nutrients
Article
Sex-Dependent Wheel Running Eﬀects on High Fat
Diet Preference, Metabolic Outcomes, and
Performance on the Barnes Maze in Rats
Tiﬀany Y. Yang 1, Zijun Gao 1
and Nu-Chu Liang 1,2,3,*
1
Department of Psychology, College of Liberal Arts and Sciences, University of Illinois—Urbana-Champaign,
Champaign, IL 61820, USA; tyang42@illinois.edu (T.Y.Y.); zijung2@illinois.edu (Z.G.)
2
Division of Nutritional Sciences, College of Agricultural, Consumer and Environmental Sciences,
University of Illinois—Urbana-Champaign, Urbana, IL 61801, USA
3
Neuroscience Program, College of Liberal Arts and Sciences, University of Illinois—Urbana-Champaign,
Urbana, IL 61801, USA
*
Correspondence: ncliang8@illinois.edu; Tel.: +1-(217)-244-7873
Received: 22 July 2020; Accepted: 30 August 2020; Published: 5 September 2020


Abstract: Excessive and prolonged intake of highly palatable, high fat (HF) foods contributes to
the pathogenesis of obesity, metabolic syndrome, and cognitive impairment. Exercise can restore
energy homeostasis and suppress HF diet preference in rats. However, it is unclear if exercise confers
similar protection against the detrimental outcomes associated with a chronic HF diet preference
and feeding in both sexes. We used our wheel running (WR) and two-diet choice (chow vs. HF)
paradigm to investigate the eﬃcacy of exercise in reversing HF diet-associated metabolic and cognitive
dysregulation in rats, hypothesizing that beneﬁcial eﬀects of exercise would be more pronounced in
males. All WR rats showed HF diet avoidance upon running initiation, and males, but not females,
had a prolonged reduction in HF diet preference. Moreover, exercise only improved glucose tolerance
and insulin proﬁle in males. Compared to sedentary controls, all WR rats improved learning to
escape on the Barnes maze. Only WR females increased errors made during subsequent reversal
learning trials, indicating a sex-dependent eﬀect of exercise on behavioral ﬂexibility. Taken together,
our results suggest that exercise is more eﬀective at attenuating HF-associated metabolic deﬁcits in
males, and highlights the importance of developing sex-speciﬁc treatment interventions for obesity
and cognitive dysfunction.
Keywords: high fat diet; wheel running; oral glucose tolerance test; Barnes maze
1. Introduction
In the United States, ~65% of adults are either overweight or obese presenting with chronic
illnesses (e.g., cardiovascular disease, type 2 diabetes, hypertension, and cancer) that can be partially
attributed to diet composition [1,2]. The shift in the types of food consumed and their nutritional
qualities are associated with the change in environment (e.g., industrialization), including the
development of agriculture, food processing, and animal husbandry [3]. Consumption of reﬁned sugars
(e.g., high-fructose corn syrup) and saturated fats has steadily increased [4–6] and has been termed
the “Western diet,” which contains ~40% calories from both carbohydrates and fats [7]. Moreover,
the modern environment favors a sedentary lifestyle and facilitates easy access to these highly processed,
palatable, energy dense foods which tend to have higher glycemic loads [8] than unreﬁned foods and
pose a threat to metabolic [9–12] and cognitive health [13].
The overconsumption of high fat (HF) food is associated with weight gain and increased abdominal
adiposity, which contributes to development of peripheral metabolic dysregulation and cognitive
Nutrients 2020, 12, 2721; doi:10.3390/nu12092721
www.mdpi.com/journal/nutrients
Nutrients 2020, 12, 2721
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deﬁcits [13–15]. Exercise appears to be more eﬀective than diet control at improving metabolic
function [16]. People who are successful at maintaining long-term weight loss report high physical
activity and a diet low in fat composition [17,18]. Rodent studies show that males consistently decrease
food intake in response to exercise [19–22] whereas results are more variable in females [21–23].
In contrast, the majority of human studies focus on changes in food intake following acute rather than
long-term exercise, and the response to exercise is highly variable in both sexes [24–29]. Although
women may lose less weight than men during long-term exercise [30–33], there has been limited
research to elucidate sex diﬀerences in exercise-related changes in energy intake and expenditure [34,35].
Therefore, it is unclear how closely sex diﬀerences in energy intake and macronutrient preference
during exercise in humans parallel the rodent literature.
Furthermore, compared with caloric
restriction-mediated weight loss, exercise training-mediated weight loss led to greater decreases in
visceral fat and hepatic insulin resistance in obese men and women [36]. Exercise can produce a
modest improvement on peripheral glucose metabolism even without signiﬁcant changes in body
mass and composition. For example, short-term running exercise was able to reduce fasting glucose
and portal vein free fatty acids in sucrose-fed rats without a concomitant reduction in adiposity [37].
Increasing the duration of running from four to 12 weeks in rats resulted in decreased mesenteric
and subcutaneous fat in addition to increased insulin sensitivity and greater improvement in their
overall metabolic proﬁle [37]. Thus, while exercise can attenuate obesity-related insulin resistance,
there may be an additive eﬀect of exercise and adiposity loss on signiﬁcantly improving peripheral
insulin resistance.
Diets high in fat composition have been implicated in aﬀecting cognitive performance in both
humans [38] and rodents [39]. More speciﬁcally, chronic HF feeding has been shown to impair
hippocampal-dependent spatial learning and memory in rodent models [39–44]. Given that exercise
has been shown to enhance cognition [45–47], it may also be able to attenuate HF-induced performance
deﬁcits. Indeed, studies have found that exercise, [48–52] but not dietary supplementation [52], reverses
HF-mediated cognitive impairment. Most studies focus on diet-induced deﬁcits in hippocampal
dysfunction.
However, beyond learning and memory, HF diet can also alter prefrontal cortex
(PFC)-mediated executive function, including behavioral ﬂexibility [15,42,53,54]. Deﬁcits in behavioral
ﬂexibility can manifest prior to the development of HF-induced insulin resistance [55]. These deﬁcits
in behavioral ﬂexibility may result in the inability to appropriately adapt dietary choices to external
environmental and internal visceral cues and consequently, promote rigid diet choices in a viscous
cycle that facilitates the development of obesity [56,57]. The few studies that examined PFC-dependent
cognition found that HF feeding led to deﬁcits in behavioral ﬂexibility in rats [15,42,53,54]. Importantly,
decreased behavioral ﬂexibility was correlated with decreased insulin sensitivity but not body weight
or plasma glucose level [54]. Dietary [58,59], but not drug [60], interventions are able to attenuate these
HF diet-induced cognitive impairments. Taken together, these studies suggest that HF diet and insulin
resistance may interact to promote the development and maintenance of cognitive rigidity.
Sex diﬀerences in HF-induced deﬁcits in metabolic and cognitive function may diﬀerentially
aﬀect the cognitive control of feeding behavior in males and females. The metabolic [61–64] and
cognitive [65–67] outcomes of HF feeding appear to be more deleterious in males than females in
both humans and rodents. However, obesity-related deﬁcits, speciﬁcally in the domain of cognitive
ﬂexibility, are greater in women than men [68]. In contrast, HF-mediated deﬁcits in behavioral ﬂexibility
are more pronounced in male rats compared to females [65–67]. Notably, both the human [69–73]
and rodent [74–76] literature suggests that males are more responsive to the beneﬁcial eﬀects of
exercise. Thus, exercise may more readily counteract the detrimental eﬀects of HF-feeding in males
than females. While exercise has some eﬃcacy at counteracting HF-mediated cognitive decline in
rodents [16,36–39,48,50,52], studies primarily focus on behaviors mediated by the hippocampus [48,50]
rather than the PFC [49] and rarely include both sexes within the same experiment for the direct
assessment of sex diﬀerences. Thus, whether exercise is able to attenuate functional dysregulation of
the PFC to the same extent in both male and female rats is unclear.
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To our knowledge, no study has investigated the eﬃcacy of exercise at reversing HF-induced
deﬁcits in metabolic and executive function in rats of both sexes, which could provide insight into the
development of sex-speciﬁc prevention and treatment options. Furthermore, most rodent models lack a
dietary choice component so the relationships between diet preference, exercise, and metabolic function
are rarely explored. To address the gap in knowledge, rats underwent our established WR and two-diet
choice protocol for six weeks, a period of time which is suﬃcient to induce diet-induced obesity [77].
With this long-term HF diet exposure, we examined if higher HF diet preference increases susceptibility
to the adverse eﬀects of HF diet, and whether exercise can lead to similar HF-diet associated alterations
in metabolic proﬁle and cognitive performance in male and female rats. We hypothesized that chronic
HF feeding would impair peripheral metabolic function and PFC-mediated behavioral ﬂexibility in
a Barnes maze [58,78] to a greater extent in female than male rats that have a preference for HF diet.
Furthermore, we hypothesized that exercise would have a greater eﬃcacy at attenuating the adverse
eﬀects HF diet exposure in males compared to females.
2. Materials and Methods
2.1. Subjects
The subjects included 24 male (250–275 g) and 24 female (150–175 g) Sprague-Dawley rats
(Envigo, Indianapolis, IN, USA) that were ~7–8 weeks old upon arrival. Rats were group housed
on a standard 12:12 light-dark cycle (lights on at 0700 h). During habituation, rats had ad lib access
to a standard chow diet (chow; Teklad global 2018, Teklad Diets, Madison, WI, USA) and tap water.
See Table 1 for details about macronutrient sources. During the experimental period, rats had diet
choice between the standard, high carbohydrate chow and a novel 45% HF diet (HF; D12451, Research
Diets, New Brunswick, NJ, USA). All groups were fed ad libitum.
Table 1. Diet composition.
Macronutrient
Description
Unit
Teklad 2018
(3.1 kcal/g)
45% HF Diet
(4.74 kcal/g)
Protein
Total
% kcal
24
20
Carbohydrate
Sucrose
% kcal
-
17
Other carbohydrates
% kcal
58
18
Fat
Total
% kcal
18
45
Saturated fats
% of total fat (wt)
0.9
31.4
Monounsaturated fats
% of total fat (wt)
1.3
35.5
Polyunsaturated fats
% of total fat (wt)
3.4
33.1
All experimental procedures were approved by the Institutional Animal Care and Use Committee
at the University of Illinois, Urbana-Champaign (Protocol #16178) and are in accordance with the
Guide for the Care and Use of Laboratory Animals [79].
2.2. Procedures
2.2.1. Wheel Running and Two-Diet Choice
Daily recording of body weight, food, and water intake occurred at 0800 h. Running activity was
recordedonacomputerandprocesseddailyimmediatelyfollowingdailycare(VitalView,StarrLifeSciences,
Oakmont, PA, USA). After habituation, sedentary (Sed) rats were moved to standard individual housing
cages that included cotton nesting materials as enrichment, while wheel running (WR) rats were transferred
to running wheel cages (13” diameter wheel; Mini Mitter, Starr Life Sciences, Oakmont, PA, USA) with
the wheel locked for a 4-day acclimatization period. After this 4-day period, a novel 45% HF diet was
introduced to all rats 2 h before dark onset (1700 h) during which running wheels were simultaneously
unlocked for the WR rats. The sample size, n = 10–11 for Sed groups and n = 13–14 for WR groups,
Nutrients 2020, 12, 2721
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was determined based on our previous studies using the same two-diet choice and wheel running
paradigm [80]. The observed power with such a sample size was ≥0.80, which is the typical cutoff used
for power analyses. The wheel running and two-diet choice procedures continued for ~6 weeks after
which the rats were sacrificed (Figure 1). Retroperitoneal, mesenteric, and gonadal fat pads were dissected
and weighed after sacrifice.
Nutrients 2020, 12, x FOR PEER REVIEW 
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same two-diet choice and wheel running paradigm [80]. The observed power with such a sample size 
was ≥0.80, which is the typical cutoff used for power analyses. The wheel running and two-diet choice 
procedures continued for ~6 weeks after which the rats were sacrificed (Figure 1). Retroperitoneal, 
mesenteric, and gonadal fat pads were dissected and weighed after sacrifice. 
 
