Research article Special Issues

Effect of combined training in water on hippocampal neuronal Plasticity and memory function in healthy elderly rats

  • Running title: Effect of Aquatic Training on Hippocampal Plasticity
  • Purpose 

    The cyclic AMP response element–binding protein (CREB) and nerve growth factor (NGF) have been proposed as key modulators of brain health and are involved in synaptic plasticity. The study investigates how combined water-based training affects hippocampal neuron plasticity and memory function in old rats.

    Methods 

    16 Wistar male rats 24-month-old were randomly divided into two groups: combined training (n = 8) and control (n = 8). Four sessions were performed per week for 10 weeks, and consisted of resistance and endurance training in water. The control group was placed in a water container during training for 30 minutes to be homogenized in terms of the stress conditions. The.NGF and CREB genes in the hippocampus were evaluated and the working memory was measured using real-time PCR and Y-maze tests. The SPSS 26 software was utilized in which independent t-tests were used to analyze the genes and the Mann-Whitney U test was used to analyze functional memory with a significant level of (P < 0.05).

    Results 

    The combined training resulted in a significant rise in NGF and CREB gene expression in the hippocampus tissue of elderly rats compared to the control group (P < 0.05); however, there was no notable difference in the Y maze performance test between the two groups (P < 0.05).

    Conclusions 

    These findings suggest that water-based combined training has beneficial effects on gene expression of NGF and CREB; however, it is necessary to conduct more studies to comprehend the effects of combined training on memory function.

    Citation: Roya. Askari, Mohadeseh. NasrAbadi, Amir Hossein. Haghighi, Mohammad Jahan Mahin, Rajabi Somayeh, Matteo. Pusceddu. Effect of combined training in water on hippocampal neuronal Plasticity and memory function in healthy elderly rats[J]. AIMS Neuroscience, 2024, 11(3): 260-274. doi: 10.3934/Neuroscience.2024017

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  • Purpose 

    The cyclic AMP response element–binding protein (CREB) and nerve growth factor (NGF) have been proposed as key modulators of brain health and are involved in synaptic plasticity. The study investigates how combined water-based training affects hippocampal neuron plasticity and memory function in old rats.

    Methods 

    16 Wistar male rats 24-month-old were randomly divided into two groups: combined training (n = 8) and control (n = 8). Four sessions were performed per week for 10 weeks, and consisted of resistance and endurance training in water. The control group was placed in a water container during training for 30 minutes to be homogenized in terms of the stress conditions. The.NGF and CREB genes in the hippocampus were evaluated and the working memory was measured using real-time PCR and Y-maze tests. The SPSS 26 software was utilized in which independent t-tests were used to analyze the genes and the Mann-Whitney U test was used to analyze functional memory with a significant level of (P < 0.05).

    Results 

    The combined training resulted in a significant rise in NGF and CREB gene expression in the hippocampus tissue of elderly rats compared to the control group (P < 0.05); however, there was no notable difference in the Y maze performance test between the two groups (P < 0.05).

    Conclusions 

    These findings suggest that water-based combined training has beneficial effects on gene expression of NGF and CREB; however, it is necessary to conduct more studies to comprehend the effects of combined training on memory function.



    According to the World Health Organization, healthy aging is defined as “the process of developing and maintaining functional ability that promotes well-being in the elderly” [1]. Aging causes physiological changes in various systems of the body, especially the nervous system. The set of changes that occur in the brain with age reduces cell-to-cell efficiency (cellular communication), and thus the ability to remember and learn [2]. Although inactivity can lead to decreased physical fitness and the incidence of chronic diseases in older adults [3], regular physical training leads to increased functional activity, improved health, and optimal social relationships, and thus, the opportunity to experience healthy aging [1]. Physical activity enhances [4] and thereby counteracts an age-related cognitive decline [5]. The beneficial effects of exercise activity on brain structure and cognitive function occur through improved levels of neurotrophins in the brain [6].

    Neurotrophins, such as brain-derived neurotrophic factor (BDNF) and neural growth factor (NGF), have been proposed as key brain health regulators and are involved in neurogenesis, neuronal survival, and synaptic plasticity [5],[7]. NGF is important in neuronal health [8],[9]. Reduced NGF levels have been observed in the hippocampus of older mice and may be implicated in age-related cognitive function [8]. Additionally, NGF helps in the survival and regeneration of neurons during aging and in age-related diseases such as Alzheimer's [10]. Several studies have reported an increase in the NGF protein within the blood and brain after various exercise activities in humans and animals [11][14].

