Review SDA

7/30/2019 Review SDA

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Review

Specific dynamic action: A century of investigation

M.D. McCue

Department of Biology, University of Arkansas, 601 Science Engineering, Fayetteville, AR, 72701, USA

Received 2 December 2005; received in revised form 15 March 2006; accepted 21 March 2006

Available online 30 March 2006

Abstract

Specific dynamic action (SDA) is the term used to refer to the increased metabolic expenditure that occurs in postprandial animals. Postprandialincreases in metabolism were first documented in animals over two hundred years ago, and have since been observed in every species thus far

examined.Ironically, theubiquityof this physiological response to feeding understates itscomplex nature. This reviewis designed to summarizeboth

classical and modern hypotheses regarding the causality of SDA as well as to review important findings from the past century of scientific research

into SDA. A secondary aim of this work is to emphasize the importance of carefully designed experiments and systematic hypothesis testing to make

more rapid progress in understanding thephysiological processes that contribute to SDA. I also identify three areas in SDAresearch that deserve more

detailed investigation. The first area is identification of the causality of SDA in model organisms. The second area is characterization of SDA

responses in novel species. The third area is exploration of the ecological and potential evolutionary significance of SDA in energy budgets of

animals.

2006 Elsevier Inc. All rights reserved.

Keywords: Calorigenesis; Diet; Digestive energetics; Feeding costs; Gut-upregulation; Metabolic increment; Nutrition; Postprandial metabolism; SDA; Temperature

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

2. History of SDA investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383

3. Characterizing SDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384

4. Recent studies of SDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389

5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391

1. Introduction

Specific dynamic action (SDA) refers to the increased meta-

bolic rate an animal experiences following ingestion of a meal.

The physiological causality of this phenomenon has a long

history in comparative nutritional and physiological research.

Over the past one-hundred years dozens of hypotheses have

been advanced to explain the physiological processes that ac-

count for SDA. These hypotheses can be grossly categorized

into three groups (preabsorptive, absorptive, and postabsorptive

physiological processes).

Preabsorptive explanations of SDA involve the energetic

costs of meal heating (Wilson and Culik, 1991), gut peristalsis

(Borsook, 1936; Tandler and Beamish, 1979), enzyme secretion

(Gawecki and Jeszka, 1978; Coulson and Hernandez, 1979;

Owen, 2001), protein catabolism (Iwata, 1970; Pierce and

Wissing, 1974; Coulson and Hernandez, 1979; Houlihan, 1991),

acid secretion (Secor, 2003), intestinal remodeling (Secor and

Diamond, 1995; Wang et al., 2001; Secor and Faulkner, 2002),

Comparative Biochemistry and Physiology, Part A 144 (2006) 381 394

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and blood pH regulation (Secor and Diamond, 1995; Owen,

2001). Absorptive explanations of SDA typically involve ener-

getic costs related to intestinal absorption (Secor et al., 1994;

Secor, 2003; McCue et al., 2005) and nutrient transport across

extradigestive membranes (Beamish, 1974; Soofiani and

Hawkins, 1982), or imply that hormone secretions directly in-

duce increased postprandial metabolism (Baumann and Hunt,1925). Postabsorptive explanations of SDA are thought to in-

volve costs of protein synthesis (Grisolia and Kennedy, 1965;

Garrow and Hawes, 1972; Coulson and Hernandez, 1979;

Brown and Cameron, 1991a,b; Houlihan, 1991; Whiteley et al.,

2001; McCue et al., 2005), ketogenesis (Borsook, 1935, 1936),

amino acid deamination and/or oxidation (Lusk, 1922; Cham-

bers and Lusk, 1930; Wilhelmj, 1934; Borsook, 1936; Kriss,

1941; Coulson and Hernandez, 1979), glycogen production

(Adams, 1926; Wilson and Lewis, 1930; Wilhelmj, 1935), urea

production (Terroine and Bonnet, 1929; Borsook and Keighley,

1933; Brody, 1945), renal excretion (Wishart, 1928; Borsook

and Winegarden, 1931; Dock, 1934; Borsook, 1935; Brody,1945; Hoar, 1983; Kalarani and Davies, 1994), and general costs

of growth (Brody, 1945; Ashworth, 1969; Krieger, 1978; Vahl,

1984; Carter and Brafield, 1992). The multitude of physiological

processes that apparently contribute to SDA is potentially over-

whelming to many researchers in this field. After decades of

research arguably the most prolific investigator of SDA, Graham

Lusk, eventually realized that, A complete analyses of all the

factors which meter into the specific dynamic action of protein

is quite impossible, but their way of discovery appears open.

(Lusk, 1931)

It should be noted that many of the pre- and postabsorptive

physiological processes are inevitably linked to one another,

and thus the energetic costs associated with each are difficult toisolate in vivo. For example, rates of renal excretion are highly

dependent on rates of urea formation, which are dependent on

rates of amino acid deamination, which are in turn dependent on

the balance between protein catabolism and anabolism. Many of

these physiological processes are also difficult to isolate tem-

porally and spatially within an animal (Fig. 1). For example, the

liver might be a primary site for amino acid deamination and

urea formation, but is also the primary site for ketogenesis and

glycogenesis. Similarly, intestinal tissues may incur the distinct

costs of tissue remodeling, peristalsis, and absorption.

Since Lusk's time, researchers investigating SDA have madegreat progress in understanding how various endogenous and

exogenous factors influence SDA in different species. However,

our ability to identify the fundamental energetic processes un-

derlying SDA is scarcely better now than it was in the first

quarter of the twentieth century. Modern researchers investigat-

ing SDA may find it surprising that the rates of scientific de-

velopment for most other physiological phenomena consistently

outpace the progress toward understanding the causality of

SDA; it is certainly not a result of a lack of effort (see below).

In his classic paper on strong inference, Platt (1964) recog-

nizes the fact that some areas of science are experiencing limited

rates of progression. As previously described research into SDAphysiology clearly falls into this category. In his manuscript Platt

notes, Anyone who looks at the matter closely will agree that

some fields of science are moving forward very much faster than

others, perhaps by an order of magnitude, if numbers could be

put on such estimates. Platt's solution to apparent scientific

stagnation involves a rigorous battery of hypothesis testing. He

further states, We praise the lifetime of study, but in dozens

of cases, in every field, what was needed was not a lifetime

but rather a few short months or weeks of analytical inductive

inference. We should try, like Pasteur, to see whether we can

reach strong inferences that encyclopedism could not discern.

