Limits to sustained energy intake VII. Milk energy output in laboratory mice at thermoneutrality
1 Aberdeen Centre for Energy Regulation and Obesity (ACERO), School of
Biological Sciences, University of Aberdeen, Aberdeen AB24 2TZ, UK
2 ACERO, Division of Appetite and Energy Balance, Rowett Research Institute,
Bucksburn, Aberdeen AB21 9SB, UK
* Author for correspondence (e-mail: e.krol{at}abdn.ac.uk)
Accepted 14 August 2003
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Summary |
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Key words: doubly labelled water, daily energy expenditure, water turnover, water balance, milk composition, peripheral limit, heat dissipation limit, laboratory mouse, Mus musculus
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Introduction |
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Early studies on food intake at peak lactation suggested that the limits
reflected the capacity of the alimentary tract and associated organs such as
the liver to process the ingested food (the `central limitation hypothesis';
Kirkwood, 1983;
Perrigo, 1987
; Hammond and
Diamond, 1992
,
1994
;
Koteja, 1996a
). However, mice
and hispid cotton rats (Sigmodon hispidus) forced to lactate at low
ambient temperatures are able to increase their food intake to above the
supposed centrally mediated limit (Hammond
et al., 1994
; Rogowitz,
1998
; Johnson and Speakman,
2001
). This suggested that the limit was not mediated centrally
but was controlled by the ability to expend or export the energy at the sites
of utilisation (the `peripheral limitation hypothesis'). Several lines of
evidence support this idea. For example, surgical manipulation of the number
of teats in lactating mice demonstrated that females with five or ten teats
(but with the same number of pups per teat) weaned pups that did not differ in
body mass (Hammond et al.,
1996
). These results suggest that the mammary tissue remaining
after surgery was unable to increase milk production to compensate for the
lost production of the tissue that had been removed, presumably because
mammary tissue before surgery was already at maximal performance. This
conclusion is also consistent with the observation that hispid cotton rats
lactating in the cold, despite the increased thermoregulatory demands of their
offspring, did not increase milk energy output (MEO) and therefore
produced smaller pups (Rogowitz,
1998
). Again, this implies that the mammary glands of females in
the warm were already working at maximal capacity.
However, several other studies are not compatible with the peripheral
limitation hypothesis. Johnson et al.
(2001c), for example, made
mice simultaneously pregnant while lactating. In theory, these mice should
upregulate their food intake above that of mice that were only lactating,
because the demands for pregnancy do not require elevated milk production. Yet
the mice did not do this. Similarly, lactating mice forced to run to obtain
food also failed to upregulate their energy intake to meet the demands of milk
production and exercise (Perrigo,
1987
). Perhaps most critically, Johnson and Speakman
(2001
) found that milk
production in the cold (8°C) was elevated relative to mice housed at
21°C. This shows that animals can increase their milk production above the
level thought to be maximal.
Król and Speakman
(2003) have suggested a novel
hypothesis to explain these conflicting data. According to this hypothesis,
the limits to food intake are imposed centrally but at a location different
from the alimentary track. We suggest that this central limitation is the
maximal capacity of the animal to dissipate body heat, generated as a
by-product of processing food and producing milk. This hypothesis predicts
that lactating mice kept at 21°C would not elevate their food intake,
whatever the additional demands placed on them
(Perrigo, 1987
;
Johnson et al., 2001c
),
because ingesting additional food would have made them dangerously
hyperthermic. However, when females were transferred to the cold
(Johnson and Speakman, 2001
),
the increased driving gradient between body temperature and ambient
temperature relaxed the heat dissipation constraint, and the animals were able
to elevate their food intake and use that energy for greater milk production.
The critical difference between this viewpoint and previous interpretations is
that the heat dissipation limit hypothesis views cold as a factor allowing the
animals to overcome a constraint on food intake, while previous
interpretations have considered exposure to the cold as an additional
burden.
To test the heat dissipation limit hypothesis, Król and Speakman
(2003) exposed reproducing MF1
laboratory mice (Mus musculus L.) to their thermoneutral temperature
(30°C) and measured their food intake and reproductive output. Consistent
with the heat dissipation limit hypothesis, food intake at peak lactation was
lower than observed previously in the same strain of mice lactating at either
21°C (Johnson et al.,
2001a
) or 8°C (Johnson and
Speakman, 2001
). Taken alone, this reduction in food intake is
also consistent with the peripheral limitation hypothesis as it could be
interpreted as a consequence of a reduced demand for thermoregulatory energy
expenditure. However, mice exposed to 30°C had a smaller litter size, pup
body mass and litter mass as well as a lower rate of litter mass increase than
those exposed to 21°C and/or 8°C. This might indicate that milk
production was reduced at 30°C, which is consistent with the heat
dissipation limit hypothesis but not the peripheral limitation hypothesis. An
alternative explanation, however, is that milk production was the same at each
temperature but that there were differences in the abilities of the offspring
to translate milk into growth.
In the present paper, we provide a further test of the heat dissipation
limit hypothesis by measuring the MEO of MF1 laboratory mice (Mus
musculus L.) lactating at 30°C compared with those measured
previously in mice at 21°C (Johnson et
al., 2001a) and 8°C
(Johnson and Speakman, 2001
).
The heat dissipation limit hypothesis predicts that at the higher ambient
temperature MEO will be lower because of the lower driving gradient
for heat loss. Conversely, the peripheral limitation hypothesis predicts that
milk production should not be reduced relative to that observed at lower
temperatures.
MEO in small mammals has been evaluated using a variety of
methods. These include timed milking (e.g.
Harris et al., 1966;
Hanrahan and Eisen, 1970
;
König et al., 1988
), mass
differences of the litter before and after a suckling bout (e.g.
Morag, 1970
;
Mepham and Beck, 1973
),
isotope transfer from mother to pups (e.g.
Rath and Thenen, 1979
;
Kunz et al., 1983
) and isotope
dilution in the body water of the mother (e.g.
McLean and Speakman, 1999
;
Johnson et al., 2001a
;
Johnson and Speakman, 2001
) or
the pups (e.g. Stern et al.,
1997
; Ahlstrøm and
Wamberg, 2000
; Tardif et al.,
2001
). Estimates of MEO have also been derived from the
metabolizable energy intake of the mother (e.g.
