Abstract: Reasons for performing study: Identifying the underlying problem of equine back pain and diseases of the spine are significant problems in veterinary orthopaedics. A study to validate a preliminary biomechanical model of the equine back based on CT images including longissimus dorsi (LD) muscle is therefore important. Objectives: Validation of the back model by comparing the shortening of LD muscles in the model with integrated EMG (IEMG) at stance during induced lateral flexion of the spine. Methods:Longissimus dorsi muscle activity at stance has been used for validation. EMG electrodes were placed laterally at the level of T12, T16 and L3. Reflective markers have been attached on top of the spinous processes T5, T12, T16, L1 and the sacral bone (OS1, OS2) for motion tracking analysis. A virtual model of the equine's back (T1–S5) was built with inclusion of a simplified LD muscle by 2 separate contours left and right of the spine, starting at tuber coxae laterally and attaching to the spinous process T5 medially. Shortening of LD during induced lateral flexion caused by the kinematic data (input) was compared to the 3 EMG signals (T12, T16 and L3) on the active side via correlation. Results: Pearson correlation coefficient between IEMG and shortening length of LD in the model was (mean ± s.d.) 0.95 ± 0.07 for the left side and 0.91 ± 0.07 for the right side of LD. Conclusions: Activity of the LD muscles is mainly responsible for stabilisation of the vertebral column with isometric muscle contraction against dynamic forces in walk and trot. This validation requires muscle shortening in the back, like induced lateral flexion at stance. The length of the shortening muscle model and the IEMG show a linear relationship. These findings will help to model the LD for forward simulations, e.g. from force to motion.

Abstract: Reasons for performing study: In horses, serum cortisol concentration is considered to provide an indirect measurement of stress. However, it includes both free and bound fractions. The sampling method is also invasive and often stressful. This is not the case for salivary cortisol, which is collected using a more welfare-friendly method and represents a part of the free cortisol fraction, which is the biologically active form. Objectives: To compare salivary and serum cortisol assays in horses, in a wide range of concentrations, using an adrenocorticotropic hormone (ACTH) stimulation test, in order to validate salivary cortisol for stress assessment in horse. Methods: In 5 horses, blood samples were drawn using an i.v. catheter. Saliva samples were taken using swabs. Cortisol was assayed by radioimmunoassay. All data were treated with a regression method, which pools and analyses data from multiple subjects for linear analysis. Results: Mean ± s.d. cortisol concentrations measured at rest were 188.81 ± 51.46 nmol/l in serum and 1.19 ± 0.54 nmol/l in saliva. They started increasing immediately after ACTH injection and peaks were reached after 96 ± 16.7 min in serum (356.98 ± 55.29 nmol/l) and after 124 ± 8.9 min in saliva (21.79 ± 7.74 nmol/l, P<0.05). Discharge percentages were also different (225% in serum and 2150% in saliva, P<0.05). Correlation between serum and salivary cortisol concentrations showed an adjusted r2= 0.80 (P<0.001). The strong link between serum and salivary cortisol concentrations was also estimated by a regression analysis. Conclusions: The reliability of both RIAs and regression found between serum and salivary cortisol concentrations permits the validation of saliva-sampling as a noninvasive technique for cortisol level assessment in horses.