Forthcoming investigations of SDA should not overlook this

traditional yet effective approach to problem solving in science.As a result, this review is designed to summarize the existing

encyclopedic knowledge of SDA as well as to provoke testing

of critical hypotheses that will hopefully allow researchers to

make more rapid progress in understanding SDA.

Peristalsis

Enzyme production/secretion

Enzyme production/secretion

Acid secretion

Mechanical digestion

Deamination

Ketogenesis

Glycogenesis

Urea production

Protein catabolism

Peristalsis

Gut remodeling

Absorption

Excretion

Peristalsis

Absorption

Anabolism

New growth

Liver

Stomach

Kidney Kidney

Pancreas

Esophagus

Fig. 1. Schematic illustrating some of the physiological processes that have been hypothesized to be contributing factors to specific dynamic action.

382 M.D. McCue / Comparative Biochemistry and Physiology, Part A 144 (2006) 381394


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The concept of SDA is commonly introduced in textbooks

of physiological nutrition (DuBios, 1936; White et al., 1964;

Blaxter, 1989; Whitney and Rolfes, 1996; Randall et al., 1997),

however most of these sources devote only one or two para-

graphs to SDA. These brief overviews of SDA fail to emphasize

multiplicity of physiological processes that underlie SDA

and imply that this phenomenon is fully understood by scientists.A text published by the American Medical Association even

laments SDA stating, In our opinion, the importance of SDA

in human nutrition has been misunderstood and overrated

(Bradfield and Jourdan, 1973). Such an attitude discounts both

the enigmatic nature and the biological significance of SDA.

Texts on clinical nutrition similarly suggest that the costs

of SDA are negligible to digestive energetics (Taylor and Pye,

1966; Kreutler, 1980; Whitney and Rolfes, 1996), but this is

clearly not the case in animals generally. While accounting for

617% of the energy budget in humans (Taylor and Pye, 1966),

SDA accounts for approximately one third of the ingested

energy in several nonhuman animals (Pierce and Wissing, 1974;Hailey and Davies, 1987; Secor and Phillips, 1997; Hailey,

1998; McCue and Lillywhite, 2002; McCue et al., 2005), and

thus should not be ignored by biologists. Some studies of SDA

even demonstrate that animals may demonstrate behavioral or

physiological adaptations to minimize energy devoted to SDA

(Taylor and Pye, 1966; Wilson and Culik, 1991; Boyce and

Clarke, 1997; Radford et al., 2004; Fu et al., 2005; Jordan and

Steffensen, 2005). These studies suggest that energy not appro-

priated to costs of digestion may then be spent on growth and

activity of the organism (Kalarani and Davies, 1994; Alsop and

Wood, 1997; Owen, 2001), however, no studies have yet inves-

tigated the potential influence of SDA costs on dietary choices

and ultimately on the foraging behaviors of animals. BecauseSDA can account for a potentially large, albeit variable, fraction

of animal energy budgets, a better understanding of SDA related

energy expenditure promises to increase our general under-

standing of ecological and evolutionary bioenergetics.

2. History of SDA investigation

Specific dynamic action has been described by several names

in literature including Darmarbeit (von Mering and Zuntz,

1877; Zuntz and von Mering, 1883), metabolism of plethora

(Lusk, 1922; Mason et al., 1927), generic dynamic action

(Wilhelmj, 1935), secondary dynamic action (Wishart, 1928),thermic energy (Brody and Procter, 1933) thermic effect of

food, (Whitney and Rolfes, 1996) diet-induced thermogenesis

(Newsholme and Leech, 1983), heat increment (Blaxter,

1989),postprandial calorigenesis (McCue et al., 2002a;

McCue, 2003) calorigenic effect (Pike and Brown, 1984), as

well as SDA. Each of the aforementioned terms were chosen by

various researchers for its respective explanatory power, how-

ever the multiple nomenclature used to refer to this enigmatic

phenomenon is indicative of its complex physiological nature.

The most commonly used term specific dynamic action

(and the initialism SDA) was adapted from the German phrase

(specifisch-dynamische wirkung) coined by Max Rubner in the

1890s. Although in its native language this phrase referred to

specific physiological changes induced by food processing, its

English translation is misleading (Pike and Brown, 1984). For

example, it was a result of the disconnect between this term and

its physiological significance that one study erroneously ref-

erred to specific dynamic action as secondary dynamic action

(Wishart, 1928). Whether related to its antiquity or its trans-

lation from its native tongue, the term specific dynamic action issomewhat confusing and does little to communicate any rela-

tionship between metabolism and feeding. Nevertheless SDA

remains the most historically common term to refer to this

phenomenon and thus will be employed throughout the re-

mainder of this review.

Most textbook descriptions of SDA still rely exclusively on

Rubner's turn of the century metabolic measurements on post-

prandial dogs consuming lipid, carbohydrate or protein meals

(White et al., 1964; Newsholme and Leech, 1983; Blaxter, 1989;

Whitney and Rolfes, 1996). While Rubner's work was critical to

the early characterization of specific dynamic action in animals,

it was certainly not the first; the earliest observations of post-prandially elevated metabolism were made by Lavoisier in 1780,

Pettenkpfer and Voit in 1862, and Bidder and Schmidt in 1852

(see Borsook, 1936; Taylor and Pye, 1966). While Rubner's

measurements of SDA on dogs clearly provided an initial frame-

work on which to base hypothesis regarding the physiological

processes underlying specific dynamic action, it is important to

note that these conclusions may not apply to SDA in other

animals. With the exception of Benedict's (1932) investiga-

tion into SDA of ectotherms, virtually all of the investigations

of SDA prior to the 1940s employed endothermic animals as

research subjects (most frequently dogs and rats). Regular in-

vestigations of SDA in ectotherms were not conducted until

paramagnetic oxygen analyzers became widely available in the1950s. Modern studies of SDA now embrace the use of ecto-

thermic animals for several reasons (see below).

