FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Biology (Basel) / Cardiac-Metabolic Coupling Revealed by Lipid and Energy Meta...
Biology2025; 14(11); 1581; doi: 10.3390/biology14111581

Cardiac-Metabolic Coupling Revealed by Lipid and Energy Metabolomics Determines 80 km Endurance Performance in Yili Horses.

Abstract: This study aimed to investigate the regulatory mechanisms underlying the relationship between cardiac structure and function and plasma metabolic characteristics in Yili horses participating in an 80-km endurance, by integrating echocardiography, lipidomics, and energy metabolomics analyses. Twenty four competing Yili horses were selected and divided based on competition outcomes: Pre-Completion Group: PCG ( = 6); Post-Completion Group: PoCG ( = 6); Overtime Completion Group: OCG ( = 6); and Non-Completion Group: NCG ( = 6). Cardiac structural and functional parameters were assessed via echocardiography, and intergroup differences were analyzed using one-way ANOVA with a significance threshold of < 0.05. Plasma lipids and energy metabolites were quantified using UPLC-MS/MS, applying screening criteria of variable importance in projection (VIP) > 1, < 0.05, and fold change (FC) > 1.2 or FC < 0.833. Bioinformatics analyses were subsequently conducted to identify intergroup variations and correlations. Specifically, associations between cardiac structure/function and metabolites were examined using Pearson correlation analysis, with screening criteria of < 0.05 and correlation coefficient > 0.8. The results revealed the following: (1) Regarding cardiac structure and function, the PCG group exhibited significantly superior indices, including End-diastolic left ventricular diameter (LVIDd), End-diastolic left ventricular volume (EDV), stroke volume (SV), and ejection fraction (EF), compared with OCG and NCG, and LVIDd showed a highly significant negative correlation with competition completion time. (2) In metabolomic analyses, few differential metabolites were found among groups before the competition (only 60 between PCG and NCG), whereas 234 differential lipids were detected between PoCG and PCG, mainly enriched in sphingolipid metabolism and fatty acid degradation pathways. Energy metabolites showed distinct exercise-responsive patterns, with 22 differential metabolites between PCG and NCG and 21 between PoCG and PCG, significantly enriched in amino sugar and nucleotide sugar metabolism and TCA pathways. Dynamic changes in key TCA intermediates, such as citrate and succinate, reflected enhanced aerobic oxidative metabolism during endurance exercise. (3) Carnitine C18:1, Carnitine C10:2, FFA (20:3), Cer (t17:2/23:0) and 3-phenyllactic acid were significantly correlated with cardiac indicators such as LVLD and LVFWs ( < 0.05). In summary, performance in the 80-km endurance of Yili horses was primarily influenced by enlarged LVIDd and EDV, as well as the regulation of sphingolipid-fatty acid metabolic pathways. Triglycerides, specific acyl compounds, and ceramides may serve as potential biomarkers for evaluating endurance performance, providing a theoretical basis for scientific training and breeding of endurance horses.
Get Full Text
Publication Date: 2025-11-12 PubMed ID: 41300371PubMed Central: PMC12650485DOI: 10.3390/biology14111581Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Objective Overview

  • This research investigates how the heart’s structure and function relate to plasma metabolic profiles in Yili horses running an 80-km endurance race by combining echocardiography with detailed lipid and energy metabolite analysis.

Research Purpose and Design

  • The study aims to understand the regulatory mechanisms linking cardiac characteristics with plasma metabolites to determine factors influencing endurance performance in Yili horses.
  • Twenty-four Yili horses competing in an 80-km endurance race were divided into four groups by their race completion outcomes:
    • Pre-Completion Group (PCG) – horses before race completion (n=6)
    • Post-Completion Group (PoCG) – horses after race completion (n=6)
    • Overtime Completion Group (OCG) – horses completing overtime (n=6)
    • Non-Completion Group (NCG) – horses that did not complete the race (n=6)