McClure, 1987
;
Künkele and Kenagy, 1997
;
Künkele and Trillmich,
1997
) and the litter energy budget (e.g.
Knight and Peaker, 1982
;
Oftedal, 1984
;
Gittleman and Oftedal, 1987
).
Data obtained using these methods, however, are not necessarily comparable due
to potential differences in the precision of each method and the validity of
assumptions on which they are based. Thus, differences in MEO between
studies could be attributed to variation in the methodology used
(Knight et al., 1986
) rather
than reflecting real biological differences. Only a few studies have compared
the estimates of MEO evaluated by different methods, and most of
these have been performed on humans (e.g.
Fjeld et al., 1988
;
Butte et al., 1991
) and large
animals such as marine mammals (e.g.
Costa, 1987
;
Arnould et al., 1996
) or farm
animals (e.g. Holleman et al.,
1975
; Coward et al.,
1982
). Therefore, our second aim was to compare the methods
commonly used to calculate MEO in small mammals by making
simultaneous measurements of components of the energy and water budgets in
lactating female mice and their pups.
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Materials and methods |
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Doubly labelled water measurements
We used the doubly labelled water (DLW) method to measure daily energy
expenditure (DEE; respiratory energy metabolism as carbon dioxide
production) from the elimination rates of 2H (deuterium) and
18O in lactating and nonreproductive females. We also calculated
total water turnover (rH2O) from the elimination rate of
2H in lactating females, non-reproductive females and pups. The
estimates of DEE and rH2O in adult mice were
based on the same 2H turnover data.
The DLW measurements were conducted on 24 lactating females (litter size
115), 24 non-reproductive females and 43 pups from seven litters of
size 10 and 12 (37 pups were labelled in each litter and raised by a
non-labelled mother). On day 14 of lactation (between 10:00 h and 12:00 h),
mice were injected intraperitoneally with approximately 0.2 g (adult mice) and
0.05 g (pups) of water containing enriched 2H (4.6 atom%) and
18O (9.4 atom%). The syringe used to inject the DLW was weighed
(±0.0001 g; Ohaus Analytical Plus) immediately before and after the
injection. Mice were replaced in their cages during the 1 h equilibration
period (Speakman, 1997).
Initial and final blood samples were taken by tail tipping 1 h and 25 h after
injection, respectively. Blood samples (30100 µl for adult mice and
1520 µl for pups) were immediately flame sealed into pre-calibrated
Vitrex pipettes (Modulohm A/S, Herlev, Denmark) and stored at 4°C until
analysis. Each adult mouse was also blood sampled on the day before injection
to determine background isotope levels. Background 2H enrichment
for the pups labelled in each litter was determined from a blood sample of a
non-labelled pup that was taken 510 min before the first pup was
labelled in that litter. The same non-labelled pup was blood sampled 24 h
later to allow correction for any incidental 2H uptake or
recycling. The body mass of each animal was measured before injection and
before taking the final blood sample.
Samples of blood were vacuum distilled into glass Pasteur pipettes
(Nagy, 1983) and the resultant
distilled water used for mass spectrometric analysis of 2H and
18O. The 2H analysis was performed on hydrogen gas,
produced from the distilled water after reaction with LiAlH4
(Ward et al., 2000
). For the
18O analysis, distilled water was converted to carbon dioxide gas
using the small sample equilibration technique
(Speakman et al., 1990
). The
2H:1H and 18O:16O ratios were
established using dual inlet gas source isotope ratio mass spectrometers
(Optima, Micromass IRMS; Manchester, UK), as described previously
(Król and Speakman,
1999
). Measurements of isotope enrichment in blood samples were
based on analysis of either two sub-samples (adult mice), in which case
further calculations were performed on the mean values, or one sample (pups)
of distilled water.
For each adult mouse, we calculated initial 2H and
18O dilution spaces by the intercept method
(Coward and Prentice, 1985).
Final 2H and 18O dilution spaces were inferred from the
final body mass, assuming the same percentage of body mass as measured for the
initial dilution spaces. The isotope elimination rate was calculated following
Nagy (1975
). For calculation
of DEE based on CO2 production, we used single-pool model
equation 3.14 (Lifson and McClintock,
1966
) with a pooled fractionation factor of 0.0249
(Speakman, 1997
), as presented
in equation 10 in Visser and Schekkerman
(1999
). We assumed a
fractional evaporative water loss of 0.64 for non-reproductive mice (3.37 g
day1 of 5.24 g day1;
Table 3) and 0.38 for lactating
mice. The latter value was derived from direct measurements of evaporative,
faecal and urinary water loss of lactating mice (10.94 g
day1, 4.10 g day1 and 5.94 g
day1, respectively; Table
3) combined with the amount of water exported in milk (7.96 g
day1, as estimated from water turnover of pups) and
calculated as 10.94 g day1 of (10.94+4.10+5.94+7.96) g
day1. Energy equivalents of CO2 production were
calculated using a conversion factor of 24.026 J ml1
CO2, derived from the Weir equation
(Weir, 1949
) for a respiratory
quotient (RQ) of 0.85 (Speakman,
1997
). Female total water turnover
(rH2Ofem) was calculated according to Lifson
and McClintock (1966
). We
assumed that 64% (non-reproductive mice) or 38% (lactating mice) of the water
leaving the body was fractionated. We applied a fractionation factor for
2H of 0.9366 (Speakman, 1977). This approach assumes that rates of
water influx and efflux are constant, so
rH2Ofem = total water influx = total water
efflux (Nagy and Costa,
1980
).
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We calculated the initial and final 2H dilution spaces of pups
in the same way as for adult animals. The elimination rate of 2H
was calculated according to Nagy
(1975) and corrected for
uptake of 2H from the environment or isotope recycling
(Baverstock and Green, 1975
;
Friedman and Bruno, 1976
). The
estimation of pup total water turnover
(rH2Opup) was based on the assumption of linear
pup growth during the measurement period and was calculated according to
Coward et al. (1982
). We
assumed the same fractional evaporative water loss as for non-reproductive
mice (0.64). rH2Opup represents the total water
influx according to this approach (Coward
et al., 1982
).