As previously discussed, there are at least as many con-

tributing factors to SDA as there are names for this phenomenon.

Perhaps the earliest hypothesis to explain the source of increased

postprandial metabolism was associated with the physiological

costs associated with alimentary peristalsis, glandular secretion

and mechanical digestion of a meal (see Borsook, 1936). Late

in the nineteenth century Rubner's contemporary, Zuntz termed

these collective costs darmarbeit (von Mering and Zuntz, 1877;

Zuntz and von Mering, 1883). However, the darmarbeithypothe-

sis was not supported by a series of studies where various non-nutritive meals were fed to dogs (Lusk, 1922; Mason et al., 1927).

Despite additional comparative evidence against the darmarbeit-

hypothesis (Lusk, 19121913b, 1915; Rapport, 1924; Coulson

and Hernandez, 1979; McCue et al., 2005), some researchers have

not completely abandoned this theory to explain the causality of

SDA (Pierce and Wissing, 1974; Gawecki and Jeszka, 1978;

Secor and Diamond, 1995).

Prior to the past decade the richest period of inquiry into

SDA occurred between 1910 and 1940, and attracted a diverse

group of scientists including clinical physicians, biochemists,

and comparative physiologists. In this early period, most of the

scientific discourse on the subject was published in the Journal

of Biological Chemistry and the Journal of Nutrition. Many of

383M.D. McCue / Comparative Biochemistry and Physiology, Part A 144 (2006) 381394


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these early publications contain scientific debates regarding the

causality of SDA that are virtually identical to those found in

modern literature (see below). Interestingly, these perspectives

are rarely cited by current researchers of SDA.

According to an elegant literature review by Wilhelmj (1935),

three observations regarding SDA of proteins were consistently

noted among endotherms. The first was that SDAwas nota resultof directcombustion of amino acids. This pattern has been later

confirmed in studies of ectotherms. Coulson and Hernandez

(1979) and McCue et al. (2005) found no correlation between the

energy content of amino acids and resulting SDA in alligators

and pythons respectively. The second observation was that SDA

was nota result of direct stimulation of metabolism as a result of

increased amino acid levels in tissues (but see Rapport and Katz,

1927). This observation was further supported in modern experi-

ments on rodents (McNurlan et al., 1982) and several ecto-

therms. For example, Brown and Cameron (1991a,b) failed to

observe SDA in catfish previously treated with cycloheximide, a

chemical to inhibit protein synthesis, before being injected withseveral different amino acid solutions. Similar results with cy-

cloheximide were observed in pythons (McCue et al., 2005).

Wilhelmj's third observation was that SDA could not be fully

explained by work of the digestive glands, intestinal movements,

or nutrient absorption. This observation is also supported by

data obtained from diverse ectothermic species. For example,

Coulson et al. (1978) reported that the processes of absorption

and transport are dominantly passive co-transport processes in

alligators and caimans consuming complete, balanced protein

meals. Tandler and Beamish (1979) also concluded that the

mechanical component of SDA in bass fed cellulose was only a

small fraction of total SDA.

The 1950s and 1960s marked a relatively quiescent period ininvestigations of SDA. Although a few reports of SDA in ecto-

therms were published in these decades (e.g. Roberts, 1968),

comparative studies of digestion did not emphasize SDA. How-

ever, in the 1970s Herbert Coulson's research into the digestive

physiology of ectothermic tetrapods marked a renaissance for

investigations into the causality of SDA (Coulson and Hernan-

dez, 1968, 1970, 1979; Herbert and Coulson, 1975, 1976). In an

apparent response to Coulson's ideas about SDA in ectotherms,

aquacultural researchers charged with maximizing growth rates

of fishes developed an obvious appreciation for SDA. By the

1980s SDA research was dominated by studies involving com-

mercially raised fishes (see Jobling, 1981, 1983; Machida, 1981;Belokopytin, 2004).

In the past decade, Secor and Diamond conducted experi-

ments revealing that pythons exhibited comparatively large

metabolic responses to feeding (Secor and Diamond, 1995). The

ease in measuring SDA in pythons has allowed them and related

snake species to become popular organisms for current studies of

SDA (Secor and Diamond, 1998); however, the specialized diets

of these animals preclude them from being the ideal model

organism for all SDA investigations. Moreover, like much of the

early research into SDA, modern interpretations of SDA are not

without controversy. Secor and Diamond's work frequently

stated that costs of gut upregulation accounted for the majority of

SDA in pythons. However, recent experiments by Starck pre-

sented data that failed to support this hypothesis (Starck, 1999;

Starck and Beese, 2001; Overgaard et al., 2002; Starck et al.,

2004). Other studies conducting repeated feedings in fishes and

turtles also concluded that gut upregulation was not a significant

component of SDA (Owen, 2001; Pan et al., 2005b).

Although early SDA research regularly employed endo-

therms, recent researchers tend to focus on the SDA of ecto-thermic species, particularly fishes and reptiles. Unfortunately,

because of the specialized digestive physiology, morphology,

and diet of many ectotherms, conclusions drawn from studies

involving highly specialized species may not apply to many

taxa. Current understanding of SDA of animals in general would

certainly benefit from renewed research of SDA in endother-

mic animals. Patterns uncovered from such experiments would

complement the ongoing investigations involving ectotherms

and expand physiological understanding of SDA in animals

generally.

3. Characterizing SDA

Several methods are used to characterize the meal size in

SDA trials; some of these methods more readily lend themselves

to hypothesis testing than others. Early studies generally des-

cribe SDA response as a function of the absolute mass ingest-

ed (Lusk, 19121913a,b, 1915; Wilhelmj and Bollman, 1928;

Wilhelmj et al., 1931), or as a function of the caloric value of the

meal (Lusk, 1910, 1922; Kriss et al., 1934; Kriss, 1938; Kriss

and Marcy, 1940). Many modern studies of tetrapods charac-

terize SDA as a function of relative prey mass (Muir and Niimi,

1972; Janes and Chappell, 1995; Secor and Phillips, 1997;

Hopkins et al., 1999; Overgaard et al., 1999; Busk et al., 2000;

Hicks et al., 2000; Secor, 2003; Roe et al., 2004), and studies onfishes often describe SDA as a function of the percent of protein

in the diet (Hamada and Maeda, 1983; Chakraborty et al., 1992).

