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. 2026 Jun 15;13:1836969. doi: 10.3389/fvets.2026.1836969

Physical activity–induced myokine responses in major mammalian farm animal species: a mini-review

Annika Krause 1,†,, Katharina Metzger 1,*,†,, Birger Puppe 1,2,, Claudia Kalbe 1,
PMCID: PMC13312813  PMID: 42375509

Abstract

Physical activity, including related concepts such as locomotion, movement, and exercise, is a fundamental behavior in humans and animals and contributes to physical and mental health. Although physical activity is essential for maintaining skeletal muscle function, farm animals are often kept under housing conditions with limited space and restricted opportunities for locomotion. Skeletal muscle secretes myokines that contribute to interorgan crosstalk; however, the relationship between physical activity and myokine-related responses in farm animals remains poorly understood. To summarize the current state of knowledge, we conducted a systematic literature search in PubMed, Scopus, and Web of Science in April 2026, focusing on studies addressing physical activity and myokine-related outcomes in major mammalian farm animal species. In total, 35 studies were identified. These studies examined several myokines, including interleukin-6 (IL6), fibronectin type III domain-containing protein 5 (FNDC5/irisin), brain-derived neurotrophic factor (BDNF), myostatin (MSTN), and insulin-like growth factor 1 (IGF1). The included studies showed substantial heterogeneity in experimental design, activity assessment, biological sample type, and the type, intensity, and quantification of activity. Overall, the current literature provides preliminary but fragmented evidence that physical activity is associated with myokine-related responses. However, a major limitation is the lack of standardized and objective methods for quantifying physical activity in farm animals, particularly within voluntary, self-directed activity paradigms. Conceptually, farm-relevant studies combining objective activity monitoring with skeletal muscle and systemic myokine analyses are required to clarify how physical activity contributes to muscle biology, performance, health, and welfare in livestock species.

Keywords: animal welfare, exercise, farm animal, locomotion, myokine, physical activity

1. Introduction

Skeletal muscle in farm animals is of particular interest because it constitutes the primary source of meat. Consequently, farm animals have undergone decades of selective breeding for enhanced muscle growth. In pigs, for example, approximately 50% of total body mass consists of muscle (1, 2). Although locomotion is essential for the proper development and function of skeletal muscle, farm animals are typically housed in confined systems that provide limited opportunities for species-appropriate locomotor behavior (3). The ability to express such behavior is fundamental not only for skeletal muscle development and maintenance but also for overall animal welfare. Locomotor behavior can provide insights into behavioral disorders and health status and has important welfare implications. However, studies quantifying distances covered by farm animals in conventional housing systems and at different developmental stages remain scarce (4, 5). In free-range systems, locomotion is often estimated indirectly, for example, based on the distance between feeding and resting areas (6, 7).

The terms “physical activity,” “locomotion,” “movement,” and “exercise” refer to related but distinct concepts in human and animal research, although they are often used interchangeably. Physical activity encompasses any bodily movement produced by skeletal muscles that results in energy expenditure, including locomotion and exercise (8). Locomotion specifically refers to motor activity that results in displacement of the whole body in external space (9). Exercise is a subset of physical activity that is planned, structured, and repetitive, with the objective of improving or maintaining physical fitness (8, 10). Under commercial housing conditions, farm animals have limited opportunities for physical activity, and exercise in the strict sense is virtually absent. In contrast, extensive human research has demonstrated that physical activity reduces the risk of cardiovascular and metabolic diseases, decreases the incidence of several cancers, enhances brain function, and alleviates pain and depression (11).

In recent years, several molecular mediators underlying the beneficial effects of exercise have been identified (12). These factors are collectively referred to as “exerkines,” defined as signaling molecules released in response to acute or chronic exercise that act via endocrine, paracrine, and/or autocrine pathways (13, 14). The concept that humoral factors mediate the systemic effects of exercise has long been recognized. Pedersen et al. demonstrated that contracting human skeletal muscle releases interleukin-6 (IL6) into the circulation during prolonged exercise, thereby introducing the term “myokine” (15, 16). Since then, additional myokines have been identified, including myostatin [MSTN; (17)], fibronectin type III domain-containing protein 5 [FNDC5, also known as irisin; (18)], insulin-like growth factor 1 [IGF1; (19)], and brain-derived neurotrophic factor [BDNF; (20)]. The biological relevance of myokines has been widely reviewed (21–25). More recently, the concept of the “myokinome,” encompassing the entirety of myokines, has provided a new framework for understanding how skeletal muscle communicates with other organs (26). In farm animals, however, knowledge about the role of myokines remains limited. Initial evidence in pigs suggests distance-related differences in myogenic growth potential (5), indicating that physical activity may influence muscle biology in livestock species.

This mini-review aims to provide a concise overview of current evidence on the effects of different forms of physical activity on myokine-related responses in major mammalian farm animal species, including pigs, cattle, goats, and sheep.

2. Methodology

The literature search was conducted in April 2026 and was broadly guided by the PRISMA guidelines [Preferred Reporting Items for Systematic Reviews and Meta-Analyses; (77)]. Searches were performed in PubMed, Scopus, and Web of Science using three search concepts: (a) “farm animal” and related terms, (b) “physical activity” and related terms, and (c) “myokine” and related terms (Figure 1A), following Jardat and Lansade (27). The full search strings are provided in the Supplementary material S1. Concepts were enclosed in parentheses and combined using the Boolean operator AND to retrieve publications addressing all three search concepts.

Figure 1.

Figure includes a table and a flowchart. The table lists comprehensive literature search terms by concepts: farm animal, physical activity, and myokine. The flowchart summarizes the identification and screening process for studies on physical activity-induced myokine responses in farm animals, starting from 1,247 records down to 35 included articles, detailing exclusions at each stage.

Search strategy and flowchart overview of record identification, screening, and final study selection. The diagram was adapted from the systematic review flow diagram template by Page et al. (77): grey boxes were removed as recommended, and the central section was modified to include our study-specific data.

The farm animal concept included mammalian livestock species relevant to global red meat production, namely pigs, cattle, goats, and sheep (28). The physical activity concept included terms related to movement, locomotion, and exercise. The myokine concept included “myokine,” “exercise factor,” and specific myokines as defined by Severinsen and Pedersen (26), together with their official gene symbols (Supplementary material S2). Only English-language, peer-reviewed research articles were considered.

