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1.
Animals (Basel) ; 12(20)2022 Oct 20.
Article in English | MEDLINE | ID: mdl-36290249

ABSTRACT

Obesity is a common feature in horses suffering from metabolic syndrome. While adipokines involvement as biomarkers is better established in human pathology, little data are available on horses. This study aimed to investigate the possible association and relationship between selected metabolic parameters and morphological traits in equine metabolic syndrome. Adiposity was evaluated using body condition score (BCS) and cresty neck score (CNS). Plasma levels of total cholesterol, insulin, NEFA, and adipokines (omentin and chemerin) were determined using enzyme-linked immunosorbent assays. Spearman correlation, univariate linear regression analysis and hierarchical clustering were performed. Significant positive correlations were observed between NEFA and bodyweight (r = 0.322; p = 0.006), BCS (r = 0.295; p = 0.013), and CNS (r = 0.267; p = 0.024), total cholesterol and bodyweight (r = 0.262; p = 0.027), and omentin and CNS (r = 0.234; p = 0.049). Cluster analysis supported these results and provided more details on the relationships between studied variables within and between the four resulting groups. These findings highlight NEFA, chemerin, and omentin as valuable biomarkers that could be further analyzed in other horse breeds for a better understanding of equine metabolic pathology.

2.
Sensors (Basel) ; 22(18)2022 Sep 19.
Article in English | MEDLINE | ID: mdl-36146429

ABSTRACT

Both as an aid for less experienced clinicians and to enhance objectivity and sharp clinical skills in professionals, quantitative technologies currently bring the equine lameness diagnostic closer to evidence-based veterinary medicine. The present paper describes an original, inertial sensor-based wireless device system, the Lameness Detector 0.1, used in ten horses with different lameness degrees in one fore- or hind-leg. By recording the impulses on three axes of the incorporated accelerometer in each leg of the assessed horse, and then processing the data using custom-designed software, the device proved its usefulness in lameness identification and severity scoring. Mean impulse values on the horizontal axis calculated for five consecutive steps above 85, regardless of the leg, indicated the slightest subjectively recognizable lameness, increasing to 130 in severe gait impairment. The range recorded on the same axis (between 61.2 and 67.4) in the sound legs allowed a safe cut-off value of 80 impulses for diagnosing a painful limb. The significance of various comparisons and several correlations highlighted the potential of this simple, affordable, and easy-to-use lameness detector device for further standardization as an aid for veterinarians in diagnosing lameness in horses.


Subject(s)
Horse Diseases , Lameness, Animal , Animals , Biomechanical Phenomena , Extremities , Gait , Hindlimb , Horse Diseases/diagnosis , Horses , Lameness, Animal/diagnosis , Pain
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