Figure 1. Experimental timeline. Sed: sedentary, WR: wheel running; HF: high fat; OGTT: oral glucose 
tolerance test. 
2.2.2. Oral Glucose Tolerance Test (OGTT) 
Two OGTTs were performed for this experiment, one at baseline and one after HF diet exposure 
(post-HF) to examine within-group effects of HF diet on glucose tolerance. Baseline OGTT was 
performed the day before the wheels were unlocked (day 0), and post-HF OGTT was performed the 
day of sacrifice (day 44), which was two days after the end of the Barnes maze. The day before both 
OGTTs, food was removed ~3 h after dark onset (2200 h) where rats would have eaten ≥60% of their 
daily food intake. Rats were only moderately fasted because complete overnight fasting enhances 
insulin-stimulated glucose utilization, and we were interested in assessing insulin action in a more 
physiological context [81,82]. After the baseline/fasting blood glucose (0 min) measurement and tail 
blood collection, rats underwent a glucose challenge where they were orally gavaged with 2 g/kg of 
20% glucose dissolved in distilled water. Tail blood was collected from the same tail nick made 
during baseline sampling at 15, 30, 60, and 120 min time points from the time they were gavaged. 
Blood glucose levels were also measured at these time points using a handheld glucometer 
(AlphaTRAK2, Abbott, Abbott Park, IL, USA). Tail blood was centrifuged at 870 × g for 15 min at 4 
°C. For each sampling time point, ~25 µL of plasma was collected and stored at −80 °C until the 
samples were processed for plasma insulin concentrations using the Rat Ultrasensitive Insulin ELISA 
(ALPCO, Salem, NH, USA) according to manufacturers’ protocol. 
Blood glucose and plasma insulin data from the baseline and post-HF OGTT was used to assess 
insulin sensitivity [83] with the following two methods: (1) Hepatic insulin resistance was calculated 
using the homeostasis model assessment method for insulin resistance (HOMA-IR) model [84] and 
(2) peripheral insulin resistance was calculated using Gutt’s index of insulin sensitivity (ISI0,120) [85]. 
HOMA − IR = 
fasting insulin (μU
ml) × fasting glucose (mmol
L
)
22.5
 
 
𝐈𝐒𝐈𝟎,𝟏𝟐𝟎
=
glucose load (mg) + (glucose0 min − glucose120 min (mg
L )) × 0.19 × body weight (kg)
120 × log (
insulin0 min + insulin120 min (mU
L )
2
) + (
glucose0 min + glucose120 min (mmol
L
)
2
)
 
(1) 
2.2.3. Barnes Maze 
Figure 1. Experimental timeline. Sed: sedentary, WR: wheel running; HF: high fat; OGTT: oral glucose
tolerance test.
2.2.2. Oral Glucose Tolerance Test (OGTT)
Two OGTTs were performed for this experiment, one at baseline and one after HF diet exposure
(post-HF) to examine within-group eﬀects of HF diet on glucose tolerance. Baseline OGTT was
performed the day before the wheels were unlocked (day 0), and post-HF OGTT was performed the
day of sacriﬁce (day 44), which was two days after the end of the Barnes maze. The day before both
OGTTs, food was removed ~3 h after dark onset (2200 h) where rats would have eaten ≥60% of their
daily food intake. Rats were only moderately fasted because complete overnight fasting enhances
insulin-stimulated glucose utilization, and we were interested in assessing insulin action in a more
physiological context [81,82]. After the baseline/fasting blood glucose (0 min) measurement and tail
blood collection, rats underwent a glucose challenge where they were orally gavaged with 2 g/kg of
20% glucose dissolved in distilled water. Tail blood was collected from the same tail nick made during
baseline sampling at 15, 30, 60, and 120 min time points from the time they were gavaged. Blood
glucose levels were also measured at these time points using a handheld glucometer (AlphaTRAK2,
Abbott, Abbott Park, IL, USA). Tail blood was centrifuged at 870× g for 15 min at 4 ◦C. For each
sampling time point, ~25 µL of plasma was collected and stored at −80 ◦C until the samples were
processed for plasma insulin concentrations using the Rat Ultrasensitive Insulin ELISA (ALPCO, Salem,
NH, USA) according to manufacturers’ protocol.
Blood glucose and plasma insulin data from the baseline and post-HF OGTT was used to
assess insulin sensitivity [83] with the following two methods: (1) Hepatic insulin resistance was
calculated using the homeostasis model assessment method for insulin resistance (HOMA-IR) model [84]
and (2) peripheral insulin resistance was calculated using Gutt’s index of insulin sensitivity (ISI0,120) [85].
HOMA − IR =
fasting insulin
 µU
ml

× fasting glucose
 mmol
L

22.5
ISI0,120
=
glucose load (mg)+(glucose0 min−glucose120 min (
mg
L ))×0.19×body weight (kg)
120×log


insulin0 min+insulin120 min( mU
L )
2

+


glucose0 min+glucose120 min( mmol
L )
2


(1)
Nutrients 2020, 12, 2721
5 of 22
2.2.3. Barnes Maze
During the last week of the WR and two-diet choice period, all rats were trained on the Barnes
maze starting 2.5 h after light onset (0930 h). A concealed overhead-mounted camera aimed directly at
the center of the maze was used to ﬁlm each trial, which was operated using a computer from the
adjacent room. The Barnes maze was 99 cm high and 122 cm in diameter, with 20 evenly spaced holes
that were 10 cm in diameter and 2 cm away from the edge. The apparatus was mounted on a rotatable
wooden support system that allowed the maze to be rotated 360◦. The escape box (30 × 12.5 × 14.5 cm)
was mounted underneath one hole with a 20◦ incline ramp. The location of ﬁve visuospatial cues was
held constant during training and reversal learning. For both training and reversal learning trials,
a trail ended when the rat entered the escape box or after the allotted time had elapsed. The maze
and escape box were cleaned using a non-alcohol-based coverage spray between each rat to eliminate
odor cues.
After daily care, rats were single caged in standard tubs and moved to the room adjacent to the
testing room for at least 1 h of habituation prior to testing. There were 4 trials/day during training
(total of 16 trials) with 4 diﬀerent starting locations (Figure 2). Rats were placed on the edge of the
maze facing the wall/away from the center of the maze. All rats ﬁnished a trial at the ﬁrst starting
location with an inter-trial interval of 30 min before being tested at the second starting location. In other
words, all rats completed a trial from the same starting location before the next round of trials began.
The order of the starting locations remained the same for each training day. Rats were given 90 s to
ﬁnd the escape box, and if a rat failed to ﬁnd the escape box within the allotted time, they were gently
guided into the box, which was then covered. Rats were allowed to remain in the escape box for 15 s
before being returned to their home cage.
Nutrients 2020, 12, x FOR PEER REVIEW 
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During the last week of the WR and two-diet choice period, all rats were trained on the Barnes 
maze starting 2.5 h after light onset (0930 h). A concealed overhead-mounted camera aimed directly 
at the center of the maze was used to film each trial, which was operated using a computer from the 
adjacent room. The Barnes maze was 99 cm high and 122 cm in diameter, with 20 evenly spaced holes 
that were 10 cm in diameter and 2 cm away from the edge. The apparatus was mounted on a rotatable 
wooden support system that allowed the maze to be rotated 360°. The escape box (30 × 12.5 × 14.5 
cm) was mounted underneath one hole with a 20° incline ramp. The location of five visuospatial cues 
was held constant during training and reversal learning. For both training and reversal learning trials, 
a trail ended when the rat entered the escape box or after the allotted time had elapsed. The maze 
and escape box were cleaned using a non-alcohol-based coverage spray between each rat to eliminate 
odor cues. 
After daily care, rats were single caged in standard tubs and moved to the room adjacent to the 
testing room for at least 1 h of habituation prior to testing. There were 4 trials/day during training 
(total of 16 trials) with 4 different starting locations (Figure 2). Rats were placed on the edge of the 
maze facing the wall/away from the center of the maze. All rats finished a trial at the first starting 
location with an inter-trial interval of 30 min before being tested at the second starting location. In 
other words, all rats completed a trial from the same starting location before the next round of trials 
began. The order of the starting locations remained the same for each training day. Rats were given 
90 s to find the escape box, and if a rat failed to find the escape box within the allotted time, they were 
gently guided into the box, which was then covered. Rats were allowed to remain in the escape box 
for 15 s before being returned to their home cage. 
On the fifth day of the Barnes maze, rats were placed at the center of the maze facing away from 
the escape box for a probe trial to ensure they learned the task. The procedures were the same from 
testing. After the probe trial, the escape box was rotated 180°, but none of the visuospatial cues were 
moved. For the 3 reversal learning trials with 30 min inter-trial intervals, rats were given 150 s to 
locate the new location of the escape box and were gently guided in if they failed to find the escape 
box and allowed to remain in the box for 15 s. 
 
Figure 2. Barnes maze. Starting locations on the Barnes maze for training and reversal learning trials. 
(A) Rats underwent 4 trails/day during training. (B) On the testing day, rats went through a probe 
trial to assess task acquisition and 3 reversal learning trials to assess behavioral flexibility. 
2.3. Statistical Analysis 
Figure 2. Barnes maze. Starting locations on the Barnes maze for training and reversal learning trials.
(A) Rats underwent 4 trails/day during training. (B) On the testing day, rats went through a probe trial
to assess task acquisition and 3 reversal learning trials to assess behavioral ﬂexibility.
On the ﬁfth day of the Barnes maze, rats were placed at the center of the maze facing away from
the escape box for a probe trial to ensure they learned the task. The procedures were the same from
testing. After the probe trial, the escape box was rotated 180◦, but none of the visuospatial cues were
moved. For the 3 reversal learning trials with 30 min inter-trial intervals, rats were given 150 s to locate
Nutrients 2020, 12, 2721
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the new location of the escape box and were gently guided in if they failed to ﬁnd the escape box and
allowed to remain in the box for 15 s.
2.3. Statistical Analysis
Statistical analyses were performed using Statistica 13.3 (TIBCO, Palo Alto, CA, USA). Data are
presented as the mean ± standard error of the mean (SEM). Post hoc Fisher’s LSD tests were performed
when signiﬁcant main eﬀects or interactions were identiﬁed.
For the WR and two-diet choice portion, raw data included weekly averages of body weight,
energy intake, and running activity. These measures were analyzed separately using 3-way mixed
model ANOVAs with sex (male vs. female) and exercise (Sed vs. WR) as between-subject factors and
time (6 weekly averages) as the within-subject factor. Diet choice was analyzed using a 4-way mixed
model ANOVA with sex and exercise as the between-subject factors and diet (chow vs. HF) and time
(6 weekly averages) as the within-subject factors.
Raw data from OGTT included plasma glucose and insulin measurements. Baseline OGTT and
post-HF OGTT results were analyzed separately using a 3-way mixed model ANOVAs with sex and
exercise as between-subject factors, and time (0, 15, 30, 60, and 120 min) as the within-subjects factor.
Glucose and insulin area under curve (AUC) results were analyzed separately using a 2-way mixed
model ANOVA with sex and exercise as the between-subject factors and time (baseline vs. post-HF) as
the within-subjects factor. Two measures of insulin sensitivity were ﬁrst calculated using HOMA-IR
and ISI0,120 and then analyzed separately using a 2-way mixed model ANOVA with sex and exercise
as the between-subject factors and time (baseline vs. post-HF) as the within-subject factor. A 2-way
ANOVA with sex and exercise as the between-subject factors was performed to analyze trunk plasma
insulin levels at the termination of the experiment. In addition, separate correlation analyses were
performed to determine if there was an association between glucose AUC during OGTT, insulin AUC
during OGTT, and trunk plasma insulin levels with average HF diet preference ratio.
For the Barnes maze, the training days were manually scored for latency to enter the escape box
and errors. The test day was manually scored for the same measures. An error was counted each time
the rat checked a hole other than the one leading to the escape box by poking its nose into the hole.
At least two individuals video scored the training and testing portion of the Barnes maze for all rats.
Training and testing data were analyzed using a 3-way mixed model ANOVA with sex and exercise as
between-subject factors and trial (daily average) as the within-subject factor.
3. Results
3.1. Wheel Running and Two-Diet Choice
Sedentary rats decreased HF diet intake and increased chow intake across time whereas WR
rats expressed the opposite diet choice pattern (time × diet × exercise F (5,220) = 37.35, p < 0.001;
Figure 3A–D). Upon initial access to the two-diet choice, Sed rats showed extreme preference for the
HF diet whereas WR rats avoided it. Subsequently, these opposite diet choice patterns were reﬂected
as Sed rats decreased and WR rats increased HF diet preference over time (time × exercise F (5,220)
= 42.28, p < 0.001; Figure 3E,F). Furthermore, HF diet preference did not appear to be inﬂuenced by
sex, i.e., all WR females and 12 out of 14 WR males reversed HF diet avoidance (sex F (1,44) = 1.63,
p > 0.20). However, when examining the average ratios of HF diet preference across the duration of
two-diet choice, nine out of 14 WR males had a HF diet preference ratio < 0.5, which indicates that they
preferred HF to chow diet for less than half of the six weeks choice period. In addition, WR females
reversed HF diet avoidance earlier than males and expressed greater preference for HF diet (time × sex
× exercise F (5,220) = 3.92, p < 0.05).
Nutrients 2020, 12, 2721
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Nutrients 2020, 12, x FOR PEER REVIEW 
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Figure 3. Diet choice and HF diet preference ratios in males (M, left) and females (F, right). WR rats 
expressed opposite diet choice patterns from their Sed controls. The vertical and horizontal dashed 
red lines denote the start of the two-diet choice and WR period and preference for HF diet where any 
value greater than 0.5 indicates a preference for HF diet, respectively. (A,B) Sedentary male rats 
maintained higher intake of HF than chow diet throughout the experiment whereas there was a two-
week period in which Sed females did not show a preference for either diet. * chow vs. HF, p < 0.05. 
(C,D) Both male and female WR rats increased HF diet intake across time. The reversal of HF diet 
avoidance occurred earlier in females than males. * chow vs. HF, p < 0.05. (E,F) HF diet preference 
went in opposite directions among Sed and WR rats in both sexes. * Sed vs. WR, p < 0.05. 
 