It is important to realizethat the best characterization of a meal in

SDA trials is not necessarily the one that is most frequently used

in literature, but the one that most appropriately suits the phe-

nomenon being evaluated. In many cases measurements of rel-

ative prey mass are among the least informative measures of

meal size because such metrics are invariably confounded by

animal size and fail to characterize meals at a molecular level.

Like many physiological variables, SDA responses are well-

known to vary allometrically with an animal's body mass (Carter

and Brafield, 1992; Beaupre et al., 1993; Boyce and Clarke,1997; Clarke and Prothero-Thomas, 1997; Secor and Faulkner,

2002; Toledo et al., 2003; Beaupre, 2005; Fu et al., 2005).

Interpretations of SDA that neglect to account for the allometric

nature of the response could be misleading since a 1 kg animal

consuming a 0.1 kg meal might be viewed identically to a 10 kg

animal consuming a 1 kg meal. Consequently, SDA responses

from these two situations can only be directly compared if SDA

is known to scale linearly with meal size or if the allometric

relationship between animal mass and SDA responses to a given

meal type is known. Thus, the practice of describing meals based

on their relative prey mass is only valid when dealing with

conspecifics of a given age/size that are consuming identical

meals. Although individual studies of SDA generally compare



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similar age/size classes within a species, comparisons of results

from other studies using identical species can be precluded when

a different size class is used.

Some studies of SDA control for relative meal size, but they do

not account for the differences in energy content of meals (Tandlerand Beamish, 1979; Hamada and Maeda, 1983; Chakraborty et

al., 1992; McGaw and Reiber, 2000; Grayson et al., 2005; Pan et

al., 2005a). Like comparisons involving different relative meal

sizes, the results of these studies should be interpretedwith caution

since two identical rations might have drastically different caloric

content and induce differential SDA responses. For example, a

pure lipid meal of a given mass has a smaller volume, but a caloric

value much greater than that of a hydrated carbohydrate meal.

Comparisons of SDA responses from isoenergetic meals of a

given physiological fuel should also be interpreted with caution.

For example protein meals consisting of gelatin and casein are

subject to differential physiological processing because of their

dramatically different amino acid composition; casein can bereadily converted to new tissue growth whereas gelatin contains a

very incomplete mixture of amino acids and cannot be used to

support extensive protein synthesis (Coulson and Hernandez,

1979; McCue et al., 2002b, 2005). Similar results are expected

from comparisons of lipid or carbohydrate meals if they differ

greatly in their molecular composition.

Because SDA is an increase in metabolic expenditure following

feeding, it is important that researchers develop uniform methods

for characterizing the pre- and postfeeding metabolic rates in

various animals. Many animals are known to demonstrate diel

fluctuation in metabolic rates; these fluctuating metabolic rates

must be subtracted from the postprandial metabolic expenditure todetermine actual energy devoted to SDA. Some studies have

ignored diel fluctuations in metabolic rates and used the lowest

metabolic measurement made during a 24 h period to characterize

postabsorptive metabolic expenditure (Beaupre, 2005). This

technique will not only overestimate the magnitude and duration

of the SDA response in postprandial animals, but will also yield an

apparent SDA response in postabsorptive animals!

A recent study outlines criteria for identifying SDA in ani-

mals that exhibit strong diel fluctuations in metabolic rate. Roe

et al. (2004) suggest defining the SDA response in animals that

exhibit diel variation in resting metabolic rates by subtracting

the dynamic postabsorptive metabolic rate from dynamic pre-

feeding values. They also recommend defining the terminus of

the SDA response in animals as the point in time when post-

prandial metabolic rates return to the upper 25% of prefeeding

metabolic rates for a given time of day (Fig. 2). This technique

of course requires detailed information about pre-feeding meta-

bolic rates, but allows researchers to precisely determine the

terminus of SDA. Unfortunately this method may not be useful

for some animal species that consume very large meals. Someanimals that consume relatively large meals (i.e. pythons, star-

fish, or nemerteans) are able to convert the majority of ingested

matter into biologically active tissue during the course of di-

gestion; thus the metabolic rate of the animal would never return

to its original value, ultimately obscuring the terminus of the

actual SDA response. Although no technique has been proposed

to standardize SDA measurements in such animals, a method

that allows for inter-species comparisons of SDA responses is

desirable.

Because SDA is an increase in energy expenditure follow-

ing feeding, it can also be characterized using several metrics

(Fig. 3). Numerous metrics for quantifying SDA have been de-veloped presumably because they offer insight into the various

physiological processes underlying SDA (see Jobling, 1981;

Guinea and Fernandez, 1997). Most accounts of SDA utilize

multiple measurements to characterize postprandial metabolic

responses. Some investigations of SDA emphasize the duration of

elevated metabolism (Hamada and Maeda, 1983; Kalarani and

Davies, 1994; Guinea and Fernandez, 1997; Roberts and Thomp-

son, 2000), or an animal's absolute increase in metabolic rate

(Overgaard et al., 1999; Somanath et al., 2000). Other studies

emphasize the duration following feeding at which peak post-

prandial metabolism occurs (Machida, 1981; Hamada and

Maeda, 1983; Ross et al., 1992; Janes and Chappell, 1995;

Roberts and Thompson, 2000). This latter measure allows domi-nant physiological processes during SDA to be temporally cate-

gorized into early or late SDA responses. Measures of SDA

duration vary widely among taxa compared to other measures,

and thus often preclude meaningful interspecific comparisons.

For example, while birds and mammals typically demonstrate

SDA responses lasting only hours (Janes and Chappell, 1995),

animals with very low metabolic rates may demonstrate responses

Duration

Diel fluction in RMR

Metab

olicrate

Resting metabolic rate

Fig. 2. Schematic illustrating the difficulty in precisely identifying the terminus

of the SDA response in animals that exhibit strong diel fluctuations in resting

metabolic rates (Based on Roe et al., 2004).

