Effects of Different Dietary Protocols on General Activity and Frailty of Male Wistar Rats During Aging

Smilja T Todorovic; Kosara R Smiljanic; Sabera D Ruzdijic; Aleksandra N Mladenovic Djordjevic; Selma D Kanazir

doi:10.1093/gerona/gly015

. 2018 Feb 3;73(8):1036–1044. doi: 10.1093/gerona/gly015

Effects of Different Dietary Protocols on General Activity and Frailty of Male Wistar Rats During Aging

Smilja T Todorovic ¹, Kosara R Smiljanic ¹, Sabera D Ruzdijic ¹, Aleksandra N Mladenovic Djordjevic ^#,^✉, Selma D Kanazir ^#

PMCID: PMC6037071 PMID: 29415252

Abstract

Dietary restriction (DR) is an important experimental paradigm for lifespan and healthspan extension, but its specific contribution regarding the type, onset, and duration are still debatable. This study was designed to examine the impact of different dietary protocols by assessing the behavioral changes during aging. We exposed male Wistar rats of various age to ad libitum (AL) or DR (60 per cent of AL daily intake) feeding regimens with different onsets. The impact of DR on locomotor activity, memory, and learning was examined in 12-, 18-, and 24-month-old treated animals and controls using open field and Y-maze tests. We have also evaluated the effects of different DR’s through the quantification of animal frailty, using behavioral data to create the frailty score. Our results indicated that DR improves general animal activity and spatial memory and decreases frailty with the effect being highly dependent on DR duration and onset. Notably, life-long restriction started at young age had the most profound effect. In contrast, shorter duration and later onset of restricted diet had significantly lower or no impact on animal’s behavior and frailty. This study signifies the importance of DR starting point and duration as critical determinants of DR effects on healthspan.

Keywords: Antiaging, Dietary restriction, Frailty, Animal model, Behavior

Humans are facing an unprecedented increase in their lifespan mainly in the last 70 years; still, motor and cognitive skills are jeopardized during aging (1). The current antiaging strategies are switching the focus from suppressing aging to promote successful aging and healthspan, in order to maximize the period of life time spent free of the costly and harmful conditions that usually accompany old age (2). Optimal aging would then depend on factors that promote longer life and factors that diminish diseases and morbidity (3). This is where the concept of frailty comes in the spotlight, as an important tool in predicting negative health outcomes during aging. Frailty is referred as a “multidimensional syndrome in aging” and its origin is based on the combination of genetic, biological, physical, psychological, social, and environmental factors and can be evaluated using frailty index (4, 5) or frailty score (FS) (6). Frail individuals are at higher risk of accelerated physical and cognitive decline, disability, and inevitably death. However, one of the major characteristics of frailty is that it is considered to be a dynamic and a potentially reversible condition (7).

There are many promising treatments for prolonging both the lifespan and the healthspan and therefore strong candidates for reversing frailty. Dietary restriction (DR) is unquestionably one of the most investigated and most widely used experimental interventions in aging research. Specifically, DR holds the great potential to induce life extension, delay aging, and attenuate a number of age-associated disorders (8–11). It is considered that DR represents the most promising avenue for treating age-related impairments in learning and memory in a wide variety of species (3, 8, 9). Nevertheless, there is some evidence that challenges the beneficial DR effect in these processes. Specifically, few authors reported negative or even detrimental effect of DR if implemented in early life (12–14) or on the contrary, in aged subjects (15, 16). Moreover, the positive impact of DR on life-span, cancer incidence, and age-related immune decline in mice was shown to vary dependently on the age when DR is implemented (17, 18). These results pointed to a certain “time window” during the lifetime, when DR can be applied in order to elicit the favorable response.

In previous studies, we have already reported the positive effects of long-term DR implemented at adult age (19, 20). In this study, we have focused on behavioral effects of different DR paradigms. We aimed to examine how various onsets and durations of DR influenced the animal’s motor and cognitive abilities during aging. We performed behavioral analysis of 12-, 18-, and 24-month-old male Wistar rats exposed to DR [60 per cent of ad libitum (AL) daily intake] that varied in length and onset. Using Open field (OF) test, we assessed general locomotor activity, novel environment exploration, and habituation of rats, whereas Y-maze testing was used to measure cognitive deficits in spatial memory. The obtained behavioral parameters were then exploited in order to design an extended 11-item FS to further validate the effects of various onsets and durations of restricted feeding regimen.

Herein, we demonstrated that significant difference in the response to DR could arise in animals depending on duration of the restricted diet and the time when it is implemented.

Methods

Animals and Treatment

Male Wistar rats were used in this study (n = 167). All animal procedures complied with the EEC Directive (2–59/12) on the protection of animals used for experimental and other scientific purposes and were approved by the Ethical Committee for the Use of Laboratory Animals of the Institute for Biological Research “Sinisa Stankovic,” University of Belgrade. Animals were maintained in a 12 hour light/dark cycle and divided into two main groups, AL and DR. DR groups were maintained on 60 per cent of the mean daily intake of a standard laboratory diet and divided into three subgroups, based on different dietary regimens (Supplementary Figure 1). DR1 started at the age of 6 months and rats were maintained on this dietary regimen until they were 12, 18, and 24 months old. DR2 was implemented at 12 and 18 months of age and lasted for 6 months. DR3 type of diet started at 15 and 21 months of age and lasted for 3 months. Given the long time interval between DR1, and DR2 and DR3 experiments (8 years), we used two cohorts of AL animals as controls at different time points. Specifically, first AL cohort of different ages (AL1: 12-, 18-, and 24-month-old groups of animals) served as control groups for DR1 treatment, whereas the second AL cohort (AL2: 18- and 24-month-old animals) served as controls for DR2 and DR3 treatments. Behavioral testing was performed in all experimental groups at 12, 18, and 24 months of age. Number of animals per group varied between n = 8–22.

Open Field Test

Motor activity of rats was recorded in Opto-Varimex cages (Columbus Instruments, OH). Data were analyzed using Auto-Track software (Columbus Instruments). Rats were allowed to freely explore the test arena for 40 minutes during the five consecutive days. Locomotor (distance traveled) and vertical activity (ie rearing–standing on rear limbs; both free-standing and against the walls) was observed and habituation was determined. Habituation was characterized by a decrease in activity upon repeated exposure to the stimulus (activity cage). We measured intersession (between sessions) habituation by detecting either total (40 minutes) or first 5 minutes of locomotor and vertical activity for 5 consecutive days. Intrasession (within session) habitation was determined by analyzing locomotor and vertical activity during first and last 5 minutes within the same day, for 5 days.