Faecal, urinary and evaporative water loss
Measurements of faecal water loss (FWL), urinary water loss
(UWL) and evaporative water loss (EWL) were conducted on
five lactating females (litter size 611) and five nonreproductive
females. On day 14 of lactation, lactating females and their offspring, or
non-reproductive females, were placed individually in metabolic cages (code
3700MO-000, Tecniplast Gazzada, Buguggiate, Italy), provided with water and a
weighed portion of food. After 24 h, the food was reweighed, and all faeces
and urine were collected and dried at 60°C to constant mass. Sorting
through the faeces samples revealed that contribution of pups to faecal and,
presumably, urine production was negligible. On day 15 of lactation, we placed
the same females on a smooth non-absorbant surface and collected fresh faeces
and fresh urine within 2 s of them being produced. These samples were
immediately weighed before drying at 60°C to constant mass. FWL
and UWL (g day1) were calculated by multiplying the
amount of faeces (or urine) produced (g dry mass day1) by
the ratio of water to dry mass content of fresh faeces (or urine).
EWL was measured gravimetrically on day 15 of lactation. Mice were placed individually in a respirometry chamber for 1 h, with an ambient air flow of 649701 ml min1. The same flow rate was used for the chamber without a mouse, as a control. During the measurements, mice sat on a wire mesh grid through which faeces and urine fell into mineral oil, trapping water from these sources. Water in the excurrent air was absorbed by silica gel. The increase in mass of silica gel was corrected for water content of incurrent air by subtracting water loss from the control chamber measurements. EWL (g day1) was calculated by multiplying the corrected increase in mass of silica gel (g h1) by 24.
Total body water by desiccation
The measurements of total body water were conducted on 46 pups (58
pups from eight litters of size 513) on day 14 of lactation. Pups were
weighed and killed by cervical dislocation. The carcasses were split open
along the midline and transverse cuts across the body were made to increase
exposure of the tissues for drying. The carcasses were dried in a convection
oven at 60°C for 14 days (Król
and Speakman, 1999). Total body water was calculated as the
difference between the fresh and dry mass and was expressed as a percentage of
the body mass prior to desiccation.
Resting metabolic rate measurements
We assessed resting metabolic rate (RMR) of individual pups and
whole litters from their rate of oxygen consumption at 30°C, using a
modification of the protocol for adult mice
(Król et al., 2003).
The measurement period was 1 h, thechamber volume was 81 ml (pups) or 885 ml
(litters) and the flow rate was 194208 ml min1 (pups)
or 487592 ml min1 (litters).
For individual pups, we required accurate estimates of oxygen consumption
(see equations 3, 4 in Appendix A of supplementary material), while in litters
we aimed for accurate estimate of energy expenditure (see equation 6 in
Appendix A of supplementary material). Therefore, RMR expressed as
oxygen consumption was calculated according to equation 1b in Koteja
(1996b), assuming an RQ of
0.74 derived from the composition of milk (present study). The RMR
expressed as energy expenditure was calculated in the same way as for adult
mice (Król et al.,
2003
).
The RMR of 10 pups (23 pups from four litters of size 212) and 23 litters (size 415) was measured on day 14 of lactation. Measurements of RMR in pups and litters were made from individuals from different families.
Milk collection and analysis
On day 15 of lactation, 12 females (litter size 915) were separated
from their pups for 3 h and then injected intraperitoneally with 1 IU of
oxytocin to stimulate milk flow. Each mammary gland was palpated towards the
nipple area and droplets of milk were collected in capillary tubes. Milk
collection continued until no more milk could be expressed. Samples of milk
(0.40.6 ml from each female) were frozen at 20°C prior to
analysis for water, fat, protein and sugar content.
All analyses (Rowett Research Institute Analytical Services, Aberdeen, UK)
were made on duplicate samples. Water content was determined by drying milk
samples (50 µl) in a convection oven at 100°C for 3.5 h. Fat content
(100 µl milk samples) was measured by the RoseGottlieb gravimetric
method (Kirk and Sawyer,
1991). Crude protein content was calculated as 6.38 x total
nitrogen content (Kirk and Sawyer,
1991
), determined from 15 µl samples of milk by a
micromodification of the Kjeldahl technique
(Davidson et al., 1970
). No
correction was made for nonprotein nitrogen content. Total sugar (20 µl
milk samples) was measured by the Anthrone method using lactose monohydrate as
the standard (Southgate, 1976
)
and is therefore expressed as the monosaccharide equivalent.
Gross energy content of milk (GEmilk; kJ
g1 whole milk) was calculated by multiplying fat, protein
and sugar content (g g1 whole milk) by 38.12 kJ
g1, 24.52 kJ g1 and 16.53 kJ
g1, respectively (modified from
Perrin, 1958).
Milk energy output
We evaluated MEO using four different methods: (1) as the
difference between metabolizable energy intake and daily energy expenditure of
the female, (2) from female water turnover, (3) from pup water turnover and
(4) from the energy budget of the litter. To compare the methods, we
calculated MEO for the 24 females for which we had individual
measurements of asymptotic food intake, litter size and litter mass
(Król and Speakman,
2003) as well as individual measurements of DEE and
rH2Ofem (present study). We examined the
sensitivity of each method by determining how an independent 1% change in each
parameter influenced the estimate of MEO. The maximum potential
decrease and increase in estimate of MEO, resulting from a 1% change
in all parameters, were also computed. The method that gave the most accurate,
precise and robust estimate of MEO was then applied to 67
reproductive females with individual measurements of asymptotic food intake,
litter size and litter mass (Król
and Speakman, 2003
). All estimates of MEO refer to day 14
of lactation. For full details of the four methods, see Appendix A of
supplementary material.
Statistics
Data are reported as means ± S.D. (N = sample
size). The relationships between energy and water budget components and body
mass were examined by least-squares linear regression analysis. The regression
lines were compared using analysis of covariance (ANCOVA). To test the
differences in DEE, rH2O, FWL, UWL and
EWL between reproductive and non-reproductive females we used
two-sample t-tests. Comparisons of the parameters measured in the
same individuals [DEE vs MEI (metabolizable energy input) and
FWL+UWL+EWL vs rH2O] were made using paired
t-tests. The four methods of evaluating MEO were compared
using repeated measures analysis of variance (ANOVA), followed by a Tukey
post-hoc test. Relationships between DEE and MEI,
between FWL+UWL+EWL and rH2O
and between the four estimates of MEO were described using Pearson
product-moment correlation coefficients. All statistical analyses were
conducted using Minitab for Windows (version 13.31, Minitab Inc., State
College, PA, USA; Ryan et al.,
1985). Statistical significance was determined at
P<0.05. All tests were two-tailed.