Metabolicrate

Time

Time to peak metabolic rate

Increaseinmetabolicrate

Highestrecorded

metabolicrate

Duration of increased metabolismSMR

Fig. 3. Schematic illustrating several of the metrics used typically used toquantify the SDA response (modified from McCue, 2003).



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Table 1a

Overview of SDA responses in amphibians, fishes, and invertebrates

Animal Meal CSDA (%) Duration (h) Scope Time to peak Reference

Aves

Penguin (chick) Krill 10 10 1.2 1 Janes and Chappell (1995)

MammalsDog Glucose 5 5 1.3 3 Lusk, 1912, 1915

Dog Water n/a 1.0 n/a Lusk, 1912; Rapport, 1924

Dog Olive oil 19 1.2 3 Lusk (1912)

Dog (large meal) Beef 50 Weiss and Rapport (1924)

Dog (small meal) Beef 32 Weiss and Rapport (1924)

Dog Beef 45 22 1.9 8 Williams et al. (1912)

Human Protein 17 10 2.0 Bradfield and Jourdan (1973)

Human Protein 17 1.2 3 Mason et al. (1927)

Human Glucose 4 1.2 3 Mason et al. (1927)

Human Fat 4 1.1 4 Mason et al. (1927)

Rat Beef heart a 7 b24 1.2 Kriss (1938)

Rat Gelatina 8 b24 1.2 Kriss (1938)

Rat Caseina 13 b24 1.3 1 Kriss et al., 1934; Kriss, 1938

Rat Olive oila 4 b24 1.1 2 Kriss et al. (1934)

Rat Starcha

4 b24 1.3 2 Kriss et al. (1934)Rat Casein 1.6 0 Gawecki and Jeszka (1978)

Reptiles

House snake (large meal) Mouse 15 5.3 24 Roe et al. (2004)

House snake (small meal) Mouse 17 3.2 24 Roe et al. (2004)

Alligator Caseinb 21 130 12 Coulson and Hernandez (1979)

Alligator Fishb 28 80 4.0 12 Coulson and Hernandez (1979)

Alligator Gelatinb 3 36 8 Coulson and Hernandez (1979)

Alligator Rodents 3.3 36 Busk et al. (2000)

Black racer Mouse 15 96 5.4 Secor and Diamond (2000)

Boa (large meal) Mouse 14 210 8.1 38 Toledo et al. (2003)

Boa (small meal) Mouse 12 58 2.5 14 Toledo et al. (2003)

Brown forest skink Mealworm 38 1.6 13 Lu et al. (2004)

Caiman Rodents 1.6 Gatten (1980)

Chinese skink Frog heart 17 60 2.0 19 Pan et al. (2005a)Chinese skink Mealworm 9 70 1.5 14 Pan et al. (2005a)

Colubrid snake Guinea pig 26 Benedict (1932)

Colubrid snake Mouse 28 Hailey and Davies (1987)

Corn snake Mouse 48 2.4 12 McCue, unpublished data

Cottonmouth Mouse 33 216 5.5 60 McCue and Lillywhite (2002)

Gopher snake Mouse 14 120 8.0 Secor and Diamond, 2000

Gopher snake Mouse 17 72 2.7 16 McCue (2002)

King snake Mouse 14 96 7.0 Secor and Diamond (2000)

Lizard Mealworm 48 1.9 4 Roberts and Thompson (2000)

Monitor Hardboiled egg 24 72 6.7 24 Secor and Phillips (1997)

Monitor Rat 23 90 9.9 27 Secor and Phillips (1997)

Monitor Turkey/snails 17 60 10.4 27 Secor and Phillips (1997)

Monitor Rodents 24 Hicks et al. (2000)

Python Mouse 27 40 Overgaard et al. (2002)

Python Rat 32 24 17.0 360 Secor and Diamond (1995)Python Chicken 32 96 5.4 36 McCue et al., 2005; 2002b

Python Mouse 15 56 3.4 24 McCue et al., 2005; 2002b

Python Mouse (puree) 20 56 5.2 18 McCue et al. (2005)

Python Lard 0 0 0.0 n/a McCue et al. (2005)

Python Glucose 32 85 3.4 40 McCue et al. (2005)

Python Amino acids 40 3.8 9 McCue et al. (2002a)

Python Starch 0 0 0.0 n/a McCue et al. (2005)

Python Gelatin 0 0 0.0 n/a McCue et al. (2005)

Python Casein 18 100 3.1 76 McCue et al. (2005)

Python (20 C) Mouse 25 432 6.2 216 Wang et al. (2003)

Python (35 C) Mouse 28 240 5.7 36 Wang et al. (2003)

Rattlesnake (large meal) Mouse 18 170 7.3 33 Andrade et al. (1997)

Rattlesnake (large meal) Mouse 360 10.4 36 Zaidan and Beaupre (2003)

Rattlesnake (small meal) Mouse 13 62 3.7 15 Andrade et al. (1997)

Rattlesnake (small meal) Mouse 110 3.9 24 Zaidan and Beaupre (2003)



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on the order of several days (Andrade et al., 1997; Boyce and

Clarke, 1997; Clarke and Prothero-Thomas, 1997; Secor andDiamond, 1997; Hopkins et al., 1999; McCue and Lillywhite,

2002). One starfish has even been reported to increase

postprandial metabolism for up to 42 days (Vahl, 1984). Other

studies report factorial increase in metabolism (occasionally

referred to as scope or factorial scope) resulting from SDA

(Secor and Diamond, 1995, 1997; Hailey, 1998; Hopkins et al.,

1999). SDA scope is calculated as the maximal postprandial

metabolic rate divided by the standardor basalmetabolic rate. The

SDA scope is important because it can be compared to maximal

metabolic scope of an animal in order to estimate the residual

capacity for activity during digestion. Guinea and Fernandez(1997) provide quantitative descriptions of some of the

aforementioned metrics (Fig. 3).