    The cyclic AMP response element–binding protein (CREB) is a cellular transcription factor that binds to a specific sequences of DNA, called cyclic adenosine monophosphate-responsive elements (cAMP), and either increases or decreases the transcription of upstream or downstream genes [15]. Increased calcium and cAMP concentrations in the hippocampus can lead to phosphorylation and CREB activation. This transcription factor is a component of intracellular signaling events that regulate various biological processes, including memory, and plays an undeniable role in neuroplasticity, long-term memory formation in the brain, and spatial memory [16]. Some genes regulated by CREB include BDNF and NGF. Various studies have shown that different types of exercises have increased CREB expression and improved the memory and cognition of elderly mice [17][21].

    Currently, training in water is considered a safe and useful alternative to dry training because of the nature of weight intolerance. Because of the high density and viscosity of water, the forces exerted on one's joints are less; therefore, these types of trainings are beneficial for the elderly population [22]. However, studies that evaluated the effects of water training in the elderly are very limited. For instance, training in water improves attention and memory [23]. Ultimately, CREB and BDNF improve hippocampus-dependent memory in older mice [20].

    Although the relationship between training and memory has been proven, the pathways involved in this connection and the intensity, the duration, and the type of optimal training remain unknown. Because water training is safe for the elderly, and a combination of resistance and endurance training in water can simultaneously benefit the elderly from the effects of adapting to both resistance and endurance training [24], the role of combined training (resistance and endurance), especially in the elderly, can be a good strategy to achieve these beneficial effects. This study aims to investigate the effects of 10 weeks of combined water training on hippocampal neural plasticity (CREB and NGF) and memory function in elderly rats.

    This was an experimental study with a post-test design and a control group. Sixteen 24-month-old male Wistar rats that weighed 315–325 gr were selected and randomly divided into two groups: combined training in water (n = 8) and control (n = 8). The rats were placed at a temperature of 30 ± 1 °C, humidity of approximately 45%, and a cycle of 12 to 12 h; the cages were made of Plexiglas with a net door of dimensions 43 × 27 × 25 cm and provided access to standard food and water. The animals from the training group performed physical training in water with temperatures at 30 °C in a glass container of 100 cm long, 50 cm high, and 50 cm wide [25]. The water depth was adjusted based on the rat body length. No regular physical activity was observed in the control group. For homogenization, during exercise training (i.e., for 30-minutes), they were placed in a water container at a depth of five centimeter.

    The study was approved by the research ethics committee of Sabzevar University of Medical Sciences (IR. HSU. AEC.1401.004).

    The rats alternately performed a combination of resistance and endurance training programs for four days a week (every other day). A mesh metal grating (a distance of 2 cm from each grid similar to the ladder of rat special resistance training) [24] was attached as a ladder to the container wall (Figure 1A). During resistance training in the first week, the animals performed five sessions of familiarity with the water environment and climbing the ladder (Table 1). In the first meeting of the week, the rats' release distance was close to the ladder so as to climb it with the least immersion; in the following sessions, this distance increased. After the familiarization period, the water level was adjusted to approximately 200% of the animal's body length, and the rats were released from a distance of 35 cm to climb the ladder. The selection of this interval was based on the duration of hypoxia under water so as to not exceed 10 seconds over 10 weeks. Weights were attached to the tail of rats by a band; before applying the new training load after two weeks, the weight of the animal was measured on a laboratory scale, and the weight was determined based on the new weight [24].

    Figure 1.  A) Resistance training section, B) Endurance training section.

    Similar to resistance training, endurance training was followed by five days a week of familiarity, as shown in Table 1 [26]. After familiarization with the endurance training, the main program was implemented in water with a height equal to 140% of the rat's body length [27]. During endurance training, the glass container was divided into two parts (dimensions 25 × 100 cm), and each rat swam in a separate line (Figure 1B).

    Table 1.  Combined training program (resistance-endurance) in water.
    Familiarization course of resistance training in water (one week) Familiarization course of endurance training in water (one week)
    Session 1 Climbing the ladder with a weight equal to 10% of the rat's body weight, 3 sets with 8 repetitions and 1 Minute rest between each set with a water height of 100% of the rat's length. Swimming for 10 minutes with a water height of 100% of the rat's body length
    Session 2 & 3 Climbing the ladder with a weight equal to 15% of the rat's body weight, 3 sets with 8 repetitions and 1 Minute rest between each set with a water height of 120% of the rat's length. Swimming for 15 minutes with a water height of 120% of the rat's body length
    Session 4 & 5 Climbing the ladder with a weight equal to 20% of the rat's body weight, 3 sets with 8 repetitions and 1 Minute rest between each set with a water height of 140% of the rat's length. Swimming for 20 minutes with a water height of 140% of the rat's body length
    Resistance training Program Endurance training Program

    Weeks Set Repetition Rest between each set Amount of weight based on body weight Duration of continuous swimming
    Week 1 & 2 4 10 1 Minute 30% 30 Minute
    Week 3 & 4 4 10 1 Minute 35% 35 Minute
    Week 5 & 6 4 10 1 Minute 40% 40 Minute
    Week 7 & 8 4 10 1 Minute 45% 45 Minute
    Week 9 & 10 4 10 1 Minute 50% 50 Minute

     | Show Table
    DownLoad: CSV

    The control group was placed in a 5 cm deep water container for 30 min in order not to differ from the training group in terms of the stress conditions [28].

