Objectives: In experimental pharmacology, drug effect studies currently establish and analyse cumulative concentration–response curves (CCRC) under repeated measurements designs. Usually the CCRC parameters are estimated using the Hill's function in a nonlinear regression for independent data. The two-way analysis of variance is generally used to identify a statistical difference between the responses for two treatments but that analysis does not take into account the nonlinearity of the model and the heteroscedasticity (uneven distribution) of the data. We presently tested the possibility of finding a statistical solution for the nonlinear response in repeated measurements data using the nonlinear mixed effects (nlme) models. Methods: Experimental data sets, originating from studies on β-adrenoceptor-induced relaxation in rat thoracic aorta ring, were analysed using the nlme methods. Key findings: Comparison with classical methods showed the superiority of the nlme models approach. For each pharmacological parameter (Em, n, pD2), a point estimate, a standard error and a confidence interval are returned by the nlme procedures respecting the assumption of independency and normality of the residuals. Conclusions: Using the method presently described, it is now possible to detect significant differences for each pharmacological parameter estimated in different situations, even for designs with small samples size (i.e. at least six complete curves).

Estimation of the quality of commercial diets is a topic of interest for the majority of dog owners. Recently, in a French consumer association magazine, an evaluation of eight dog commercial dry diets (from super-premium, basic-nutrition, private-label and economy brands) according to several nutritional criteria was published. The aims of the study were: (1) to evaluate the apparent digestibility of these diets; (2) to score these diets according to digestibility results; and (3) to compare these data with the scoring of the magazine. Six adult Beagle dogs were enrolled for the digestibility trials. Diets were scored according to energy, crude protein and crude fat (CF) apparent digestibility coefficients, digestible protein-to-energy ratios and ash content. Each of the five criteria was scored from 4 to 20 points. The ranges of crude protein, CF, crude fibre and ash content were 20·9–30·6 %, 6·8–19·7 %, 2·2–3·3 % and 4·6–9·7 % on a DM basis, respectively. The ranges of energy, crude protein and CF apparent digestibility coefficients were 72·6–87·7 %, 70·4–82·5 % and 76·1–95·4 %, respectively. The range of the protein-to-energy ratio was 10–14 digestible crude protein per MJ metabolisable energy. Little overlap in the scoring systems was found, but the private-label brand and economy brand diets presented the lowest scores in the two systems. These results showed that the evaluation of commercial diets should take into account multiple nutritional aspects. In particular, analytical and biological (digestibility) criteria should be considered as complementary in the evaluation of dry dog commercial diets.

The analgesic efficacy of meloxicam and ketoprofen against equine visceral pain is unclear. The aim of this study was to compare the analgesic efficacy of meloxicam (M) and ketoprofen (K) to flunixin meglumine (F) following inguinal castration. Horses undergoing inguinal castration under general anesthesia were randomly assigned F (1.1 mg/kg), M (0.6 mg/kg) or K (2.2 mg/kg) intravenously two hours pre-operatively and 24 h later. A pain score (out of 31) was recorded blindly by a senior clinician and veterinary student before NSAIDs administration (T₀), and after the first (T₁) and second (T₂) administrations, using a modified post-abdominal surgery pain assessment scale (PASPAS). Pain was classified as mild (score $\le$ 7), moderate (score = 8–14) or severe (score $>$ 14). Thirty horses (12 F, 10 M, 8 K) aged 6.2 $\pm$ 4.9 years, mostly warmbloods, were included. Horse welfare was not compromised regardless of the drug assigned. There was no statistically significant effect of NSAIDs on pain score. Mean pain scores were significantly higher at T₁ than T₀ for each NSAID (F: 5.08 ± 2.50 vs. 1.58 ± 1.38 (p < 0.001); M: 4.60 ± 2.32 vs. 1.10 ± 1.20 (p < 0.001); K: 5.25 ± 1.39 vs. 1.50 ± 1.51 (p < 0.0001)) and lower at T₂ than T₁ for F (2.92 ± 2.423 vs. 5.08 ± 2.50 (p < 0.001)) and M (2.90 ± 1.37 vs. 4.60 ± 2.32 (p < 0.0325)). At T₁, senior pain scores were significantly different than for junior (5.56 ± 0.54 vs. 3.22 ± 0.62, p = 0.005). This study indicates that meloxicam and ketoprofen provide a similar level of analgesia to flunixin meglumine for the management of mild visceral pain in horses. PASPAS is not reliable for junior evaluators.