Y-Maze Test

The Y-maze consisted of three grey plastic arms (50 × 25 × 16 cm) that are at 120° from each other. Animals were allowed to freely explore the two arms during a 10 minute session, without reinforcements, such as food and water, while the third arm (novel arm) was blocked off during this first trial. After an intertrial interval (IT) of 1 hour, rats were allowed to freely explore all three arms of the maze for the next 10 minutes (second trial). Animals were monitored with a video camera mounted above the experimental arena, connected to a computer to record a video file. Entries into arms (four paws had to be inside the arm for a valid entry) and time spent in a third arm were monitored and spontaneous alterations (SAB) were calculated as described previously (21).

Frailty Score

We calculated FS based on the “Valencia score” developed by Gomez-Cabrera and co-workers (6). They used score developed for measuring frailty in humans by Linda Fried and co-workers (22) and further adjusted it to experimental animals. We have adapted it to create a unique physical-cognitive FS, by combining the measurements of both physical strength (OF parameters and body weight) and cognitive status (OF and Y-maze parameters). We included five parameters from OF measured for the first 10 minutes (total distance traveled, DT; total duration of movement-ambulatory time, AT; percent of total time spent in moving, T/AT; average velocity of movement, DT/AT; rearing frequency, ie vertical activity, V1B), five parameters from Y maze measured for 10 minutes (total number of entries, number of third-arm entries, percentage of third-arm entries, time spent in third arm and SAB), and weight loss as the 11th parameter. Animals’ body weights were recorded through their lifespan, and the body weights at the end of the experiment were taken for frailty measurements.

In order to compare the FS among experimental animals, the following “frailty groups” were formed as follows: (i) for the effect of aging, we combined all animals from both AL cohorts and then calculated how frail are 18- and 24-month-old AL animals in comparison to 12-month-old AL rats; (ii) for the effect of different dietary restricted regimens, we paired particular DR group with the appropriate AL group (ie the AL fed group of appropriate age and cohort): 12 m AL1 and 12 m DR1, 18 m AL1 and 18 m DR1, 24 m AL1 and 24 m DR1, 18 m AL2 together with 18 m DR2 and 18 m DR3, and 24 m AL2 with 24 m DR2 and 24 mDR3.

Following “Valencia score” method (6) for calculating FS, using Graph Pad software for statistics, we established 20 per cent as a cut-off point for all parameters used. The same principle was applied for body weight, as animals on DR initially lose approximately up to 20 per cent of their weight in order to adjust to decreased amount of food. Animals that ranked below 20th percentile fulfilled the frailty criteria and were considered positive for that criterion and for that age (ie animal “failed” the test). The calculated values for 20 per cent cutoff for each parameter during aging and under various DR paradigms are given in Supplementary Tables 1 and 2, respectively. Then the FS for each “frailty group” was calculated as follows: total number of tests failed by the animals at each experimental group (A) divided by the total number of tests performed by the same group of animals (B) and expressed as percentage (6).

Statistical Analysis

Statistical analysis of intersession habituation (locomotor and vertical activity) task was performed using repeated measures one-way ANOVA with age and days as factors, followed by Tukey’s multiple-comparison post hoc tests. For intrasession habituation, paired t-test was performed. For comparisons between age-matched AL and DR groups OF activity, nonparametric two-tailed Mann–Whitney test was used. Statistical analysis for Y-maze test results was performed by using two-way ANOVA, followed by Tukey’s multiple-comparison post hoc tests for the effects of aging and different feeding regimens. All data were expressed as means ± SEM. Analysis of FS was performed by Pearson’s chi-squared test, whereas data for each of the parameters were performed using G-test with Williams correction for small number of samples. Statistical analysis was performed by using GraphPad Software (San Diego, CA). p-Value differences were considered to be statistically significant when p < .05.

Results

The Effect of Various DR Regimens on OF Activity of Rats During Aging

We used OF activity monitoring as a comprehensive assessment to track locomotor and exploratory activity as well as long-term memory of animals (Figures 1 and 2). All examined AL groups showed intersession habituation over time. There were no major variations in distance traveled or vertical activity between different groups (Figure 1A and B; Figure 2A–D). On the other hand, DR substantially influenced animal’s activity when compared with control animals, with the effect highly dependent on duration and onset of dietary regimen.

Figure 1. — Locomotor (A) and vertical activities (B) of 12-, 18-, and 24-month-old ad libitum (AL) and dietary restricted (DR1) group of animals. (A) and (B) represent intersession habituation. Results are expressed as mean ± SEM for 40 minute registration period during 5 consecutive days.*p < .05 versus the first day of the same group, #p < .05 versus age-matched control of the same day. (C) represents inter- and intrasession habituation for vertical activity of 18-month-old DR1. Results are expressed as mean ± SEM for the first and last 5 minutes of registration. *p < .05 versus the first 5 minutes of the first day, #p < .05 versus the first 5 minutes of the same day.

Figure 2. — Locomotor (A, C) and vertical activities (B, D) of 18- and 24-month-old ad libitum (AL) and dietary restricted (DR2 and DR3) group of animals. (A–D) represent intersession habituation. Results are expressed as mean ± SEM for 40 minute registration period during 5 consecutive days.*p < .05 versus the first day of the same group, #p < .05 versus age-matched control of the same day. (E) represents inter- and intrasession habituation for vertical activity of 24-month-old DR3 rats. Results are expressed as mean ± SEM for the first and last 5 minutes of registration. *p < .05 versus the first 5 minutes of the first day, #p < .05 versus the first 5 minutes of the same day. The same age-related AL groups were used as controls for DR2 and DR3 type of food regimen.

All experimental groups habituate over time (Figures 1 and 2). The significant effect of time on locomotor activity [DR1: F(4,80) = 11.34, p < .0001] and exploratory behavior [DR1: F(4,84) = 34.62, p < .0001] was observed in animals exposed to the longest dietary regimen (DR1), as well as in their AL-matched controls [AL: F(4,76) = 20.6, p < .0001; and AL: F(4,76) = 35.21, p < .0001; Figure 1A and B]. The exception was noticed in vertical activity of 18-month-old DR1 group that failed to habituate during the testing period. However, analysis of the first and last 5 minutes of each session for 5 days revealed both the intersession and intrasession (p < .05) habituation for this group (Figure 1C). Comparisons of motor activity between DR1 group and age-matched controls fed AL referred that long-term DR significantly affected locomotor and vertical activity. Specifically, locomotor activity was higher in 18-month-old DR1 group, whereas vertical activity was higher in 18- and 24-month-old DR1 group compared with age-matched controls (p < .05; Figure 1A and B).