    The working memory was measured using the Y-maze test and alternation percentages. The working memory was assessed by observing and measuring the spontaneous alternation behavior during a working session. The maze was made of Plexiglas; each arm was 15 × 30 × 40, and the arms were connected through a central area. Each rat was placed at the end of one arm of maze (A) and allowed to move freely in the arms for 8 min (Figure 2). The number of animals that entered each arm was recorded. An alternate behavior was considered successful, and a serial entry was added into all arms in the triple sets. Thus, the alternation percentage that determined the spatial memory in the animal according to formula 1 was the number of non-repetitive triad arms divided by the total arms of the triads minus 2; because it was expressed as a percentage, the total data was multiplied by 100 [29].

    Formula 1: Spatial memory percentage = number of non-repetitive triad arms/ (total number of triad arms – 2) × 100.

    Figure 2.  Y-Maze.

    Forty-eight hours after the last training session and 10 to 12 h of fasting, the animals were anesthetized with chloroform, the animal heads were removed, and the hippocampal tissue was separated. The samples were stored at −80 °C, and gene expression was analyzed by Real-Time PCR. First, all the necessary ingredients for the PCR were removed from the freezer, vortexed (Kiagene Co., Iran), spun, and stored on ice. Then, for each gene, a mixture of different PCR components was prepared; after mixing and spinning, 9 µl was distributed into the microtubes of the device, and in each vial, a microliter of cDNA sample was added (the final volume of each PCR reaction was 10 µl).

    To extract RNA from the tissues and to evaluate gene expression by Real-Time Polymerase Chain Reaction (RT-PCR), biological samples were prepared beforehand. The cell surface area was depleted. The cells were washed with PBS buffer, and after discharging the PBS, a certain amount of triazole (Kiazist Co., Iran) (1 mM of triazole in a container of 10 cm) was poured onto the cells to lyse them. The cell lysate was collected in a 1.5 ml microtube. For non-adhesive eukaryotic and bacterial cells, the existing cell suspension was centrifuged (Hettich Co., Germany), the cell surface was discarded, and the cell sediment was lysed in a certain amount of triazole (1 mM triazole per 5–10 million cells). For bacterial cells, one mM of triazole was added per 10 million cells. The resulting cell lysate was collected in a 1.5 ml microtube.

    For converting RNA to cDNA, all the Easy cDNA Synthesis Kit materials (Kiatous, Iran) were removed from −20 °C and the RNA samples were removed from −70 °C and transferred to ice after melting. All materials were shortened and spun before overtaxing. To prepare the reverse transcriptase (RT) mixture, cDNA materials including RT buffer, RT enzyme, Oligo dT primer, and diethyl pyro carbonate (DEPC)-treated water were mixed and then distributed in 9 µl volumes into 0.2 ml microtubes. Prepared microtubes that contained RT mix and the RNA samples were placed in a real-time PCR thermocycler (ABI Stepone Co., USA), and temperature change programs were implemented. The cDNA samples were stored at −20 °C. The sequences of the primers and probes used are presented in Table 2.

    Table 2.  The sequence of the investigated primers and probes.
    Host Gene Primer Oligo Length
    Rat CREB Forward Primer AAGCAGTGACGGAGGAGCTT 20
    Reverse Primer CATGGATACCTGGGCTAATGTGG 23
    Rat GAPDH Forward Primer AGGTCGGTGTGAACGGATTTG 21
    Reverse Primer TGTAGACCATGTAGTTGAGGTCA 23
    Rat NGF Forward Primer ACAGGCAGAACCGTACACAG 20
    Reverse Primer CTATTGGTTCAGCAGGGGCA 20

     | Show Table
    DownLoad: CSV

    After the experiment, the data, including the threshold cycle (CT) and replication and melting curves of each gene, were prepared for analysis. The CT numbers of the reference gene and the main gene of each sample were determined, and the relative expression of each gene was calculated using the 2−ΔΔ CT formula to examine the fold-change of each gene.

    Descriptive and inferential statistics were used to analyze the data. The Schapiro-Wilk test was used to normalize the data. In the case of normality independence, a t-test was used; otherwise, the Mann-Whitney U test was used. The Leven test was used to determine the homogeneity of variance. Data were analyzed using the SPSS 22 software at a significance level of P < 0.05.