 
Figure 3. Diet choice and HF diet preference ratios in males (M, left) and females (F, right). WR rats
expressed opposite diet choice patterns from their Sed controls. The vertical and horizontal dashed red
lines denote the start of the two-diet choice and WR period and preference for HF diet where any value
greater than 0.5 indicates a preference for HF diet, respectively. (A,B) Sedentary male rats maintained
higher intake of HF than chow diet throughout the experiment whereas there was a two-week period in
which Sed females did not show a preference for either diet. * chow vs. HF, p < 0.05. (C,D) Both male
and female WR rats increased HF diet intake across time. The reversal of HF diet avoidance occurred
earlier in females than males. * chow vs. HF, p < 0.05. (E,F) HF diet preference went in opposite
directions among Sed and WR rats in both sexes. * Sed vs. WR, p < 0.05.
Nutrients 2020, 12, 2721
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3.2. Running Activity and Energy Intake
Females ran more than males, and both sexes showed an inverted-U trend in running activity
where running activity peaked and then decreased to baseline levels (time × sex F (5,125) = 9.73,
p < 0.001; Figure 4A). There were sex-speciﬁc adaptations in energy intake to exercise (sex × exercise
F (1,440) = 28.26, p < 0.001) across time (time × sex × exercise F (5,220) = 4.97, p < 0.001; Figure 4B).
WR led to an initial decrease in total energy intake in males after which they increased food intake,
but total energy intake was not diﬀerent among Sed and WR males (post hoc p > 0.15). Conversely,
female WR rats increased their total energy intake earlier than males and had signiﬁcantly higher
energy intake than their Sed counterparts (post hoc p < 0.001).
Nutrients 2020, 12, x FOR PEER REVIEW 
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3.2. Running Activity and Energy Intake 
Females ran more than males, and both sexes showed an inverted-U trend in running activity 
where running activity peaked and then decreased to baseline levels (time × sex F (5,125) = 9.73, p < 
0.001; Figure 4A). There were sex-specific adaptations in energy intake to exercise (sex × exercise F 
(1,440) = 28.26, p < 0.001) across time (time × sex × exercise F (5,220) = 4.97, p < 0.001; Figure 4B). WR 
led to an initial decrease in total energy intake in males after which they increased food intake, but 
total energy intake was not different among Sed and WR males (post hoc p > 0.15). Conversely, female 
WR rats increased their total energy intake earlier than males and had significantly higher energy 
intake than their Sed counterparts (post hoc p < 0.001). 
 
Figure 4. Running activity and total energy intake. (A) Female rats ran more than males, and both 
sexes showed and inverted-U trend in running activity. * Male vs. female, p < 0.05. (B) Female, but not 
male, running rats had higher energy intake than their Sed counterparts. * Sed vs. WR, p < 0.05. 
3.3. Body Weight and Adiposity 
Exercise-mediated changes in total daily energy intake resulted in suppressed body weight gain 
in both males and females (exercise F (1,44) = 29.16, p < 0.001). Although exercise suppressed weight 
gain in females (Figure 5A), the difference in percent weight gain between Sed and WR rats at the 
end of the experiment was 10% in males and only 2% in females. The difference in body weight was 
reflected in fat composition. Exercise led to decreased retroperitoneal and mesenteric fat (exercise F 
(1,44) = 11.62 and 10.47, respectively, both p < 0.01) in both sexes (sex x exercise F (1,44) = 1.26 and 
3.68, respectively, both p > 0.06; Figure 5B). Although the sex x exercise interaction did not reach 
statistical significance in the mesenteric fat pad (p = 0.061), post hoc tests indicate that the effect of 
exercise was driven by males. For the gonadal fat pad, there was a sex x exercise interaction where 
exercise resulted in a loss of gonadal fat only in males (F (1,44) = 8.16, p < 0.01; post hoc male Sed vs. 
WR p < 0.01 and female Sed vs. WR p > 0.49). 
Figure 4. Running activity and total energy intake. (A) Female rats ran more than males, and both
sexes showed and inverted-U trend in running activity. * Male vs. female, p < 0.05. (B) Female, but not
male, running rats had higher energy intake than their Sed counterparts. * Sed vs. WR, p < 0.05.
3.3. Body Weight and Adiposity
Exercise-mediated changes in total daily energy intake resulted in suppressed body weight gain in
both males and females (exercise F (1,44) = 29.16, p < 0.001). Although exercise suppressed weight gain
in females (Figure 5A), the diﬀerence in percent weight gain between Sed and WR rats at the end of the
experiment was 10% in males and only 2% in females. The diﬀerence in body weight was reﬂected in
fat composition. Exercise led to decreased retroperitoneal and mesenteric fat (exercise F (1,44) = 11.62
and 10.47, respectively, both p < 0.01) in both sexes (sex x exercise F (1,44) = 1.26 and 3.68, respectively,
both p > 0.06; Figure 5B). Although the sex x exercise interaction did not reach statistical signiﬁcance
in the mesenteric fat pad (p = 0.061), post hoc tests indicate that the eﬀect of exercise was driven by
males. For the gonadal fat pad, there was a sex x exercise interaction where exercise resulted in a loss
of gonadal fat only in males (F (1,44) = 8.16, p < 0.01; post hoc male Sed vs. WR p < 0.01 and female
Sed vs. WR p > 0.49).
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Figure 5. Body weight and fat composition. (A) Exercise suppressed body weight in both sexes; 
however, this effect was more pronounced in males. * Sed vs. WR, p < 0.05. (B) Exercise led to 
decreased retroperitoneal, mesenteric, and gonadal fat in males and decreased only retroperitoneal 
adiposity in females. * Sed vs. WR, p < 0.05. 
3.4. Oral Glucose Tolerance Test (OGTT) 
At chow only baseline (BL), there were no group differences in glucose clearance following an 
oral glucose challenge (time × sex × exercise F (4,176) = 1.78, p > 0.32; Figure 6A). Following six weeks 
of chronic HF feeding, females had higher fasting blood glucose levels than males (time × sex F (4,172) 
= 5.26, p < 0.001; post hoc 0 min males vs. females 103.33 vs. 116.61 mg/dL, p < 0.05; Figure 6B). 
However, blood glucose levels returned to pre-glucose challenge levels in females, but not males 
(post hoc 0 min vs. 120 min female p > 0.32 and male p < 0.001). Analysis of area under curve (AUC) 
of blood glucose during the baseline and post-HF diet OGTT indicated that exercise decreased 
glucose AUC in males, but not females (time × sex × exercise F (1,43) = 6.81, p < 0.05; post hoc male 
WR BL vs. HF p < 0.01 and female WR BL vs. HF p > 0.12; Figure 6C). 
Prior to the WR and two-diet choice experimental period, there were no baseline differences in 
insulin levels during an OGTT (time × sex × exercise F (4,156) = 0.85, p > 0.49; Figure 6D). During the 
post-HF diet OGTT, there was a trend for exercise to decrease plasma insulin that appeared to be 
driven by males (sex × exercise F (1,41) = 2.87, p = 0.09; Figure 6E). A one-way ANOVA revealed a 
group difference at 0 min, such that exercise resulted in lower plasma insulin levels only in males 
following long-term HF diet exposure (group F (1,42) = 4.05, p < 0.05; post hoc male Sed vs. WR p < 
0.01 and female Sed vs. WR p > 0.13). Following an oral glucose challenge, there was no exercise effect 
in plasma insulin levels across different time points (time × exercise F (4,164) = 1.61, p > 0.17). On 
average, males had higher insulin AUC levels than females (sex F (1,35) = 4.41, p < 0.05; Figure 6F). 
There was also a time × sex × exercise effect (F (1,35) = 5.29, p < 0.05) where exercise decreased insulin 
AUC in males but not females. Chronic HF feeding resulted in higher insulin AUC than baseline 
levels in Sed males (post hoc M Sed BL vs. HF p < 0.001), and exercise suppressed this increase (post 
hoc M WR BL vs. HF p > 0.06). Male WR rats had lower insulin AUC post-HF diet exposure than their 
Sed counterparts (post hoc HF M Sed vs. M WR p < 0.001). In females, however, exercise did not 
suppress the amount of plasma insulin needed to clear the same dose of glucose (post hoc F Sed and 
F WR BL vs. HF both p < 0.01 and HF F Sed vs. F WR p > 0.98). 
Figure 5. Body weight and fat composition. (A) Exercise suppressed body weight in both sexes;
however, this eﬀect was more pronounced in males. * Sed vs. WR, p < 0.05. (B) Exercise led to decreased
retroperitoneal, mesenteric, and gonadal fat in males and decreased only retroperitoneal adiposity in
females. * Sed vs. WR, p < 0.05.
3.4. Oral Glucose Tolerance Test (OGTT)
At chow only baseline (BL), there were no group diﬀerences in glucose clearance following an
oral glucose challenge (time × sex × exercise F (4,176) = 1.78, p > 0.32; Figure 6A). Following
six weeks of chronic HF feeding, females had higher fasting blood glucose levels than males
(time × sex F (4,172) = 5.26, p < 0.001; post hoc 0 min males vs. females 103.33 vs. 116.61 mg/dL,
p < 0.05; Figure 6B). However, blood glucose levels returned to pre-glucose challenge levels in females,
but not males (post hoc 0 min vs. 120 min female p > 0.32 and male p < 0.001). Analysis of area under
curve (AUC) of blood glucose during the baseline and post-HF diet OGTT indicated that exercise
decreased glucose AUC in males, but not females (time × sex × exercise F (1,43) = 6.81, p < 0.05;
post hoc male WR BL vs. HF p < 0.01 and female WR BL vs. HF p > 0.12; Figure 6C).
Prior to the WR and two-diet choice experimental period, there were no baseline diﬀerences in
insulin levels during an OGTT (time × sex × exercise F (4,156) = 0.85, p > 0.49; Figure 6D). During the
post-HF diet OGTT, there was a trend for exercise to decrease plasma insulin that appeared to be driven
by males (sex × exercise F (1,41) = 2.87, p = 0.09; Figure 6E). A one-way ANOVA revealed a group
diﬀerence at 0 min, such that exercise resulted in lower plasma insulin levels only in males following
long-term HF diet exposure (group F (1,42) = 4.05, p < 0.05; post hoc male Sed vs. WR p < 0.01 and
female Sed vs. WR p > 0.13). Following an oral glucose challenge, there was no exercise eﬀect in plasma
insulin levels across diﬀerent time points (time × exercise F (4,164) = 1.61, p > 0.17). On average, males
had higher insulin AUC levels than females (sex F (1,35) = 4.41, p < 0.05; Figure 6F). There was also a
time × sex × exercise eﬀect (F (1,35) = 5.29, p < 0.05) where exercise decreased insulin AUC in males
but not females. Chronic HF feeding resulted in higher insulin AUC than baseline levels in Sed males
(post hoc M Sed BL vs. HF p < 0.001), and exercise suppressed this increase (post hoc M WR BL vs.
HF p > 0.06). Male WR rats had lower insulin AUC post-HF diet exposure than their Sed counterparts
(post hoc HF M Sed vs. M WR p < 0.001). In females, however, exercise did not suppress the amount of
plasma insulin needed to clear the same dose of glucose (post hoc F Sed and F WR BL vs. HF both
p < 0.01 and HF F Sed vs. F WR p > 0.98).
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Figure 6. Blood glucose (top row) and plasma insulin (bottom row) results from an OGTT at baseline 
(BL) and post-HF diet exposure. (A) There were no group differences in blood glucose at BL. (B) Blood 
glucose levels following an oral glucose challenge returned to fasting levels faster in females than 
males. (C) Decreased glucose clearance, indicated by AUC, from BL occurred in male WR and female 
Sed rats. * BL vs. HF, p < 0.05. (D) There were no group differences in plasma insulin at BL. (E) 
Following HF diet exposure, exercise decreased fasting plasma insulin levels in males but not females. 
@ M Sed vs. WR, p < 0.05. (F) Male WR rats had lower insulin AUC than their Sed counterparts. In 
contrast, both Sed and WR females had higher insulin AUC post-HF exposure than at chow BL. * BL 
vs. HF, p < 0.05, @ HF M Sed vs. WR, p < 0.05. 
Male Sed rats had impaired hepatic insulin sensitivity following HF feeding (time × sex × 
exercise F(1,40) = 7.73, p < 0.01; post hoc M Sed BL vs. post-HF p < 0.0001) as evidenced by increased 
HOMA-IR index (Table 2). Exercise protected against this detrimental metabolic effect of HF diet in 
male WR rats by attenuating increases in insulin resistance (post hoc WR BL vs. post-HF p > 0.18 and 
post-HF Sed vs. WR, p < 0.01). In females, both Sed and WR rats had evidence of insulin resistance 
after long-term HF diet preference (post hoc Sed and WR BL vs. HF, both p < 0.05) and exercise did 
not have the same protective effect as seen in males (post-hoc post-HF F Sed vs. F WR p > 0.08). 
Peripheral insulin sensitivity was analyzed using ISI0,120 and sex differences in the protective effect of 
exercise failed to reach statistical significance (time × sex × exercise F(1,43) = 2.29, p > 0.13). However, 
a priori t-tests revealed that post-HF feeding, male Sed rats had lower ISI0,120 than their WR 
counterparts, indicating reduced insulin sensitivity in the Sed but not WR group (t(10,14) = −2.17, p < 
0.05). This difference between Sed and WR groups was absent in females (t(10,13) = −0.21, p > 0.83). 
Table 2. Hepatic and peripheral indices of insulin sensitivity. Exercise protected against the 
development of insulin resistance by HF diet to a greater extent in males than females. HOMA-IR: 
Homeostatic assessment of insulin resistance; ISI0,120: Gutt’s insulin sensitivity index (mg × L2 × mmol−1 
× mU−1); *: Baseline vs. Post-HF, p < 0.05; ^: Sed vs. WR, p < 0.05. Data are represented as the mean ± 
SEM. 
Insulin Sensitivity 
Group 
HOMA-IR 
ISI0,120 
Baseline 
Post-HF 
Baseline 
Post-HF 
Male Sed 
1.22 ± 0.31 * 
5.01 ± 0.99 ^ 
0.79 ± 0.04 * 
0.63 ± 0.02 ^ 
Male WR 
1.34 ± 0.30 
2.15 ± 0.45 
0.74 ± 0.03 
0.71 ± 0.03 
Figure 6. Blood glucose (top row) and plasma insulin (bottom row) results from an OGTT at baseline
(BL) and post-HF diet exposure. (A) There were no group diﬀerences in blood glucose at BL. (B) Blood
glucose levels following an oral glucose challenge returned to fasting levels faster in females than
males. (C) Decreased glucose clearance, indicated by AUC (area under curve), from BL occurred in
male WR and female Sed rats. * BL vs. HF, p < 0.05. (D) There were no group diﬀerences in plasma
insulin at BL. (E) Following HF diet exposure, exercise decreased fasting plasma insulin levels in males
but not females. @ M Sed vs. WR, p < 0.05. (F) Male WR rats had lower insulin AUC than their Sed
counterparts. In contrast, both Sed and WR females had higher insulin AUC post-HF exposure than at
chow BL. * BL vs. HF, p < 0.05, @ HF M Sed vs. WR, p < 0.05.
Male Sed rats had impaired hepatic insulin sensitivity following HF feeding (time × sex × exercise
F (1,40) = 7.73, p < 0.01; post hoc M Sed BL vs. post-HF p < 0.0001) as evidenced by increased HOMA-IR
index (Table 2). Exercise protected against this detrimental metabolic eﬀect of HF diet in male WR rats
by attenuating increases in insulin resistance (post hoc WR BL vs. post-HF p > 0.18 and post-HF Sed vs.
WR, p < 0.01). In females, both Sed and WR rats had evidence of insulin resistance after long-term
HF diet preference (post hoc Sed and WR BL vs. HF, both p < 0.05) and exercise did not have the
same protective eﬀect as seen in males (post-hoc post-HF F Sed vs. F WR p > 0.08). Peripheral insulin
sensitivity was analyzed using ISI0,120 and sex diﬀerences in the protective eﬀect of exercise failed to
reach statistical signiﬁcance (time × sex × exercise F (1,43) = 2.29, p > 0.13). However, a priori t-tests
revealed that post-HF feeding, male Sed rats had lower ISI0,120 than their WR counterparts, indicating
reduced insulin sensitivity in the Sed but not WR group (t(10,14) = −2.17, p < 0.05). This diﬀerence
between Sed and WR groups was absent in females (t(10,13) = −0.21, p > 0.83).
Analysis of trunk plasma insulin after 6 weeks of HF feeding revealed that WR females had higher
plasma insulin than their Sed counterparts (M Sed 1.04 ± 0.10, M WR 0.54 ± 0.05, F Sed 0.44 ± 0.06, and F
WR 0.69 ± 0.06 ng/mL; sex × exercise F (1,44) = 31.40, p < 0.001; post hoc female Sed vs. WR p < 0.05)
whereas the opposite pattern was observed in Sed and WR males (post hoc p < 0.001). Moreover,
a regression analysis revealed a positive correlation between average ratios of HF diet preference and
plasma insulin levels at sacriﬁce in males (F (1,22) = 7.72, R = 0.51, p < 0.01; Figure 7A) but not females
(F (1,22) = 0.95, R = 0.01 p > 0.94; Figure 7B). No such correlation was found between average ratios of
HF diet preference and either glucose or insulin AUC.
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Table 2. Hepatic and peripheral indices of insulin sensitivity. Exercise protected against the development
of insulin resistance by HF diet to a greater extent in males than females.
Group
Insulin Sensitivity
HOMA-IR
ISI0,120
Baseline
Post-HF
Baseline
Post-HF
Male Sed
1.22 ± 0.31 *
5.01 ± 0.99 ˆ
0.79 ± 0.04 *
0.63 ± 0.02 ˆ
Male WR
1.34 ± 0.30
2.15 ± 0.45
0.74 ± 0.03
0.71 ± 0.03
Female Sed
1.43 ± 0.38 *
3.15 ± 0.47
0.71 ±0.03
0.64 ± 0.02
Female WR
2.25 ± 0.49 *
4.63 ± 0.81
0.70 ± 0.03
0.65 ± 0.02
HOMA-IR: Homeostatic assessment of insulin resistance; ISI0,120:
Gutt’s insulin sensitivity index
(mg × L2 × mmol−1 × mU−1); *: Baseline vs. Post-HF, p < 0.05; ˆ: Sed vs. WR, p < 0.05. Data are represented
as the mean ± SEM.
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Female Sed 
1.43 ± 0.38 * 
3.15 ± 0.47 
0.71 ±0.03 
0.64 ± 0.02 
Female WR 
2.25 ± 0.49 * 
4.63 ± 0.81 
0.70 ± 0.03 
0.65 ± 0.02 
Analysis of trunk plasma insulin after 6 weeks of HF feeding revealed that WR females had 
higher plasma insulin than their Sed counterparts (M Sed 1.04 ± 0.10, M WR 0.54 ± 0.05, F Sed 0.44 ± 
0.06, and F WR 0.69 ± 0.06 ng/mL; sex × exercise F (1,44) = 31.40, p < 0.001; post hoc female Sed vs. WR 
p < 0.05) whereas the opposite pattern was observed in Sed and WR males (post hoc p < 0.001). 
Moreover, a regression analysis revealed a positive correlation between average ratios of HF diet 
preference and plasma insulin levels at sacrifice in males (F (1,22) = 7.72, R = 0.51, p < 0.01; Figure 7A) 
but not females (F (1,22) = 0.95, R = 0.01 p > 0.94; Figure 7B). No such correlation was found between 
average ratios of HF diet preference and either glucose or insulin AUC. 
 