The article selection process is shown in Figure 1B. Briefly, duplicate records were removed before screening, either using the automated duplicate-detection tool in EndNote20 or manually (29). Titles were initially screened for publication type, language, and species. Abstracts of the remaining articles were then assessed, and records were excluded if they had an unsuitable publication type or species, described only in vitro studies, used ambiguous terminology unrelated to the search aims, or did not meet all search-concept criteria. The full texts of 38 articles were assessed for eligibility, of which six were excluded as irrelevant. The remaining 32 publications were subjected to a snowballing approach (30), which identified three additional studies and resulted in a final set of 35 articles.

3. Results

The species-specific analysis showed that studies addressing physical activity and myokine-related outcomes was identified in pigs [n = 18; (5, 31–37, 39–44, 55, 56, 60, 66)], followed by cattle [n = 13; (45, 47–54, 57–59, 61), sheep [n = 2; (46, 62)], and goats [n =  2; (38, 73)]. However, many studies were not originally designed as exercise- or activity-based myokine studies, but examined myokine-related markers within broader biomedical, nutritional, metabolic, reproductive, immune, or welfare contexts.

Across the identified studies, physical activity was assessed and quantified in markedly different ways (Table 1). Some studies objectively characterized the activity stimulus, whereas others used indirect proxies, such as housing conditions or environmental enrichment, or considered activity within frameworks in which it was not the primary exposure. Among studies that explicitly quantified physical activity—a key prerequisite for linking activity to potential myokine-related responses—two main methodological approaches were distinguished: forced exercise paradigms, marked in red in Table 1, and voluntary or spontaneous activity assessments, marked in green.

Table 1.

Overview of studies investigating physical activity–induced effects on myokines in major mammalian farm animal species.

Physical activity Quantification method Research area Farm animal species Myokine Refs.
Quantified
Exercise training Treadmill [same as 32] Medical research/tissue metabolism Pig* FNDC5 (33)
Exercise training Treadmill [45–85 min, 5 days/week, 16–20 weeks, 2.5–5 mph] Medical research/cardiovascular disease Pig* IL6 (32)
Exercise training Treadmill [same as 32] Medical research/cardiovascular disease Pig* IL6 (36)
Exercise training Treadmill [same as 32] Medical research/cardiovascular disease Pig* IL6 (37)
Exercise training Treadmill [30 min, 4 days/week, 4 weeks; warm-up, 3–4 km/h] Medical research/osteoarthritis Pig* IL6 (35)
Exercise training Treadmill [15 min, 2/day, 1.8 km/h] Immunity/stress Pig IL6 (31)
Exercise training Treadmill [85 min, 5 days/week, 16–20 weeks, 7–12 km/h, 8 km/day] Medical research/cardiovascular. Disease Pig* IGF1 (34)
Exercise training Treadmill [65–75 min, 5 days/week, 14 weeks, 4–6 mph] Medical research/cardiovascular disease Pig* IGF1 (66)
Exercise training Parcourse [50 days 7.5 km/day, ø speed 4.61 km/h] Metabolism/nutrition Goat IGF1 (38)
Exercise training Animal hot walker [20–90 min, 12 weeks, 2.5–4.5 mph] Medical research/cardiovascular disease Goat IL6 (73)
Locomotor activity Video-based VideoMotionTracker® distance [m/24 h] Metabolism/animal welfare Pig BDNF, IGF1, MSTN (5)
Walking Video recorded [ethogram; proportion of time] Animal welfare Pig IGF1, BDNF (40)
Walking Video recorded [ethogram; proportion of time] Animal welfare Pig BDNF (41)
Play behavior Video recorded [ethogram; frequency] Animal welfare/auditory enrichment Pig [*] IL6 (42)
General activity Video-based motion detection PIGLwin software [% of time] Neurodevelopment/inflammation Pig IL6 (43)
General activity Video-based motion detection PIGLwin software [counts, %] Neurodevelopment/behavior Pig IGF1 (39)
General activity Live behavioral observation [ethogram, 10-min isolation test] Immunity/stress Sheep IL6 (46)
Walking Live behavioral observation [proportion of diurnal time] Metabolism/nutrition Cattle IGF1 (45)
Targeted activity Human-approach related activity [mean time to approach, s] Metabolism/nutrition (LPS challenge) Pig IL6 (44)
Locomotor activity Collar system daily activity [mov/h] Reproduction/estrus detection Cattle IGF1 (48)
Locomotor activity Pedometer [intensity (RI), duration (h)] Reproduction/estrus detection Cattle IGF1 (50)
Locomotor activity Pedometer [intensity index, duration (h)] Reproduction/estrus detection Cattle IGF1 (51)
Locomotor activity Pedometer [motion index, min/day, steps/day] Metabolism/nutrition Cattle IGF1 (52)
Locomotor activity Motion sensor [motion index, min/day, steps/day] Metabolism/performance Cattle IGF1 (53)
Locomotor activity Motion sensor [motion index, steps/day, laying bouts] Metabolism/performance Cattle IGF1 (54)
Locomotor activity Data logger [h/day] Metabolism/nutrition Cattle IGF1 (47)
Locomotor activity Data logger [time min/day; dur min/bout; freq bouts/day] Immunity/heat stress Cattle IGF1 (49)
Without quantification
Locomotor function Scoring [1–5, no lameness—extreme] Metabolism/nutrition Cattle IGF1 (57)
Locomotor function Scoring [1–5; lameness—nonexistent] Muscular development Cattle MSTN (58)
Locomotor function Porcine Thoracic Injury Behavior Scale [score 1–10] Medical research/spinal cord injury Pig* IL6 (55)
Locomotor function Porcine Thoracic Injury Behavior Scale [score 1–10] Medical research/spinal cord injury Pig* IL6 (56)
Exhaustive exercise No [max. 10 km in 3 h] Metabolism Cattle MSTN (59)
Indirect activity No Different housing systems Cattle BDNF, IL6 (61)
Indirect activity No Different housing systems Sheep IL6 (62)
Indirect activity No Animal welfare/environmental enrichment Pig BDNF (60)

BDNF, brain-derived neurotrophic factor; FNDC5, fibronectin type III domain containing 5 (also known as irisin); IGF1, insulin-like growth factor 1; IL6, interleukin 6; MSTN, myostatin; Categorization based on voluntariness: red = forced, green = voluntary; Pig studies involving minipigs are marked with an asterisk*, hybrids between conventional pigs breeds and minipigs are marked with an asterisk in square brackets [*].