    Table 3 presents the mean and standard deviation of the hippocampal tissue variables, including NGF, CREB, and working memory.

    Table 3.  Mean values and results of Independent T Test for NGF, CREB gene expression. Mann-Whitney U Test in working memory of two groups.
    Independent T test
    Variable Groups N Mean ± std. Deviation t P
    NGF Fold change Control Training 8 1/01 ± 0/15 -4/09 0/001*
    8 1/32 ± 0/15
    CREB Fold change Control Training 8 1/16 ± 0/48 -2/53 0/024*
    8 3/14 ± 2/16

    Mann-Whitney U test

    Variable group N Mean ± std. Deviation Mean Rank Z P
    Working memory (%) control training 8 42/4 ± 60/56 6/40 -0/453 0/651
    8 44/4 ± 25/90 7/38

    * Significance at P < 0.05 level

     | Show Table
    DownLoad: CSV

    A parametric independent t-test was used to analyze NGF and CREB gene expression, and the non-parametric Mann-Whitney U test was used to compare the means for working memory.

    NGF gene expression was significantly higher in the training group than in the control group (P = 0.01) (Figure 3 and Table 3). In addition, CREB gene expression in the training group showed a significant increase in the training group compared to the control group (P = 0.024) (Figure 4), which indicates that 10 weeks of combined training increased NGF and CREB gene expression in the hippocampus of elderly rats.

    Although the combined training in water increased memory performance, this increase was not statistically significant in the working memory test (P > 0.05) (Table 3).

    Figure 3.  fold change in expression of CREB.
    Figure 4.  fold change in expression of NGF.

    Several studies have demonstrated that regular exercise may affect neuronal function in older adults [18],[20],[30],[31].

    In investigating the relationship between NGF and CREB and their possible activation mechanisms, the activation of the NGF receptor tropomyosin receptor kinase A (TrkA) stimulates three main signaling pathways—Mitogen‑activated Protein kinase (MAPK), PLC-γ, and AKT—which leads to the initiation of a cascade of intracellular events characterized by changes in the expression of the genes responsible for survival, growth, and differentiation. In the MAPK pathway, phosphorylated RSK is transferred to the nucleus for CREB phosphorylation. The CREB transcription factor hereby participates in protein translation and the control of gene transcription [32],[33]. Therefore, in the present study, the increased expression of NGF observed with the combined swimming training may lead to the positive regulation of the expression of downstream proteins such as CREB, and consequently, nerve cell survival and synaptic plasticity.

    Our findings showed that the combined training in water had a significant effect on hippocampal CREB gene expression in elderly rats. In line with our results, four weeks of swimming training (6 days Per week for 60 min) during the aging process increased the protein levels and the mRNA expression of CREB [18]. In another study, eight weeks of training in water (five days per week for 30 minutes a day) led to increased CREB, BDNF, and the activation of Sirt-1 signaling pathways in the hippocampus [20]. Additionally, in another study, the CREB levels increased after both aerobic and resistance training protocols [21]. Contrary to our data, high-intensity aerobic training did not negatively affect the CREB pathway or significantly alter memory function in mice [34]. It should be noted that the evaluation of the above research was conducted in the striatum, which is different from our evaluation of the hippocampal tissue. The reason Aguiar et al.'s (2010) results contradict the current study may be due to the type (sprint interval running on a treadmill) and intensity of the training. Another study conducted by the same group (Aguiar 2011) showed that lower intensity aerobic training in older rats improved spatial memory through increased hippocampal CREB [17]. We suggest that training in water or moderate-intensity training has better effects than strenuous training, and that the nature of exercise is effective.

    Exercise training is thought to activate neurogenesis through various pathways [35]. One of the important signaling pathways in the brain proposed over the years is the binding of BDNF to its specific receptor in different regions of the hippocampus [36]. The binding of BDNF to its receptor leads to the activation of several signaling pathways, including protein kinase A (PKA), mitogen-activated protein kinase (MAPK), and CREB [37]. In accordance, it has been demonstrated that swimming training protocol increased the signaling pathways of CREB and protein kinase B (AKT) activity in the hippocampus of older rats [38]. Therefore, the combined training in water should also be effective in activating the above-mentioned mechanisms.