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Results |
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The DEE of non-reproductive females was 45.1±5.7 kJ
day1 (range 35.955.9 kJ day1,
N=17; Table 2). On
average, DEE of non-reproductive mice was 2.0±10.0% higher
than their metabolizable energy intake, with individual differences ranging
from 10.4% to 22.9% (N=17). However, the differences between
DEE and MEI were not significant (paired t=0.7,
P=0.49, N=17). The values of DEE and MEI
were highly correlated (r=0.75, P=0.001, N=17;
Fig. 2). DEE was
2.5x RMR (range 1.93.1) for the 11 non-reproductive mice
for which both DEE and RMR were measured
(Król et al., 2003).
DEE was not related to body mass (regression,
r2=0.16, F1,15=2.8, P=0.11;
Fig. 1). Non-reproductive mice
had significantly lower DEE than lactating females, both when the
comparison was made on the raw data (t30=7.0,
P<0.001) and when corrected for the differences in body mass
(ANCOVA: interaction body mass x reproductive status, P=0.19;
body mass effect, F1,38=8.6, P=0.006;
reproductive status effect, F1,38=6.8,
P=0.013).
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The total water turnover of lactating and nonreproductive females averaged 22.63±4.82 g day1 (range 10.9230.99 g day1, N=24) and 5.32±1.24 g day1 (range 3.748.18 g day1, N=24), respectively (Table 2). In both groups of mice, rH2Ofem was positively related to female body mass (lactating females, r2=0.46, F1,22=19.0, P<0.001; nonreproductive females, r2=0.46, F1,22=18.8, P<0.001; Fig. 3). There was a significant interaction between body mass and the reproductive status (ANCOVA: F1,44=11.0, P=0.002), indicating a steeper slope of the regression line for lactating than for non-reproductive females. For a mouse with a body mass of 35.6 g (mean value for both groups of mice), the predicted rH2Ofem would be 19.73 g day1 and 5.92 g day1 for lactating and non-reproductive females, respectively. Analyses of mass-corrected rH2Ofem (the residuals from the regression lines on body mass presented in Fig. 3, added to the values of predicted mean rH2Ofem) showed that lactating females had higher total water turnover than non-reproductive females (t26=18.6, P<0.001).
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Total water turnover of pups
The total water turnover of individual pups measured on day 14 of lactation
was 1.09±0.25 g day1 (range 0.501.52 g
day1, N=43;
Table 2). The
rH2Opup increased with pup body mass
(regression, r2=0.57, F1,41=54.4,
P<0.001; Fig.
4).
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Faecal, urinary and evaporative water loss
Faecal water loss averaged 4.10±1.06 g day1 in
lactating females (N=5) and 1.14±0.21 g day1
in non-reproductive females (N=5;
Table 3). These values were
significantly different (t4=6.1, P=0.004) and
were a consequence of differences in the amount of faeces produced
(2.48±0.24 g dry mass day1 and 0.64±0.12 g dry
mass day1 for lactating and non-reproductive females,
respectively; t5=15.2, P<0.001). The water
content of faeces in lactating (61.7±4.3%) and non-reproductive
(64.0±3.4%) mice was not significantly different
(t7=0.9, P=0.37).
The urinary water loss of lactating females (5.94±1.70 g day1; N=5) was higher than in non-reproductive females (0.73±0.23 g day1; N=5) (t4=6.8, P=0.002; Table 3). Lactating mice produced more urine than non-reproductive females (0.34±0.07 g dry mass day1 and 0.09±0.01 g dry mass day1, respectively; t4=7.4, P=0.002). Furthermore, the urine of lactating females had higher water content than the urine of non-reproductive mice (93.9±2.9% and 88.4±3.4%, respectively; t7=2.9, P=0.023).
Evaporative water loss averaged 10.94±1.25 g day1 in lactating females (N=5) and 3.37±1.14 g day1 in nonreproductive females (N=5; Table 3). These values were significantly different (t7=10.0, P<0.001). EWL in lactating females was positively related to litter mass (y=1.51+0.19x, r2=0.79, F1,3=11.2, P=0.044). In non-reproductive mice, heavier females had a greater EWL (y=7.12+0.31x, r2=0.79, F1,3=11.1, P=0.044).
Using the data presented above, we predicted the water loss for the 24
non-reproductive females for which we had individual measurements of body mass
and food intake (Król and Speakman,
2003), as well as individual measurements of total water turnover
(rH2Ofem; present study). FWL was
calculated from the food intake, mean dry mass content of the food (94.4%;
Król and Speakman,
2003
), the relationship between dry mass food intake and dry mass
faecal production (Król and
Speakman, 2003
), and the mean water content of faeces (64.0%;
present study). UWL was assumed to be 0.73 g day1
(present study). We predicted EWL from body mass using the
relationship established for five nonreproductive females (present study). The
sum of FWL, UWL and EWL predicted for 24 non-reproductive
females averaged 5.22±1.20 g day1 and was not
significantly different from the directly measured
rH2Ofem (5.32±1.24 g
day1; paired t=0.5, P=0.60). The values of
predicted and actual water turnover were highly correlated (r=0.71,
P<0.001, N=24; Fig.
5).
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Resting metabolic rate of pups and litters
The RMR of individual pups and whole litters, measured on day 14
of lactation, was positively related to mass (pups,
r2=0.94, F1,8=124.6,
P<0.001, N=10; litters, r2=0.74,
F1,21=58.6, P<0.001, N=23). The
relationships between RMR (ml O2 min1)
and mass (g) are described by y=0.03+0.04x (pups) and
y=0.24+0.02x (litters) (see Appendix B of
supplementary material). After conversion of the oxygen consumption data to
energy equivalents, the relationships between RMR (kJ
day1) and mass (g) are described by
y=0.79+1.11x (pups) and
y=7.28+0.71x (litters).