Forced exercise studies exposed animals to externally imposed, standardized activity protocols with predefined duration, intensity, frequency, and/or distance. This approach was used almost exclusively in porcine biomedical or translational exercise-training studies (31–37, 66). These designs are closest to classical exercise–myokine research in humans and rodents, and the identified treadmill studies therefore used minipigs as experimental models rather than conventional agricultural pig breeds. Their main advantage is the high degree of standardization and reproducibility, as key activity characteristics can be controlled. The treadmill-based studies investigated whether defined exercise was associated with changes in myokine-related, inflammatory, metabolic, vascular, or cardiovascular markers, including IL6- or IGF1-related outcomes. Among them, Fain et al. (33) provided the most direct activity–myokine approach by examining the FNDC5 pathway after exercise training. In goats, forced walking provided a defined locomotor stimulus, but did not clearly alter the investigated growth- and metabolism-related markers, including IGF-related pathways (38). Overall, forced physical activity studies in farm animal species approximate classical human and rodent exercise–myokine research, but evidence for direct activity-induced changes in myokine-related markers remains heterogeneous and context-dependent.

A second group of studies assessed voluntary or spontaneous physical activity within the animals’ housing environment. These studies are particularly relevant for farm-animal research because they capture self-motivated activity under conditions closer to routine production systems. However, they differed substantially in the precision and type of activity quantification. Some studies used video-based tracking, motion detection, or behavioral analysis to quantify distance covered, walking, play, exploration, locomotor activity, behavioral complexity, or time spent in active behaviors (5, 39–43). Others relied on direct behavioral observation, recording the occurrence or duration of behaviors such as walking, grazing, exploration, or approach behavior (44–46). A further group used objective individual-level measures based on sensors, accelerometers, pedometers, or data loggers, including step counts, walking time, motion indices, dynamic body acceleration, or posture changes (47–54). Despite these methodological differences, all approaches assessed activity under voluntary conditions, allowing animals to express self-motivated movement rather than being exposed to imposed exercise.

Most voluntary-activity studies did not assess classical circulating myokines as direct responses to physical activity. Instead, they investigated muscle-, metabolic-, reproductive-, immune-, or stress-related markers while including activity as a behavioral or physiological variable. Among these, Kalbe et al. (5) provided the most rigorous quantification of voluntary locomotor activity and indicated that the IGF2/MSTN mRNA ratio may serve as a sensitive molecular indicator of locomotor activity in pigs. Other video-based behavioral studies linked activity-related behaviors to growth factor, neurotrophic, immune, or developmental outcomes, including IGF1, BDNF-related expression, or IL6 (39–43). Together, these studies suggest that quantified voluntary activity in mammalian farm animals may be associated with molecular pathways involved in activity-dependent plasticity, neurodevelopment, or immune-related signaling. However, in most cases, metabolic hormones or immune/inflammatory markers, including IGF1 or IL6, were investigated within frameworks such as nutrition, stress, reproduction, or health, rather than as direct activity-induced myokine responses (44–54).

A further group of studies referred to physical activity or locomotion in a broader experimental context but did not quantify physical activity as a defined exposure. Several studies assessed locomotion only indirectly within forced-activity paradigms and were primarily designed as nutritional, medical, or rehabilitation-related investigations rather than as experimental activity studies (55–58). This includes the scoring of hindlimb movements in spinal cord injury models, where locomotion was evaluated mainly as part of functional recovery or rehabilitation rather than as a defined activity stimulus (55, 56). Another study focused more directly on muscle- and myokine-related signaling pathways, but did not directly measure physical activity; therefore, conclusions regarding activity-induced myokine regulation remain limited (59). In contrast, other studies used housing conditions or environmental modifications, such as increased space allowance, as indirect proxies for higher voluntary activity while assessing BDNF, IGF1, IL6, or MSTN-related pathways (60–62). In pigs, environmental enrichment appeared to be associated with increased serum BDNF level (60). However, because actual activity levels or distance covered were not objectively assessed, it remains unclear whether these effects were driven by enrichment per se, increased physical activity, or other environmental and behavioral factors.

Finally, myokine-related outcomes were measured in diverse biological compartments, including skeletal muscle, blood, adipose tissue, reproductive tissues, brain, intestine, vascular tissue, cerebrospinal fluid, and bone. However, only few studies assessed markers directly in skeletal muscle, the primary site of activity-induced myokine production, including FNDC5, MSTN, IGF-related transcripts, and BDNF (5, 33). Thus, most evidence reflects circulating or tissue-specific associations rather than direct muscle-derived myokine secretion in response to physical activity.

4. Discussion

This mini-review shows that evidence on physical activity and myokine-related responses in major mammalian farm animal species remains limited and heterogeneous. Although our systematic literature search identified 35 studies, only few were specifically designed to investigate myokine responses triggered by physical activity. Most studies assessed myokine-related markers within broader biomedical, nutritional, metabolic, reproductive, immune, or welfare contexts. Thus, the current literature provides indications of potential links between physical activity, muscle biology, and systemic signaling, but only limited evidence for direct muscle-derived myokine secretion.