    Moreover, our study showed that the combined training in water significantly increased the hippocampal gene expression of NGF in elderly rats. Although several studies have confirmed the involvement of NGF in learning processes, its role in brain plasticity after exercise training is poorly understood. In this regard, treadmill training in rats for eight weeks has been shown to increase NGF expression and neural survival of the hippocampal gyrus [14]. In another study, moderately-intense forced treadmill training inhibited apoptosis by increasing NGF levels and activating the PI3K signaling pathway in the hippocampus of elderly rats [12]. Contrary to the results of the current study, eight weeks of swimming training (ranging from 5 min in the first week to 60 min in the last week, three sessions per week) had no significant effect on hippocampal NGF and BDNF in mice with Alzheimer's disease [13]. Considering that the exercise protocol of our study was different from that of the above study in both the intensity and the duration (combination of aerobic and strength training in water), different intensities and durations of training protocols may be one of the reasons for the lack of significant changes among our study and the above study.

    Exercise training increases hippocampal plasticity in aging through several possible mechanisms, including increased neurotrophic factors such as BDNF (one of the important mediators of crosstalk between contracted skeletal muscles and the brain during exercise training, crucial for neurogenesis and synaptic plasticity) [30], enhanced synaptic plasticity (through activation the cAMP/PKA/CREB signaling pathway) [39], reduced hippocampal atrophy [40], and decreased inflammation and oxidative stress [41]. These findings underscore the importance of physical activity as a non-pharmacological intervention to maintain cognitive health and to prevent age-related decline in brain function.

    Aging causes changes in blood vessels in the brain. Due to the narrowing of the arteries and the diminished formation of new capillaries, blood flow to the brain can decrease [42]. Evidence shows that physical activity can improve mental and cognitive performance and plays a role in preventing the decline of cognitive performance [43]. Exercise can indirectly affect the gene expression of neurotrophic factors by affecting the secretion of neurotransmitters such as acetylcholine, gamma amino butyric acid, and monoamines [44]. There is a consensus in the literature that physical training has a positive effect on improving memory function; neurotrophins can play a very important role in this scenario, such as neurogenesis, neuronal survival, and synaptic plasticity [45].

    Despite the improvements in NGF and CREB gene expression, the findings of the present study showed that the combined water training had an indirect effect on working memory in elderly rats. Some studies have demonstrated that working memory is improved by chronic exercise in older adults [30],[46],[47]. In one investigation, eight weeks of moderately-intense swimming training (30 minutes a day, 5 days a week) improved memory [20]. In another study, 4 weeks of swimming training (6 days a week, 60 min) improved spatial memory in aging rats [18]. The results of the Y-maze test after performing high-intensity exercises on the treadmill showed that there was a memory disorder in the mice [48]. In addition, three studies within a review of human samples showed that aerobic exercises had no significant effect on improving memory [49][51]. They reported that among the reasons for the lack of memory improvements may be variations in the training characteristics (such as frequency, intensity, duration, type, and duration of intervention) that could involve mechanisms underlying improving working memory in different ways. Another possible reason for the inconsistent results is the use of different tools and measurement tests, which made it difficult to comprehensively investigate the effect of physical training interventions on working memory using a single instrument [52]. However, considering that the rats in the present study did not have memory disorders, this factor can be considered as one of the mechanisms of the lack of significance of training in water on memory. In addition, environmental influences such as physical training on memory usually take more time to become institutionalized than genetic or hormonal changes that are affected faster than exercise training. One of the limitations of the present study was due to the multi-sectoral nature of working memory and different measurement tools to examine its different dimensions [52] and to examine memory. In addition, one of the primary limitations of this research is the absence of multiple functional tests, particularly those that also evaluate long-term memory. Additional limitaitons of this research include the lack of a young control group and the use of endurance and resistance training groups alone, which make it difficult to accurately discuss the reasons for the observed changes. Further research is required to clarify this.

    Our findings suggested that the combined physical training in water and similar protocols had positive effects on gene factors such as NGF and CREB. The conclusions drawn from our study emphasized the importance of further investigating the specific effects of each type of physical activity. This in-depth exploration will serve as a crucial foundation to design more effective and personalized interventions, as well as for the development of health prevention and promotion policies. However, further studies are necessary to delve into the potential of this type of training on memory in order to assess a possible positive impact in preventing the risk factors associated with cognitive decline.


    Acknowledgments



    The authors of this article would like to sincerely thank all those who helped in the implementation of this research.

    Conflict of interest



    The authors declare that there are no conflicts of interest in this research.

