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Ko HL, Manteca X, Llonch P. Consistency of convenience sampling order and its association with response to handling and weaning in domestic pigs (Sus scrofa). J Vet Behav 2023. [DOI: 10.1016/j.jveb.2023.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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Systematic review of animal-based indicators to measure thermal, social, and immune-related stress in pigs. PLoS One 2022; 17:e0266524. [PMID: 35511825 PMCID: PMC9070874 DOI: 10.1371/journal.pone.0266524] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 03/22/2022] [Indexed: 11/19/2022] Open
Abstract
The intense nature of pig production has increased the animals’ exposure to stressful conditions, which may be detrimental to their welfare and productivity. Some of the most common sources of stress in pigs are extreme thermal conditions (thermal stress), density and mixing during housing (social stress), or exposure to pathogens and other microorganisms that may challenge their immune system (immune-related stress). The stress response can be monitored based on the animals’ coping mechanisms, as a result of specific environmental, social, and health conditions. These animal-based indicators may support decision making to maintain animal welfare and productivity. The present study aimed to systematically review animal-based indicators of social, thermal, and immune-related stresses in farmed pigs, and the methods used to monitor them. Peer-reviewed scientific literature related to pig production was collected using three online search engines: ScienceDirect, Scopus, and PubMed. The manuscripts selected were grouped based on the indicators measured during the study. According to our results, body temperature measured with a rectal thermometer was the most commonly utilized method for the evaluation of thermal stress in pigs (87.62%), as described in 144 studies. Of the 197 studies that evaluated social stress, aggressive behavior was the most frequently-used indicator (81.81%). Of the 535 publications examined regarding immune-related stress, cytokine concentration in blood samples was the most widely used indicator (80.1%). Information about the methods used to measure animal-based indicators is discussed in terms of validity, reliability, and feasibility. Additionally, the introduction and wide spreading of alternative, less invasive methods with which to measure animal-based indicators, such as cortisol in saliva, skin temperature and respiratory rate via infrared thermography, and various animal welfare threats via vocalization analysis are highlighted. The information reviewed was used to discuss the feasible and most reliable methods with which to monitor the impact of relevant stressors commonly presented by intense production systems on the welfare of farmed pigs.
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Strauss ED, DeCasien AR, Galindo G, Hobson EA, Shizuka D, Curley JP. DomArchive: a century of published dominance data. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200436. [PMID: 35000444 PMCID: PMC8743893 DOI: 10.1098/rstb.2020.0436] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/21/2021] [Indexed: 11/18/2022] Open
Abstract
Dominance behaviours have been collected for many groups of animals since 1922 and serve as a foundation for research on social behaviour and social structure. Despite a wealth of data from the last century of research on dominance hierarchies, these data are only rarely used for comparative insight. Here, we aim to facilitate comparative studies of the structure and function of dominance hierarchies by compiling published dominance interaction datasets from the last 100 years of work. This compiled archive includes 436 datasets from 190 studies of 367 unique groups (mean group size 13.8, s.d. = 13.4) of 135 different species, totalling over 243 000 interactions. These data are presented in an R package alongside relevant metadata and a tool for subsetting the archive based on biological or methodological criteria. In this paper, we explain how to use the archive, discuss potential limitations of the data, and reflect on best practices in publishing dominance data based on our experience in assembling this dataset. This archive will serve as an important resource for future comparative studies and will promote the development of general unifying theories of dominance in behavioural ecology that can be grounded in testing with empirical data. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.