Figure 7. Correlation between trunk plasma insulin levels at the end of the experiment and the 
average ratios of HF diet preference. (A) There was a moderate, positive correlation between HF diet 
preference and trunk plasma insulin in males. (B) There was no relationship between HF diet 
preference and trunk plasma insulin levels in females. 
3.5. Barnes Maze 
During training, there was a sex difference in latency whereby males were slower to locate the 
escape box than females (sex and trial × sex F (1,43) = 66.58 and F (3,129) = 7.59, respectively, both p < 
0.001; Figure 8A,C). In rats of both sexes, exercise led to decreased latency to locate the escape box 
(trial × exercise and trial × sex × exercise F (3,129) = 4.23 and 2.00, p < 0.01 and p > 0.11, respectively). 
Although an effect of trial by exercise interaction on errors committed across training days reached 
statistical significance (F (3,129) = 3.37, p < 0.05), post hoc tests revealed no specific group differences 
on any given day. Thus, exercise slightly reduced the numbers of errors made during learning on the 
Barnes maze in both sexes (trial × sex × exercise F (3,129) = 0.65, p > 0.58; Figure 8B,D). On average, 
male rats made more errors than females during training (sex F (1,43) = 5.25, p < 0.05). 
A factorial ANOVA on the probe trial revealed that there was no effect of sex or exercise on task 
acquisition in regards to latency (sex × exercise F (1,43) = 1.80, p > 0.18) and errors made (F (1,43) = 
1.67, p > 0.20). There was also no effect of sex or exercise on errors made or latency to locate the escape 
box during reversal learning (sex × exercise F (1,43) = 0.79 and 0.15, respectively, both p > 0.37). 
However, when the percent increase in errors made between the probe and reversal trials was 
analyzed using a factorial ANOVA, there was a sex × exercise effect (F (1,34) = 6.48, p < 0.05). Post hoc 
analyses revealed that female WR rats increased more errors than their Sed counterparts (post hoc p 
< 0.05) whereas this effect was not seen in male rats (post hoc male Sed vs. WR p > 0.10). 
Figure 7. Correlation between trunk plasma insulin levels at the end of the experiment and the average
ratios of HF diet preference. (A) There was a moderate, positive correlation between HF diet preference
and trunk plasma insulin in males. (B) There was no relationship between HF diet preference and
trunk plasma insulin levels in females.
3.5. Barnes Maze
During training, there was a sex diﬀerence in latency whereby males were slower to locate
the escape box than females (sex and trial × sex F (1,43) = 66.58 and F (3,129) = 7.59, respectively,
both p < 0.001; Figure 8A,C). In rats of both sexes, exercise led to decreased latency to locate the
escape box (trial × exercise and trial × sex × exercise F (3,129) = 4.23 and 2.00, p < 0.01 and p > 0.11,
respectively). Although an eﬀect of trial by exercise interaction on errors committed across training
days reached statistical signiﬁcance (F (3,129) = 3.37, p < 0.05), post hoc tests revealed no speciﬁc group
diﬀerences on any given day. Thus, exercise slightly reduced the numbers of errors made during
learning on the Barnes maze in both sexes (trial × sex × exercise F (3,129) = 0.65, p > 0.58; Figure 8B,D).
On average, male rats made more errors than females during training (sex F (1,43) = 5.25, p < 0.05).
A factorial ANOVA on the probe trial revealed that there was no eﬀect of sex or exercise on task
acquisition in regards to latency (sex × exercise F (1,43) = 1.80, p > 0.18) and errors made (F (1,43) = 1.67,
p > 0.20). There was also no eﬀect of sex or exercise on errors made or latency to locate the escape box
during reversal learning (sex × exercise F (1,43) = 0.79 and 0.15, respectively, both p > 0.37). However,
when the percent increase in errors made between the probe and reversal trials was analyzed using a
factorial ANOVA, there was a sex × exercise eﬀect (F (1,34) = 6.48, p < 0.05). Post hoc analyses revealed
Nutrients 2020, 12, 2721
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that female WR rats increased more errors than their Sed counterparts (post hoc p < 0.05) whereas this
eﬀect was not seen in male rats (post hoc male Sed vs. WR p > 0.10).
Both male and female rats used a non-spatial serial search strategy (Video S1), e.g., a clockwise or
counterclockwise sequential search, rather than a direct search strategy where the rats utilize spatial cues,
e.g., signs in the testing room to ﬁnd the escape box. Despite not using the visual cues, the decreased
latency and errors indicated that all rats learned the task (Video S2). While Sprague-Dawley rats
have poor visual acuity biasing them towards using a serial search strategy [78], visual acuity has not
been correlated with deﬁcits in learning and memory issues in mice tested on the Barnes maze [86].
Moreover, our results for latency and errors made are comparable to what has been reported in the
literature [78,87].
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Both male and female rats used a non-spatial serial search strategy (Video S1), e.g., a clockwise 
or counterclockwise sequential search, rather than a direct search strategy where the rats utilize 
spatial cues, e.g., signs in the testing room to find the escape box. Despite not using the visual cues, 
the decreased latency and errors indicated that all rats learned the task (Video S2). While Sprague-
Dawley rats have poor visual acuity biasing them towards using a serial search strategy [78], visual 
acuity has not been correlated with deficits in learning and memory issues in mice tested on the 
Barnes maze [86]. Moreover, our results for latency and errors made are comparable to what has been 
reported in the literature [78,87]. 
 