    Author contributions



    Conceptualization: Roya Askari
    Data curation: Mohadeseh Nasr Abadi
    Formal analysis: Mohadeseh Nasr Abadi, Roya Askari
    Funding acquisition: ----------
    Methodology: Mohammad Jahan Mahin
    Project administration: Roya Askari- Amir Hossein Haghighi
    Visualization: Roya Askari- Amir Hossein Haghighi, Matteo Pusceddu
    Writing - original draft: Somayeh Rajabi
    Writing - review & editing: Somayeh Rajabi- Roya Askari-Matteo Pusceddu

    [1] Pac A, Tobiasz-Adamczyk B, Błędowski P, et al. (2019) Influence of sociodemographic, behavioral and other health-related factors on healthy ageing based on three operative definitions. J Nutr Health Aging 23: 862-869. https://doi.org/10.1007/s12603-019-1243-5
    [2] Amarya S, Singh K, Sabharwal M (2018) Ageing process and physiological changes. Gerontology . Intech. https://doi.org/10.5772/intechopen.76249
    [3] Lu W, Pikhart H, Sacker A (2019) Domains and measurements of healthy aging in epidemiological studies: a review. Gerontologist 59: e294-e310. https://doi.org/10.1093/geront/gny029
    [4] Huang T, Larsen K, Ried-Larsen M, et al. (2014) The effects of physical activity and exercise on brain-derived neurotrophic factor in healthy humans: A review. Scand J Med Sci Sports 24: 1-10. https://doi.org/10.1111/sms.12069
    [5] Bonanni R, Cariati I, Tarantino U, et al. (2022) Physical exercise and health: a focus on its protective role in neurodegenerative diseases. J Funct Morphol Kinesiol 7: 38. https://doi.org/10.3390/jfmk7020038
    [6] Tomlinson L, Leiton CV, Colognato H (2016) Behavioral experiences as drivers of oligodendrocyte lineage dynamics and myelin plasticity. Neuropharmacology 110: 548-562. https://doi.org/10.1016/j.neuropharm.2015.09.016
    [7] Varela RB, Valvassori SS, Lopes-Borges J, et al. (2015) Sodium butyrate and mood stabilizers block ouabain-induced hyperlocomotion and increase BDNF, NGF and GDNF levels in brain of Wistar rats. J Psychiatr Res 61: 114-121. https://doi.org/10.1016/j.jpsychires.2014.11.003
    [8] Budni J, Bellettini-Santos T, Mina F, et al. (2015) The involvement of BDNF, NGF and GDNF in aging and Alzheimer's disease. Aging Dis 6: 331. https://doi.org/10.14336/AD.2015.0825
    [9] Murawska-Ciałowicz E, Wiatr M, Ciałowicz M, et al. (2021) BDNF impact on biological markers of depression—role of physical exercise and training. Int J Env Res Pub He 18: 7553. https://doi.org/10.3390/ijerph18147553
    [10] Mitra S, Behbahani H, Eriksdotter M (2019) Innovative therapy for Alzheimer's disease-with focus on biodelivery of NGF. Front Neurosci 13. https://doi.org/10.3389/fnins.2019.00038
    [11] Allard S, Jacobs ML, Do Carmo S, et al. (2018) Compromise of cortical proNGF maturation causes selective retrograde atrophy in cholinergic nucleus basalis neurons. Neurobiol Aging 67: 10-20. https://doi.org/10.1016/j.neurobiolaging.2018.03.002
    [12] Chae C-H, Kim H-T (2009) Forced, moderate-intensity treadmill exercise suppresses apoptosis by increasing the level of NGF and stimulating phosphatidylinositol 3-kinase signaling in the hippocampus of induced aging rats. Neurochem Int 55: 208-213. https://doi.org/10.1016/j.neuint.2009.02.024
    [13] Dehbozorgi A, Tabrizi LB, Hosseini SA, et al. (2020) Effects of Swimming Training and Royal Jelly on BDNF and NGF Gene Expression in Hippocampus Tissue of Rats with Alzheimer's Disease. Zahedan J Res Med Sci 22: e98310. https://doi.org/10.5812/zjrms.98310
    [14] Hong Y-P, Lee H-C, Kim H-T (2015) Treadmill exercise after social isolation increases the levels of NGF, BDNF, and synapsin I to induce survival of neurons in the hippocampus, and improves depression-like behavior. J Exer Nutr Biochem 19: 11. https://doi.org/10.5717/jenb.2015.19.1.11
    [15] Kandel ER (2012) The molecular biology of memory: cAMP, PKA, CRE, CREB-1, CREB-2, and CPEB. Mol Brain 5: 1-12. https://doi.org/10.1186/1756-6606-5-14
    [16] Matos MR, Visser E, Kramvis I, et al. (2019) Memory strength gates the involvement of a CREB-dependent cortical fear engram in remote memory. Nat Commun 10: 2315. https://doi.org/10.1038/s41467-019-10266-1