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Affiliation(s)
- Eli D. Strauss
- Department of Collective Behavior, Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany
- School of Biological Sciences, University of Nebraska Lincoln, Lincoln, NE, 68588-0118 USA
| | - Alex R. DeCasien
- Department of Anthropology, New York University, New York, NY, USA
- New York Consortium in Evolutionary Primatology, New York, NY, USA
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MA, USA
| | - Gabriela Galindo
- Department of Anthropology, New York University, New York, NY, USA
| | - Elizabeth A. Hobson
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Daizaburo Shizuka
- School of Biological Sciences, University of Nebraska Lincoln, Lincoln, NE, 68588-0118 USA
| | - James P. Curley
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
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An approach to assess stress in response to drive hunts using cortisol levels of wild boar (Sus scrofa). Sci Rep 2021; 11:16381. [PMID: 34385546 PMCID: PMC8361105 DOI: 10.1038/s41598-021-95927-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 08/02/2021] [Indexed: 11/25/2022] Open
Abstract
Hunting can easily be linked to stress in wildlife. Drive hunts performed two to three times in one area during the respective hunting period, are thought to decrease the pressure hunting places on wildlife. Nevertheless, the expression of cortisol—one of the main mammalian stress hormones—is considered to have negative impacts on animals’ well-being if expressed excessively, which may occur during some (especially repeated) hunting events. We explored the effect of drive hunts on cortisol levels in wild boar in Lower Saxony, Germany, compared these cortisol levels to reference values given by a similar study, and investigated the effect of age, sex, and pregnancy. Blood collected from wild boar shot on drive hunts was analysed using a radioimmunoassay. As expected, we observed elevated cortisol levels in all samples, however, we still found significant differences between age groups and sexes, as well as an influence of pregnancy on cortisol levels. The effect of drive hunts on cortisol levels appears to be weaker than predicted, while the effects of other variables, such as sex, are distinct. Only half of the evaluated samples showed explicitly increased cortisol levels and no significant differences were found between sampling months and locations. Group living animals and pregnant females showed significantly higher cortisol levels. The impact of hunting is measurable but is masked by natural effects such as pregnancy. Thus, we need more information on stress levels in game species.
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Prims S, Van Raemdonck G, Vanden Hole C, Van Cruchten S, Van Ginneken C, Van Ostade X, Casteleyn C. On the characterisation of the porcine gland-specific salivary proteome. J Proteomics 2019; 196:92-105. [DOI: 10.1016/j.jprot.2019.01.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 01/14/2019] [Accepted: 01/25/2019] [Indexed: 12/22/2022]
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Li Z, Yang HY, Wang Y, Zhang ML, Liu XR, Xiong Q, Zhang LN, Jin Y, Mou LS, Liu Y, Li RF, Rao Y, Dai YF. Generation of tryptophan hydroxylase 2 gene knockout pigs by CRISPR/Cas9-mediated gene targeting. J Biomed Res 2017; 31:445-452. [PMID: 28866660 PMCID: PMC5706437 DOI: 10.7555/jbr.31.20170026] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Unbalanced brain serotonin (5-HT) levels have implications in various behavioral abnormalities and neuropsychiatric disorders. The biosynthesis of neuronal 5-HT is regulated by the rate-limiting enzyme, tryptophan hydroxylase-2 (TPH2). In the present study, the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas) system was used to target theTph2 gene in Bama mini pig fetal fibroblasts. It was found that CRISPR/Cas9 targeting efficiency could be as high as 61.5%, and the biallelic mutation efficiency reached at 38.5%. The biallelic modified colonies were used as donors for somatic cell nuclear transfer (SCNT) and 10Tph2 targeted piglets were successfully generated. These Tph2 KO piglets were viable and appeared normal at the birth. However, their central 5-HT levels were dramatically reduced, and their survival and growth rates were impaired before weaning. TheseTph2 KO pigs are valuable large-animal models for studies of 5-HT deficiency induced behavior abnomality.
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Affiliation(s)
- Ze Li
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Hai-Yuan Yang
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Ying Wang
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Man-Ling Zhang
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Xiao-Rui Liu
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Qiang Xiong
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Li-Ning Zhang
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yong Jin
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Li-Sha Mou
- Shenzhen Xenotransplantation Medical Engineering Research and Development Center, Institute of Translational Medicine, Shenzhen Second People's Hospital, First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong 518035, China
| | - Yan Liu
- Peking-Tsinghua Center for Life Sciences, PKU-IDG/McGovern Institute for Brain Research, the School of Life Sciences, Peking University, Beijing 100871, China
| | - Rong-Feng Li
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yi Rao
- Peking-Tsinghua Center for Life Sciences, PKU-IDG/McGovern Institute for Brain Research, the School of Life Sciences, Peking University, Beijing 100871, China
| | - Yi-Fan Dai
- Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing, Jiangsu 211166, China
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