OF activity analysis of animals exposed to DR2 regimen and their AL-matched controls revealed normal habitation during the testing period (Figure 2A and B). A significant impact of time [AL: F(4,180) = 28.45, p < .0001; DR2: F(4,128) = 37.90, p < .0001] on total distance traveled was detected in all examined groups (Figure 2A). All animals also displayed expected habituation of vertical activity [AL: F(4,180) = 29.21, p < 0.0001: DR2: F(4,148) = 10.25, p < .0001] during 5 consecutive days (Figure 2B). DR2 treatment did not elicit any significant changes in OF behavior except in locomotor activity of 24-month-old animals. Following DR2 type of feeding regimen, these animals traveled significantly longer distance on the first testing day compared with AL counterparts (p < .05, Figure 2A).

Next, analysis of animals kept under the shortest dietary regimen (DR3) revealed a significant effect of time on locomotor activity in both age groups (F_(4,64) = 9.293, p < .0001; Figure 2C). Intersession habituation of vertical activity was detected in 18-month-old DR3 animals [F(1,16) = 9.181, *p < .008; Figure 2D]. In the oldest group of DR3 animals, intersession habituation was absent, either by analyzing the entire session (Figure 2D) or the first 5 minutes of each session (Figure 2E, light grey bars). However, the intrasession habituation was detected by analyzing the first and the last 5 minutes of each session (p < .05; Figure 2E, light grey and black bars, respectively). Both 18- and 24-month-old DR3 animals traveled significantly lesser distance than their AL matched counterparts (p < .05; Figure 2C). On the other hand, the higher vertical activity observed in 24-month-old DR3 animals compared with their age-matched AL controls (p < .05; Figure 2D) could be due to inability of 24-month-old DR3 rats to habituate over time.

The Effect of Various DR Regimens on Spatial Memory of Rats During Aging

Using Y-maze test, we analyzed spontaneous alternation performance (SAB), total number of entries, number of novel (3rd) arm entries, and time spent in a novel arm during aging and under the influence of different dietary regimens (Figure 3A–D).

All AL animals from both cohorts were organized in the same group on the graphs according to their age, as there were no differences between cohorts in Y-maze performances. Two-way ANOVA analysis of variance revealed significant effect of age on total number of arm entries [F(2,67) = 10.61, p < .001], number of third-arm entries [F(2,68) = 3.500, p = .0375], and time spent in third arm [F(1,53) = 4.375, p = .0413] but not in SAB values (Figure 3A–D, white bars). Tukey’s post hoc test revealed a significant decrease in total number of arm entries, number of third-arm entries, and time spent in third arm in 18-month-old AL group compared with 12-month-old (p = .0286, p = .0008, p = .0351, respectively).

Analysis of different dietary regimens revealed no differences in SAB values between experimental groups (Figure 3A). However, two-way ANOVA revealed significant effect of dietary regimens on total number of entries [F(3,56) = 8.515, p < .001], number of third-arm entries [F(3,54) = 15.74, p < .001], and time spent in third arm [F(3,53) = 19.48, p < .001; Figure 3B–D]. Tukey’s post hoc test showed that under the influence of long-term dietary restriction (DR1), total number of entries (12-month-old: p = .0166; 18-month-old: p = .0015; 24-month-old: p = .048) and number of novel arm visits (12-month-old: p = 0.0119, 18-month-old: p = 0.0001, 24-month-old: p = 0.042) were significantly increased in 12-, 18-, and 24-month-old animals compared with age-matched AL controls, suggesting higher inquisitive behavior of DR1 animals (Figure 3B and C light grey bars).

Both DR1 and DR2 had a significant and continual positive impact on novel arm exploratory time in all age groups compared with age-matched controls (12-month-old: DR1 p = .043; 18-month-old DR1 and DR2: p ≤ .0001 and p ≤ .0001; 24-month-old DR1 and DR2: p = 0.0176, p = 0.0094, respectively; Figure 3D). The shortest dietary restriction regimen (DR3) increased number of third-arm entries and time spent in third arm only in 18-month-old animals (p = .00251, p ≤ .0001, respectively; Figure 3C and D).

The Effect of Various DR Regimens on Rat’s FS During Aging

An 11-item FS was calculated in order to better assess the impact of various DRs on motor and cognitive skills during aging. First, we analyzed the influence of aging and feeding regimens on each parameter used in this study (Supplementary Figures 2–7), and then, we calculated FS (as explained in Methods). At the beginning of the experiment, all animals of the same age had the similar weight. Small, but not significant influence of age was detected on the body weight (Supplementary Figure 2F). On the other hand, aging led to a significant increase of the percentage of animals that fulfilled frailty criterion for all other parameters examined except the velocity (Supplementary Figures 2 and 3).

Beneficial effect of DR1 in all aging groups was detected, as DR1-treated animals were significantly less positive for several frailty parameters than controls (Supplementary Figures 4 and 5). DR1 rats expressed better results in total distance traveled, V1B, AT, percent of time spent in moving (Supplementary Figure 4A, B, D, and E) and time spent in a new environment (Supplementary Figure 5D). Higher percent of success was also observed for those animals in total number of entries and number of third-arm entries (Supplementary Figure 5B and C). Positive outcome of DR2 and DR3 regimens was observed only in 18-month-old animals and only in few parameters analyzed (Supplementary Figure 7C–E). Moreover, several parameters like ambulatory time, percentage of time spent moving, and total number of entries indicated a significant negative effect of DR3 regimen in the oldest group of animals (Supplementary Figures 6D, E, and 7B).

All of these examined frailty parameters pointed to a significant effect of age and dietary regimens on frailty (Figure 4). We noticed higher FS in 18- and 24- compared with 12-month-old AL group (p = .0002, p < .0001, respectively; Figure 4A), that is, the percentage of frail rats in these groups was significantly higher than in 12-month-old group. However, FS was under a substantial influence of dietary regimens. The number of AL1 and DR1 animals that ranked in the lowest 20 per cent for each frailty criteria, the number of tests performed, and tests failed are presented in Table 1. The total number of AL rats that failed the test was much higher when compared with dietary-restricted animals. This resulted in the significantly lower number of frail rats exposed to dietary restriction (DR1) in comparison to the groups that were fed AL during aging.

Table 1.