Figure 8. Barnes maze results for males (M, top) and females (F, bottom). (A,C) Both male and female 
rats decreased latency to locate the escape box during training. On average, females had shorter 
latencies to find the escape box than males across training days. (B,D) All groups committed fewer 
errors when searching for the escape box across training days. 
4. Discussion 
Currently, it is unclear whether exercise has a similar efficacy at reversing the adverse metabolic 
and cognitive effects of HF preference and intake in rats of both sexes. To address this, we used a 
long-term two-diet choice and WR model to examine the relationship between preference for HF diet 
and the detrimental metabolic and cognitive outcomes associated with chronic HF feeding, and 
whether exercise has the ability to attenuate these negative effects. We found that both male and 
female WR rats recovered from their initial running-induced HF diet avoidance and increased both 
HF diet intake and preference across time (Figure 3C,D). Exercise had a protective effect in males, but 
Figure 8. Barnes maze results for males (M, top) and females (F, bottom). (A,C) Both male and female
rats decreased latency to locate the escape box during training. On average, females had shorter
latencies to ﬁnd the escape box than males across training days. (B,D) All groups committed fewer
errors when searching for the escape box across training days.
4. Discussion
Currently, it is unclear whether exercise has a similar eﬃcacy at reversing the adverse metabolic
and cognitive eﬀects of HF preference and intake in rats of both sexes. To address this, we used a
long-term two-diet choice and WR model to examine the relationship between preference for HF
diet and the detrimental metabolic and cognitive outcomes associated with chronic HF feeding,
Nutrients 2020, 12, 2721
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and whether exercise has the ability to attenuate these negative eﬀects. We found that both male and
female WR rats recovered from their initial running-induced HF diet avoidance and increased both
HF diet intake and preference across time (Figure 3C,D). Exercise had a protective eﬀect in males,
but not females, on HF-mediated weight gain and adiposity (Figure 5) and metabolic dysfunction
(Figure 6C,F). Moreover, the positive association between preference for HF diet and trunk plasma
insulin was only seen in males (Figure 7A). Wheel running rats had signiﬁcantly faster escape latencies
and made slightly fewer errors than their sedentary counterparts in both sexes across training days,
suggesting improved learning and memory through exercise (Figure 8). Although our interpretation
of behavioral ﬂexibility was limited due to the utilization of a non-spatial search strategy by the rats
(Video S1), female WR rats were the only group to increase the number of errors made between the
probe and reversal learning trials compared to their Sed controls. Taken together, our results suggest
that exercise-mediated changes in HF diet preference lead to sex-speciﬁc eﬀects in regards to the
protective eﬀect of exercise on both peripheral metabolic function and cognitive performance.
The opposite diet choice patterns observed among Sed and WR rats (Figure 3A–D) may be due to
the increased metabolic requirement from exercise to maintain energy balance where the HF diet is a
more eﬃcient fuel source than the standard chow diet, which is higher in carbohydrates than fats [88,89].
Indeed, human studies have shown that there is a crossover eﬀect during which the ratio of lipolysis
to carbohydrate oxidation during submaximal and endurance exercise increases [90–92]. While this
crossover eﬀect is inﬂuenced by exercise duration and intensity, it may partially contribute to diﬀerences
in macronutrient preference among sedentary and physically active individuals.
Our previous
short-term studies with the same paradigm of wheel running and two-diet choice revealed that the
majority of male rats express persistent HF diet avoidance whereas the majority of females reverse HF
diet avoidance [80,93–95]. These results are consistent with the report that estradiol enhances lipid
metabolism during exercise in rats [96]. Furthermore, results with respiratory exchange ratio as a
measure of substrate utilization from human studies using indirect calorimetry suggest that compared
to men, women utilize more fat as the fuel source as a result of long-term exercise [90,91,97,98]. A direct
assessment of fuel oxidation will be necessary to support our hypothesis that sex diﬀerences in substrate
utilization may contribute to diﬀerences in running-associated macronutrient preference. When the
choice duration was extended, both male and female WR groups preferred the HF diet by the end of
the six-week period (Figure 3E,F). It is unclear whether this increase in fat preference would occur
in humans if the behavior can be examined without the inﬂuence of the cognitive component of
making healthier food choices in subjects who incorporate regular exercise as a lifestyle. Nevertheless,
carbohydrate metabolism is positively correlated with exercise intensity in humans [99] whereas
fat oxidation is more likely to occur during low intensity exercise, especially when prolonged [100].
Thus, this shift in fat preference may be a compensatory result of increased energy requirement
from long-term aerobic exercise where carbohydrates are no longer the most eﬃcient fuel substrate.
The addition of groups undergoing diﬀerent types of exercise (e.g., strength, treadmill, swimming, etc.)
for diﬀerent lengths of time would provide additional evidence for the eﬀect of exercise on energy
intake and macronutrient preference if results are consistent.
Although both male and female WR rats reversed their initial avoidance for HF diet, there was a
sex diﬀerence in which the reversal of HF diet avoidance occurred with females reversing earlier than
males. One potential explanation for this sex diﬀerence is that females are more prone to hedonic and
binge eating than males [101,102] and their feeding behavior appears to be driven by palatability rather
than physiological hunger or metabolic state [103,104]. Both of these factors could act together and
exacerbate the development of obesity [56,57], which is more prevalent in females [105]. In addition,
females have higher reward sensitivity than males [106,107] which may predict decreased restraint
of fat intake [108]. HF diet is highly palatable and can stimulate eating in the absence of hunger
by acting on the reward system [104], potentially leading to overeating. Although WR is naturally
rewarding for rodents [109], it may not be a suﬃcient substitute for the reinforcing eﬀects of the
palatable HF diet for females [110]. In support of this, studies have shown that male rats are more
Nutrients 2020, 12, 2721
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responsive to the reinforcing eﬀects of voluntary WR to attenuate seeking of drugs of abuse [111,112].
The high sensitivity to WR reinforcement could facilitate males’ ability to maintain lower preference
for HF diet for a longer duration than females that are more sensitive to the reinforcing eﬀects of diet
palatability [110].
Sex diﬀerences in adapting to the increased energy requirement of exercise led to diﬀerential
eﬃcacies for exercise to attenuate HF-mediated insults on metabolic function in male and female rats.
Consistent with the literature [21,23,113], females ran more than males (Figure 4A) and compensated
for the increased energy expenditure by increasing total energy intake earlier than males [22,114].
This may have led to the limited eﬀect of exercise on suppressing body weight and adiposity [19–22]
and attenuating HF mediated metabolic dysregulation in females (Figure 6). Here, we report that
exercise suppressed HF diet preference, total energy intake, body weight, and adiposity, and improved
glucose metabolism to a greater degree in males than females. This is consistent with the consensus
in the literature stating that males are more responsive to the beneﬁcial eﬀects of exercise, resulting
in improved glucose tolerance and insulin sensitivity [74–76]. Thus, it appears that exercise has a
protective eﬀect on insulin sensitivity in males despite increased HF diet intake [69,70,73,115–120].
We also found a positive association between HF diet preference and insulin levels in males but not
females (Figure 7). The greater protective eﬀect of exercise on peripheral metabolic function in males
may be mediated by two eﬀects acting in concert: (1) a slower compensatory response to the increased
energy expenditure from exercise [114] and (2) maintenance of a lower preference for HF diet for a
longer duration of time compared to females.
Our results suggest that that without a concurrent decrease in body weight, adiposity, and HF
diet preference, exercise has a limited eﬀect on signiﬁcantly improving peripheral insulin resistance
during chronic access to HF diet [16,36,37]. Female rats had increased HOMA-IR (Table 2) above the
2.60 cutoﬀ [121] for evidence of hepatic insulin resistance after long-term HF feeding regardless of the
opportunity to exercise. In contrast, exercise appeared to protect against the development of insulin
resistance in males. The results of ISI0,120 also suggest that male WR rats were the only group that
maintained insulin sensitivity after six weeks of exposure to HF diet. Although higher HF diet and total
energy intake in WR females may play a role in these observed sex diﬀerences and additional pair-fed
groups will be needed to assess such possibility in future studies, our results reveal that exercise
produces more protective eﬀects against insulin resistance in males than females by reducing HF diet
preference and consumption. Consequently, an optimal treatment for weight loss and improving
insulin sensitivity for females would be a combination of diet and exercise [122].
The improved performance during training on the Barnes maze in WR rats of both sexes relative
to their Sed counterparts suggests that exercise can be protective against insults to cognitive behavior
from chronic HF diet consumption independent of sex (Figure 8). This aligns with rodent literature
linking HF feeding to deﬁcits in cognitive behaviors [15,42,53,54], which exercise can reverse [44,48–52].
In contrast to reports that male and female rats performed similarly on the Barnes maze [123,124],
we found that females had faster latencies than males to locate the escape box. Rather than enhanced
learning, this eﬀect could be a result of hormonal/estrous status or higher general locomotor activity
exhibited by females [125,126]. Although our results conﬂict with previous literature reporting either
a male advantage or no diﬀerence in performance between males and females, sex diﬀerences have
not been consistently reported in regards to learning visuospatial tasks [86,127–129]. Moreover, task
performance is inﬂuenced by a variety of factors including task design, species, strain, hormonal
status, stress, and age [130]. To our knowledge, there have been a limited number of studies that
investigate sex diﬀerences in cognitive behavior using the Barnes maze in rats [127,128,131] with the
Morris water maze being the more popular task [130]. More standardized research is necessary to draw
ﬁrm conclusions on subtle sex diﬀerences in cognitive and spatial ability given how the Barnes maze is
sensitive to a variety of conditions that may inﬂuence task performance and subsequent interpretation
of the data.
Nutrients 2020, 12, 2721
15 of 22
Despite similar search strategies and learning outcomes, there was evidence of sex-speciﬁc eﬀects
of running on reversal learning on the Barnes maze. The non-spatial serial search strategy (Video S1)
is not uncommon in Sprague-Dawley rats [128] that have lower visual acuity than other strains