Methodology

  • Cardiac Assessment: Echocardiography was used to measure cardiac structural and functional parameters such as:
    • End-diastolic left ventricular diameter (LVIDd)
    • End-diastolic left ventricular volume (EDV)
    • Stroke volume (SV)
    • Ejection fraction (EF)
  • Metabolomic Analyses:
    • Plasma lipids and energy metabolites were quantified using UPLC-MS/MS.
    • Significant differences were screened using criteria including variable importance in projection (VIP) >1, p-value < 0.05, and fold change thresholds.
    • Bioinformatics tools were employed to analyze group differences and to perform correlation analyses between cardiac parameters and metabolites using Pearson correlation (p < 0.05 and correlation coefficient > 0.8).

Key Findings – Cardiac Structure and Function

  • The PCG group exhibited significantly better cardiac performance indicators than the OCG and NCG groups, specifically:
    • Greater end-diastolic left ventricular diameter (LVIDd)
    • Larger end-diastolic left ventricular volume (EDV)
    • Higher stroke volume (SV)
    • Improved ejection fraction (EF)
  • LVIDd was strongly negatively correlated with the time to complete the race, suggesting larger LVIDd predicts faster endurance performance.

Key Findings – Metabolomic Profiles

  • Before the competition, few differences in metabolites were found between groups (only 60 differential metabolites between PCG and NCG).
  • After competition (PoCG vs PCG), 234 differential lipids were detected, mainly implicating:
    • Sphingolipid metabolism
    • Fatty acid degradation pathways
  • Energy metabolites showed distinct patterns in response to exercise with notable differences:
    • 22 metabolites differing between PCG and NCG
    • 21 metabolites differing between PoCG and PCG

    These changes were enriched in pathways related to:

    • Amino sugar and nucleotide sugar metabolism
    • Tricarboxylic acid cycle (TCA) pathways
  • Dynamic variations in TCA intermediates like citrate and succinate indicate enhanced aerobic oxidative metabolism during endurance exercise.

Metabolite and Cardiac Correlations

  • Certain metabolites were significantly correlated with cardiac structural indicators:
    • Carnitine C18:1 and Carnitine C10:2
    • Free fatty acid (FFA) 20:3
    • Ceramide (Cer t17:2/23:0)
    • 3-phenyllactic acid
  • These metabolites showed strong associations with left ventricular diameter and wall thickness, highlighting their potential role in cardiac-metabolic coupling and endurance capacity.

Conclusions and Implications

  • Endurance performance in Yili horses is mainly influenced by:
    • Cardiac adaptations, specifically enlarged LVIDd and EDV
    • Regulation of sphingolipid and fatty acid metabolic pathways
  • Specific lipids such as triglycerides, acylcarnitines, and ceramides may serve as biomarkers for evaluating endurance capacity in horses.
  • The findings provide a theoretical basis for:
    • Developing scientific training methods tailored to cardiac and metabolic profiles
    • Informing selective breeding programs focused on improving endurance traits in horses

Cite This Article

APA
Wang T, Huang J, Ren W, Meng J, Yao X, Chu H, Yao R, Zhai M, Zeng Y. (2025). Cardiac-Metabolic Coupling Revealed by Lipid and Energy Metabolomics Determines 80 km Endurance Performance in Yili Horses. Biology (Basel), 14(11), 1581. https://doi.org/10.3390/biology14111581

Publication

Biology
ISSN: 2079-7737
NlmUniqueID: 101587988
Country: Switzerland
Language: English
Volume: 14
Issue: 11
PII: 1581

Researcher Affiliations

Wang, Tongliang
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
  • Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
  • Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
Huang, Jinlong
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
Ren, Wanlu
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
  • Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
  • Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
Meng, Jun
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
  • Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
  • Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
Yao, Xinkui
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
  • Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
  • Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
Chu, Hongzhong
  • Xinjiang Yili Kazakh Autonomous Prefecture Animal Husbandry Station, Urumqi 835000, China.
Yao, Runchen
  • Xinjiang Yili Kazakh Autonomous Prefecture Animal Husbandry Station, Urumqi 835000, China.
Zhai, Manjun
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
  • Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
Zeng, Yaqi
  • College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
  • Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
  • Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.