Some measures of SDA demonstrate more bioenergetic

relevance compared to others. Since the energy devoted to SDA

generally increases with ration and meal size (Hamada and

Maeda, 1983; Wilson et al., 1985; Chakraborty et al., 1992;

Andrade et al., 1997; Boyce and Clarke, 1997; Secor and

Diamond, 1997; Secor and Phillips, 1997; Hailey, 1998; Toledo

et al., 2003; Fu et al., 2005), the most informative measures of

Red-eared slider turtle Mealworm 55 1.5 18 Pan et al. (2004)

Red-eared slider turtle Shrimp 45 1.5 14 Pan et al. (2004)

Stripe-necked turtle Mealworm 11 72 1.8 13 Pan et al. (2005b)

Stripe-necked turtle Shrimp 13 72 1.4 12 Pan et al. (2005b)Tortoise Fungi 14 144 2.2 Hailey (1998)

Tortoise Leaves 16 72 Hailey (1998)

Tortoise Insects 23 72 1.6 Hailey (1998)

Turtles Beef 20 120 2.7 36 Secor and Diamond (1999)

Water skink Mealworm 8 48 1.9 25 Iglesias et al. (2003)

Water snake Unknown 83 5.0 22 Hopkins et al. (1999)

Water snake Fish 3.2 18 Sievert and Andreadis (1999)

CSDA refers to SDA coefficient (see text), scope refers to the maximal metabolic rate during digestion divided by the standard or basal metabolic rate of the animal, and

time to peak refers to the time period after feeding at which the SDA response reaches a peak level.a Corrected for basal ration (5.5 g calf meal; approx. 98.9 kJ).b Estimated for 1 kg alligator.

Table 1b

Overview of SDA responses in birds, mammals and reptiles


Amphibians

Horned frog Pinky mouse 66 4.2 20 Grayson et al. (2005)

Horned frog Earthworm 69 4.4 16 Grayson et al. (2005)

Horned frog Amino acids 15 33 Powell et al. (1999)

Horned frog Mice 13 51 3.5 24 Powell et al. (1999)

Salamander Fly larvae 11 1.8 24 Feder (1984)

Toad Small rat 13 2 2.9 34 Secor and Faulkner (2002)

Toad Large rat 23 6 6.4 48 Secor and Faulkner (2002)

Toad Earthworm 37 4 4.2 18 Secor and Faulkner (2002)

Toad Superworm 21 7 4.2 48 Secor and Faulkner (2002)

Toad Rodent (20 C) 16 9 3.8 96 Secor and Faulkner (2002)

Toad Rodent (35 C) 17 2.5 4.2 20 Secor and Faulkner (2002)

Toad Insects 7 1.7 3 Sievert and Bailey (2000)

Fishes

Aholehole (small meal) Fish 16 60 2.6 16 Muir and Niimi (1972)

Aholehole (large meal) Fish 16 42 1.9 16 Muir and Niimi (1972)

Bass Fish 16 1.4 10 Machida (1981)

Bass Fish 14 30 10 Beamish (1974)

Bluegill Mayfly nymphs 13 1.8 18 Pierce and Wissing (1974)

Bluegill Fish 14 1.6 13 Machida (1981)

Bluegill Earthworm 14 1.7 9 Machida (1981)

Carp High carb diet 15 Carter and Brafield (1992)

Carp High lipid diet 21 Carter and Brafield (1992)

Carp High protein diet 23 Carter and Brafield (1992)

Carp Plants 7 Carter and Brafield (1992)

Carp Low protein 9 20 2.0 6 Chakraborty et al. (1992)

Carp High protein 16 24 2.9 8 Chakraborty et al. (1992)

(continued on next page)

Table 1a (continued)

Animal Meal CSDA

(%) Duration (h) Scope Time to peak Reference

Reptiles



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SDA are those that correlate the energetic content of a meal with

the total energy devoted to SDA. This is most commonly ac-

complished by calculating the SDA coefficient (CSDA). CSDA istraditionally calculated by dividing the energy devoted to SDA

(ESDA) by the energy contained in the meal (Emeal). Sometimes,

this divisor is corrected to reflect only the metabolizable energy

in a meal. It is expressed using the following formula.

CSDA ESDA=Emeal100

Because of the nonlinearity of SDA responses resulting from

variable meal sizes or different animal masses (see Beaupre, 2005

and references therein), CSDA can only be reliably compared

within similar sized conspecifics ingesting identical meals unless

allometric relationships between meal size, meal type, and animalsize are known. Unfortunately, such relationships are rarely

known. Therefore, in the absence of such information CSDA can be

used to broadly compare results among studies that vary by

species, body masses, and meal sizes and type. CSDA is similar to

the variable apparent specific dynamic action coefficient

(ASDAC) and SDA coefficient described by Guinea and

Fernandez (1997) and Ross et al. (1992) respectively. The tables

belowpresents CSDA, and other metrics of SDA responses reported

in studies of animals ingesting various meals (Tables 1a and b).

Some of these values were not implicitly presented in primary

literature and had to be calculated from other information

provided in the text. While this table is not intended to include all

studies reporting CSDA, it does embody the SDA responses of a

diverse collection of animals consuming a variety of diets. It

should again be mentioned that measures ofCSDA are not always

linear and are often subject to allometric constraints, particularlywhen animals consume unusually small or unusually large

meals. In some cases CSDA is reported to increase exponentially

with meal size (Lusk, 19121913b, 1922; Weiss and Rapport,

1924; Carter and Brafield, 1992), whereas in other studies CSDAis differentially reduced as meal size increases (Toledo et al.,

2003; Fu et al., 2005). Although CSDA is an ideal measure for

comparing SDA in some situations, it is not beneficial for testing

all hypotheses about SDA. This is especially true when

comparing the postprandial calorigenic effects of individual

amino acids or other mixtures of purified physiological fuels. In

cases where animals are ingesting various mixtures, it is more

helpful to quantify SDA using molar quantities (Lusk, 1912;

Meal Size

SDA

Activity

Activity

SDA

Fig. 4. Schematic illustrating the potential tradeoff between activity scope andmetabolic increment associated with SDA (modified from Owen, 2001).

