The use of electromyography interference pattern analysis to determine muscle force of the deep digital flexor muscle in healthy and laminitic horses

BACKGROUND: In equine laminitis, the deep digital flexor muscle (DDFM) appears to have increased muscle force, but evidence-based confirmation is lacking. OBJECTIVES: The purpose of this study was to test if the DDFM of laminitic equines has an increased muscle force detectable by needle electromyography interference pattern analysis (IPA). ANIMALS AND METHODS: The control group included six Royal Dutch Sport horses, three Shetland ponies and one Welsh pony [10 healthy, sound adults weighing 411 ± 217 kg (mean ± SD) and aged 10 ± 5 years]. The laminitic group included three Royal Dutch Sport horses, one Friesian, one Haflinger, one Icelandic horse, one Welsh pony, one miniature Appaloosa and six Shetland ponies (14 adults, weight 310 ± 178 kg, aged 13 ± 6 years) with acute/chronic laminitis. The electromyography IPA measurements included firing rate, turns/second (T), amplitude/turn (M) and M/T ratio. Statistical analysis used a general linear model with outcomes transformed to geometric means. RESULTS: The firing rate of the total laminitic group was higher than the total control group. This difference was smaller for the ponies compared to the horses; in the horses, the geometric mean difference of the laminitic group was 1.73 [geometric 95% confidence interval (CI) 1.29-2.32], and in the ponies this value was 1.09 (geometric 95% CI 0.82-1.45). CONCLUSION AND CLINICAL RELEVANCE: In human medicine, an increased firing rate is characteristic of increased muscle force. Thus, the increased firing rate of the DDFM in the context of laminitis suggests an elevated muscle force. However, this seems to be only a partial effect as in this study, the unchanged turns/second and amplitude/turn failed to prove the recruitment of larger motor units with larger amplitude motor unit potentials in laminitic equids.

Using multiple landscape genetic approaches to test the validity of genetic clusters in a species characterized by an isolation-by-distance pattern

Bayesian clustering methods are typically used to identify barriers to gene flow, but they are prone to deduce artificial subdivisions in a study population characterized by an isolation-by-distance pattern (IbD). Here we analysed the landscape genetic structure of a population of wild boars (Sus scrofa) from south-western Germany. Two clustering methods inferred the presence of the same genetic discontinuity. However, the population in question was characterized by a strong IbD pattern. While landscape-resistance modelling failed to identify landscape features that influenced wild boar movement, partial Mantel tests and multiple regression of distance matrices (MRDMs) suggested that the empirically inferred clusters were separated by a genuine barrier. When simulating random lines bisecting the study area, 60% of the unique barriers represented, according to partial Mantel tests and MRDMs, significant obstacles to gene flow. By contrast, the random-lines simulation showed that the boundaries of the inferred empirical clusters corresponded to the most important genetic discontinuity in the study area. Given the degree of habitat fragmentation separating the two empirical partitions, it is likely that the clustering programs correctly identified a barrier to gene flow. The differing results between the work published here and other studies suggest that it will be very difficult to draw general conclusions about habitat permeability in wild boar from individual studies.