Frailty Score Calculation in AL1 and DR1 Animals

		12 months		18 months		24 months
		AL1	DR1	AL1	DR1	AL1	DR1
Number of animals in the lowest 20%	Distance traveled	2	1	3	0	2	0
	Vertical activity	2	1	3	0	3	0
	Velocity	2	1	1	2	1	2
	Ambulatory time	2	1	3	0	2	1
	% of total time spent in moving	2	1	3	0	2	1
	Weight	1	1	2	3	5	4
	Spontaneous alterations	1	1	1	2	2	1
	Total number of entries	3	0	2	0	3	0
	Number of 3rd arm entries	3	1	2	0	3	0
	Time spent in 3rd arm	3	0	2	0	3	0
	% of 3rd arm entries	2	1	1	1	2	1
Total number of tests failed (A)		23	9	23	8	28	10
Total number of tests performed (B)		65	77	53	66	57	66
(A/B)		0.35	0.12	0.43	0.12	0.49	0.15
Frailty score (A/B × 100)		35	12	43	12	49	15

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Notes: Number of animals in the lowest 20% for each parameter used to calculate frailty score; the frailty score for each experimental group, calculated as follows: total number of tests failed by the animals at each experimental group divided by the total number of tests performed by those animals, expressed in percentage.

AL = Ad libitum; DR = Dietary restriction.

When the same parameters were analyzed for the animals exposed to DR2 and DR3 regimens (Table 2), the significantly lower number of frail animals were detected in 18-month-old DR2 and DR3 groups in comparison to age-matched AL counterparts.

Table 2.

Frailty Score Calculation in AL2, DR2, and DR3 Animals

		18 months			24 months
		AL2	DR2	DR3	AL2	DR2	DR3
Number of animals in the lowest 20%	Distance traveled	1	5	1	2	1	2
	Vertical activity	0	5	0	1	3	2
	Velocity	3	1	2	3	2	1
	Ambulatory time	2	3	1	2	1	3
	% of total time spent in moving	2	4	1	2	1	3
	Weight	2	2	2	1	3	1
	Spontaneous alterations	1	2	4	5	1	1
	Total number of entries	3	3	1	2	0	4
	Number of 3rd arm entries	5	4	1	3	0	4
	Time spent in 3rd arm	6	1	1	2	1	3
	% of 3rd arm entries	5	2	1	2	2	1
Total number of tests failed (A)		30	32	15	25	15	25
Total number of tests performed (B)		79	161	111	122	95	52
(A/B)		0.38	0.20	0.14	0.20	0.16	0.48
Frailty score (A/Bx100)		38	20	14	20	16	48

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AL = Ad libitum; DR = Dietary restriction.

Overall, DR1 type of diet decreased FS in 12-, 18-, and 24-month-old animals compared with age-matched controls (p = .01, p = .004, p = .005, respectively; Figure 4B), whereas DR2 and DR3 regimens lowered FS only in 18-month-old animals (p = .02, p = .002, respectively; Figure 4C). Interestingly, DR3 regimen increased FS in 24-month-old animals and doubled a percentage of frail animals in the oldest group, indicating negative effect of this type of regimen (Figure 4C).

Discussion

DR is widely used and broadly accepted as an experimental paradigm with numerous antiaging properties. However, there are reports inconsistent with this classic beneficial DR effect. For instance, several reports implicated that DR effects could vary with the level, onset, and duration of restrictive diet (12–18, 23, 24). It is generally accepted that for its most favorable outcome DR has to be initiated in young adult animals (25). Young and old age are considered to be more vulnerable and susceptible to the environmental interventions like nutritional deprivations, whereas the adult phase represents the most resistant one (26). This is why the DR duration and the age of animals are essential factors in determining the outcome of DR treatment. To the best of our knowledge, no study so far have comparatively analyzed the differences that would arise if DR is implemented at various periods during the lifespan. Therefore, we conducted a study where we compared the impact of early-, middle-, and late-onset of DR, as well as the impact of different durations of DR. We used the reduction of diet to 60 per cent of AL level as one of the most frequently used approach (27, 28). Using behavioral analysis, we showed that the most favorable DR outcome strongly depends on the starting point and duration of applied DR. Namely, we found that moderate DR established at young adult stage (6 months of age) led to numerous beneficial outcomes, regardless of DR duration (6, 12, or 18 months). In all of these cases, DR significantly improved general motor and cognitive capacities of aging animals and lowered the frailty commonly increased in aging. However, starting from the late adulthood, the benefit of reduced food amount was highly debatable and depended significantly on the combination of the onset and duration of DR. If started during the period of 12–18 months of age, DR was either beneficial or had no effect. After that age, there is a risk that DR would cause negative effects, as it was observed in 24-month-old DR3 group. Those animals showed significantly worse open filed activity and FS in comparison to their age-matched controls. The effect of DR was also very dependent on the trait examined. The most positive effect of DR could be detected in Y-maze performance and in FS. OF activities of DR-treated animals were more variable and it was harder to make the general conclusion.

OF assay is a comprehensive assessment of novel environment exploration and general locomotor activity of the animal. Literature data about the effect of age on the activity in open-field are contradictory, indicating that sex, time of testing, and other factors could contribute as well (29–31). There are also controversies regarding the effects of DR on locomotor activity. Administration of caloric restriction for 8 weeks failed to increase locomotor activity (32), whereas life-long DR even aggravates the age-related impairment of spontaneous locomotor activity (33) in mice. On the contrary, 6 months long calorie restriction implemented in early-aged rats (18 months old) increased spontaneous locomotor activity compared with AL rats (34). We did not observe any effect of age on OF activity in animals fed AL. However, various types of diet induced different performance in the OF. Long-term DR started during adulthood (6 months) has the most pronounced beneficial effect on animal’s behavior, increasing physical performance and exploratory behavior. Considerably lesser effect was noticed in rats exposed to restriction that started later in life and lasted for 6 months (DR2), whereas the shortest dietary restriction (DR3) even decreased locomotor activity of rats. Although vertical activity of the oldest DR3 group of rats was substantially higher compared with their age-matched counterparts, we cannot claim that this type of diet elicited beneficial changes. On the contrary, the lack of intersession habituation of vertical activity in this group points to possible detrimental effects (35) of late-onset DR to the learning process.

The Y-shaped maze is a test that mirrors the rodent’s spatial working memory. Several studies have shown that cognitive tasks which require the use of spatial learning and memory in rodents is significantly sensitive to age (36–38). Our results demonstrated that aging affected Y-maze performances in rats, eliciting a decrease in total number of entries, novel arm entries, and time spent in a novel arm in the two oldest groups of rats. A positive effect of DR on spatial memory was observed, but the level of favorable outcome was dependent on DR duration and onset. The long-term diet significantly improved spatial memory, whereas shorter DR’s had only a minor influence. The literature data are controversial. Some authors reported that chronic caloric restriction in developing mice disturbs spatial learning in mazes if it is severe (39). In contrast, lifelong duration of DR was shown to improve working memory, but DR with the late onset was not capable to ameliorate age-related deficits (33). Furthermore, the 3 months long DR increased learning, but not memory retention, and only in male mice (40). Acute restriction exerts diverse effects on the memory, either positive or negative, depending on the age when is implemented (39). These data are supportive to the notion we introduced in this work that for the maximal beneficial effect, diet should start at optimal time point in life and last for sustainable period.