Milk composition
Milk samples collected on day 15 of lactation contained 65.6±1.9%
water, 20.0±2.5% fat, 10.3±0.7% crude protein and
2.1±0.4% total sugar (N=12). Variation in milk composition was
not correlated with litter size or litter mass (in all cases
P>0.05). The gross energy content of whole milk, calculated from
the milk composition, averaged 10.5±1.0 kJ g1
(N=12).
Comparison of methods for evaluating milk energy output
The milk energy output of 24 females determined from (1) the difference
between MEI and DEE of the female, (2) female water
turnover, (3) pup water turnover and (4) the litter energy budget averaged
79.5±22.5, 57.0±42.5, 93.7±27.0 and 80.3±20.0 kJ
day1, respectively (Fig.
6). The MEO determined from female water turnover was
significantly lower than the other three estimates (repeated measures ANOVA,
F3,92=13.7, P<0.001; Tukey pairwise
comparisons between the female water turnover method and the other methods,
P<0.05). Evaluation of MEO using the difference between
MEI and DEE, pup water turnover and litter energy budget
produced similar results (all Tukey pairwise comparisons, P>0.05).
The estimates of MEO from female water turnover were also
approximately twice as variable (i.e. less precise) as those yielded by the
other methods.
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Analysis of the sensitivity of the four methods showed that the evaluation of MEO from the litter energy budget was the most robust to changes in the measured parameters (see Appendix C of supplementary material). None of the parameters, which increased or decreased by 1%, caused an increase or decrease in the estimate of MEO from the litter energy budget by greater than 1%. The maximum potential change in MEO from the litter energy budget, resulting from combining a 1% change in all six parameters, ranged from 3.5% to 3.8%. The sensitivity of the MEIDEE method and the pup water turnover method were similar. For both methods, increases or decreases of 1% in any of the parameters did not change the estimate of MEO by more than 2%. The maximum potential change in estimated MEO ranged from 10.0% to 11.1% (the MEIDEE method) and from 7.2% to 8.1% (the pup water turnover method). The method that was most sensitive to errors in the component variables was based on female water turnover. Four of 10 parameters, when changed individually by 1%, had an impact on the estimate of MEO larger than 2%, while a 1% change in female water turnover (rH2Ofem) changed MEO by 6.0%. Female water turnover, therefore, contributes most of the imprecision in this method. The maximum potential change in estimates of MEO, when all 10 parameters varied by 1%, ranged from 20.5% to 21.6% when MEO was calculated from female water turnover.
Among the three methods that yielded similar estimates of MEO, the
MEIDEE method involved the minimum number of
assumptions (i.e. parameter values taken from the literature) and predictions
(i.e. parameter values predicted from relationships for mice not included in
the estimate of MEO). Apart from the urinary energy loss (assumed
from the literature), all other physiological parameters were either measured
individually in the 24 females (FI and DEE) or measured in a
similar group of lactating mice (e.g. apparent digestibility of energy;
Król and Speakman,
2003). We believe, therefore, that the
MEIDEE method provides the most accurate estimate of
MEO for the 24 mice and can be treated as a reference method.
Individual estimates of MEO from the pup water turnover method and the MEIDEE method were highly correlated (r=0.89, P<0.001, N=24; Fig. 7B), as were the estimates from the litter energy budget method and the MEIDEE method (r=0.94, P<0.001, N=24; Fig. 7C). Thus, the pup water turnover method, the litter energy budget method and the reference MEIDEE method appear to provide accurate and precise estimates of MEO. The estimates of MEO produced by the female water turnover method were not correlated with those yielded by the MEIDEE method (r=0.20, P=0.34, N=24; Fig. 7A).
|
To calculate MEO for the 67 reproductive females with individual
measurements of food intake, litter mass and litter size
(Król and Speakman,
2003), we used the litter energy budget method. This approach is
not only as accurate and precise as the reference method but also the most
robust to changes in parameters.
Milk energy output at 30°C
Milk energy output on day 14 of lactation calculated for 67 females using
the litter energy budget method ranged from 27.2 kJ day1 to
117.9 kJ day1, with a mean value of 85.3±19.0 kJ
day1. MEO was related to litter size on day 14 of
lactation (ANOVA, F14,52=5.8, P<0.001,
N=67). Females raising six pups exported more energy in milk than
females raising 13 pups (Tukey pairwise comparisons between litter
sizes 6 and 1, 2 or 3, P<0.05;
Fig. 8). For litter size
increasing from 6 to 15, no further increase in MEO was observed (all
Tukey pairwise comparisons for litters size 615, P>0.05).
The mean MEO for females raising 615 pups was 89.4±13.5
kJ day1 (N=61). This value corresponds to
40.8±3.4% of gross energy intake and to 54.6±4.6% of
MEI.
|
The effect of temperature on milk composition and milk energy
output
We compared milk composition and milk energy output of mice that were
raising their first litters in hot (30°C; present study), warm (21°C;
Johnson et al., 2001a) and
cold (8°C; Johnson and Speakman,
2001
) temperatures. The hot and the warm mice were exposed to
30°C and 21°C, respectively, prior to breeding and were kept in those
temperatures through the whole course of pregnancy and lactation. By contrast,
mice from the cold group were maintained at 21°C until the pups had grown
fur and were then exposed to 8°C from day 10 of lactation onwards. The
sample sizes for hot, warm and cold groups were 12, 10 and 10,
respectively.
All milk samples were collected on day 15 of lactation, using the same protocol. Their composition was analysed using the same methods, and the gross energy content of milk was calculated from the composition using the same formula.
On the day when the milk samples were collected, the body mass of the hot, warm and cold mice averaged 40.0±1.8 g, 49.9±3.0 g and 50.1±3.3 g, respectively (ANOVA, F2,29=50.0, P<0.001; mean for the hot mice significantly lower than for both warm and cold mice, Tukey pairwise comparisons, P<0.05). The hot, warm and cold mice raised, on average, 12.0±1.9, 12.4±1.7 and 10.3±1.4 pups, respectively (ANOVA, F2,29=4.4, P=0.021; mean for the warm mice significantly greater than for the cold mice, Tukey pairwise comparison, P<0.05). The litter mass of the hot, warm and cold mice averaged 66.7±6.6 g, 82.4±11.0 g and 69.0±13.6 g, respectively (ANOVA, F2,29=6.8, P=0.004; mean for the warm mice significantly greater than for both hot and cold mice, Tukey pairwise comparisons, P<0.05).