The risks during early growth on becoming overweight in adulthood are widely studied in humans. However, early-life predictive factors for canine adult overweight and obesity have not yet been studied. To identify factors that may help explain the development of overweight and obesity at adulthood in dogs, a longitudinal study of 2 years was conducted in 24 female Beagle dogs of the same age, sexual status, and raised under identical environmental conditions. By means of a hierarchical classification on principal components with the following quantitative values: fat-free mass (FFM), percentage fat mass and pelvic circumference at 2 years of age, three groups of dogs were established and were nominally named: ideal weight (IW, n = 9), slightly overweight (OW1, n = 6) and overweight (OW2, n = 9). With the aim of identifying predictive factors of development of obesity at adulthood parental characteristics, growth pattern, energy balance and plasma factors were analysed by logistic regression analysis. At 24 months, the group compositions were in line with the body condition scores (BCS 1–9) values of the IW (5 or 6/9), the OW1 (6/9) and the OW2 (7 or 8/9) groups. Logistic regression analysis permitted the identification of neonatal growth rate during the first 2 weeks of life (GR2W) and BCS at 7 months as predictors for the development of obesity at adulthood. Seventy percent of dogs with either GR2W >125% or with BCS > 6/9 at 7 months belonged to the OW2 group. Results from energy intake and expenditure, corrected for FFM, showed that there was a greater positive energy imbalance between 7 and 10 months for the OW2, compared to the IW group. This study expands the understanding of previously reported risk factors for being overweight or obese in dogs, establishing that (i) 15 out of 24 of the studied dogs became overweight and (ii) GR2W and BCS at 7 months of age could be used as predictive factors as overweight adult dogs in the OW2 group had higher values compared the other groups of dogs.

Accelerometric analysis of gait abnormalities in golden retriever muscular dystrophy (GRMD) dogs is of limited sensitivity, and produces highly complex data. The use of discriminant analysis may enable simpler and more sensitive evaluation of treatment benefits in this important preclinical model. Accelerometry was performed twice monthly between the ages of 2 and 12 months on 8 healthy and 20 GRMD dogs. Seven accelerometric parameters were analysed using linear discriminant analysis (LDA). Manipulation of the dependent and independent variables produced three distinct models. The ability of each model to detect gait alterations and their pattern change with age was tested using a leave-one-out cross-validation approach. Selecting genotype (healthy or GRMD) as the dependent variable resulted in a model (Model 1) allowing a good discrimination between the gait phenotype of GRMD and healthy dogs. However, this model was not sufficiently representative of the disease progression. In Model 2, age in months was added as a supplementary dependent variable (GRMD_2 to GRMD_12 and Healthy_2 to Healthy_9.5), resulting in a high overall misclassification rate (83.2%). To improve accuracy, a third model (Model 3) was created in which age was also included as an explanatory variable. This resulted in an overall misclassification rate lower than 12%. Model 3 was evaluated using blinded data pertaining to 81 healthy and GRMD dogs. In all but one case, the model correctly matched gait phenotype to the actual genotype. Finally, we used Model 3 to reanalyse data from a previous study regarding the effects of immunosuppressive treatments on muscular dystrophy in GRMD dogs. Our model identified significant effect of immunosuppressive treatments on gait quality, corroborating the original findings, with the added advantages of direct statistical analysis with greater sensitivity and more comprehensible data representation. Gait analysis using LDA allows for improved analysis of accelerometry data by applying a decision-making analysis approach to the evaluation of preclinical treatment benefits in GRMD dogs.