| Literature DB >> 29977895 |
Francesca Marcato1,2, Henry van den Brand1, Bas Kemp1, Kees van Reenen2.
Abstract
Veal calves undergo many challenges in the early stages of their life. Such challenges, including mixing procedures and transportation of calves to the veal farm, may have a negative influence on growth rate, feed intake, metabolism, immunity and disease susceptibility of calves. As a consequence, many hematological, physiological, metabolic and immunological parameters of stressed calves might be altered on arrival at the veal farm. Some of these response variables might be useful as biomarkers of performance of calves at the veal farm as they might provide information about an ongoing disease process, or may predict future diseases. Biomarkers might be helpful to group and manage calves in different risk categories after arrival. By adopting treatment decisions and protocols on a risk-group or individual basis, it would be possible to improve animal health and reduce both disease incidence and antibiotic use. Moreover, the use of biomarkers might be an economically feasible approach as some of them do not need invasive techniques and others can be measured in blood already taken during routine checks. Previous literature mainly assessed the physiological responses of calves to transportation. However, information on the link between on-farm arrival data and future health and performance of veal calves is limited. This review, therefore, examined a wide range of papers and aimed to identify potential biomarkers of future health and performance.Entities:
Keywords: biomarkers; challenges; diseases; health; stress; veal calves
Year: 2018 PMID: 29977895 PMCID: PMC6021515 DOI: 10.3389/fvets.2018.00133
Source DB: PubMed Journal: Front Vet Sci ISSN: 2297-1769
Figure 1Effects of short and long-term exposure to environmental challenges on disease susceptibility. HPA axis, hypothalamic-pituitary-adrenal axis; GH, growth hormone; BW, body weight; PCV, packed cell volume; Hb, hemoglobin; β-HB, β- hydroxybutyrate; NEFA, non-esterified fatty acids; WBC, white blood cells; APPs, acute phase proteins; CK, creatine kinase; LDH, lactate dehydrogenase; AST, aspartate aminotransferase; CPK, creatine phosphokinase.
Figure 2Diagram of routes of communication between the brain and the immune system, including HPA axis, sympathetic nervous system, and cytokine feedback to the brain [© 2011. Oscar Vegas, Larraitz Garmendia, Amaia Arregi and Arantza Azpiroz. Originally published in “Effects of social stress on immunomodulation and tumor development” under CC BY 3.0 license. Available from Vegas et al. (43)].
Some associations between body weight (BW) and future risk of respiratory diseases or early mortality in different studies on cattle.
| ( | ≤43 | 7.6 | 0.004 | |
| ( | Per 1-kg increase | 0.93 | < 0.01 | |
| ( | Per pound | 0.99 | 0.03 | |
| ( | 272–317 | 1.08 | 0.99 | <0.05 |
| ( | 363–408 | 0.02 | 0.0012 | |
Bovine respiratory disease.
Figure 3Metabolite profiles for animals that survived or died. Letters (A) to (D) represent four different situations depending on metabolite data derived from samples collected on Day 0 (prior to viral infection) and samples collected on Day 4 (post BHV-1 infection). Bar charts for distribution profile of identified metabolites from 1H-NMR studies for animals that died or survived following synergic viral-bacterial infection are shown in bar chart form. Error bars shown indicate 1-standard deviation. Metabolite IDs are shown on the x-axis [The publisher for this copyrighted material is Mary Ann Liebert, Inc., publishers Aich et al. (49)]. *Significant differences p < 0.05.