The three groups differed in the dry mass content of milk (ANOVA, F2,29=10.7, P<0.001), with the hot mice having, on average, less total solids in milk (34.4±1.9%) than both the warm (40.9±4.4%) and the cold (41.5±5.3%) mice (Fig. 9A). The effect of temperature on the dry mass content of milk remained significant after adjusting for the differences in maternal body mass (ANCOVA: interaction body mass x temperature, P=0.07; body mass effect, F1,28=9.1, P=0.005; temperature effect, F2,28=12.5, P<0.001). Dry mass content of milk across temperature was not affected by litter size (ANCOVA, P=0.47) or litter mass (ANCOVA, P=0.21).
|
Milk produced by mice exposed to 30°C, 21°C and 8°C contained 20.0±2.5%, 26.4±3.0% and 30.3±3.8% fat, respectively (ANOVA, F2,29=31.6, P<0.001; all three means significantly different, Tukey pairwise comparisons, P<0.05; Fig. 9B). The fat content of milk across temperature was not affected by maternal body mass (ANCOVA, P=0.30). The effect of temperature on milk fat content was still significant when corrected for the differences in litter size (ANCOVA: interaction litter size x temperature, P=0.66; litter size effect, F1,28=4.6, P=0.041; temperature effect, F2,28=28.6, P<0.001) and litter mass (ANCOVA: interaction litter mass x temperature, P=0.37; litter mass effect, F1,28=11.1, P=0.002; temperature effect, F2,28=49.1, P<0.001).
The hot, warm and cold mice had similar milk protein content (ANOVA, F2,29=3.0, P=0.07), which averaged 10.3±0.7%, 11.3±1.1% and 11.2±1.4%, respectively (Fig. 9C), as well as similar sugar content (F2,29=2.8, P=0.08), which averaged 2.1±0.4%, 1.7±0.3% and 1.8±0.4%, respectively (Fig. 9D). Neither milk protein content nor sugar content were affected by maternal body mass (ANCOVA, P=0.50 and 0.61, respectively), litter size (ANCOVA, P=0.10 and 0.89, respectively) or litter mass (ANCOVA, P=0.07 and 0.10, respectively).
Gross energy content of milk produced by the hot, warm and cold mice averaged 10.5±1.0 kJ g1, 13.1±1.3 kJ g1 and 14.6±1.5 kJ g1, respectively (ANOVA, F2,29=30.9, P<0.001; all three means significantly different, Tukey pairwise comparisons, P<0.05; Fig. 10A). Gross energy content of milk across temperature was not affected by maternal body mass (ANCOVA, P=0.24). The effect of temperature on gross milk energy content remained significant after adjusting for the differences in litter size (ANCOVA: interaction litter size x temperature, P=0.60; litter size effect, F1,28=5.7, P=0.023; temperature effect, F2,28=28.4, P<0.001) and litter mass (ANCOVA: interaction litter mass x temperature, P=0.40; litter mass effect, F1,28=16.3, P<0.001; temperature effect, F2,28=55.3, P<0.001).
|
Milk energy output was calculated for the same individuals for which milk
composition data were also available. The estimates of MEO for the
mice exposed to 21°C and 8°C were derived from the female water
turnovers as the product of the rate of milk flow and gross energy content of
milk (Johnson et al., 2001a;
Johnson and Speakman, 2001
).
In the present paper we have shown that this method is less accurate and less
precise than the others, but we had insufficient data to recalculate the
MEO of the warm and the cold mice using the
MEIDEE, pup water turnover or litter energy budget
methods. To allow comparison between the three groups, the estimates of
MEO for the hot mice were also derived from the female water
turnovers. All estimates of milk flow and MEO refer to day 14 of
lactation.
The rate of milk flow at 30°C, 21°C and 8°C averaged 8.5±1.8 g day1, 12.9±2.7 g day1 and 20.0±5.0 g day1, respectively (ANOVA, F2,29=27.9, P<0.001; all three means significantly different, Tukey pairwise comparisons, P<0.05; Fig. 10B). The effect of temperature on milk flow was still significant when corrected for the differences in maternal body mass (ANCOVA: interaction body mass x temperature, P=0.32; body mass effect, F1,28=4.5, P=0.046; temperature effect, F2,28=12.2, P<0.001), litter size (ANCOVA: interaction litter size x temperature, P=0.08; litter size effect, F1,28=13.1, P=0.001; temperature effect, F2,28=46.5, P<0.001) and litter mass (ANCOVA: interaction litter mass x temperature, P=0.89; litter mass effect, F1,28=14.4, P=0.001; temperature effect, F2,28=43.2, P<0.001).
The three groups differed significantly in the milk energy output (ANOVA, F2,29=28.5, P<0.001). The hot mice exported less energy in milk (87.7±17.2 kJ day1) than the warm mice (166.7±22.7 kJ day1), while the cold mice, after 5 days of exposure to 8°C, increased their MEO to 288.0±60.7 kJ day1 (Fig. 10C). The MEO across temperature was not affected by maternal body mass (ANCOVA, P=0.09). The effect of temperature on amount of energy exported in milk remained significant after adjusting for the differences in litter size (ANCOVA: interaction litter size x temperature, P=0.06; litter size effect, F1,28=7.6, P=0.012; temperature effect, F2,28=85.9, P<0.001) and litter mass (ANCOVA: interaction litter mass x temperature, P=0.73; litter mass effect, F1,28=4.8, P=0.043; temperature effect, F2,28=80.6, P<0.001).
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Discussion |
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The first method is based on an assumption that the difference between
energy assimilated (= metabolizable energy intake) and energy used for
maternal maintenance represents energy that is allocated for milk. The
metabolizable energy intake is relatively easy to measure, but maternal
maintenance expenditure is not. For this reason, milk energy output is
frequently calculated as an increase in metabolizable energy intake above the
non-reproductive level, i.e. as the difference between the MEI of
lactating and non-reproductive females (e.g.