Grant Funding

  • 32202667 / National Natural Science Foundation of China Youth Program
  • 2022A02013-1 / Major Science and Technology Project of Xinjiang Uygur Autonomous Region
  • ZYYD2025JD02 / Central Guidance Project for Local Science and Technology Development-(Research on the Regulation Mechanism of Horse Breeding and Athletic Performance)
  • 2024D01B40 / The Youth Science Fund of the Natural Science Foundation of Xinjiang Uygur Autonomous Re-gion
  • XJMFY202401 / Key Laboratory of Horse Breeding and Exercise Physiology of Xinjiang Project

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

This article includes 42 references
  1. Williams JM, Douglas J, Davies E, Bloom E. Performance demands in the endurance rider.. Comp. Exerc. Physiol. 2021;17:199–218.
    doi: 10.3920/CEP200033google scholar: lookup
  2. Wang T, Meng J, Peng X, Huang J, Huang Y, Yuan X, Li X, Yang X, Chang X, Zeng Y. Metabolomics analysis and mRNA/miRNA profiling reveal potential cardiac regulatory mechanisms in Yili racehorses under different training regimens.. PLoS ONE 2025;20:e0322468.
    doi: 10.1371/journal.pone.0322468pmc: PMC12258599pubmed: 40658689google scholar: lookup
  3. Rodriguez-López AM, Javier G, Carmen P, Esteban P, Luisa GC, Tomas F, Josefa HM, Luis F. Athlete heart in children and young athletes. Echocardiographic Findings in 331 Cases.. Pediatr. Cardiol. 2022;43:407–412.
    doi: 10.1007/s00246-021-02736-5pubmed: 34586455google scholar: lookup
  4. Young L, Rogers K, Wood J. Leftventricular size and systolic function in Thoroughbredracehorses and their relationships to race performance.. J. Appl. Physiol. 2005;99:1278–1285.
    doi: 10.1152/japplphysiol.01319.2004pubmed: 15920096google scholar: lookup
  5. Williams JM, Douglas J, Davies E, Chen F, Ni C, Wang X, Cheng R, Pan C, Wang Y, Liang J. S1P defects cause a new entity of cataract, alopecia, oral mucosal disorder, and psoriasis-like syndrome.. EMBO Mol. Med. 2022;14:e14904.
    pmc: PMC9081911pubmed: 35362222
  6. Wong A, Sun Q, Latif II, Karwi QG. Macrophage energy metabolism in cardiometabolic disease.. Mol. Cell. Biochem. 2025;480:1763–1783.
    doi: 10.1007/s11010-024-05099-6pmc: PMC11842501pubmed: 39198360google scholar: lookup
  7. Żebrowska A, Waśkiewicz Z, Nikolaidis PT, Mikołajczyk R, Kawecki D, Rosemann T, Knechtle B. Acute responses of novel cardiac biomarkers to a 24-h ultra-marathon.. J. Clin. Med. 2019;8:57.
    doi: 10.3390/jcm8010057pmc: PMC6351937pubmed: 30625976google scholar: lookup
  8. Venckunas T, Stasiulis A, Raugaliene R. Concentric myocardial hypertrophy after one year of increased training volume in experienced distance runners.. Br. J. Sports Med. 2006;40:706–709.
    doi: 10.1136/bjsm.2006.027813pmc: PMC2579464pubmed: 16723401google scholar: lookup
  9. Ellison GM, Waring CD, Vicinanza C, Torella D. Physiological cardiac remodelling in response to endurance exercise training: Cellular and molecular mechanisms.. Heart 2012;98:5–10.
    doi: 10.1136/heartjnl-2011-300639pubmed: 21880653google scholar: lookup