(e.g., Long-Evans and Wistar) [128,132] where using a serial search strategy may be more eﬃcient.
Notably, the increase in errors made from the probe to reversal learning trials was higher in WR
females compared to their Sed counterparts, whereas there was no such group diﬀerence in males. This
sex-speciﬁc eﬀect may be interpreted as WR females having the worst behavioral ﬂexibility among
all groups, which conﬂicts with the ﬁnding that PFC-mediated deﬁcits in behavioral ﬂexibility are
more pronounced in males than females following HF feeding [65–67]. However, our interpretation of
the data is limited such that (1) rats did not appear to use spatial cues to locate the escape box and (2)
learning without utilizing spatial cues may render weak task acquisition and as such, poses a confound
for the analysis of potentially increased errors during the reversal learning trials. Thus, an alternate
interpretation to our result that only female WR rats signiﬁcantly increased their errors during reversal
learning may be that this was the only group that acquired the original task and could exhibit deﬁcits in
behavioral ﬂexibility. Nevertheless, while adjustments can be made to promote the use of spatial cues
(e.g., moving cues closer to the maze, adding an aversive stimulus/bright light, etc.), the Barnes maze
may not be the most optimal behavioral task to assess subtle deﬁcits in cognitive behavior. In humans,
obesity generally results in mild rather than severe cognitive impairment [133,134]. Therefore, a more
sensitive behavioral task may allow us to uncover cognitive deﬁcits more readily than the Barnes maze.
Cognition is a complex and multi-faceted construct. Thus, while we found evidence for diﬀerences in
cognitive performance, future studies should include a battery of behavioral tests to tap into diﬀerent
aspects of cognitive behavior that may be adversely inﬂuenced by HF diet. Importantly, prolonged HF
diet intake and preference may impair speciﬁc, rather than global, domains of cognitive function in a
sex-speciﬁc fashion. Impairments in one domain may be more inﬂuential in the regulation of feeding
behavior and lead to worse outcomes depending on sex.
Caution should be taken when interpreting the results due to inherent limitations resulting from
the complexity of the study design. Diﬀerent fat sources and compositions (e.g., polyunsaturated,
monounsaturated) may diﬀerentially aﬀect aspects of metabolism and cognition. Future studies should
utilize diets matched in macronutrient sources as much as possible to limit the confounding eﬀect of
diﬀerences in raw materials. To our knowledge, no study has assessed changes in insulin sensitivity
following HF diet and voluntary exercise in rats of both sexes. The addition of a naïve chow-fed control
group is necessary to make between-group comparisons to strengthen the argument for the protective
eﬀect of exercise against HF diet. Exercise is more likely to have a greater beneﬁcial eﬀect in males,
but the addition of a WR group maintained on only HF diet is necessary to make this conclusion given
the shift in HF diet preference across time and the highly variable HF diet intake between subjects and
sexes. Here, we focused on voluntary exercise; however, the eﬀect of exercise may shift depending on
exercise conditions (forced vs. voluntary, strength vs. endurance, acute vs. chronic, etc.). An extensive
investigation is necessary before results can be directly translated to humans. Nevertheless, our results
lend support to our hypotheses regarding the protective eﬀect of exercise against the detrimental
outcomes of HF feeding and inform the development of more optimized designs for future studies.
5. Conclusions
We examined sex diﬀerences in exercise-mediated changes in diet choice and the degree to
which exercise can reverse the metabolic dysregulation and improve cognitive performance associated
with long-term HF feeding. The protective eﬀect of exercise on suppressing HF diet preference and
HF-mediated insults to peripheral metabolism was speciﬁc to males whereas exercise similarly enhanced
learning on the Barnes maze in both males and females. Intriguingly, despite less improvement on their
metabolic proﬁle, female WR rats still beneﬁted from the exercise and showed improved performance
on the Barnes maze. This ﬁnding suggests that cardio-based exercise can potentially exert diﬀerential
eﬀects on metabolic and cognitive function. Taken together, these results suggest that the adverse
Nutrients 2020, 12, 2721
16 of 22
metabolic eﬀects of chronic HF feeding and preference are especially detrimental to females, but exercise
remains a good intervention option for both males and females to prevent cognitive decline resulting
from poor dietary choices.
Supplementary Materials: The following are available online at http://www.mdpi.com/2072-6643/12/9/2721/s1,
Video S1: Serial search training trial, Video S2: Serial search probe trial.
Author Contributions: Conceptualization, N.-C.L. and T.Y.Y.; methodology, N.-C.L. and T.Y.Y.; formal analysis,
T.Y.Y. and N.-C.L.; data curation, T.Y.Y. and Z.G.; writing—original draft preparation, T.Y.Y.; writing—review
and editing, N.-C.L.; visualization, T.Y.Y.; funding acquisition, N.-C.L. All authors have read and agreed to the
published version of the manuscript.
Funding: This study was supported by the UIUC Psychology Department startup funds (to N.-C.L.).
Acknowledgments: We thank Fatima Najera and Gabi Petrus for their help with videoscoring and animal care.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
References
1.
Hedley, A.A.; Ogden, C.L.; Johnson, C.L.; Carroll, M.D.; Curtin, L.R.; Flegal, K.M. Prevalence of overweight
and obesity among US children, adolescents, and adults, 1999–2002. JAMA 2004, 291, 2847–2850. [CrossRef]
[PubMed]
2.
Crittenden, A.N.; Schnorr, S.L. Current views on hunter-gatherer nutrition and the evolution of the human
diet. Am. J. Phys. Anthropol. 2017, 162 (Suppl. 63), 84–109. [CrossRef]
3.
Cordain, L.; Eaton, S.B.; Sebastian, A.; Mann, N.; Lindeberg, S.; Watkins, B.A.; O’Keefe, J.H.; Brand-Miller, J.
Origins and evolution of the Western diet: Health implications for the 21st century. Am. J. Clin. Nutr. 2005,
81, 341–354. [CrossRef] [PubMed]
4.
Ziegler, E. Secular changes in the stature of adults and the secular trend of the modern sugar consumption.
Z. Kinderheilkd 1967, 99, 146–166. [CrossRef] [PubMed]
5.
Shan, Z.; Rehm, C.D.; Rogers, G.; Ruan, M.; Wang, D.D.; Hu, F.B.; Mozaﬀarian, D.; Zhang, F.F.;
Bhupathiraju, S.N. Trends in Dietary Carbohydrate, Protein, and Fat Intake and Diet Quality Among
US Adults, 1999–2016. JAMA 2019, 322, 1178–1187. [CrossRef]
6.
Vadiveloo, M.; Scott, M.; Quatromoni, P.; Jacques, P.; Parekh, N. Trends in dietary fat and high-fat food
intakes from 1991 to 2008 in the Framingham Heart Study participants. Br. J. Nutr. 2014, 111, 724–734.
[CrossRef]
7.
Okreglicka, K. Health eﬀects of changes in the structure of dietary macronutrients intake in western societies.
Rocz. Panstw. Zakl. Hig. 2015, 66, 97–105.
8.
Foster-Powell, K.; Holt, S.H.; Brand-Miller, J.C. International table of glycemic index and glycemic load
values: 2002. Am. J. Clin. Nutr. 2002, 76, 5–56. [CrossRef]
9.
Steenbergen, L.; Colzato, L.S. Overweight and Cognitive Performance: High Body Mass Index Is Associated
with Impairment in Reactive Control during Task Switching. Front. Nutr. 2017, 4, 51. [CrossRef]
10.
Yang, Y.; Shields, G.S.; Guo, C.; Liu, Y. Executive function performance in obesity and overweight individuals:
A meta-analysis and review. Neurosci. BioBehav. Rev. 2018, 84, 225–244. [CrossRef]
11.
Smith, E.; Hay, P.; Campbell, L.; Trollor, J.N. A review of the association between obesity and cognitive
function across the lifespan: Implications for novel approaches to prevention and treatment. Obes. Rev. 2011,
12, 740–755. [CrossRef]
12.
Chen, F.T.; Chen, S.R.; Chu, I.H.; Liu, J.H.; Chang, Y.K. Multicomponent Exercise Intervention and
Metacognition in Obese Preadolescents: A Randomized Controlled Study. J. Sport Exerc. Psychol. 2017, 39,
302–312. [CrossRef] [PubMed]
13.
Martin, B.; Pearson, M.; Kebejian, L.; Golden, E.; Keselman, A.; Bender, M.; Carlson, O.; Egan, J.; Ladenheim, B.;
Cadet, J.L.; et al. Sex-dependent metabolic, neuroendocrine, and cognitive responses to dietary energy
restriction and excess. Endocrinology 2007, 148, 4318–4333. [CrossRef] [PubMed]
14.
Winocur, G.; Greenwood, C.E.; Piroli, G.G.; Grillo, C.A.; Reznikov, L.R.; Reagan, L.P.; McEwen, B.S. Memory
impairment in obese Zucker rats: An investigation of cognitive function in an animal model of insulin
resistance and obesity. Behav. Neurosci. 2005, 119, 1389–1395. [CrossRef]
Nutrients 2020, 12, 2721
17 of 22
15.
Kanoski, S.E.; Meisel, R.L.; Mullins, A.J.; Davidson, T.L. The eﬀects of energy-rich diets on discrimination
reversal learning and on BDNF in the hippocampus and prefrontal cortex of the rat. Behav. Brain Res. 2007,
182, 57–66. [CrossRef] [PubMed]
16.
Maesako, M.; Uemura, K.; Kubota, M.; Kuzuya, A.; Sasaki, K.; Hayashida, N.; Asada-Utsugi, M.; Watanabe, K.;
Uemura, M.; Kihara, T.; et al. Exercise is more eﬀective than diet control in preventing high fat diet-induced
beta-amyloid deposition and memory deﬁcit in amyloid precursor protein transgenic mice. J. Biol. Chem.
2012, 287, 23024–23033. [CrossRef] [PubMed]
17.
Klem, M.L.; Wing, R.R.; McGuire, M.T.; Seagle, H.M.; Hill, J.O. A descriptive study of individuals successful
at long-term maintenance of substantial weight loss. Am. J. Clin. Nutr. 1997, 66, 239–246. [CrossRef]
[PubMed]
18.
Shick, S.M.; Wing, R.R.; Klem, M.L.; McGuire, M.T.; Hill, J.O.; Seagle, H. Persons successful at long-term
weight loss and maintenance continue to consume a low-energy, low-fat diet. J. Am. Diet. Assoc. 1998, 98,
408–413. [CrossRef]
19.
Looy, H.; Eikelboom, R. Wheel running, food intake, and body weight in male rats. Physiol. Behav. 1989, 45,
403–405. [CrossRef]
20.
Kawaguchi, M.; Scott, K.A.; Moran, T.H.; Bi, S. Dorsomedial hypothalamic corticotropin-releasing factor
mediation of exercise-induced anorexia. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2005, 288, R1800–R1805.
[CrossRef]
21.
Tokuyama, K.; Saito, M.; Okuda, H. Eﬀects of wheel running on food intake and weight gain of male and
female rats. Physiol. Behav. 1982, 28, 899–903. [CrossRef]
22.
Carrera, O.; Cerrato, M.; Vazquez, R.; Sineiro, C.; Gutierrez, E. Gender dimorphic eﬀects of voluntary running
in laboratory rats depends on maturational status. Q. J. Exp. Psychol. (Hove) 2011, 64, 823–832. [CrossRef]
[PubMed]
23.
Eckel, L.A.; Moore, S.R. Diet-induced hyperphagia in the rat is inﬂuenced by sex and exercise. Am. J. Physiol.
Regul. Integr. Comp. Physiol. 2004, 287, R1080–R1085. [CrossRef] [PubMed]
24.
Blundell, J.E.; King, N.A. Physical activity and regulation of food intake: Current evidence. Med. Sci.
Sports Exerc. 1999, 31, S573–S583. [CrossRef] [PubMed]
25.
Donnelly, J.E.; Herrmann, S.D.; Lambourne, K.; Szabo, A.N.; Honas, J.J.; Washburn, R.A. Does increased
exercise or physical activity alter ad-libitum daily energy intake or macronutrient composition in healthy
adults? A systematic review. PLoS ONE 2014, 9, e83498. [CrossRef]
26.
Ebrahimi, M.; Rahmani-Nia, F.; Damirchi, A.; Mirzaie, B.; Asghar Pur, S. Eﬀect of Short-term Exercise on
Appetite, Energy Intake and Energy-regulating Hormones. Iran. J. Basic Med. Sci. 2013, 16, 829–834.
27.
King, N.A.; Hopkins, M.; Caudwell, P.; Stubbs, R.J.; Blundell, J.E. Beneﬁcial eﬀects of exercise: Shifting the
focus from body weight to other markers of health. Br. J. Sports Med. 2009, 43, 924–927. [CrossRef]
28.
Schubert, M.M.; Desbrow, B.; Sabapathy, S.; Leveritt, M. Acute exercise and subsequent energy intake.
A meta-analysis. Appetite 2013, 63, 92–104. [CrossRef]
29.
Castro, E.A.; Carraca, E.V.; Cupeiro, R.; Lopez-Plaza, B.; Teixeira, P.J.; Gonzalez-Lamuno, D.; Peinado, A.B.
The Eﬀects of the Type of Exercise and Physical Activity on Eating Behavior and Body Composition in