McClure, 1987;
Künkele and Kenagy, 1997
;
Künkele and Trillmich,
1997
). However, the assumption that the MEI of
non-reproductive individuals provides a good estimate of maternal maintenance
expenditure may be incorrect, since lactation is frequently associated with an
increase in body mass. Furthermore, lactating and non-reproductive females are
also likely to differ in their mass-specific maintenance expenditure because
of additional heat losses incurred during milk production. Therefore, we
suggest that maternal maintenance expenditure should be measured directly,
using the doubly labelled water technique.
We validated the DLW technique in non-reproductive mice by simultaneous measurements of MEI in a feeding trial (Fig. 2) and demonstrated that DEE measured from DLW turnover was, on average, 2.0% higher than MEI, with individual errors ranging from 10.4% to 22.9%. A similar range of individual errors is likely to be observed in estimates of MEO, since a 1% change in DEE would change MEO by 0.9% (Appendix C of supplementary material). The MEIDEE method uses a relatively small number of assumptions and predictions (equation 1 in Appendix A of supplementary material) and involves minimal experimental interactions with the animals. However, since the measurements of DEE must be conducted immediately after the measurements of MEI, the use of this method is limited to the laboratory.
The second method assumes that the difference between the total water
turnover of a lactating female and the water she loses through faeces, urine
and evaporation represents the water exported in milk (equation 2 in Appendix
A of supplementary material). The calculation of total water turnover
following an injection of deuterium or tritium into the female body water
could be subject to error since the method does not include any protocol to
correct for isotope recycling between the mother and the pups
(Baverstock and Green, 1975).
Furthermore, a 1% change in the female water turnover would change
MEO by 6.0% (Appendix C of supplementary material). Since the water
turnover measured by isotope dilution is expected to be within ±10% of
actual flux rates (Nagy and Costa,
1980
), estimates of MEO could have a potential error of
±60%. Indeed, we demonstrated that the estimates of MEO
derived from female water turnover were significantly lower and more variable
than those from other methods (Fig.
6).
The third method relies on the difference between total water turnover of
the pup and the influx of atmospheric and metabolic water, representing the
milk water intake (equation 5 in Appendix A of supplementary material). The
total water turnover is calculated from the turnover of deuterium or tritium
injected into the pup. The main sources of error associated with this
technique include: (1) recycling of isotopes from pups to mother (via
maternal ingestion of pup urine and faeces) and from the mother back to the
pups by uptake of the isotope in milk
(Baverstock and Green, 1975),
(2) reduction of isotope concentration due to increasing size of the body
water pool (Dove and Freer,
1979
) and (3) incorporation of isotopes into non-exchangeable
hydrogen sites in newly synthesized tissue
(Oftedal and Iverson, 1987
).
To correct for the isotope recycling, we measured accumulation of deuterium in
control pups that had not been dosed with the isotope
(Baverstock and Green, 1975
;
Friedman and Bruno, 1976
). We
eliminated the error related to changing body water pool of growing pup by use
of the appropriate flux equation (Coward
et al., 1982
). However, due to lack of the relevant data, we did
not correct for deuterium sequestration. Although the quantitative importance
of these errors is difficult to assess, many of them appear to cancel each
other out (Oftedal et al.,
1993
). The pup water turnover method requires a lot of parameters
to be measured, but variation in most of them (apart from the pup body mass
and the pup water turnover) has little effect on the evaluation of
MEO (Appendix C of supplementary material). The parameters to which
the method is most sensitive (pup body mass and water turnover) are relatively
easy to measure in the laboratory as well as in the wild. In our study, the
estimates of MEO produced by the pup water turnover method were
similar to those derived from the MEIDEE and litter
energy budget methods (Fig.
6).
Because the energy demands of pups for growth and respiration are met
entirely by energy of milk, it is possible to calculate MEO from the
litter energy budget (equation 6 in Appendix A of supplementary material). The
amount of energy accumulated as new tissues is relatively easy to measure, but
the measurements of pup respiration are more difficult to perform. The pup
respiration is the sum of resting metabolic rate (including the heat increment
of feeding and energy costs of biosynthesis), costs of thermoregulation and
costs of activity. Since all our measurements were conducted on mice exposed
to 30°C (thermoneutrality), we assumed that there were no thermoregulatory
costs and that the respiration of the pups was the same as the RMR of
the litter, corrected for the cost of pup activity (equation 3 in Appendix A
of supplementary material). These assumptions significantly simplified our
measurements, but it is important to note that at sub-thermoneutral
temperatures the thermoregulatory costs also need to be taken into account.
Thus, the best approach would be to measure the respiration of the pups
directly using the DLW technique. However, the applicability of this technique
might be limited by the size of the blood sample. In our study, for example,
for 45 pups injected with DLW, the blood samples from only two individuals
were sufficiently large to run both 2H and 18O. Recent
advances in mass spectrometry technology
(Begley and Scrimgeour, 1996)
may enable measurements on much smaller samples removing this constraint.
In summary, we compared four methods of measuring MEO in laboratory mice and showed that significant differences exist between the various methods that have been employed. The MEIDEE method, pup water turnover method and litter energy budget method produced similar estimates of MEO, while the estimates of MEO derived from the female water turnover were significantly lower and more variable.
Peripheral versus heat dissipation limit
hypotheses
We measured milk energy output in MF1 mice exposed to 30°C to test
whether limits to lactational energy intake are imposed peripherally by the
capacity of mammary glands to produce milk (Hammond et al.,
1994,
1996
;
Rogowitz, 1998
) or centrally
by the capacity of the animal to dissipate body heat
(Król and Speakman,
2003
). According to the peripheral limitation hypothesis, mammary
glands at peak lactation would work at maximal capacity regardless of ambient
temperature, and therefore MEO measured at 30°C (present study)
should not differ significantly from that measured at 21°C
(Johnson et al., 2001a
) or
8°C (Johnson and Speakman,
2001
). The heat dissipation limit hypothesis predicts that
reducing the driving gradient between body temperature and environment by
exposing mice to 30°C would lead to a decrease in food intake and milk
production, since both these processes contribute greatly to metabolic heat
production. We have already demonstrated the decrease in asymptotic food
intake following exposure to 30°C
(Król and Speakman,
2003
), but this behaviour, without concurrent measurements of
MEO, is inconclusive because the decline in food intake at 30°C
is predicted by both hypotheses.