    [17] Aguiar AS, Castro AA, Moreira EL, et al. (2011) Short bouts of mild-intensity physical exercise improve spatial learning and memory in aging rats: involvement of hippocampal plasticity via AKT, CREB and BDNF signaling. Mech Ageing Dev 132: 560-567. https://doi.org/10.1016/j.mad.2011.09.005
    [18] Li X, Wang L, Zhang S, et al. (2019) Timing-dependent protection of swimming exercise against d-galactose-induced aging-like impairments in spatial learning/memory in rats. Brain Sci 9: 236. https://doi.org/10.3390/brainsci9090236
    [19] Sabouri M, Kordi M, Shabkhiz F, et al. (2020) Moderate treadmill exercise improves spatial learning and memory deficits possibly via changing PDE-5, IL-1 β and pCREB expression. Exp Gerontol 139: 111056. https://doi.org/10.1016/j.exger.2020.111056
    [20] Tunca U, Saygin M, Ozmen O, et al. (2021) The impact of moderate-intensity swimming exercise on learning and memory in aged rats: The role of Sirtuin-1. Iran J Basic Med Sci 24: 1413.
    [21] Vilela TC, Muller AP, Damiani AP, et al. (2017) Strength and aerobic exercises improve spatial memory in aging rats through stimulating distinct neuroplasticity mechanisms. Mol Neurobiol 54: 7928-7937. https://doi.org/10.1007/s12035-016-0272-x
    [22] Yoo J-H (2020) The psychological effects of water-based exercise in older adults: an integrative review. Geriatr Nurs 41: 717-723. https://doi.org/10.1016/j.gerinurse.2020.04.019
    [23] Fedor A, Garcia S, Gunstad J (2015) The effects of a brief, water-based exercise intervention on cognitive function in older adults. Arch Clin Neuropsych 30: 139-147. https://doi.org/10.1093/arclin/acv001
    [24] Jahanmahin M, Askari R, Haghighi A, et al. (2022) The Effect of 10 Weeks Combined Training in Water on Immunosenescence in Elderly Rats. J Isfahan Med School 40: 890-899.
    [25] Bryczkowska I, Baranowska-Bosiacka I, Lubkowska A (2017) Effect of repeated cold water swimming exercise on adaptive changes in body weight in older rats. Central Eur J Sport Sci Med 18: 77-87. https://doi.org/10.18276/cej.2017.2-08
    [26] Silva RTB, Castro PVd, Coutinho MPG, et al. (2017) Resistance jump training may reverse the weakened biomechanical behavior of tendons of diabetic Wistar rats. Fisioterapia e Pesquisa 24: 399-405. https://doi.org/10.1590/1809-2950/17198024042017
    [27] Xie Y, Li Z, Wang Y, et al. (2019) Effects of moderate-versus high-intensity swimming training on inflammatory and CD4+ T cell subset profiles in experimental autoimmune encephalomyelitis mice. J Neuroimmunol 328: 60-67. https://doi.org/10.1016/j.jneuroim.2018.12.005
    [28] Altarifi AA, Kalha Z, Kana'An SF, et al. (2019) Effects of combined swimming exercise and non‑steroidal anti‑inflammatory drugs on inflammatory nociception in rats. Exp Ther Med 17: 4303-4311. https://doi.org/10.3892/etm.2019.7413
    [29] Shi X, Bai H, Wang J, et al. (2021) Behavioral assessment of sensory, motor, emotion, and cognition in rodent models of intracerebral hemorrhage. Front Neurol 12: 667511. https://doi.org/10.3389/fneur.2021.667511
    [30] Babaei P, Azari HB (2022) Exercise training improves memory performance in older adults: a narrative review of evidence and possible mechanisms. Front Hum Neurosci 15: 771553. https://doi.org/10.3389/fnhum.2021.771553
    [31] Lin J-Y, Kuo W-W, Baskaran R, et al. (2020) Swimming exercise stimulates IGF1/PI3K/Akt and AMPK/SIRT1/PGC1α survival signaling to suppress apoptosis and inflammation in aging hippocampus. Aging (Albany NY) 12: 6852. https://doi.org/10.18632/aging.103046
    [32] Naletova I, Satriano C, Pietropaolo A, et al. (2019) The copper (II)-assisted connection between NGF and BDNF by means of nerve growth factor-mimicking short peptides. Cells 8: 301. https://doi.org/10.3390/cells8040301
    [33] Niewiadomska G, Mietelska-Porowska A, Mazurkiewicz M (2011) The cholinergic system, nerve growth factor and the cytoskeleton. Behav Brain Res 221: 515-526. https://doi.org/10.1016/j.bbr.2010.02.024
    [34] Aguiar A, Boemer G, Rial D, et al. (2010) High-intensity physical exercise disrupts implicit memory in mice: involvement of the striatal glutathione antioxidant system and intracellular signaling. Neuroscience 171: 1216-1227. https://doi.org/10.1016/j.neuroscience.2010.09.053