Based on evidence from human and laboratory animal research, skeletal muscle is a key mediator of the physiological effects of physical activity (63). The concept that humoral factors mediate the systemic benefits of exercise is well established, and contracting muscle releases myokines, such as IL6, FNDC5, BDNF, and IGF1, thereby contributing to interorgan crosstalk (26, 64, 65). In the present mini-review, we focused on myokines well established in human exercise research and relevant to farm-animal studies. IL6 was the first myokine to be identified and remains one of the most intensively studied. However, it is also a cytokine associated with various disease states and is secreted by both skeletal muscle and activated immune cells (67, 68). MSTN is an inhibitor of muscle growth and is particularly relevant in farm animals because of its direct link to muscle development and carcass traits (17, 69). A potential functional counterpart to MSTN is IGF1, a key regulator of muscle metabolism (64, 65). IGF1 was frequently addressed in the reviewed studies, but was investigated in diverse contexts, including voluntary locomotion (5), forced walking (34), metabolism (53), neurodevelopment (39), and reproduction (48). FNDC5 represents another key exercise-associated factor, but was addressed only in the treadmill-trained pig study by Fain et al. (33). Both FNDC5 and BDNF are considered important components of a neuroprotective network (70). Although BDNF is expressed in skeletal muscle, it is not substantially released into the circulation (71); rather, it plays a pivotal role in linking physical activity to brain health and cognitive function (20, 72).

A central finding of this mini-review was the marked variation in how physical activity was defined and quantified. This variation limits study comparability and determines how observed myokine-related responses can be interpreted. Forced exercise studies, often conducted in minipigs rather than conventional agricultural pig breeds, provide standardized activity exposure and therefore most closely resemble classical exercise–myokine research in humans and rodents. These studies allow control over duration, intensity, frequency, and distance, and have examined inflammatory, metabolic, cardiovascular, regenerative, or growth-related outcomes, including FNDC5-, IL6-, and IGF-related markers (31, 32, 35–38, 66, 73). For example, Fain et al. (33) investigated FNDC5 responses in treadmill-trained pigs after 16–20 weeks of training, although exercise did not increase FNDC5 mRNA or protein expression in skeletal muscle. Although these approaches are methodologically robust and demonstrate the value of controlled activity exposure, their relevance for conventional livestock production is limited because the activity is externally imposed and typically involves biomedical models rather than agricultural breeds. In modern livestock production, increasing emphasis is placed on animal-friendly housing and welfare, including the ability of animals to express self-directed and self-motivated behavioral activity.

In contrast, voluntary-activity studies are more relevant for farm-animal research because they capture self-motivated locomotion under housing and management conditions closer to routine production systems. However, these studies varied widely in activity assessment, ranging from video tracking and behavioral observation to sensor-based measures, which limits direct comparability. A particularly strong example is the study by Kalbe et al. (5), in which voluntary locomotion in pigs was quantified at the individual level as walking distance using video tracking. This voluntary locomotor behavior influenced skeletal muscle expression of genes involved in myogenesis and muscle growth, including MSTN as a classical myokine, as well as the growth factor IGF2 and myogenic transcription factors such as MRF4 and MYOD (5). Thus, this study provides one of the clearest links between voluntary locomotor activity under conventional housing conditions and molecular adaptations in pig skeletal muscle.

Enrichment-related studies further quantified behavior using ethograms, including foraging, exploration, walking, play behavior, and inactivity. However, this approach captures the duration or proportion of behavioral categories rather than individual distance covered, step count, or speed (40, 41). In Brown et al. (41), enrichment-induced upregulation of genes related to neuronal activity and synaptic plasticity coincided with peaks in locomotion, consistent with findings in rodents suggesting reduced neuroinflammation and enhanced neuroprotection. In pigs, enrichment was associated with neurotrophic changes, including increased serum BDNF level and a tendency toward higher BDNF expression in the frontal cortex (40, 60). BDNF is essential for neuronal survival and plasticity, and elevated brain BDNF levels are associated with stress resilience (74). However, it remains unclear whether these effects result from enrichment itself, increased physical activity, greater distance covered, or other enrichment-related stimuli.

Sensor-based studies further demonstrate that voluntary activity can be assessed objectively and at the individual-animal level under practical farm conditions, at least in cattle. Data loggers have been used to quantify steps, motion index, lying and standing behavior, or movement activity, and these measures have been related to endocrine, metabolic, or physiological parameters, including IGF1 and health status. For example, IGF1 or IGF-related gene expression was measured in grazing, calf development, or reproductive contexts, where activity was related to grazing behavior or estrous expression rather than to a defined distance covered (47–52). Conceptually, these studies link farm-animal research to human exercise-myokine research through the role of IGF1 in growth, metabolic regulation, and muscle adaptation. However, IGF1 should be interpreted cautiously because circulating IGF1 reflects systemic endocrine regulation and is not necessarily a direct skeletal muscle-derived exercise signal (64). Thus, these studies show how activity and metabolic physiology can be assessed under practical farm conditions in cattle, but they were not designed to test whether voluntary physical activity directly induces myokine regulation.

Taken together, the current literature provides important methodological approaches, but not yet a coherent body of evidence. Forced-exercise studies provide a high degree of standardization because physical activity is clearly quantified, whereas voluntary-activity studies are more relevant for farm animals but often quantify physical activity less precisely or measure myokine-related factors in broader biological contexts. This indicates an important research gap. Future studies should combine objective, individual-level activity monitoring with targeted assessment of myokine-related markers in skeletal muscle and circulation. A promising approach would be to develop experimental behavioral paradigms in which animals can voluntarily engage in quantifiable physical activity, for example through self-initiated treadmill access or other operant locomotor challenges embedded in cognitive environmental enrichment. In domestic pigs, activation of intrinsic reward and motivational systems through cognitive enrichment has been shown to markedly increase voluntary behavioral activity, including quantified locomotor activity (75, 76). Conceptually, such approaches are particularly valuable in farm-animal research because they support the interpretation of physiological data in contexts more closely related to natural behavioral needs and animal welfare than to basic mechanistic research, as is often the case in laboratory and biomedical studies. Moreover, these approaches would preserve the voluntary nature of physical activity, while advanced video monitoring, automated AI-based behavioral analysis, and sensor-based technologies could quantify spontaneous locomotor activity under farm-relevant conditions. Reproducible and standardized protocols for behavioral activity assessment and physiological sampling, together with careful consideration of confounding factors such as breed, age, sex, housing system, nutrition, and health status, will be essential to distinguish direct effects of physical activity from broader environmental or management-related influences.