Comparison of MEO between mice exposed to 30°C (present
study), 21°C (Johnson et al.,
2001a) and 8°C (Johnson
and Speakman, 2001
) showed that females lactating at 30°C
exported less energy as milk than those at 21°C, which in turn had a lower
MEO than mice exposed to 8°C
(Fig. 10C). This decline in
MEO was caused by a decline in both milk flow
(Fig. 10B) and gross energy
content of milk (Fig. 10A).
Milk produced at 30°C contained less total solids
(Fig. 9A) and less fat
(Fig. 9B) than milk produced at
21°C and 8°C. Milk protein and sugar content, however, did not vary
with ambient temperature (Fig.
9C,D). Thus, the data presented in the present study indicate that
mice exposed to 30°C responded by reducing their milk flow, milk energy
content and consequently milk energy output. These results are consistent with
the heat dissipation limit hypothesis.
Reduction in food intake and milk production associated with heat stress is
well documented in domestic ruminants and pigs (e.g.
Legates, 1960;
Abdalla et al., 1993
;
Silanikove, 2000
;
Renaudeau and Noblet, 2001
).
Albright and Alliston (1972
)
demonstrated that heat stress in dairy cows reduces food intake via
effects in the hypothalamus. However, the mechanisms by which heat stress
affects milk yield are unknown. A heat-induced reduction in milk yield is
frequently reported to be similar in magnitude to concurrent decrease in food
intake (reviewed by Silanikove,
2000
; Renaudeau and Noblet,
2001
). In our study, for example, mice exposed to 30°C reduced
their food intake and milk energy output by 47% when compared with mice
lactating at 21°C (Johnson et al.,
2001a
). Because of the similarity in food intake and milk yield
depression, several authors have suggested that the effect of high temperature
on milk production could simply be explained by a decline in nutrient supply
due to reduced food intake. However, changes in the amount of nutrients in the
milk do not necessarily reflect changes in the availability of dietary
nutrients, since most mammals, including laboratory mice, exhibit homeorhetic
(preferential) partitioning of nutrients to the mammary glands
(Vernon, 1989
;
Vernon et al., 1999
). The
uptake of nutrients by mammary glands depends not only on nutrient
availability but also on blood flow through the tissue, and suppression of
mammary blood flow may compromise mammogenesis as well as milk secretion
(Linzell, 1974
;
Ota and Peaker, 1979
).
Consequently, it has been suggested that heat stress reduces milk yield by
redistributing the blood flow from mammary glands to the skin to improve
conductive heat loss (Black et al.,
1993
). Indeed, this effect has been demonstrated in non-pregnant
rabbits during early lactation but not at peak lactation or when lactating
females were simultaneously pregnant
(Lublin and Wolfenson,
1996
).
Milk production is a function of the number and activity of mammary
secretory cells. The number of secretory cells increases exponentially during
pregnancy (prepartum mammogenesis), as a consequence of very high rates of
cell division. In many eutherian mammals, including laboratory mice, prepartum
mammogenesis is stimulated by placental lactogen and placental oestrogen
(Nagasawa and Yanai, 1971;
Jameson, 1998
). Both hormones
are produced in proportion to the number of placentae, and therefore the
number of secretory cells is adjusted to the number of neonates to be fed.
After parturition, the mammary cell division drops dramatically, but a limited
amount of proliferation continues (postpartum mammogenesis;
Knight, 2000
). In the
laboratory mouse, the maximum number of secretory cells is achieved on day 5
of lactation, at least seven days before peak milk production
(Knight and Peaker, 1982
).
Thus, when mammogenesis is completed, further adjustments in milk production
are likely to occur through changes in activity of the secretory cells.
Indeed, we demonstrated that mice exposed to 30°C and 21°C, despite
the differences in milk production (present study), did not differ in the dry
mass of mammary glands at peak lactation
(Król et al., 2003
).
Assuming that the mass of mammary glands correlates with the number of
secretory cells, our data suggest that heat stress might constrain milk
production by reducing secretory cell activity. However, without direct
measurements of the number and activity of secretory cells, this remains
unproven (Król et al.,
2003
).
After the onset of lactation, the maintenance of milk synthesis and
secretion requires regular removal of milk. The suckling stimulus induces the
release of oxytocin and prolactin from the pituitary gland via a
neuroendocrine reflex. Oxytocin is responsible for milk let-down and ejection,
whereas prolactin, which is the most important lactogenic hormone, activates
the transcription of RNAs for milk proteins and enzymes involved in the
synthesis of milk fats and sugars (Russel,
1980; Barber et al.,
1992
; Flint and Knight,
1997
). Consequently, frequent suckling (or milking) increases milk
production, whilst forced weaning, or a gradual cessation of milk removal that
occurs during natural weaning, initiates the process of mammary gland
involution (e.g. Peaker, 1995
;
Quarrie et al., 1996
;
Capuco et al., 2002
). Although
the frequency at which each mammary gland is sucked depends primarily on the
number of pups per teat, the regular suckling pattern is likely to be
disrupted when the mother is not in the nest. It has been demonstrated that
the females lactating at high ambient temperature are at risk of developing
prolonged maternal hyperthermia, and therefore they frequently interrupt pup
contact and leave the nest area to dissipate the heat load
(Croskerry et al., 1978
;
Adels and Leon, 1986
;
Scribner and Wynne-Edwards,
1994
). Thus, the detrimental effect of heat stress on milk
production in mice exposed to 30°C (present study) could be related to a
reduced stimulation of mammary glands by offspring, caused by a decrease in
the frequency and duration of maternal nest attendance (but see
Stern and Azzara, 2002
).
Our results suggest that laboratory mice at peak lactation are limited
centrally by their capacity to dissipate body heat generated by processing
food and producing milk (Król and
Speakman, 2003). Mice exposed to 30°C decreased their food
intake (Król and Speakman,
2003
) and their milk production (present study), presumably
because both these processes contribute to metabolic heat production.
Consequently, mice exposed to 30°C had a lower reproductive output than
mice lactating at cooler temperatures
(Król and Speakman,
2003
). Taken together, these results argue against the peripheral
limitation hypothesis (Hammond et al.,
1994
,
1996
;
Rogowitz, 1998
) and support
the heat limit dissipation hypothesis.
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Acknowledgments |
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Footnotes |
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References |
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