  10. Sleeper MM, Durando MM, Holbrook TC, Payton ME, Birks EK. Comparison of echocardiographic measurements in elite and nonelite Arabian endurance horses.. Am. J. Vet. Res. 2014;75:893–898.
    doi: 10.2460/ajvr.75.10.893pubmed: 25255178google scholar: lookup
  11. Schweitzer R, de Marvao A, Shah M, Inglese P, Kellman P, Berry A, Statton B, O’Regan DP. Establishing cardiac MRI reference ranges stratified by sex and age for cardiovascular function during exercise.. Radiol. Cardiothorac. Imaging 2025;7:e240175.
    doi: 10.1148/ryct.240175pmc: PMC12207647pubmed: 40471075google scholar: lookup
  12. Vernemmen I, Vera L, Van Steenkiste G, van Loon G, Decloedt A. Reference values for 2-dimensional and M-mode echocardiography in Friesian and Warmblood horses.. J. Vet. Intern. Med. 2020;34:2701–2709.
    doi: 10.1111/jvim.15938pmc: PMC7694853pubmed: 33098342google scholar: lookup
  13. Young LE, Marlin DJ, Deaton C, Brown-Feltner H, Roberts CA, Wood JL. Heart size estimated by echocardiography correlates with maximal oxygen uptake.. Equine Vet. J. 2010;34:467–471.
    doi: 10.1111/j.2042-3306.2002.tb05467.xpubmed: 12405735google scholar: lookup
  14. Sharma S. Endurance sport and cardiovascular health.. BMC Sports Sci. Med. Rehabil. 2015;7((Suppl. S1)):O13.
    doi: 10.1186/2052-1847-7-S1-O13google scholar: lookup
  15. Wang T, Meng J, Yang X, Zeng Y, Yao X, Ren W. Differential metabolomics and cardiac function in trained vs. untrained Yili performance horses.. Animals 2025;15:2444.
    doi: 10.3390/ani15162444pmc: PMC12382719pubmed: 40867773google scholar: lookup
  16. Burtscher J, Strasser B, Burtscher M, Millet G.P. The impact of training on the loss of cardiorespiratory fitness in aging masters endurance athletes.. Int. J. Environ. Res. Public Health 2022;19:11050.
    doi: 10.3390/ijerph191711050pmc: PMC9517884pubmed: 36078762google scholar: lookup
  17. Hanssen H, Keithahn A, Hertel G, Drexel V, Stern H, Schuster T, Lorang D, Beer A.J, Schmidt-Trucksass A, Nickel T. Magnetic resonance imaging of myocardial injury and ventricular torsion after marathon running.. Clin. Sci. 2011;120:143–152.
    doi: 10.1042/CS20100206pubmed: 20815809google scholar: lookup
  18. Ball D. Metabolic and endocrine response to exercise: Sympathoadrenal integration with skeletal muscle.. J. Endocrinol. 2015;224:R79–R95.
    doi: 10.1530/JOE-14-0408pubmed: 25431226google scholar: lookup
  19. Latino F, Cataldi S, Carvutto R, De Candia M, D’Elia F, Patti A, Bonavolontà V, Fischetti F. The Importance of lipidomic approach for mapping and exploring the molecular networks underlying physical exercise: A Systematic Review.. Int. J. Mol. Sci. 2021;22:8734.
    doi: 10.3390/ijms22168734pmc: PMC8395903pubmed: 34445440google scholar: lookup
  20. Le Moyec L, Robert C, Triba M.N, Billat V.L, Mata X, Schibler L, Barrey E. Protein catabolism and high lipid metabolism associated with long-distance exercise are revealed by plasma NMR metabolomics in endurance horses.. PLoS ONE 2017;9:e90730.
    doi: 10.1371/journal.pone.0090730pmc: PMC3962349pubmed: 24658361google scholar: lookup