In conclusion, the current literature provides preliminary but fragmented evidence that physical activity is associated with myokine-related responses in mammalian livestock species. Forced-exercise studies offer a high degree of experimental and methodological control, but are largely limited to biomedical minipig models. In contrast, voluntary-activity studies are more relevant to livestock housing and welfare, but often lack precise activity quantification or direct evidence of muscle-derived myokine secretion. Clear methodological improvements are therefore needed in experimental design and analysis of physical activity as well as in the selection and measurement of myokines. Conceptually, farm-relevant studies combining objective activity monitoring with skeletal muscle and systemic myokine analyses are required to clarify how physical activity contributes to muscle biology, health, and welfare in livestock species.

Funding Statement

The author(s) declared that financial support was received for this work and/or its publication. This study is part of the KI-TIERWOHL project (EXF-25-1032), which is funded by the EFRE program 2021-2027 of the state of Mecklenburg-Western Pomerania. The publication of this article was funded by the Open-Access Fund of the Research Institute for Farm Animal Biology (FBN).

Footnotes

Edited by: Edward Narayan, Southern Cross University, Australia

Reviewed by: Irfan Arif, University of Southern Queensland, Australia

Author contributions

AK: Conceptualization, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing. KM: Conceptualization, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing. BP: Conceptualization, Writing – review & editing. CK: Conceptualization, Writing – review & editing.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was used in the creation of this manuscript. The authors declare that Generative AI (DeepL SE) was used solely for language editing, including minor adjustments to selected terms and improvements in grammar and syntax to enhance the readability of the text. Afterwards, the English text was checked by native English speakers using an English editing service (American Journal Experts; https://www.aje.com/). All content was reviewed, edited, and approved by the authors, who retain full responsibility for the manuscript.

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Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fvets.2026.1836969/full#supplementary-material

Table_1.DOCX (24.2KB, DOCX)