Overweight and Obese Subjects. Nutrients 2020, 12, 557. [CrossRef]
30.
Donnelly, J.E.; Smith, B.K. Is exercise eﬀective for weight loss with ad libitum diet? Energy balance,
compensation, and gender diﬀerences. Exerc. Sport Sci. Rev. 2005, 33, 169–174. [CrossRef]
31.
Anderson, J.W.; Konz, E.C.; Frederich, R.C.; Wood, C.L. Long-term weight-loss maintenance: A meta-analysis
of US studies. Am. J. Clin. Nutr. 2001, 74, 579–584. [CrossRef] [PubMed]
32.
Despres, J.P.; Bouchard, C.; Savard, R.; Tremblay, A.; Marcotte, M.; Theriault, G. The eﬀect of a 20-week
endurance training program on adipose-tissue morphology and lipolysis in men and women. Metabolism
1984, 33, 235–239. [CrossRef]
33.
Williams, R.L.; Wood, L.G.; Collins, C.E.; Callister, R. Eﬀectiveness of weight loss interventions–is there
a diﬀerence between men and women: A systematic review. Obes. Rev. 2015, 16, 171–186. [CrossRef]
[PubMed]
34.
Washburn, R.A.; Honas, J.J.; Ptomey, L.T.; Mayo, M.S.; Lee, J.; Sullivan, D.K.; Lambourne, K.; Willis, E.A.;
Donnelly, J.E. Energy and Macronutrient Intake in the Midwest Exercise Trial 2 (MET-2). Med. Sci. Sports Exerc.
2015, 47, 1941–1949. [CrossRef] [PubMed]
Nutrients 2020, 12, 2721
18 of 22
35.
Westerterp, K.R.; Meijer, G.A.; Janssen, E.M.; Saris, W.H.; Ten Hoor, F. Long-term eﬀect of physical activity
on energy balance and body composition. Br. J. Nutr. 1992, 68, 21–30. [CrossRef] [PubMed]
36.
Coker, R.H.; Williams, R.H.; Yeo, S.E.; Kortebein, P.M.; Bodenner, D.L.; Kern, P.A.; Evans, W.J. The impact
of exercise training compared to caloric restriction on hepatic and peripheral insulin resistance in obesity.
J. Clin. Endocrinol. Metab. 2009, 94, 4258–4266. [CrossRef] [PubMed]
37.
Nara, M.; Takahashi, M.; Kanda, T.; Shimomura, Y.; Kobayashi, I. Running exercise improves metabolic
abnormalities and fat accumulation in sucrose-induced insulin-resistant rats. Obes. Res. 1997, 5, 348–353.
[CrossRef]
38.
Greenwood, C.E.; Winocur, G. High-fat diets, insulin resistance and declining cognitive function.
Neurobiol. Aging 2005, 26 (Suppl. 1), 42–45. [CrossRef]
39.
Winocur, G.; Greenwood, C.E. Studies of the eﬀects of high fat diets on cognitive function in a rat model.
Neurobiol. Aging 2005, 26 (Suppl. 1), 46–49. [CrossRef]
40.
Greenwood, C.E.; Winocur, G. Cognitive impairment in rats fed high-fat diets: A speciﬁc eﬀect of saturated
fatty-acid intake. Behav. Neurosci. 1996, 110, 451–459. [CrossRef]
41.
Winocur, G.; Greenwood, C.E. The eﬀects of high fat diets and environmental inﬂuences on cognitive
performance in rats. Behav. Brain Res. 1999, 101, 153–161. [CrossRef]
42.
Stranahan, A.M.; Norman, E.D.; Lee, K.; Cutler, R.G.; Telljohann, R.S.; Egan, J.M.; Mattson, M.P. Diet-induced
insulin resistance impairs hippocampal synaptic plasticity and cognition in middle-aged rats. Hippocampus
2008, 18, 1085–1088. [CrossRef] [PubMed]
43.
Valladolid-Acebes, I.; Stucchi, P.; Cano, V.; Fernandez-Alfonso, M.S.; Merino, B.; Gil-Ortega, M.; Fole, A.;
Morales, L.; Ruiz-Gayo, M.; Del Olmo, N. High-fat diets impair spatial learning in the radial-arm maze in
mice. Neurobiol. Learn. Mem. 2011, 95, 80–85. [CrossRef] [PubMed]
44.
Kanoski, S.E.; Davidson, T.L. Diﬀerent patterns of memory impairments accompany short- and longer-term
maintenance on a high-energy diet. J. Exp. Psychol. Anim. Behav. Process. 2010, 36, 313–319. [CrossRef]
[PubMed]
45.
Brockett, A.T.; LaMarca, E.A.; Gould, E. Physical exercise enhances cognitive ﬂexibility as well as astrocytic
and synaptic markers in the medial prefrontal cortex. PLoS ONE 2015, 10, e0124859. [CrossRef] [PubMed]
46.
Fordyce, D.E.; Farrar, R.P. Enhancement of spatial learning in F344 rats by physical activity and related
learning-associated alterations in hippocampal and cortical cholinergic functioning. Behav. Brain Res. 1991,
46, 123–133. [CrossRef]
47.
Voss, M.W.; Vivar, C.; Kramer, A.F.; van Praag, H. Bridging animal and human models of exercise-induced
brain plasticity. Trends Cogn. Sci. 2013, 17, 525–544. [CrossRef]
48.
Molteni, R.; Wu, A.; Vaynman, S.; Ying, Z.; Barnard, R.J.; Gomez-Pinilla, F. Exercise reverses the harmful
eﬀects of consumption of a high-fat diet on synaptic and behavioral plasticity associated to the action of
brain-derived neurotrophic factor. Neuroscience 2004, 123, 429–440. [CrossRef]
49.
Klein, C.; Jonas, W.; Iggena, D.; Empl, L.; Rivalan, M.; Wiedmer, P.; Spranger, J.; Hellweg, R.; Winter, Y.;
Steiner, B. Exercise prevents high-fat diet-induced impairment of ﬂexible memory expression in the water
maze and modulates adult hippocampal neurogenesis in mice. Neurobiol. Learn. Mem. 2016, 131, 26–35.
[CrossRef]
50.
Noble, E.E.; Mavanji, V.; Little, M.R.; Billington, C.J.; Kotz, C.M.; Wang, C. Exercise reduces diet-induced
cognitive decline and increases hippocampal brain-derived neurotrophic factor in CA3 neurons.
Neurobiol. Learn. Mem. 2014, 114, 40–50. [CrossRef]
51.
Woo, J.; Shin, K.O.; Park, S.Y.; Jang, K.S.; Kang, S. Eﬀects of exercise and diet change on cognition function and
synaptic plasticity in high fat diet induced obese rats. Lipids Health Dis. 2013, 12, 144. [CrossRef] [PubMed]
52.
Gibbons, T.E.;
Pence, B.D.;
Petr, G.;
Ossyra, J.M.;
Mach, H.C.;
Bhattacharya, T.K.;
Perez, S.;
Martin, S.A.; McCusker, R.H.; Kelley, K.W.; et al. Voluntary wheel running, but not a diet containing
(-)-epigallocatechin-3-gallate and beta-alanine, improves learning, memory and hippocampal neurogenesis
in aged mice. Behav. Brain Res. 2014, 272, 131–140. [CrossRef] [PubMed]
53.
Aslani, S.; Vieira, N.; Marques, F.; Costa, P.S.; Sousa, N.; Palha, J.A. The eﬀect of high-fat diet on rat’s mood,
feeding behavior and response to stress. Transl. Psychiatry 2015, 5, e684. [CrossRef] [PubMed]
54.
McNeilly, A.D.; Williamson, R.; Sutherland, C.; Balfour, D.J.; Stewart, C.A. High fat feeding promotes
simultaneous decline in insulin sensitivity and cognitive performance in a delayed matching and
non-matching to position task. Behav. Brain Res. 2011, 217, 134–141. [CrossRef] [PubMed]
Nutrients 2020, 12, 2721
19 of 22
55.
Bocarsly, M.E.; Fasolino, M.; Kane, G.A.; LaMarca, E.A.; Kirschen, G.W.; Karatsoreos, I.N.; McEwen, B.S.;
Gould, E. Obesity diminishes synaptic markers, alters microglial morphology, and impairs cognitive function.
Proc. Natl. Acad. Sci. USA 2015, 112, 15731–15736. [CrossRef]
56.
Edwards, C.G.; Walk, A.M.; Thompson, S.V.; Mullen, S.P.; Holscher, H.D.; Khan, N.A. Disordered Eating
Attitudes and Behavioral and Neuroelectric Indices of Cognitive Flexibility in Individuals with Overweight
and Obesity. Nutrients 2018, 10, 1902. [CrossRef]
57.
Perpina, C.; Segura, M.; Sanchez-Reales, S. Cognitive ﬂexibility and decision-making in eating disorders and
obesity. Eat. Weight Disord. 2017, 22, 435–444. [CrossRef]
58.
McNeilly, A.D.; Gao, A.; Hill, A.Y.; Gomersall, T.; Balfour, D.J.K.; Sutherland, C.; Stewart, C.A. The eﬀect of
dietary intervention on the metabolic and behavioural impairments generated by short term high fat feeding
in the rat. Physiol. Behav. 2016, 167, 100–109. [CrossRef]
59.
Boitard, C.; Parkes, S.L.; Cavaroc, A.; Tantot, F.; Castanon, N.; Laye, S.; Tronel, S.; Pacheco-Lopez, G.;
Coutureau, E.; Ferreira, G. Switching Adolescent High-Fat Diet to Adult Control Diet Restores Neurocognitive
Alterations. Front. Behav. Neurosci. 2016, 10, 225. [CrossRef]
60.
McNeilly, A.D.; Williamson, R.; Balfour, D.J.; Stewart, C.A.; Sutherland, C. A high-fat-diet-induced cognitive
deﬁcit in rats that is not prevented by improving insulin sensitivity with metformin. Diabetologia 2012, 55,
3061–3070. [CrossRef]
61.
Amengual-Cladera, E.; Llado, I.; Gianotti, M.; Proenza, A.M. Sex diﬀerences in the eﬀect of high-fat diet
feeding on rat white adipose tissue mitochondrial function and insulin sensitivity. Metabolism 2012, 61,
1108–1117. [CrossRef] [PubMed]
62.
Barron, A.M.; Rosario, E.R.; Elterieﬁ, R.; Pike, C.J. Sex-speciﬁc eﬀects of high fat diet on indices of metabolic
syndrome in 3xTg-AD mice: Implications for Alzheimer’s disease. PLoS ONE 2013, 8, e78554. [CrossRef]
[PubMed]
63.
Elias, M.F.; Elias, P.K.; Sullivan, L.M.; Wolf, P.A.; D’Agostino, R.B. Lower cognitive function in the presence of
obesity and hypertension: The Framingham heart study. Int. J. Obes. Relat. Metab. Disord. 2003, 27, 260–268.
[CrossRef] [PubMed]
64.
Underwood, E.L.; Thompson, L.T. High-fat diet impairs spatial memory and hippocampal intrinsic excitability
and sex-dependently alters circulating insulin and hippocampal insulin sensitivity. Biol. Sex Diﬀer. 2016, 7, 9.
[CrossRef]
65.
Shields, G.S.; Trainor, B.C.; Lam, J.C.; Yonelinas, A.P. Acute stress impairs cognitive ﬂexibility in men, not
women. Stress 2016, 19, 542–546. [CrossRef]
66.
Laredo, S.A.; Steinman, M.Q.; Robles, C.F.; Ferrer, E.; Ragen, B.J.; Trainor, B.C. Eﬀects of defeat stress on
behavioral ﬂexibility in males and females: Modulation by the mu-opioid receptor. Eur. J. Neurosci. 2015, 41,
434–441. [CrossRef]
67.
Hwang, L.L.; Wang, C.H.; Li, T.L.; Chang, S.D.; Lin, L.C.; Chen, C.P.; Chen, C.T.; Liang, K.C.; Ho, I.K.;
Yang, W.S.; et al. Sex diﬀerences in high-fat diet-induced obesity, metabolic alterations and learning, and
synaptic plasticity deﬁcits in mice. Obesity (Silver Spring) 2010, 18, 463–469. [CrossRef]
68.
Li, W.; Qiu, Q.; Sun, L.; Yue, L.; Wang, T.; Li, X.; Xiao, S. Sex diﬀerences in obesity and cognitive function in a
cognitively normal aging Chinese Han population. Neuropsychiatr. Dis. Treat. 2017, 13, 2405–2410. [CrossRef]
69.
Gollisch, K.S.; Brandauer, J.; Jessen, N.; Toyoda, T.; Nayer, A.; Hirshman, M.F.; Goodyear, L.J. Eﬀects of
exercise training on subcutaneous and visceral adipose tissue in normal- and high-fat diet-fed rats. Am. J.
Physiol. Endocrinol. Metab. 2009, 297, E495–E504. [CrossRef]
70.
Tokuyama, K.;
Suzuki, M. Intravenous glucose tolerance test-derived glucose eﬀectiveness in
endurance-trained rats. Metabolism 1998, 47, 190–194. [CrossRef]
71.
Goodyear, L.J.; Hirshman, M.F.; Knutson, S.M.; Horton, E.D.; Horton, E.S. Eﬀect of exercise training on
glucose homeostasis in normal and insulin-deﬁcient diabetic rats. J. Appl. Physiol. (1985) 1988, 65, 844–851.
[CrossRef] [PubMed]
72.
Beaudry, J.L.; Dunford, E.C.; Leclair, E.; Mandel, E.R.; Peckett, A.J.; Haas, T.L.; Riddell, M.C. Voluntary
exercise improves metabolic proﬁle in high-fat fed glucocorticoid-treated rats. J. Appl. Physiol. (1985) 2015,
118, 1331–1343. [CrossRef] [PubMed]
73.
Bongbele, J.; Gutierrez, A.; Cardin, S.; Lavoie, J.M. Eﬀect of physical training on insulin response to
intravenous glucose in male peripubertal rats. J. Appl. Physiol. (1985) 1992, 73, 1227–1231. [CrossRef]
[PubMed]
Nutrients 2020, 12, 2721
20 of 22
74.
Caudwell, P.; Gibbons, C.; Finlayson, G.; Naslund, E.; Blundell, J. Exercise and weight loss: No sex diﬀerences
in body weight response to exercise. Exerc. Sport Sci. Rev. 2014, 42, 92–101. [CrossRef]
75.
Donnelly, J.E.; Smith, B.; Jacobsen, D.J.; Kirk, E.; Dubose, K.; Hyder, M.; Bailey, B.; Washburn, R. The role of
exercise for weight loss and maintenance. Best Pract. Res. Clin. Gastroenterol. 2004, 18, 1009–1029. [CrossRef]
76.
Hill, J.O.; Thiel, J.; Heller, P.A.; Markon, C.; Fletcher, G.; DiGirolamo, M. Diﬀerences in eﬀects of aerobic
exercise training on blood lipids in men and women. Am. J. Cardiol. 1989, 63, 254–256. [CrossRef]
77.
Buettner, R.; Scholmerich, J.; Bollheimer, L.C. High-fat diets: Modeling the metabolic disorders of human
obesity in rodents. Obesity (Silver Spring) 2007, 15, 798–808. [CrossRef]
78.
Gawel, K.; Gibula, E.; Marszalek-Grabska, M.; Filarowska, J.; Kotlinska, J.H. Assessment of spatial learning
and memory in the Barnes maze task in rodents-methodological consideration. Naunyn. Schmiedebergs
Arch. Pharmacol. 2019, 392, 1–18. [CrossRef]
79.
National Research Council. Guide for the Care and Use of Laboratory Animals, 8th ed.; National Research
Council: Washington, DC, USA, 2011. [CrossRef]
80.