Table 1b (continued)


Carp Pellets 15 1.5 4 Hamada and Maeda (1983)

Catfish Amino acids 3 Brown and Cameron (1991b)

Catfish (large meal) Loach 14 52 4.1 22 Fu et al. (2005)

Catfish (small meal) Loach 13 16 1.5 4 Fu et al. (2005)Cichlid Pellets 6 2.4 3 Somanath et al. (2000)

Hawkfish Shrimp/squid 15 36 2.2 12 Johnston and Battram (1993)

Plunder Fish (large ration) Krill muscle 10 390 2.4 36 Boyce and Clarke (1997)

Plunder Fish (small ration) Krill muscle 56 324 2.5 6 Boyce and Clarke (1997)

Sculpin Shrimp/squid 17 160 2.4 48 Johnston and Battram (1993)

Shark Fish 12 2.3 9 Ferry-Graham and Gibb (2001)

Sleeper Fish 18 2.7 12 Machida (1981)

Sparus Pellets 18 38 2.6 3 Guinea and Fernandez (1997)

Tilapia Fish meal 10 2.4 8 Ross et al. (1992)

Walleye Fish 10 36 4.0 10 Tarby (1981)

Invertebrates

Blue crab Fish and clams 2.6 4 McGaw and Reiber (2000)

Copepod Algae (A) 19 Thor et al., 2002

Copepod Algae (B) 6 Thor et al., 2002Flea Blood 1.8 Fielden et al. (2004)

Leech T. tubifex 8 1.2 4 Kalarani and Davies (1994)

Lobster (day fed) Mussels 29 30 1.6 18 Radford et al. (2004)

Lobster (night fed) Mussels 38 36 1.8 3 Radford et al. (2004)

Mosquito Blood 55 1.5 Gray and Bradley (2003)

Nemertean Limpet 2 720 1.7 10,30 Clarke and Prothero-Thomas (1997)

Prawn Pellets 36 2.0 6 Gonzalez-Pena and da Gloria Blumer Soares Moreira (2003)

Starfish Mussels 1200 2.3 336 Vahl (1984)

CSDA refers to SDA coefficient (see text), scope refers to the maximal metabolic rate during digestion divided by the standard or basal metabolic rate of the animal, and

time to peak refers to the time period after feeding at which the SDA response reaches a peak level.

Fishes



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Wilhelmj, 1934; Herbert and Coulson, 1976; Coulson et al.,

1978; Coulson and Hernandez, 1979; McCue et al., 2005).

4. Recent studies of SDA

Recent studies investigating SDA can be divided into three

major categories. Some of these studies are designed to in-

vestigate the specific physiological causality of SDA in species

in which SDA is well characterized. Other studies focus on

characterizing SDA responses in species in which it has not yet

been quantified. A third group of studies seeks to understand the

ecological and evolutionary significance of SDA in the context

of natural history and energy budgets. These three lines of

investigation are complementary to one another, and much has

been learned from each of these approaches. The following

section reviews some of the most recent advances in SDA

research in these areas.

Using an ecological approach, Alsop and Wood (1997)introduced the idea that animals devoting energy to SDA may

not be able to devote maximal energy toward other activities

such as locomotion. They concluded that postprandial trout

exhibited lower maximal swimming speeds compared to

postabsorptive cohorts. Similar observations have been made

in Atlantic cod (Jordan and Steffensen, 2005). This concept of

division of energy was later formalized by Owen (2001) who

speculated that aerobic expenditure of an animal must be

partitioned between the demands of SDA and those involved in

activity (Fig. 4).

On the other hand, Hicks and Bennett (2004), examining the

traditional concept of maximal aerobic rate in varanid lizards

running on a treadmill, found that postprandial lizards were able

to achieve a new, highermaximal aerobic rate compared to the

maximal metabolic rates measured in postabsorptive lizards

(Fig. 5). Interestingly, Hicks and Bennett's findings failed to

support the energy partitioning hypothesis advanced by Owen

(2001), and concluded that the ability to separate cost of SDAand activity may vary among taxa. In light of these findings,

these researchers speculated that the additive effect of

metabolism devoted to locomotion and SDA in lizards was

possible because these two physiological states utilized different

tissue groups (i.e. viscera and locomotory muscles), and are thus

not mutually exclusive. As a result of these findings, further

examination of energetic partitioning between SDA and other

energetic demands in additional species is recommended.

Several studies have examined the influence of temperature

on SDA. Most of these investigations reported that temperature

had dramatic influence on the duration and peak metabolic rate

during digestion, but had little influence on the total energy

devoted to SDA and thus CSDA (Machida, 1981; Powell et al.,1999; Whiteley et al., 2001; Robertson et al., 2002; Secor and

Faulkner, 2002; Wang et al., 2003; Zaidan and Beaupre, 2003 ).

Although one study of SDA and temperature reported that

energy devoted to SDA in boid snakes is slightly greater at

digestion temperatures of 25 C compared to 30 C (Toledo et

al., 2003), most studies investigating the relationships between

Duration

SDA

Meal Size

SDA

SDA

25% RPM

5% RPM

20% RPM

15% RPM

10% RPM

Fig. 7. Schematic illustrating the nonlinear relationship between relative meal

size or relative prey mass (RPM) and SDA response typical in ectotherms.

Duration

SDA

warmer temperatures

cooler temperatures

Fig. 6. Schematic illustrating influence of digestion temperature on SDA inectotherms (based on Wang et al., 2003).

Mealm

assAnimalmass

SDA

Fig. 8. Schematic illustrating the allometric relationship between animal bodymass, meal size, and SDA increment (based on Beaupre, 2005).

Running speed

Me

tabolicrate

Postp

rand

ial

Posta

bsorptive

Fig. 5. Schematic illustrating the maximal aerobic metabolic rate of postprandial

and postabsorptive lizards (modified from Hicks and Bennett 2004).



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SDA and temperature employed larger sample sizes and thermal

ranges greater than 5 C than those described by Toledo et al.

(2003). In a simultaneous investigation, Wang et al. (2003)

found no thermal dependence of total energy devoted to SDA in

pythons. The results of this study are indicative of most studies

on thermal dependence of SDA, and are thus summarized in the

following schematic (Fig. 6).Because of its dramatic effect on SDA, meal size is one of the

most examined variables in SDA studies. Most recent

investigations report that SDA is highly dependent on ration.