References

  • 1.Rehfeldt C, Fiedler I, Dietl G, Ender K. Myogenesis and postnatal skeletal muscle cell growth as influenced by selection. Livest Prod Sci. (2000) 66:177–88. doi: 10.1016/S0301-6226(00)00225-6 [DOI] [Google Scholar]
  • 2.Lösel D, Franke A, Kalbe C. Comparison of different skeletal muscles from growing domestic pigs and wild boars. Arch Tierz. (2013) 76:766–77. doi: 10.7482/0003-9438-56-076 [DOI] [Google Scholar]
  • 3.Spitz F, Janeau G. Spatial strategies: an attempt to classify daily movements of wild boar. Acta Theriol. (1990) 35:129–49. doi: 10.4098/AT.ARCH.90-14 [DOI] [Google Scholar]
  • 4.Brendle J, Hoy S. Investigation of distances covered by fattening pigs measured with VideoMotionTracker®. Appl Anim Behav Sci. (2011) 132:27–32. doi: 10.1016/j.applanim.2011.03.004 [DOI] [Google Scholar]
  • 5.Kalbe C, Zebunke M, Lösel D, Brendel J, Hoy S, Puppe B. Voluntary locomotor activity promotes myogenic growth potential in domestic pigs. Sci Rep. (2018) 8:2533. doi: 10.1038/s41598-018-20652-2, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Jensen P. Observation on the maternal-behavior of free-ranging domestic sows. Appl Anim Behav Sci. (1986) 16:131–42. doi: 10.1016/0168-1591(86)90105-X [DOI] [Google Scholar]
  • 7.Lachica M, Aguilera JF. Estimation of the energy costs of locomotion in the Iberian pig (Sus mediterraneus). Br J Nutr. (2000) 83:35–41. doi: 10.1017/S0007114500000064, [DOI] [PubMed] [Google Scholar]
  • 8.Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. (1985) 100:126–31. [PMC free article] [PubMed] [Google Scholar]
  • 9.Latash ML. The bliss (not the problem) of motor abundance (not redundancy). Exp Brain Res. (2012) 217:1–5. doi: 10.1007/s00221-012-3000-4, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Dasso NA. How is exercise different from physical activity? A concept analysis. Nurs Forum. (2019) 54:45–52. doi: 10.1111/nuf.12296, [DOI] [PubMed] [Google Scholar]
  • 11.Stranahan AM, Martin B, Maudsley S. Anti-inflammatory effects of physical activity in relationship to improved cognitive status in humans and mouse models of Alzheimer's disease. Curr Alzheimer Res. (2012) 9:86–92. doi: 10.2174/156720512799015019, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Vega RB, Konhilas JP, Kelly DP, Leinwand LA. Molecular mechanisms underlying cardiac adaptation to exercise. Cell Metab Rev. (2017) 25:1012–26. doi: 10.1016/j.cmet.2017.04.025, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Safdar A, Saleem A, Tranopolsky MA. The potential of endurance exercise-derived exosomes to treat metabolic diseases. Nat Rev Endocrinol. (2016) 12:504–17. doi: 10.1038/nrendo.2016.76, [DOI] [PubMed] [Google Scholar]
  • 14.Chow LS, Gerszten RE, Taylor JM, Pedersen BK, van Praag H, Trappe S, et al. Exerkines in health, resilience and disease. Nat Rev Endocrinol. (2022) 18:273–89. doi: 10.1038/s41574-022-00641-2, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Steensberg A, van Hall G, Osasda T, Sacchetti M, Saltin B, Klarlund PB. Production of interleukin-6 in contracting human skeletal muscles can account for the exercise-induced increase in plasma interleukin-6. J Physiol. (2000) 529:237–42. doi: 10.1111/j.1469-7793.2000.00237.x, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Pedersen BK, Steensberg A, Keller P, Keller C, Fischer C, Hiscock N, et al. Muscle-derived interleukin-6: lipolytic, anti-inflammatory and immune regulatory effects. Pflugers Arch. (2003) 446:9–16. doi: 10.1007/s00424-002-0981-z, [DOI] [PubMed] [Google Scholar]
  • 17.McPherron AC, Lawler AM, Lee SJ. Regulation of skeletal muscle mass in mice by a new TGF-beta superfamily member. Nature. (1997) 387:83–90. doi: 10.1038/387083a0, [DOI] [PubMed] [Google Scholar]
  • 18.Boström P, Wu J, Jedrychowski MP, Korde A, Ye L, Lo JC, et al. A PGC1-α-dependent myokine that drives brown-fat-like development of white fat and thermogenesis. Nature. (2012) 481:463–8. doi: 10.1038/nature10777, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Yakar S, Rosen CJ, Beamer WG, Ackert-Bicknell CL, Wu Y, Liu J-L, et al. Circulating levels of IGF1 directly regulate bone growth and density. J Clin Invest. (2002) 110:771–81. doi: 10.1172/JCI15463 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Pedersen BK. Physical activity and muscle–brain crosstalk. Nat Rev Endocrinol. (2019) 15:383–92. doi: 10.1038/s41574-019-0174-x, [DOI] [PubMed] [Google Scholar]
  • 21.Lee JH, Jun H-S. Role of myokines in regulating skeletal muscle mass and function. Front Physiol. (2019) 10:42. doi: 10.3389/fphys.2019.00042, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Piccirillo R. Exercise-induced myokines with therapeutic potential for muscle wasting. Front Physiol. (2019) 10:287. doi: 10.3389/fphys.2019.00287, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Bay ML, Pedersen BK. Muscle-organ crosstalk: focus on immunometabolism. Front Physiol. (2020) 11:567881. doi: 10.3389/fphys.2020.567881, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Laurens C, Bergouignan A, Moro C. Exercise-released myokines in the control of energy metabolism. Front Physiol. (2020) 11:91. doi: 10.3389/fphys.2020.00091, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Rentería I, García-Suárez PC, Fry AC, Moncada-Jiménez J, Machado-Parra JP, Antunes BM, et al. The molecular effects of BDNF synthesis on skeletal muscle: a mini-review. Front Physiol. (2022) 13:934714. doi: 10.3389/fphys.2022.934714, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Severinsen MCK, Pedersen BK. Muscle–organ crosstalk: the emerging roles of myokines. Endocr Rev. (2020) 41:594–609. doi: 10.1210/endrev/bnaa016, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Jardat P, Lansande L. Cognition and the human–animal relationship: a review of the sociocognitive skills of domestic mammals toward humans. Anim Cogn. (2022) 25:369–84. doi: 10.1007/s10071-021-01557-6 [DOI] [PubMed] [Google Scholar]
  • 28.Scartezini ADA, Sarti FM. Trends in global trade of red meats from 1986 to 2023: a complex network analysis with implications for public health. J. (2025) 8:35. doi: 10.3390/j8030035, 30654563 [DOI] [Google Scholar]
  • 29.Jorgensen CC, Thöne-Reineke C, Moscovice LR, Gimsa U. Critical biological systems linking early-life stress to later-life outcomes: a systematic review of animal models. Neurosci Biobehav Rev. (2025) 179:106425. doi: 10.1016/j.neubiorev.2025.106425, [DOI] [PubMed] [Google Scholar]
  • 30.Wohlin C. Guidelines for snowballing in systematic literature studies and a replication in software engineering (2014). Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering 1–10. [Google Scholar]