  21. Nosaka N, Suzuki Y, Suemitsu H, Kasai M, Kato K, Taguchi M. Medium-chain triglycerides with maltodextrin increase fat oxidation during moderate-intensity exercise and extend the duration of subsequent high-intensity exercise.. J. Oleo Sci. 2018;67:1455–1462.
    doi: 10.5650/jos.ess18112pubmed: 30404966google scholar: lookup
  22. Getzin A.R, Milner C, LaFace K.M. Nutrition update for the ultraendurance athlete.. Curr. Sports Med. Rep. 2011;10:330–339.
    doi: 10.1249/JSR.0b013e318237fcdfpubmed: 22071393google scholar: lookup
  23. Soria M, Ansón M, Lou-Bonafonte J.M, Andrés-Otero M.J, Puente J.J, Escanero J. Fat oxidation rate as a function of plasma lipid and hormone response in endurance athletes.. J. Strength Cond. Res. 2020;34:104–113.
    doi: 10.1519/JSC.0000000000003034pubmed: 30707143google scholar: lookup
  24. Kim J, Lim K. Relationship between FAT/CD36 protein in skeletal muscle and whole-body fat oxidation in endurance-trained mice.. J. Exerc. Nutr. Biochem. 2016;20:48–52.
    doi: 10.20463/jenb.2016.0057pmc: PMC5545196pubmed: 28150475google scholar: lookup
  25. Girona J, Soler O, Samino S, Junza A, Martinez-Micaelo N, Garcia-Altares M, Rafols P, Esteban Y, Yanes O, Correig X. Lipidomics reveals myocardial lipid composition in a murine model of insulin resistance induced by a high-fat diet.. Int. J. Mol. Sci. 2024;25:2702.
    doi: 10.3390/ijms25052702pmc: PMC10932381pubmed: 38473949google scholar: lookup
  26. McGavock J.M, Lingvay I, Zib I, Tillery T, Salas N, Unger R, Levine B.D, Raskin P, Victor R.G, Szczepaniak L.S. Cardiac steatosis in diabetes mellitus: A 1H-magnetic resonance spectroscopy study.. Circulation 2007;116:1170–1175.
    doi: 10.1161/CIRCULATIONAHA.106.645614pubmed: 17698735google scholar: lookup
  27. Rijzewijk L.J, van der Meer R.W, Smit J.W, Diamant M, Bax J.J, Hammer S, Romijn J.A, de Roos A, Lamb H.J. Myocardial steatosis is an independent predictor of diastolic dysfunction in type 2 diabetes mellitus.. J. Am. Coll. Cardiol. 2008;52:1793–1799.
    doi: 10.1016/j.jacc.2008.07.062pubmed: 19022158google scholar: lookup
  28. Baranowski M, Zabielski P, Blachnio A, Gorski J. Effect of exercise duration on ceramide metabolism in the rat heart.. Acta Physiol. 2008;192:519–529.
    doi: 10.1111/j.1748-1716.2007.01755.xpubmed: 17970831google scholar: lookup
  29. Wang S.Y, Zhu S, Wu J, Zhang M, Xu Y, Xu W, Cui J, Yu B, Cao W, Liu J. Exercise enhances cardiac function by improving mitochondrial dysfunction and maintaining energy homoeostasis in the development of diabetic cardiomyopathy.. J. Mol. Med. 2020;98:245–261.
    doi: 10.1007/s00109-019-01861-2pubmed: 31897508google scholar: lookup
  30. Martland R, Mondelli V, Gaughran F, Stubbs B. Can high-intensity interval training improve physical and mental health outcomes? A meta-review of 33 systematic reviews across the lifespan.. J. Sports Sci. 2020;38:430–469.
    doi: 10.1080/02640414.2019.1706829pubmed: 31889469google scholar: lookup
  31. Fontani G, Corradeschi F, Felici A, Alfatti F, Migliorini S, Lodi L. Cognitive and physiological effects of Omega-3 polyunsaturated fatty acid supplementation in healthy subjects.. Eur. J. Clin. Investig. 2005;35:691–699.
    doi: 10.1111/j.1365-2362.2005.01570.xpubmed: 16269019google scholar: lookup