However not all researchers arrive at this conclusion (Machida,

1981; Boyce and Clarke, 1997). As previously discussed,

studies of endotherms typically conclude that energy devoted to

SDA increases at a rate disproportionately greater than meal

size, but most recent studies of ectotherms tend to suggest that

increases in meal size result in disproportionately lower SDA

responses (Andrade et al., 1997; Secor and Faulkner, 2002;

Toledo et al., 2003; Zaidan and Beaupre, 2003; Fu et al., 2005 )

(Fig. 7). Variability among studies investigating the relationshipbetween meal size and SDA has prompted Fu et al. (2005) to

conclude, More data about the effect of meal size on SDA in

different kinds of animals should be documented. Additional

information about the effect of relative meal size is also required

to further investigate the physiological basis for observed

allometric relationships in SDA.

Recent studies have uncovered the influence animal size has

on SDA responses. Typically researchers consciously minimize

the variance in the masses of the animals used in their studies,

however studies investigating SDA in individuals of dramatically

different size have revealed that SDA is dependent on animal

mass (Secor and Faulkner, 2002; Zaidan and Beaupre, 2003;

Beaupre, 2005). This observation was apparently first quantifiedby Beamish (1974) in feeding trials of bass. The figure below

illustrates the generalized interaction between animal mass, meal

mass and SDA (Fig. 8). Although many physiological responses

associated with metabolism are well-known to scale with

allometric exponents of 0.67 to 0.75 (Kleiber, 1932, 1947; Von

Bertalanffy, 1957; Schmidt-Nielsen, 1970; Schmidt-Nielsen,

1975; West et al., 2000), little is known about why SDA

responses are far less dependent on body mass. Only two

physiological mechanisms have thus far been advanced to explain

why SDA scales allometrically with body mass. The first

hypothesis involvesdifferential rates of intestinal tissue sloughing

during digestion (Beamish, 1974), whereas the second hypothesispertains to differential costs of upregulation of intestinal

transporters (Secor and Faulkner, 2002). However because the

costs involved in nutrientuptake are believedto be much less than

the observed body-size related difference in SDA (McCue et al.,

2005), additional hypotheses should be investigated.

The energetic costs of gut upregulation on SDA have been

debated in recent SDA literature, particularly in animals that

undergo long periods of fasting between meals. This debate

centers on the mechanism of gut upregulation exhibited by

pythons (see Starck and Beese, 2001; Zaidan and Beaupre, 2003;

McCue et al., 2002a,b; Overgaard et al., 2002). While the actual

costs associated with gut remodeling in pythons still remain

unknown, it is likely that the costs of gut upregulation in most

animals are dramatically less than in pythons since most animalstypically feed more frequently than pythons (Hailey, 1998). Two

studies examining the costs of gut upregulation in pythons and

turtles by refeeding postprandial animals before the terminus of

the SDA response (Overgaard et al., 2002; Pan et al., 2005b)

document an additive response between the end of the initial

SDA response and the second SDA response (Fig. 9). Because

these meals were fed so closely to one another gut atrophy (or

gut-downregulation) could not occur, the results allowed the

researchers to conclude that the cost of gut remodeling was

negligible in this species. Additional research is required to

determine if this pattern is exhibited in other animals.

5. Conclusion

The energetic costs associated with SDA are the result of

numerous preabsorptive, absorptive, and postabsorptive phys-

iological processes. These costs vary with diet and might serve

an important role in shaping natural history and foraging

behavior in animal species. Although SDA responses can be

easily detected in animals through indirect calorimetric

measurements, accounts of SDA that rely exclusively on

metabolic responses have demonstrated only limited promise

in identifying the underlying causality of SDA. Several

alternatives to simple measurements of metabolic rate show

the greatest promise in identifying the dominant physiologicalprocesses responsible for SDA. One of the earliest experimental

approaches to identify the specific tissues involved in SDA

responses was made by William Dock. Dock (1931, 1934)

ligated various organs in postprandial rats in order to identify

how particular organs and tissues differentially contributed to

SDA; he concluded that much of the energetic costs of

physiological processing associated with SDA occurred in

hepatic tissues. Modern experiments have been able to further

expand this line of investigation. The use of chemicals that block

particular processes (i.e. acid secretion and protein synthesis)

have allowed researchers to develop estimates of the energetic

contribution of specific physiological processes related to SDA.

Forthcoming investigations might similarly involve drug use

Duration

Metabolicrate

Second feeding

Fig. 9. Schematic illustrating the additive response of the SDA response in

pythons and turtles refed before metabolic rates returned to postabsorptive

levels. The open circles represent the actual metabolic response to feeding on

two meals, whereas the curves beneath the open circles represent the theoretical

nonadditive SDA responses (based on data presented in Overgaard et al., 2002;

Pan et al., 2005b).



11/14

such as muscle relaxers to examine the energetic costs associated

with peristalsis or hormone blockers to investigate the role of

hormonal regulation of SDA. Other experimental approaches for

investigating the causality of SDA might involve the use of

artificial dialysis to examine the excretory costs associated with

SDA, as well as technologies that allow measurements of blood

flow, metabolism, and nutrient flux in various organs and tissues.The numbers of scientific studies investigating the phenom-

enon of SDA has grown dramatically over the past decade. This

trend will likely continue as comparative researchers come to

appreciate the interactions among SDA, whole animal energetics,

and performance variables. I suggest we employ hypothesis-

driven experiments that focus on three important areas of SDA

research. The first area is identification of the causality of SDA in

model organisms. The second area is characterization of SDA

responses in novel species. The third area is exploration of the

ecological and evolutionary significance of SDA in energy

budgets of animals.

Acknowledgments

I wish to thank Drs. T.J.Bradley, A.F. Bennett, S.J. Beaupre,H.

B. Lillywhite, K.E. McCue, and G. Huxel as well as R. Wittenberg

for helpful comments on various phases of this manuscript.

Constructive comments were also provided by two anonymous

reviewers. I also wish to acknowledge funding provided by the

National Science Foundation Predoctoral Fellowship and the

Walton Distinguished Doctoral Fellowship awarded to MDM.

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