  • 31.Ciepielewski ZM, Stojek W, Borman A, Myslinska D, Palczynska P, Kamyczek M. The effects of ryanodine receptor (RYR1) mutation on natural killer cell cytotoxicity, plasma cytokines and stress hormones during acute intermittent exercise in pigs. Res Vet Sci. (2016) 105:77–86. doi: 10.1016/j.rvsc.2016.01.012, [DOI] [PubMed] [Google Scholar]
  • 32.Company JM, Booth FW, Laughlin MH, Arce-Esquivel AA, Sacks HS, Bahouth SW, et al. Epicardial fat gene expression after aerobic exercise training in pigs with coronary atherosclerosis: relationship to visceral and subcutaneous fat. J Appl Physiol. (2010) 109:1904–12. doi: 10.1152/japplphysiol.00621.2010, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Fain JN, Company JM, Booth FW, Laughlin MH, Padilla J, Jenkins NT, et al. Exercise training does not increase muscle FNDC5 protein or mRNA expression in pigs. Metabolism. (2013) 62:1503–11. doi: 10.1016/j.metabol.2013.05.021, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Jankord R, Turk JR, Schadt JC, Casati J, Ganjam VK, Price EM, et al. Sex difference in link between interleukin-6 and stress. Endocrinology. (2007) 148:3758–64. doi: 10.1210/en.2006-1650, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Lin CC, Chu CJ, Chou PH, Liang CH, Liang PI, Chang NJ. Beneficial therapeutic approach of acellular PLGA implants coupled with rehabilitation exercise for osteochondral repair: a proof of concept study in a minipig model. Am J Sports Med. (2020) 48:2796–807. doi: 10.1177/0363546520940306, [DOI] [PubMed] [Google Scholar]
  • 36.Padilla J, Simmons GH, Davis JW, Whyte JJ, Zderic TW, Hamilton MT, et al. Impact of exercise training on endothelial transcriptional profiles in healthy swine: a genome-wide microarray analysis. Am J Physiol Heart Circ Physiol. (2011) 301:H555–64. doi: 10.1152/ajpheart.00065.2011, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Simmons GH, Padilla J, Jenkins NT, Laughlin MH. Exercise training and vascular cell phenotype in a swine model of familial hypercholesterolaemia: conduit arteries and veins. Exp Physiol. (2014) 99:454–65. doi: 10.1113/expphysiol.2013.075838, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.D'Oliveira MC, Vedovatto M, Neto IMC, Coelho RN, Morais MD, Gomes MDB, et al. Effect of walking exercise and nutritional plan on goat performance. Livest Sci. (2012) 246:104450. doi: 10.1016/j.livsci.2021.104450 [DOI] [Google Scholar]
  • 39.Andersen AD, Sangild PT, Munch SL, van der Beek EM, Renes IB, Ginneken C, et al. Delayed growth, motor function and learning in preterm pigs during early postnatal life. Am J Physiol Regul Integr Comp Physiol. (2016) 310:R481–92. doi: 10.1152/ajpregu.00349.2015 [DOI] [PubMed] [Google Scholar]
  • 40.Brown SM, Peters R, Lawrence AB. Up-regulation of IGF1 in the frontal cortex of piglets exposed to an environmentally enriched arena. Physiol Behav. (2017) 173:285–92. doi: 10.1016/j.physbeh.2017.02.030, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Brown SM, Bush SJ, Summers KM, Hume DA, Lawrence AB. Environmentally enriched pigs have transcriptional profiles consistent with neuroprotective effects and reduced microglial activity. Behav Brain Res. (2018) 350:6–15. doi: 10.1016/j.bbr.2018.05.015, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Nian HY, Zhang RX, Ding SS, Wang YL, Li JF, Liu HG, et al. Emotional responses of piglets under long-term exposure to negative and positive auditory stimuli. Domest Anim Endocrinol. (2023) 82:106771. doi: 10.1016/j.domaniend.2022.106771, [DOI] [PubMed] [Google Scholar]
  • 43.Sun J, Pan X, Christiansen LI, Yuan XL, Skovgaard K, Chatterton DEW, et al. Necrotizing enterocolitis is associated with acute brain responses in preterm pigs. J Neuroinflammation. (2018) 15:180. doi: 10.1186/s12974-018-1201-x, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Koopmans SJ, van der Staay FJ, Le Floc'h N, Dekker R, van Diepen JTM, Jansman AJM. Effects of surplus dietary L-tryptophan on stress, immunology, behavior, and nitrogen retention in endotoxemic pigs. J Anim Sci. (2012) 90:241–51. doi: 10.2527/jas.2010-3372, [DOI] [PubMed] [Google Scholar]
  • 45.Claramunt M, Meikle A, Soca P. Metabolic hormones, grazing behaviour, offspring physical distance and productive response of beef cow grazing at two herbage allowances. Animal. (2020) 14:1520–8. doi: 10.1017/S1751731119003021, [DOI] [PubMed] [Google Scholar]
  • 46.Caroprese M, Albenzio M, Marzano A, Schena L, Annicchiarico G, Sevi A. Relationship between cortisol response to stress and behavior, immune profile, and production performance of dairy ewes. J Dairy Sci. (2010) 93:2395–403. doi: 10.3168/jds.2009-2604, [DOI] [PubMed] [Google Scholar]
  • 47.Bodrogi L, Csorba BB, Jurkovich V, Kiss G, Bagi Z, Bakony M, et al. Effect of ad libitum feeding of Holstein Friesian calves on immunological parameters and molecular stress on a transcriptional level. Saudi J Biol Sci. (2023) 30:103701. doi: 10.1016/j.sjbs.2023.103701, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Gaillard C, Barbu H, Sørensen MT, Sehested J, Callesen H, Vestergaard M. Milk yield and estrous behavior during eight consecutive estruses in Holstein cows fed standardized or high energy diets and grouped according to live weight changes in early lactation. J Dairy Sci. (2016) 99:3134–43. doi: 10.3168/jds.2015-10023, [DOI] [PubMed] [Google Scholar]
  • 49.Laporta J, Fabris TF, Skibiel AL, Powell JL, Hayen MJ, Horvath K, et al. In utero exposure to heat stress during late gestation has prolonged effects on the activity patterns and growth of dairy calves. J Dairy Sci. (2017) 100:2976–84. doi: 10.3168/jds.2016-11993, [DOI] [PubMed] [Google Scholar]
  • 50.Marques JCS, Maciel JPO, Denis-Robichaud J, Conceicao RS, Moore S, Piau T, et al. Progesterone concentrations during superovulation and estrous behavior affect post-estrus endometrial gene expression in Holstein heifers. J Dairy Sci. (2025) 108:10391–409. doi: 10.3168/jds.2025-26522, [DOI] [PubMed] [Google Scholar]
  • 51.Marques JCS, Maciel JPO, Denis-Robichaud J, Madureira AML, Conceicao RS, Moore S, et al. Endometrial gene expression of lactating Holstein cows: impact of pre-estrus progesterone and intensity of estrous expression. J Dairy Sci. (2025) 108:11651–71. doi: 10.3168/jds.2025-26521, [DOI] [PubMed] [Google Scholar]
  • 52.Thanner S, Schori F, Bruckmaier RM, Dohme-Meier F. Grazing behaviour, physical activity and metabolic profile of two Holstein strains in an organic grazing system. J Anim Physiol Anim Nutr. (2014) 98:1143–53. doi: 10.1111/jpn.12172, [DOI] [PubMed] [Google Scholar]