    [35] Mohseni I, Peeri M, Azarbayjani MA (2020) Dietary supplementation with Salvia officinalis L. and aerobic training attenuates memory deficits via the CREB-BDNF pathway in amyloid beta-injected rats. J Med Plants 1: 119-132. https://doi.org/10.29252/jmp.1.73.119
    [36] Aoki C, Wu K, Elste A, et al. (2000) Localization of brain-derived neurotrophic factor and TrkB receptors to postsynaptic densities of adult rat cerebral cortex. J Neurosci Res 59: 454-463. https://doi.org/10.1002/(SICI)1097-4547(20000201)59:3<454::AID-JNR21>3.0.CO;2-H
    [37] Vaynman S, Ying Z, Gomez-Pinilla F (2003) Interplay between brain-derived neurotrophic factor and signal transduction modulators in the regulation of the effects of exercise on synaptic-plasticity. Neuroscience 122: 647-657. https://doi.org/10.1016/j.neuroscience.2003.08.001
    [38] Cechella JL, Leite MR, Rosario AR, et al. (2014) Diphenyl diselenide-supplemented diet and swimming exercise enhance novel object recognition memory in old rats. Age 36: 1-10. https://doi.org/10.1007/s11357-014-9666-8
    [39] Jin Y, Li X, Wei C, et al. (2024) Effects of exercise-targeted hippocampal PDE-4 methylation on synaptic plasticity and spatial learning/memory impairments in D-galactose-induced aging rats. Exp Brain Res 242: 309-320. https://doi.org/10.1007/s00221-023-06749-9
    [40] Feter N, Penny J, Freitas M, et al. (2018) Effect of physical exercise on hippocampal volume in adults: Systematic review and meta-analysis. Sci Sport 33: 327-338. https://doi.org/10.1016/j.scispo.2018.02.011
    [41] Vints WA, Šeikinaitė J, Gökçe E, et al. (2024) Resistance exercise effects on hippocampus subfield volumes and biomarkers of neuroplasticity and neuroinflammation in older adults with low and high risk of mild cognitive impairment: a randomized controlled trial. GeroScience 46: 3971-3991. https://doi.org/10.1007/s11357-024-01110-6
    [42] Zimmerman B, Rypma B, Gratton G, et al. (2021) Age-related changes in cerebrovascular health and their effects on neural function and cognition: A comprehensive review. Psychophysiology 58: e13796. https://doi.org/10.1111/psyp.13796
    [43] Corbi G, Conti V, Filippelli A, et al. (2015) The role of physical activity on the prevention of cognitive impairment. Translational medicine@ UniSa 13: 42.
    [44] Vints WA, Levin O, Fujiyama H, et al. (2022) Exerkines and long-term synaptic potentiation: Mechanisms of exercise-induced neuroplasticity. Front Neuroendocrin 66: 1-27. https://doi.org/10.1016/j.yfrne.2022.100993
    [45] Di Raimondo D, Rizzo G, Musiari G, et al. (2020) Role of regular physical activity in neuroprotection against acute ischemia. Int J Mol Sci 21: 1-30. https://doi.org/10.3390/ijms21239086
    [46] Damirchi A, Tehrani BS, Alamdari KA, et al. (2014) Influence of aerobic training and detraining on serum BDNF, insulin resistance, and metabolic risk factors in middle-aged men diagnosed with metabolic syndrome. Clin J Sport Med 24: 513-518. https://doi.org/10.1097/JSM.0000000000000082
    [47] Kelly ME, Duff H, Kelly S, et al. (2017) The impact of social activities, social networks, social support and social relationships on the cognitive functioning of healthy older adults: a systematic review. Sys Rev 6: 1-18. https://doi.org/10.1186/s13643-017-0632-2
    [48] Sun Ln, Li Xl, Wang F, et al. (2017) High-intensity treadmill running impairs cognitive behavior and hippocampal synaptic plasticity of rats via activation of inflammatory response. J Neurosci Res 95: 1611-1620. https://doi.org/10.1002/jnr.23996
    [49] Baddeley A (2003) Working memory: looking back and looking forward. Nat Rev Neurosci 4: 829-839. https://doi.org/10.1038/nrn1201
    [50] Gothe N, Pontifex MB, Hillman C, et al. (2013) The acute effects of yoga on executive function. J Phys Act Health 10: 488-495. https://doi.org/10.1123/jpah.10.4.488
    [51] Kramer AF, Hahn S, Cohen NJ, et al. (1999) Ageing, fitness and neurocognitive function. Nature 400: 418-419. https://doi.org/10.1038/22682
    [52] Zhidong C, Wang X, Yin J, et al. (2021) Effects of physical exercise on working memory in older adults: a systematic and meta-analytic review. Eur Rev Aging Phys A 18: 1-15. https://doi.org/10.1186/s11556-021-00272-y
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