Correlation between the OF and Y-maze assessment of animal’s behavioral abilities was previously established (41). Our results confirmed that link. Both open-field and Y-maze data jointly revealed the maximal beneficial effect of long-term DR on animal’s spatial memory, exploratory behavior, and a general activity level. Shorter duration and late start point of DR had a less pronounced positive impact. Both tests also showed the absence of beneficial outcome if DR was implemented at the advanced age.

To perform a more detailed evaluation of animals on different dietary regimens, we also examined animal’s frailty. Besides the “Fried phenotype” (22) and the “Rockwood frailty index” (42), there were several attempts in defining frailty in animals, mostly in mice (43, 44). Very recently, two studies have laid a first stone on the development of suitable frailty index in rats (45, 46). Both studies were performed on Fisher 344 rats, but authors also pointed out the necessity of determining frailty index in other rat strains and its relation with cognitive deficits. Thus, using physical and cognitive parameters, we determined the frailty status in Wistar rats, another rat strain widely used in aging studies. We implemented frailty assessment that originated from the “Valencia score” method for frailty (6), based on the previously established one for frailty in humans by Fried and co-workers (22). The detected age-related progression of FS in Wistar rats was comparable to one seen in Fisher 344 rats (45). The frailty of both rat strains changed in similar manner during aging, with a significant increase of FS at 17–18 months of age, even when different frailty parameters are employed. Furthermore, this is the very first study aiming to examine the impact of dietary intervention on rat frailty in the course of aging. Another study in long-lived male mice revealed that food restriction implemented at 6 months of age (until 18 months) significantly reduced frailty (47). That was also found in male Wistar rats and more importantly, we observed a decreased FS, which in turn suggests that early-onset, long-term DR acted towards the improvement of healthspan. Likewise, with the results obtained in behavioral tasks, frailty assessment showed that beneficial effect of shorter DR regimens is questionable. Both DR2 and DR3 were inadequate to improve the FS in oldest age, although a positive effect was observed in previous time point for DR2 and DR3 groups. DR implemented at the age of 21 months further enhances age-related increase in frailty. These results further support the notion that shorter duration of DR and when initiated later in life has no general positive effect. These, as well as OF data reported here, are in compliance with the previously published report (48) where 60 per cent DR initiated in old mice (22–24 months) increased mortality in three mouse strains and switching to AL diet was beneficial for survival of those mice.

We have previously shown that life-long DR can neutralize a significant synaptic protein loss in the hippocampus during aging (19, 20) and has complex consequences on animal’s behavior depending on the animal’s age and duration of diet (49). In this study, we have shown that for the most favorable outcome, DR onset should be in a young adult phase followed by a life-long duration. Although, some positive effects could also be achieved with DR applied later in life, even in aged animals, the duration of DR was crucial in distinguishing beneficial from harmful effects. These findings impute a new light into the current view of the impact of DR, as they clarify the applicability of DR as a strategy for prolonging the healthspan.

Supplementary Material

Supplementary data are available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online.

Supplementary_Material

Click here for additional data file.^{(813.1KB, docx)}

Funding

This work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (grant No. ON173056) and National Institutes of Health (grant No. 1R03AG046216-01A1).

Conflict of interest

None reported.

Acknowledgments

The authors thank Professors Susane Howlett and Ilaria Bellantuono for their insightful comments in conducting frailty data analysis. We are grateful to Dr. Tanja Vukov for her assistance regarding statistical analysis of data. All authors are involved in EU Cost Action MouseAge (BM1402).