  • 53.van Hoeij RJ, Kok A, Bruckmaier RM, Haskell MJ, Kemp B, van Knegsel ATM. Relationship between metabolic status and behavior in dairy cows in week 4 of lactation. Animal. (2019) 13:640–8. doi: 10.1017/S1751731118001842, [DOI] [PubMed] [Google Scholar]
  • 54.Zhang MQ, Heirbaut S, Jing XP, Stefańska B, Vandaele L, De Neve N, et al. Systemic inflammation in early lactation and its relation to the cows' oxidative and metabolic status, productive and reproductive performance, and activity. J Dairy Sci. (2024) 107:7121–37. doi: 10.3168/jds.2023-24156, [DOI] [PubMed] [Google Scholar]
  • 55.Streijger F, Lee JHT, Chak J, Dressler D, Manouchehri N, Okon EB, et al. The effect of whole-body resonance vibration in a porcine model of spinal cord injury. J Neurotrauma. (2015) 32:908–21. doi: 10.1089/neu.2014.3707, [DOI] [PubMed] [Google Scholar]
  • 56.Streijger F, Lee JHT, Manouchehri N, Melnyk AD, Chak J, Tigchelaar S, et al. Responses of the acutely injured spinal cord to vibration that simulates transport in helicopters or mine-resistant-ambush-protected vehicles. J Neurotrauma. (2016) 33:2217–26. doi: 10.1089/neu.2016.4456, [DOI] [PubMed] [Google Scholar]
  • 57.Ramos JM, Sosa C, Ruprechter G, Pessina P, Carriquiry M. Effect of organic trace minerals supplementation during early postpartum on milk composition, and metabolic and hormonal profiles in grazing dairy heifers. Span J Agric Res. (2012) 10:681–9. doi: 10.5424/sjar/2012103-441-11 [DOI] [Google Scholar]
  • 58.Vallée A, Daures J, van Arendonk JAM, Bovenhuis H. Genome-wide association study for behavior, type traits, and muscular development in Charolais beef cattle. J Anim Sci. (2016) 94:2307–16. doi: 10.2527/jas.2016-0319, [DOI] [PubMed] [Google Scholar]
  • 59.Zhu L, Bai C, Wang X, Wei Z, Gu M, Zhou X, et al. Myostatin knockout limits exercise-induced reduction in bovine erythrocyte oxidative stress by enhancing the efficiency of the pentose phosphate pathway. Animals. (2022) 12:927. doi: 10.3390/ani12070927, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Rault JL, Lawrence AJ, Ralph CR. Brain-derived neurotrophic factor in serum as an animal welfare indicator of environmental enrichment in pigs. Domest Anim Endocrinol. (2018) 65:67–70. doi: 10.1016/j.domaniend.2018.05.007, [DOI] [PubMed] [Google Scholar]
  • 61.Favole A, Testori C, Bergagna S, Gennero MS, Ingravalle F, Costa B, et al. Brain-derived neurotrophic factor, kynurenine pathway, and lipid-profiling alterations as potential animal welfare indicators in dairy cattle. Animals. (2023) 13:1167. doi: 10.3390/ani13071167, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Bloor ID, Sébert SP, Saroha V, Gardner DS, Keisler DH, Budge H, et al. Sex differences in metabolic and adipose tissue responses to juvenile-onset obesity in sheep. Endocrinology. (2013) 154:3622–31. doi: 10.1210/en.2013-1207, [DOI] [PubMed] [Google Scholar]
  • 63.Chen W, Wang L, You W, Shan T. Myokines mediate the cross talk between skeletal muscle and other organs. J Cell Physiol. (2021) 236:2393–412. doi: 10.1002/jcp.30033, [DOI] [PubMed] [Google Scholar]
  • 64.Kraemer WJ, Ratamess NA, Hymer WC, Nindl BC, Fragala MS. Growth hormone(s), testosterone, insulin-like growth factors, and cortisol: roles and integration for cellular development and growth with exercise. Front Endocrinol. (2020) 11:33. doi: 10.3389/fendo.2020.00033, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Pedersen BK, Febbraio MA. Muscles, exercise and obesity: skeletal muscle as a secretory organ. Nat Rev Endocrinol. (2012) 8:457–65. doi: 10.1038/nrendo.2012.49, [DOI] [PubMed] [Google Scholar]
  • 66.Ahmad I, Gupta S, Faulkner P, Mullens D, Thomas M, Sytha SP, et al. Single-nucleus transcriptomics of epicardial adipose tissue from female pigs reveals effects of exercise training on resident innate and adaptive immune cells. Cell Commun Signal. (2024) 22:243. doi: 10.1186/s12964-024-01587-w, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Frei K, Malipiero UV, Leist TP, Zinkernagel RM, Schwab ME, Fontana A. On the cellular source and function of interleukin 6 produced in the central nervous system in viral diseases. Eur J Immunol. (1989) 19:689–94. doi: 10.1002/eji.1830190418, [DOI] [PubMed] [Google Scholar]
  • 68.Pedersen BK, Febbraio MA. Muscle as an endocrine organ: focus on muscle-derived Interleukin-6. Physiol Rev. (2008) 88:1379–406. doi: 10.1152/physrev.90100.2007, [DOI] [PubMed] [Google Scholar]
  • 69.Aiello D, Patel K, Lasagna E. The myostatin gene: an overview of mechanisms of action and its relevance to livestock animals. Anim Genet. (2018) 49:505–19. doi: 10.1111/age.12696, [DOI] [PubMed] [Google Scholar]
  • 70.Wrann CD, White JP, Salogiannnis J, Laznik-Bogoslavski D, Wu J, Ma D, et al. Exercise induces hippocampal BDNF through a PGC-1α/FNDC5 pathway. Cell Metab. (2013) 18:649–59. doi: 10.1016/j.cmet.2013.09.008, [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Matthews VB, Åström MB, Chan MHS, Bruce CR, Krabbe KS, Prelovsek O, et al. Brain-derived neurotrophic factor is produced by skeletal muscle cells in response to contraction and enhances fat oxidation via activation of AMP-activated protein kinase. Diabetologia. (2009) 52:1409–18. doi: 10.1007/s00125-009-1364-1, [DOI] [PubMed] [Google Scholar]
  • 72.Vaynman S, Ying Z, Gomez-Pinilla F. Hippocampal BDNF mediates the efficacy of exercise on synaptic plasticity and cognition. Eur J Neurosci. (2004) 20:2580–90. doi: 10.1111/j.1460-9568.2004.03720.x, [DOI] [PubMed] [Google Scholar]
  • 73.Regouski M, Galenko O, Doleac J, Olsen AL, Jacobs V, Liechty D, et al. Spontaneous atrial fibrillation in transgenic goats with TGF (transforming growth factor)-β1 induced atrial myopathy with endurance exercise. Circ Arrhythm Electrophysiol. (2019) 12:e007499. doi: 10.1161/CIRCEP.119.007499, [DOI] [PubMed] [Google Scholar]
  • 74.Mosaferi B, Babri S, Gisou Mohaddes G, Khamnei S, Mesgari M. Post-weaning environmental enrichment improves BDNF response of adult male rats. Int J Dev Neurosci. (2015) 46:108–14. doi: 10.1016/j.ijdevneu.2015.07.008, [DOI] [PubMed] [Google Scholar]
  • 75.Puppe B, Ernst K, Schön PC, Manteuffel G. Cognitive enrichment affects behavioural reactivity in domestic pigs. Appl Anim Behav Sci. (2007) 105:75–86. doi: 10.1016/j.applanim.2006.05.016 [DOI] [Google Scholar]
  • 76.Kalbe C, Puppe B. Long-term cognitive enrichment affects opioid receptor expression in the amygdala of domestic pigs. Genes Brain Behav. (2010) 9:75–83. doi: 10.1111/j.1601-183X.2009.00536.x, [DOI] [PubMed] [Google Scholar]
  • 77.Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. (2021) 372:n7. doi: 10.1136/bmj.n71 [DOI] [PMC free article] [PubMed] [Google Scholar]

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