmeas) with an R2 of 0.96; predictions were not significantly different from the observed data, one way ANOVA (p>0.05), F = 0.025. In the model, muscle has a contribution of approximately 53% to BMR, while the viscera (liver, kidney, heart, GIT) contribute less (32%). There are differences between SpMR data used in the present study and those reported elsewhere (Even et al., 2001) but the calculated BMR values in both studies are close, pointing out the occurrence of the compensatory errors and the need to consider a large data base for species and mass range, in order to consider the SpMR values.The normalised residuals ((P-O)/O, where P is predicted value and O is observed one) for wild mammals (Navarrete et al., 2011) (Fig. 2) must be carefully analysed: a) the data base used to derive the allometric relationships for organs SpMR do not contain wild species; b) basal metabolism is subjected to the hormonal control. Considering the previous simplifications, the best BMR is reproduced with less than 30% in the normalised residuals. The cases with larger uncertainty (Glaucomys volans, Neomys anomalus, Neomys fodiens and Sorex araneus) can be also explained considering animal adaptation to its habitat. The adaptation to ecological and climatic niche can modify the organ mass and organ SpMR. The muscle SpMR (basal metabolism) is important within our model and improved data are needed. General_)200 General_)400 General_)600General_)100General_)120General_)140General_)160General_)180General_)200General_)220General_)240General_)260 BMRmeasBMRcalc (Wistar)BMRcalc (Zucker rats)BMRcalc (Sprague-Dawleyrats)Body mass (g)BMR (kJ/d)Figure 1. Comparison between measured (meas) and calculated (calc) BMR for Wistar, Zucker, Sprague-Dawley and food-restricted Wistar rats1 5001 10001 15001 20001 25001-0.8-0.6-0.4-0.200.20.40.60.8Body mass (g)(P-O)/OFigure 2. Normalised residuals ((P-O)/O) as function of body mass for wild speciesNo significant differences for calculated BMR of birds were observed between the revised model (present study), and the previous one (Galeriu and Melintescu, 2011) regarding predictions, but in both models, viscera use a large portion of energy from BMR. For birds, the model prediction for BMR has larger uncertainty than for mammals.For animals in active state (where energy expenditure is given by FMR and not BMR), the energy partition to organs or group of organs (e.g. viscera) is obtained by addition of energy needs in basal state (BMR) and specific energy needs in active states (HIF and locomotion) and depends on the ratio between FMR and BMR.  In most cases viscera metabolic rate is higher than that of muscle, higher metabolic rates for muscle are only estimated for animals eating good quality diets and having a high ratio between FMR and BMR. The revised model was applied to mouse (Mus Musculus) in order to assess the turnover rates for OBT in case of a continuous OBT intake of 1 Bq d-1 for 60 days (Fig. 3) and a single OBT intake of 1 Bq d-1 (Fig. 4). In Figs. 3 and 4, it is observed that the turnover rates in muscle and viscera are much shorter than the experimental ones for 13C. The model application to 137Cs (no transfer to adipose tissue) successfully reproduce the experimental data (about 5 days for the whole body). Any further development of the model and its potential adaptation to a specific site depends on the understanding of the sources of variability for basal (resting, standard) and sustained metabolic rates. The allometric mass relationship of metabolic rate (MR) (MR=aMassb) is not a ‘law’ but a trend (Hulbert, 2014) and the scaling exponent “b” as well as the intercept “a” show a large variability especially due to the relative sizes of tissues and organs relevant for the measured activity (allometric models are proposed to represent qualitative trends over orders of magnitude of body mass (Higley and Bytwerk, 2007)).For radionuclides emitting relatively short range radiations (such as alpha particles and low energy beta radiations) and for organisms above a certain size and complexity, doses to radiosensitive tissues are likely to dictate the resultant radiation effect and consequently, a model based on organs is more appropriate than one based on the whole body as currently used in wildlife models. 0 10 20 30 40 50 60 70 80 90 100020406080100120140160180200220adiposebloodbrainmuscleresidualvisceratime (days)OBT conc. in model compartmentsand whole body (Bq/kg) 0 2 4 6 8 10 12 14 16051015202530 adipose blood brainmuscle residual viscerawhole bodytime (days)OBT conc in model compartmentsand whole body (Bq/kg)Figure 3. Predicted OBT concentration in model compartments and in whole body of rat (Mus musculus) for a continuous intake of 60 daysFigure 4. Predicted OBT concentration in model compartments and in whole body of rat (Mus musculus) after a single intake Further efforts for model upgrades will be focused on the improving of the data base for organs SpMR of birds and the development of a strategy to assess the consequences of a hypothetical tritium accident for protected species around Cernavoda Nuclear Power Plant (NPP) (Romania).ACKNOWLEDGEMENTSThis study is part of the project EXPLORATORY IDEAS 65/2011 financed by the Romanian Authority for Scientific Research. REFERENCESGaleriu, D., A. Melintescu, N.A. Beresford, H. Takeda, and N.M.J Crout, 2009. The dynamic transfer of 3H and 14C in mammals – a proposed generic model. Radiat. Environ. Biophys. 48:29-45.Galeriu, D., A. Melintescu, N.A. Beresford, N.M.J. Crout and H. Takeda, 2005. 14C and tritium dynamics in wild mammals: A metabolic model. Radioprotection, 40:S351-S357.Melintescu and D. Galeriu, 2010. Energy metabolism used as a tool to model the transfer of 14C and 3H in  animals. Radiat. Environ. Biophys. 49:657–672.Galeriu, D. And A. Melintescu, 2011. A model approach for tritium dynamics in wild mammals.   Radioprotection, 46: S445–S451.Navarrete, A, C.P. van Schaik and K. Isler, 2011. Energetics and the evolution of human brain size. Nature, 480:91-94.Daan, S., D. Masman and A. Groenewold, 1990. Avian basal metabolic rates: their association with body composition and energy expenditure in nature. Am. J. Physiol. 259:R333–R340.Even, P.C., V. Rolland, S. Roseau, J.-C. Bouthegourd and D. Tome, 2001. Prediction of basal metabolism from organ size in the rate: relationship to strain, feeding, age, and obesity. Am. J. Physiol. Regulatory Integrative Comp. Physiol. 280:R1887-R1896.Wang, Z., T. P. O’Connor, S. Heshka, and S. B. Heymsfield, 2001.The reconstruction of Kleiber’s law at theorgan-tissue level. J. Nutr. 131:2967–2970.MacAvoy, S.E, L.S. Arneson and E. Bassett, 2006. Correlation of metabolism with tissue carbon and nitrogenturnover rate in small mammals. Oecologia, 150:190-201. Hulbert, A.J., 2014. A Sceptics View: “Kleiber’s Law” or the “3/4 Rule” is neither a Law nor a Rule but Rather an Empirical Approximation. Systems, 2:186-202.Higley, K.A. and D.P. Bytwerk, 2007. Generic approaches to tranfer, J. Environ. Radioactiv. 98:4-23.

Energy metabolism and transfer of 3H and 14C in mammals and birds

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Energy metabolism and transfer of 3H and 14C in mammals and birds

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