References

1. Klencklen G, Després O, Dufour A. What do we know about aging and spatial cognition? Reviews and perspectives. Ageing Res Rev. 2012;11:123–135. doi: 10.1016/j.arr.2011.10.001. [DOI] [PubMed] [Google Scholar]
2. Fouweather T, Gillies C, Wohland P, et al. JA: EHLEIS Team Comparison of socio-economic indicators explaining inequalities in healthy life years at age 50 in Europe: 2005 and 2010. Eur J Public Health. 2015; 25:978–983. doi: 10.1093/eurpub/ckv070. [DOI] [PubMed] [Google Scholar]
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4. Fulop T, Larbi A, Witkowski JM, et al. Aging, frailty and age-related diseases. Biogerontology. 2010;11:547–563. doi: 10.1007/s10522-010-9287-2. [DOI] [PubMed] [Google Scholar]
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6. Gomez-Cabrera MC, Garcia-Valles R, Rodriguez-Mañas L, et al. A new frailty score for experimental animals based on the clinical phenotype: inactivity as a model of frailty. J Gerontol A Biol Sci Med Sci. 2017;72:885–891. doi: 10.1093/gerona/glw337. [DOI] [PubMed] [Google Scholar]
7. Michel JP, Lang PO, Zekry D. The frailty process: update of the phenotype and preventive strategies. Ann Gérontol. 2008; 1:e1–e7. doi: 10.1684/age.2008.0001. [Google Scholar]
8. Colman RJ, Beasley TM, Kemnitz JW, et al. Caloric restriction reduces age-related and all-cause mortality in rhesus monkeys. Nat Commun. 2014;5:3557. doi: 10.1038/ncomms4557. [DOI] [PMC free article] [PubMed] [Google Scholar]
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13. Jahng JW, Kim JG, Kim HJ, Kim BT, Kang DW, Lee JH. Chronic food restriction in young rats results in depression- and anxiety-like behaviors with decreased expression of serotonin reuptake transporter. Brain Res. 2007;1150:100–107. doi: 10.1016/j.brainres.2007.02.080. [DOI] [PubMed] [Google Scholar]
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19. Mladenovic Djordjevic A, Perovic M, Tesic V, et al. Long-term dietary restriction modulates the level of presynaptic proteins in the cortex and hippocampus of the aging rat. Neurochem Int. 2010;56:250–255. doi: 10.1016/j.neuint.2009.10.008. [DOI] [PubMed] [Google Scholar]
20. Smiljanic K, Vanmierlo T, Mladenovic Djordjevic A, et al. Cholesterol metabolism changes under long-term dietary restrictions while the cholesterol homeostasis remains unaffected in the cortex and hippocampus of aging rats. Age (Dordr). 2014;36:9654. doi: 10.1007/s11357-014-9654-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
21. Maurice T, Hiramatsu M, Itoh J, Kameyama T, Hasegawa T, Nabeshima T. Behavioral evidence for a modulating role of sigma ligands in memory processes. I. attenuation of dizocilpine (MK-801)-induced amnesia. Brain Res. 1994;30:44–56. doi.10.1016/0006-8993(94)91397–8 [DOI] [PubMed] [Google Scholar]
22. Fried LP, Tangen CM, Walston J, et al. ; Cardiovascular Health Study Collaborative Research Group Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146–M156. doi.10.1093/gerona/56.3.M146. [DOI] [PubMed] [Google Scholar]
23. Goto S. Health span extension by later-life caloric or dietary restriction: a view based on rodent studies. Biogerontology. 2006;7:135–138. doi: 10.1007/s10522-006-9011-4. [DOI] [PubMed] [Google Scholar]
24. Singh R, Manchanda S, Kaur T, et al. Middle age onset short-term intermittent fasting dietary restriction prevents brain function impairments in male Wistar rats. Biogerontology. 2015;16:775–788. doi: 10.1007/s10522-015-9603-y. [DOI] [PubMed] [Google Scholar]
25. Mattson MP. Energy intake, meal frequency, and health: a neurobiological perspective. Annu Rev Nutr. 2005;25:237–260. doi: 10.1146/annurev.nutr.25.050304.092526. [DOI] [PubMed] [Google Scholar]
26. Morgane PJ, Miller M, Kemper T, Stern W, Forbes W, Hall R. The effects of protein malnutrition on the developing central nervous system in the rat. Neurosci Biobehav Rev. 1978;2:137–230. doi.10.1016/0149-7634(78)90059-3. [Google Scholar]
27. Speakman JR, Mitchell SE. Caloric restriction. Mol Aspects Med. 2011;32:159–221. doi: 10.1016/j.mam.2011.07.001. [DOI] [PubMed] [Google Scholar]
28. Chung KW, Kim DH, Park MH, et al. Recent advances in calorie restriction research on aging. Exp Gerontol. 2013;48:1049–1053. doi: 10.1016/j.exger.2012.11.007. [DOI] [PubMed] [Google Scholar]
29. Gould TD, Dao DT, Kovacsics CE. The open field test. In: Gould TD, ed. Mood and Anxiety Related Phenotypes in Mice. Characterization Using Behavioral Tests. New York: Humana Press, 2009: 1–20. doi: 10.1007/978-1-60761-303-9. [Google Scholar]
30. Willig F, Palacios A, Monmaur P, M’Harzi M, Laurent J, Delacour J short-term memory, exploration and locomotor activity in aged rats. Neurobiol Aging. 1987; 5:393–402. doi: 10.1016/0197-4580(87)90033–9. [DOI] [PubMed] [Google Scholar]
31. Zhang B, Sannajust F. Diurnal rhythms of blood pressure, heart rate, and locomotor activity in adult and old male Wistar rats. Physiol Behav. 2000;70:375–380. doi:10.1016/S0031-9384(00)00276-6 [DOI] [PubMed] [Google Scholar]
32. Minor RK, Villarreal J, McGraw M, Percival SS, Ingram DK, de Cabo R. Calorie restriction alters physical performance but not cognition in two models of altered neuroendocrine signaling. Behav Brain Res. 2008;189:202–211. doi: 10.1016/j.bbr.2007.12.030. [DOI] [PubMed] [Google Scholar]
33. Kuhla A, Lange S, Holzmann C, et al. Lifelong caloric restriction increases working memory in mice. PLoS One. 2013;8:e68778. doi: 10.1371/journal.pone.0068778. [DOI] [PMC free article] [PubMed] [Google Scholar]
34. Geng YQ, Guan JT, Xu MY, Xu XH, Fu YC. Behavioral study of calorie-restricted rats from early old age. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:2393–2395. doi: 10.1109/IEMBS.2007.4352809. [DOI] [PubMed] [Google Scholar]
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36. Shukitt-Hale B, McEwen JJ, Szprengiel A, Joseph JA. Effect of age on the radial arm water maze—a test of spatial learning and memory. Neurobiol Aging. 2004; 25:223–229. doi: 10.1016/S0197-4580(03)00041-1. [DOI] [PubMed] [Google Scholar]
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40. Wu A, Wan F, Sun X, Liu Y. Effects of dietary restriction on growth, neurobehavior, and reproduction in developing Kunmin mice. Toxicol Sci. 2002;70:238–244. doi:10.1093/toxsci/70.2.238. [DOI] [PubMed] [Google Scholar]
41. Wetzel W, Matthies H. Differences in Y-maze retention of rats: selection according to open field activity. Physiol Behav. 1982;28:619–622. doi.10.1016/0031-9384(82)90040–3. [DOI] [PubMed] [Google Scholar]
42. Rockwood K, Fox RA, Stolee P, Robertson D, Beattie BL. Frailty in elderly people: an evolving concept. CMAJ. 1994;150:489–495. [PMC free article] [PubMed] [Google Scholar]
43. Whitehead JC, Hildebrand BA, Sun M, et al. A clinical frailty index in aging mice: comparisons with frailty index data in humans. J Gerontol A Biol Sci Med Sci. 2014;69:621–632. doi: 10.1093/gerona/glt136. [DOI] [PMC free article] [PubMed] [Google Scholar]
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45. Yorke A, Kane AE, Hancock Friesen CL, Howlett SE, O’Blenes S. Development of a rat clinical frailty index. J Gerontol A Biol Sci Med Sci. 2017;72:897–903. doi: 10.1093/gerona/glw339. [DOI] [PMC free article] [PubMed] [Google Scholar]
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47. Kane AE, Hilmer SN, Boyer D, et al. Impact of longevity interventions on a validated mouse clinical frailty index. J Gerontol A Biol Sci Med Sci. 2016;71:333–339. doi: 10.1093/gerona/glu315. [DOI] [PMC free article] [PubMed] [Google Scholar]
48. Forster MJ, Morris P, Sohal RS. Genotype and age influence the effect of caloric intake on mortality in mice. FASEB J. 2003;17:690–692. doi: 10.1096/fj.02-0533fje. [DOI] [PMC free article] [PubMed] [Google Scholar]
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[CIT0001] 1. Klencklen G, Després O, Dufour A. What do we know about aging and spatial cognition? Reviews and perspectives. Ageing Res Rev. 2012;11:123–135. doi: 10.1016/j.arr.2011.10.001. [DOI] [PubMed] [Google Scholar]

[CIT0002] 2. Fouweather T, Gillies C, Wohland P, et al. JA: EHLEIS Team Comparison of socio-economic indicators explaining inequalities in healthy life years at age 50 in Europe: 2005 and 2010. Eur J Public Health. 2015; 25:978–983. doi: 10.1093/eurpub/ckv070. [DOI] [PubMed] [Google Scholar]