Yang, T.Y.; Liang, N.C. Ovarian hormones mediate running-induced changes in high fat diet choice patterns
in female rats. Horm. Behav. 2018, 100, 81–93. [CrossRef]
81.
Bowe, J.E.; Franklin, Z.J.; Hauge-Evans, A.C.; King, A.J.; Persaud, S.J.; Jones, P.M. Metabolic phenotyping
guidelines: Assessing glucose homeostasis in rodent models. J. Endocrinol. 2014, 222, G13–G25. [CrossRef]
82.
Ayala, J.E.;
Bracy, D.P.;
McGuinness, O.P.;
Wasserman, D.H. Considerations in the design of
hyperinsulinemic-euglycemic clamps in the conscious mouse. Diabetes 2006, 55, 390–397. [CrossRef]
[PubMed]
83.
Tran, T.T.; Gupta, N.; Goh, T.; Naigamwalla, D.; Chia, M.C.; Koohestani, N.; Mehrotra, S.; McKeown-Eyssen, G.;
Giacca, A.; Bruce, W.R. Direct measure of insulin sensitivity with the hyperinsulinemic-euglycemic clamp
and surrogate measures of insulin sensitivity with the oral glucose tolerance test: Correlations with aberrant
crypt foci promotion in rats. Cancer Epidemiol. Biomarkers Prev. 2003, 12, 47–56. [PubMed]
84.
Matthews, D.R.; Hosker, J.P.; Rudenski, A.S.; Naylor, B.A.; Treacher, D.F.; Turner, R.C. Homeostasis model
assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations
in man. Diabetologia 1985, 28, 412–419. [CrossRef] [PubMed]
85.
Gutt, M.; Davis, C.L.; Spitzer, S.B.; Llabre, M.M.; Kumar, M.; Czarnecki, E.M.; Schneiderman, N.; Skyler, J.S.;
Marks, J.B. Validation of the insulin sensitivity index (ISI(0,120)): Comparison with other measures.
Diabetes Res. Clin. Pract. 2000, 47, 177–184. [CrossRef]
86.
O’Leary, T.P.; Savoie, V.; Brown, R.E. Learning, memory and search strategies of inbred mouse strains with
diﬀerent visual abilities in the Barnes maze. Behav. Brain Res. 2011, 216, 531–542. [CrossRef]
87.
Rosenfeld, C.S.; Ferguson, S.A. Barnes maze testing strategies with small and large rodent models. J. Vis. Exp.
2014, e51194. [CrossRef]
88.
Brooks, G.A. Importance of the ’crossover’ concept in exercise metabolism. Clin. Exp. Pharmacol. Physiol.
1997, 24, 889–895. [CrossRef]
89.
Horowitz, J.F. Fatty acid mobilization from adipose tissue during exercise. Trends Endocrinol. Metab. 2003, 14,
386–392. [CrossRef]
90.
Ruby, B.C.; Robergs, R.A. Gender diﬀerences in substrate utilisation during exercise. Sports Med. 1994, 17,
393–410. [CrossRef]
91.
Horton, T.J.; Pagliassotti, M.J.; Hobbs, K.; Hill, J.O. Fuel metabolism in men and women during and after
long-duration exercise. J. Appl. Physiol. (1985) 1998, 85, 1823–1832. [CrossRef]
92.
Brooks, G.A.; Mercier, J. Balance of carbohydrate and lipid utilization during exercise: The “crossover”
concept. J. Appl. Physiol. (1985) 1994, 76, 2253–2261. [CrossRef] [PubMed]
93.
Liang, N.C.; Bello, N.T.; Moran, T.H. Wheel running reduces high-fat diet intake, preference and mu-opioid
agonist stimulated intake. Behav. Brain Res. 2015, 284, 1–10. [CrossRef] [PubMed]
94.
Moody, L.; Liang, J.; Choi, P.P.; Moran, T.H.; Liang, N.C. Wheel running decreases palatable diet preference
in Sprague-Dawley rats. Physiol. Behav. 2015, 150, 53–63. [CrossRef] [PubMed]
95.
Yang, T.Y.; Gardner, J.C.; Gao, Z.; Pan, Y.X.; Liang, N.C. Role of glucocorticoid signaling in exercise-associated
changes in high-fat diet preference in rats. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2020, 318, R515–R528.
[CrossRef]
96.
Ellis, G.S.; Lanza-Jacoby, S.; Gow, A.; Kendrick, Z.V. Eﬀects of estradiol on lipoprotein lipase activity and
lipid availability in exercised male rats. J. Appl. Physiol (1985) 1994, 77, 209–215. [CrossRef]
Nutrients 2020, 12, 2721
21 of 22
97.
Roepstorﬀ, C.; Steﬀensen, C.H.; Madsen, M.; Stallknecht, B.; Kanstrup, I.L.; Richter, E.A.; Kiens, B. Gender
diﬀerences in substrate utilization during submaximal exercise in endurance-trained subjects. Am. J. Physiol.
Endocrinol. Metab. 2002, 282, E435–E447. [CrossRef]
98.
Carter, S.L.; Rennie, C.; Tarnopolsky, M.A. Substrate utilization during endurance exercise in men and
women after endurance training. Am. J. Physiol. Endocrinol. Metab. 2001, 280, E898–E907. [CrossRef]
99.
Romijn, J.A.; Coyle, E.F.; Sidossis, L.S.; Gastaldelli, A.; Horowitz, J.F.; Endert, E.; Wolfe, R.R. Regulation of
endogenous fat and carbohydrate metabolism in relation to exercise intensity and duration. Am. J. Physiol.
1993, 265, E380–E391. [CrossRef]
100. Hawley, J.A.; Hopkins, W.G. Aerobic glycolytic and aerobic lipolytic power systems. A new paradigm with
implications for endurance and ultraendurance events. Sports Med. 1995, 19, 240–250. [CrossRef]
101. Hudson, J.I.; Hiripi, E.; Pope, H.G., Jr.; Kessler, R.C. The prevalence and correlates of eating disorders in the
National Comorbidity Survey Replication. Biol. Psychiatry 2007, 61, 348–358. [CrossRef]
102. Klump, K.L.; Racine, S.; Hildebrandt, B.; Sisk, C.L. Sex diﬀerences in binge eating patterns in male and
female adult rats. Int. J. Eat. Disord. 2013, 46, 729–736. [CrossRef] [PubMed]
103. Tapia, M.A.; Lee, J.R.; Weise, V.N.; Tamasi, A.M.; Will, M.J. Sex diﬀerences in hedonic and homeostatic
aspects of palatable food motivation. Behav. Brain Res. 2019, 359, 396–400. [CrossRef] [PubMed]
104. Buczek, L.; Migliaccio, J.; Petrovich, G.D. Hedonic Eating: Sex Diﬀerences and Characterization of Orexin
Activation and Signaling. Neuroscience 2020, 436, 34–45. [CrossRef] [PubMed]
105. Ng, M.; Fleming, T.; Robinson, M.; Thomson, B.; Graetz, N.; Margono, C.; Mullany, E.C.; Biryukov, S.;
Abbafati, C.; Abera, S.F.; et al. Global, regional, and national prevalence of overweight and obesity in children
and adults during 1980-2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet
2014, 384, 766–781. [CrossRef]
106. Lynch, W.J. Sex diﬀerences in vulnerability to drug self-administration. Exp. Clin. Psychopharmacol. 2006,
14, 34–41. [CrossRef]
107. Carroll, M.E.; Anker, J.J. Sex diﬀerences and ovarian hormones in animal models of drug dependence.
Horm. Behav. 2010, 58, 44–56. [CrossRef]
108. Day, C.J.; McHale, S.; Francis, J. Individual diﬀerences and preference for dietary fat using the Fat Preference
Questionnaire((c)) in a UK sample. Appetite 2012, 58, 679–686. [CrossRef]
109. Belke, T.W.; Wagner, J.P. The reinforcing property and the rewarding aftereﬀect of wheel running in rats:
A combination of two paradigms. Behav. Process. 2005, 68, 165–172. [CrossRef]
110. Spierling, S.R.; Kreisler, A.D.; Williams, C.A.; Fang, S.Y.; Pucci, S.N.; Kines, K.T.; Zorrilla, E.P. Intermittent,
extended access to preferred food leads to escalated food reinforcement and cyclic whole-body metabolism
in rats: Sex diﬀerences and individual vulnerability. Physiol. Behav. 2018, 192, 3–16. [CrossRef]
111. Peterson, A.B.; Hivick, D.P.; Lynch, W.J. Dose-dependent eﬀectiveness of wheel running to attenuate
cocaine-seeking: Impact of sex and estrous cycle in rats. Psychopharmacology (Berl) 2014, 231, 2661–2670.
[CrossRef]
112. Zhou, Y.; Zhao, M.; Zhou, C.; Li, R. Sex diﬀerences in drug addiction and response to exercise intervention:
From human to animal studies. Front. Neuroendocrinol. 2016, 40, 24–41. [CrossRef]
113. Pitts, G.C. Body composition in the rat: Interactions of exercise, age, sex, and diet. Am. J. Physiol. 1984, 246,
R495–R501. [CrossRef] [PubMed]
114. Foright, R.M.; Johnson, G.C.; Kahn, D.; Charleston, C.A.; Presby, D.M.; Bouchet, C.A.; Wellberg, E.A.;
Sherk, V.D.; Jackman, M.R.; Greenwood, B.N.; et al. Compensatory eating behaviors in male and female rats
in response to exercise training. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2020. [CrossRef] [PubMed]
115. Latour, M.G.; Shinoda, M.; Lavoie, J.M. Metabolic eﬀects of physical training in ovariectomized and
hyperestrogenic rats. J. Appl. Physiol. (1985) 2001, 90, 235–241. [CrossRef] [PubMed]
116. Lamontagne, J.; Jalbert-Arsenault, E.; Pepin, E.; Peyot, M.L.; Ruderman, N.B.; Nolan, C.J.; Joly, E.;
Madiraju, S.R.; Poitout, V.; Prentki, M. Pioglitazone acutely reduces energy metabolism and insulin
secretion in rats. Diabetes 2013, 62, 2122–2129. [CrossRef] [PubMed]
117. Vallerand, A.L.; Lupien, J.; Deshaies, Y.; Bukowiecki, L.J. Intensive exercise training does not improve
intravenous glucose tolerance in severely diabetic rats. Horm. Metab. Res. 1986, 18, 79–81. [CrossRef]
118. Goodyear, L.J.; Kahn, B.B. Exercise, glucose transport, and insulin sensitivity. Annu. Rev. Med. 1998, 49,
235–261. [CrossRef]
Nutrients 2020, 12, 2721
22 of 22
119. Goodyear, L.J.; Hirshman, M.F.; Horton, E.D.; Knutson, S.M.; Wardzala, L.J.; Horton, E.S. Exercise training
normalizes glucose metabolism in a rat model of impaired glucose tolerance. Metabolism 1991, 40, 455–464.
[CrossRef]
120. LaPier, T.L.; Swislocki, A.L.; Clark, R.J.; Rodnick, K.J. Voluntary running improves glucose tolerance and
insulin resistance in female spontaneously hypertensive rats. Am. J. Hypertens 2001, 14, 708–715. [CrossRef]
121. Ascaso, J.F.; Pardo, S.; Real, J.T.; Lorente, R.I.; Priego, A.; Carmena, R. Diagnosing insulin resistance by
simple quantitative methods in subjects with normal glucose metabolism. Diabetes Care 2003, 26, 3320–3325.
[CrossRef]
122. Swift, D.L.; McGee, J.E.; Earnest, C.P.; Carlisle, E.; Nygard, M.; Johannsen, N.M. The Eﬀects of Exercise and
Physical Activity on Weight Loss and Maintenance. Prog. Cardiovasc. Dis. 2018, 61, 206–213. [CrossRef]
[PubMed]
123. Villanueva Espino, L.A.; Silva Gomez, A.B.; Bravo Duran, D.A. Cognitive training increases dendritic
arborization in the dorsal hippocampal CA1 and CA3 neurons of female and male Long-Evans rats. Synapse
2020, 74, e22140. [CrossRef] [PubMed]
124. Betancourt, E.; Wachtel, J.; Michaelos, M.; Haggerty, M.; Conforti, J.; Kritzer, M.F. The impact of biological
sex and sex hormones on cognition in a rat model of early, pre-motor Parkinson’s disease. Neuroscience 2017,
345, 297–314. [CrossRef] [PubMed]
125. Beatty, W.W. Gonadal hormones and sex diﬀerences in nonreproductive behaviors in rodents: Organizational
and activational inﬂuences. Horm. Behav. 1979, 12, 112–163. [CrossRef]
126. Tropp, J.; Markus, E.J. Sex diﬀerences in the dynamics of cue utilization and exploratory behavior.
Behav. Brain Res. 2001, 119, 143–154. [CrossRef]
127. Jonasson, Z. Meta-analysis of sex diﬀerences in rodent models of learning and memory: A review of
behavioral and biological data. Neurosci. BioBehav. Rev. 2005, 28, 811–825. [CrossRef]
128. Locklear, M.N.; Kritzer, M.F. Assessment of the eﬀects of sex and sex hormones on spatial cognition in adult
rats using the Barnes maze. Horm. Behav. 2014, 66, 298–308. [CrossRef]
129. Bucci, D.J.; Chiba, A.A.; Gallagher, M. Spatial learning in male and female Long-Evans rats. Behav. Neurosci.
1995, 109, 180–183. [CrossRef]
130. Koss, W.A.; Frick, K.M. Sex diﬀerences in hippocampal function. J. Neurosci. Res. 2017, 95, 539–562.
[CrossRef]
131. Barrett, G.L.; Bennie, A.; Trieu, J.; Ping, S.; Tsafoulis, C. The chronology of age-related spatial learning
impairment in two rat strains, as tested by the Barnes maze. Behav. Neurosci. 2009, 123, 533–538. [CrossRef]
132. Sadeghian, A.; Fathollahi, Y.; Javan, M.; Shojaei, A.; Kosarmadar, N.; Rezaei, M.; Mirnajaﬁ-Zadeh, J. Spatial
Learning and Memory in Barnes Maze Test and Synaptic Potentiation in Schaﬀer Collateral-CA1 Synapses of
Dorsal Hippocampus in Freely Moving Rts. Basic Clin. Neurosci. 2019, 10, 461–468. [CrossRef] [PubMed]
133. Lin, K.A.; Choudhury, K.R.; Rathakrishnan, B.G.; Marks, D.M.; Petrella, J.R.; Doraiswamy, P.M.; Alzheimer’s
Disease Neuroimaging, I. Marked gender diﬀerences in progression of mild cognitive impairment over
8 years. Alzheimers Dement. (NY) 2015, 1, 103–110. [CrossRef] [PubMed]
134. Seshadri, S.; Wolf, P.A.; Beiser, A.; Au, R.; McNulty, K.; White, R.; D’Agostino, R.B. Lifetime risk of dementia
and Alzheimer’s disease. The impact of mortality on risk estimates in the Framingham Study. Neurology
1997, 49, 1498–1504. [CrossRef] [PubMed]
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Sex-Dependent Wheel Running Effects on High Fat Diet Preference, Metabolic Outcomes, and Performance on the Barnes Maze in Rats.
Yang, Tiffany Y,Gao, Zijun,Liang, Nu-Chu