  32. Meienberg F, Loher H, Bucher J, Jenni S, Krüsi M, Kreis R, Boesch C, Betz M.J, Christ E. The effect of exercise on intramyocellular acetylcarnitine (AcCtn) concentration in adult growth hormone deficiency (GHD). Sci. Rep. 2019;9:19431.
    doi: 10.1038/s41598-019-55942-wpmc: PMC6923484pubmed: 31857652google scholar: lookup
  33. Zeng Q, Isobe K, Fu L, Ohkoshi N, Ohmori H, Takekoshi K, Kawakami Y. Effects of exercise on adiponectin and adiponectin receptor levels in rats.. Life Sci. 2006;10:454–459.
    doi: 10.1016/j.lfs.2006.09.031pubmed: 17070556google scholar: lookup
  34. Kriketos A.D, Gan S.K, Poynten A.M, Furler S.M, Chisholm D.J, Campbell L.V. Exercise increases adiponectin levels and insulin sensitivity in humans.. Diabetes Care 2004;27:629–630.
    doi: 10.2337/diacare.27.2.629pubmed: 14747265google scholar: lookup
  35. Kondo T, Kobayashi I, Murakami M. Effect of exercise on circulating adipokine levels in obese young women.. Endocr. J. 2006;53:189–195.
    doi: 10.1507/endocrj.53.189pubmed: 16618976google scholar: lookup
  36. Rodrigues A, De Lucca L. Acute leptin response after high intensity interval and moderate intensity continuous runs.. Eur. J. Hum. Mov. 2020;45.
    doi: 10.21134/eurjhm.2020.45.3google scholar: lookup
  37. Hui S, Ghergurovich J.M, Morscher R.J, Jang C, Teng X, Lu W, Esparza L.A, Reya T, Zhan L, Guo Y. Glucose feeds the TCA cycle via circulating lactate.. Nature 2017;551:115–118.
    doi: 10.1038/nature24057pmc: PMC5898814pubmed: 29045397google scholar: lookup
  38. van Hall G. The physiological regulation of skeletal muscle fatty acid supply and oxidation during moderate-intensity exercise.. Sports Med. 2015;45((Suppl. S1)):23–32.
    doi: 10.1007/s40279-015-0394-8pmc: PMC4672010pubmed: 26553490google scholar: lookup
  39. Rustad P.I, Sailer M, Cumming K.T, Jeppesen P.B, Kolnes K.J, Sollie O, Franch J, Ivy J.L, Daniel H, Jensen J. Intake of protein plus carbohydrate during the first two hours after exhaustive cycling improves performance the following day.. PLoS ONE 2016;11:e0153229.
    doi: 10.1371/journal.pone.0153229pmc: PMC4831776pubmed: 27078151google scholar: lookup
  40. Zhao M, Bian R, Xu X, Zhang J, Zhang L, Zheng Y. Sphingolipid Metabolism and signalling pathways in heart failure: From molecular mechanism to therapeutic potential.. J. Inflamm. Res. 2025;18:5477–5498.
    doi: 10.2147/JIR.S515757pmc: PMC12034266pubmed: 40291458google scholar: lookup
  41. Iqbal J., Walsh M.T., Hammad S.M., Hussain M.M. Sphingolipids in cardiovascular diseases and metabolic disorders. Lipids Health Dis. 2015;14:55.
    pmc: PMC4470334pubmed: 26076974
  42. Błachnio-Zabielska A, Zabielski P, Baranowski M, Gorski J. Aerobic training in rats increases skeletal muscle sphingomyelinase and serine palmitoyltransferase activity, while decreasing ceramidase activity.. Lipids 2011;46:229–238.
    doi: 10.1007/s11745-010-3515-zpmc: PMC3058424pubmed: 21181285google scholar: lookup

Citations

This article has been cited 0 times.
Subscribe to our newsletter
Join 99,000 horse owners like you who receive our email updates on horse health and nutrition.