[CIT0003] 3. Figueira I, Fernandes A, Mladenovic Djordjevic A, et al. Interventions for age-related diseases: shifting the paradigm. Mech Ageing Dev. 2016; 160:69–92. doi: 10.1016/j.mad.2016.09.009. [DOI] [PubMed] [Google Scholar]

[CIT0004] 4. Fulop T, Larbi A, Witkowski JM, et al. Aging, frailty and age-related diseases. Biogerontology. 2010;11:547–563. doi: 10.1007/s10522-010-9287-2. [DOI] [PubMed] [Google Scholar]

[CIT0005] 5. Parks RJ, Fares E, Macdonald JK, et al. A procedure for creating a frailty index based on deficit accumulation in aging mice. J Gerontol A Biol Sci Med Sci. 2012;67:217–227. doi: 10.1093/gerona/glr193. [DOI] [PubMed] [Google Scholar]

[CIT0006] 6. Gomez-Cabrera MC, Garcia-Valles R, Rodriguez-Mañas L, et al. A new frailty score for experimental animals based on the clinical phenotype: inactivity as a model of frailty. J Gerontol A Biol Sci Med Sci. 2017;72:885–891. doi: 10.1093/gerona/glw337. [DOI] [PubMed] [Google Scholar]

[CIT0007] 7. Michel JP, Lang PO, Zekry D. The frailty process: update of the phenotype and preventive strategies. Ann Gérontol. 2008; 1:e1–e7. doi: 10.1684/age.2008.0001. [Google Scholar]

[CIT0008] 8. Colman RJ, Beasley TM, Kemnitz JW, et al. Caloric restriction reduces age-related and all-cause mortality in rhesus monkeys. Nat Commun. 2014;5:3557. doi: 10.1038/ncomms4557. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0009] 9. Rizza W, Veronese N, Fontana L. What are the roles of calorie restriction and diet quality in promoting healthy longevity?Ageing Res Rev. 2014;13:38–45. doi: 10.1016/j.arr.2013.11.002. [DOI] [PubMed] [Google Scholar]

[CIT0010] 10. Masoro EJ. Caloric restriction and aging: controversial issues. J Gerontol A Biol Sci Med Sci. 2006;61:14–19. doi.10.1093/gerona/61.1.14. [DOI] [PubMed] [Google Scholar]

[CIT0011] 11. Piper MD, Mair W, Partridge L. Counting the calories: the role of specific nutrients in extension of life span by food restriction. J Gerontol A Biol Sci Med Sci. 2005;60:549–555. doi.10.1093/gerona/60.5.549. [DOI] [PubMed] [Google Scholar]

[CIT0012] 12. Yanai S, Okaichi Y, Okaichi H. Long-term dietary restriction causes negative effects on cognitive functions in rats. Neurobiol Aging. 2004;25:325–332. doi: 10.1016/S0197-4580(03)00115-5. [DOI] [PubMed] [Google Scholar]

[CIT0013] 13. Jahng JW, Kim JG, Kim HJ, Kim BT, Kang DW, Lee JH. Chronic food restriction in young rats results in depression- and anxiety-like behaviors with decreased expression of serotonin reuptake transporter. Brain Res. 2007;1150:100–107. doi: 10.1016/j.brainres.2007.02.080. [DOI] [PubMed] [Google Scholar]

[CIT0014] 14. Cardoso A, Marrana F, Andrade JP. Caloric restriction in young rats disturbs hippocampal neurogenesis and spatial learning. Neurobiol Learn Mem. 2016;133:214–224. doi: 10.1016/j.nlm.2016.07.013. [DOI] [PubMed] [Google Scholar]

[CIT0015] 15. Morgan WW, Richardson AG, Nelson JF. Dietary restriction does not protect the nigrostriatal dopaminergic pathway of older animals from low-dose MPTP-induced neurotoxicity. J Gerontol A Biol Sci Med Sci. 2003;58:B394–B399. doi:10.1093/gerona/58.5.B394. [DOI] [PubMed] [Google Scholar]

[CIT0016] 16. Gardner EM. Caloric restriction decreases survival of aged mice in response to primary influenza infection. J Gerontol A Biol Sci Med Sci. 2005;60:688–694. doi.10.1093/gerona/60.6.688. [DOI] [PubMed] [Google Scholar]

[CIT0017] 17. Weindruch R, Walford RL. Dietary restriction in mice beginning at 1 year of age: effect on life-span and spontaneous cancer incidence. Science. 1982;215:1415–1418. doi: 10.1126/science.7063854. [DOI] [PubMed] [Google Scholar]

[CIT0018] 18. Weindruch R, Gottesman SR, Walford RL. Modification of age-related immune decline in mice dietarily restricted from or after midadulthood. Proc Natl Acad Sci U S A. 1982;79:898–902. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0019] 19. Mladenovic Djordjevic A, Perovic M, Tesic V, et al. Long-term dietary restriction modulates the level of presynaptic proteins in the cortex and hippocampus of the aging rat. Neurochem Int. 2010;56:250–255. doi: 10.1016/j.neuint.2009.10.008. [DOI] [PubMed] [Google Scholar]

[CIT0020] 20. Smiljanic K, Vanmierlo T, Mladenovic Djordjevic A, et al. Cholesterol metabolism changes under long-term dietary restrictions while the cholesterol homeostasis remains unaffected in the cortex and hippocampus of aging rats. Age (Dordr). 2014;36:9654. doi: 10.1007/s11357-014-9654-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0021] 21. Maurice T, Hiramatsu M, Itoh J, Kameyama T, Hasegawa T, Nabeshima T. Behavioral evidence for a modulating role of sigma ligands in memory processes. I. attenuation of dizocilpine (MK-801)-induced amnesia. Brain Res. 1994;30:44–56. doi.10.1016/0006-8993(94)91397–8 [DOI] [PubMed] [Google Scholar]

[CIT0022] 22. Fried LP, Tangen CM, Walston J, et al. ; Cardiovascular Health Study Collaborative Research Group Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146–M156. doi.10.1093/gerona/56.3.M146. [DOI] [PubMed] [Google Scholar]

[CIT0023] 23. Goto S. Health span extension by later-life caloric or dietary restriction: a view based on rodent studies. Biogerontology. 2006;7:135–138. doi: 10.1007/s10522-006-9011-4. [DOI] [PubMed] [Google Scholar]

[CIT0024] 24. Singh R, Manchanda S, Kaur T, et al. Middle age onset short-term intermittent fasting dietary restriction prevents brain function impairments in male Wistar rats. Biogerontology. 2015;16:775–788. doi: 10.1007/s10522-015-9603-y. [DOI] [PubMed] [Google Scholar]

[CIT0025] 25. Mattson MP. Energy intake, meal frequency, and health: a neurobiological perspective. Annu Rev Nutr. 2005;25:237–260. doi: 10.1146/annurev.nutr.25.050304.092526. [DOI] [PubMed] [Google Scholar]

[CIT0026] 26. Morgane PJ, Miller M, Kemper T, Stern W, Forbes W, Hall R. The effects of protein malnutrition on the developing central nervous system in the rat. Neurosci Biobehav Rev. 1978;2:137–230. doi.10.1016/0149-7634(78)90059-3. [Google Scholar]

[CIT0027] 27. Speakman JR, Mitchell SE. Caloric restriction. Mol Aspects Med. 2011;32:159–221. doi: 10.1016/j.mam.2011.07.001. [DOI] [PubMed] [Google Scholar]

[CIT0028] 28. Chung KW, Kim DH, Park MH, et al. Recent advances in calorie restriction research on aging. Exp Gerontol. 2013;48:1049–1053. doi: 10.1016/j.exger.2012.11.007. [DOI] [PubMed] [Google Scholar]

[CIT0029] 29. Gould TD, Dao DT, Kovacsics CE. The open field test. In: Gould TD, ed. Mood and Anxiety Related Phenotypes in Mice. Characterization Using Behavioral Tests. New York: Humana Press, 2009: 1–20. doi: 10.1007/978-1-60761-303-9. [Google Scholar]

[CIT0030] 30. Willig F, Palacios A, Monmaur P, M’Harzi M, Laurent J, Delacour J short-term memory, exploration and locomotor activity in aged rats. Neurobiol Aging. 1987; 5:393–402. doi: 10.1016/0197-4580(87)90033–9. [DOI] [PubMed] [Google Scholar]

[CIT0031] 31. Zhang B, Sannajust F. Diurnal rhythms of blood pressure, heart rate, and locomotor activity in adult and old male Wistar rats. Physiol Behav. 2000;70:375–380. doi:10.1016/S0031-9384(00)00276-6 [DOI] [PubMed] [Google Scholar]

[CIT0032] 32. Minor RK, Villarreal J, McGraw M, Percival SS, Ingram DK, de Cabo R. Calorie restriction alters physical performance but not cognition in two models of altered neuroendocrine signaling. Behav Brain Res. 2008;189:202–211. doi: 10.1016/j.bbr.2007.12.030. [DOI] [PubMed] [Google Scholar]

[CIT0033] 33. Kuhla A, Lange S, Holzmann C, et al. Lifelong caloric restriction increases working memory in mice. PLoS One. 2013;8:e68778. doi: 10.1371/journal.pone.0068778. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0034] 34. Geng YQ, Guan JT, Xu MY, Xu XH, Fu YC. Behavioral study of calorie-restricted rats from early old age. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:2393–2395. doi: 10.1109/IEMBS.2007.4352809. [DOI] [PubMed] [Google Scholar]

[CIT0035] 35. Leussis MP, Bolivar VJ. Habituation in rodents: a review of behavior, neurobiology, and genetics. Neurosci Biobehav Rev. 2006;30:1045–1064. doi: 10.1016/j.neubiorev.2006.03.006. [DOI] [PubMed] [Google Scholar]

[CIT0036] 36. Shukitt-Hale B, McEwen JJ, Szprengiel A, Joseph JA. Effect of age on the radial arm water maze—a test of spatial learning and memory. Neurobiol Aging. 2004; 25:223–229. doi: 10.1016/S0197-4580(03)00041-1. [DOI] [PubMed] [Google Scholar]

[CIT0037] 37. Carter CS, Leeuwenburgh C, Daniels M, Foster TC. Influence of calorie restriction on measures of age-related cognitive decline: role of increased physical activity. J Gerontol A Biol Sci Med Sci. 2009;64:850–859. doi: 10.1093/gerona/glp060. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0038] 38. McQuail JA, Nicolle MM. Spatial reference memory in normal aging Fischer 344 × Brown Norway F1 hybrid rats. Neurobiol Aging. 2015;36:323–333. doi: 10.1016/j.neurobiolaging.2014.06.030. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0039] 39. Fu Y, Chen Y, Li L, Wang Y, Kong X, Wang J. Food restriction affects Y-maze spatial recognition memory in developing mice. Int J Dev Neurosci. 2017;60:8–15. doi: 10.1016/j.ijdevneu.2017.03.010. [DOI] [PubMed] [Google Scholar]

[CIT0040] 40. Wu A, Wan F, Sun X, Liu Y. Effects of dietary restriction on growth, neurobehavior, and reproduction in developing Kunmin mice. Toxicol Sci. 2002;70:238–244. doi:10.1093/toxsci/70.2.238. [DOI] [PubMed] [Google Scholar]

[CIT0041] 41. Wetzel W, Matthies H. Differences in Y-maze retention of rats: selection according to open field activity. Physiol Behav. 1982;28:619–622. doi.10.1016/0031-9384(82)90040–3. [DOI] [PubMed] [Google Scholar]

[CIT0042] 42. Rockwood K, Fox RA, Stolee P, Robertson D, Beattie BL. Frailty in elderly people: an evolving concept. CMAJ. 1994;150:489–495. [PMC free article] [PubMed] [Google Scholar]

[CIT0043] 43. Whitehead JC, Hildebrand BA, Sun M, et al. A clinical frailty index in aging mice: comparisons with frailty index data in humans. J Gerontol A Biol Sci Med Sci. 2014;69:621–632. doi: 10.1093/gerona/glt136. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0044] 44. Liu H, Graber TG, Ferguson-Stegall L, Thompson LV. Clinically relevant frailty index for mice. J Gerontol A Biol Sci Med Sci. 2014;69:1485–1491. doi: 10.1093/gerona/glt188. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0045] 45. Yorke A, Kane AE, Hancock Friesen CL, Howlett SE, O’Blenes S. Development of a rat clinical frailty index. J Gerontol A Biol Sci Med Sci. 2017;72:897–903. doi: 10.1093/gerona/glw339. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CIT0046] 46. Miller MG, Thangthaeng N, Shukitt-Hale B. A clinically relevant frailty index for aging rats. J Gerontol A Biol Sci Med Sci. 2017;72:892–896. doi: 10.1093/gerona/glw338. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Effects of Different Dietary Protocols on General Activity and Frailty of Male Wistar Rats During Aging

Smilja T Todorovic, BSc

Kosara R Smiljanic, PhD

Sabera D Ruzdijic, PhD

Aleksandra N Mladenovic Djordjevic, PhD

Selma D Kanazir, PhD

Abstract