Confidence intervals for blood parameters used for nutritional and metabolic profile testing in cattle were calculated for clinically normal lactating Holstein cows, taking into account the effects of parity, stage of lactation, and season. Blood samples were collected from 740 cows in 33 Italian dairy herds according to a predefined protocol. Herds were visited during summer and the following winter, sampling 12 lactating cows at each visit (4 primiparous and 8 multiparous). Six cows were selected from the early-lactation group (days in milk: 10 to 89) and the other 6 were selected from the mid-lactation group (days in milk: 90 to 215). Cow selection criteria excluded animals clinically exposed to periparturient diseases as well as animals not considered in good health by a veterinary clinical examination. For each blood variable, outliers were identified and discarded. Data were then analyzed for their Gaussian distribution and variables with not normal distribution were log-transformed to adjust for lack of normality. Herd mean values were calculated for each blood parameter according to 3 main classification factors: parity (primiparous vs. multiparous), stage of lactation (early vs. mid) and season of production (summer vs. winter). The resulting data set was statistically analyzed using a mixed model with the fixed effects of these factors, their interactions, and the random effect of herd. General 95% confidence intervals were calculated for blood variables that showed a relevant herd variance component such as albumin, triglycerides, aspartate, urea, glucose, alanine aminotransferase, lactate dehydrogenase, direct and total bilirubin, calcium, magnesium, and potassium. For the remaining parameters, specific confidence intervals were calculated for each level of the significant main factors. Parity affected blood concentration of total protein, globulin, creatinine, alkaline phosphatase, gamma glutamyl transferase, creatinine kinase, and phosphorus. Blood nonesterified fatty acids, aspartate aminotransferase, gamma glutamyl transferase, creatinine kinase and cholesterol were influenced by stage of lactation. The season of production had a significant effect on total protein, globulin, creatinine, alkaline phosphatase, phosphorus, sodium, and chlorine. The outcomes of this work will improve the accuracy of the biochemical profile as a tool for dairy practitioners to assess the metabolic status of lactating Holstein cows.

Predictions of growth are important factors that contribute to the profitability of an operation in poultry production. Modern commercial hybrids have a higher body growth in comparison with the local purebreds. However a niche market for meat and egg poultry production needs to be established using local purebreds to promote biodiversity. The aim of this study was to model the growth response of male and female chickens belonging to 5 local Italian populations: a commercial slow-growing hybrid (Berlanda, B), the Padovana pure breed [2 plumage varieties: silver, argentata (PA) and chamois, camosciata (PC)], and their crosses PC×B and PC×PA. A total of 398 one-day-old birds were reared until 180 d of age under indoor conditions. The linear and 3 nonlinear models (logistic, Gompertz, and Richards) were compared to study the growth patterns of these chicken populations. Significant (P < 0.01) differences were observed among the genotypes for several curve parameters. In males, PC×B showed the lowest age at inflection point, B showed the highest age and BW, whereas PA showed the highest age and the lowest weight. In females, the age at the inflection point did not differ among the groups; B showed the highest weight. All the nonlinear models gave a good fit of male and female data with R(2) ranging from 0.992 and 0.999, but the logistic equation had higher value of root mean square error than the Gompertz and the Richards values. Based on residual sum of squares for both sexes, the Richards model was better (P < 0.05) than the logistic but not superior to the Gompertz. The logistic equation showed an overestimation of initial BW for all the groups and sex. For Italian local chicken populations, the Richards model requires a measure of BW recorded at 90 d or after to obtain a good fit of the asymptotic weight. However, the Gompertz model has the advantage that it requires one less parameter than the Richards model.

Cows from 25 dairy herds were scored for body condition at 3-mo intervals for over 2 yr to study the pattern of changes during lactation and the effects of parity and milk yield capability of cows on changes in body reserves. Data were recorded for 1395 Holstein cows grouped into three parity classes and five classes of mature equivalent milk yield. The analysis model accounted for nearly 70% of the variation in body condition score. Body reserves decreased during early lactation until about 100 DIM and were restored during mid and late lactation. The pattern of change in body condition score varied among lactations and dairy merit of cows. Depletion and subsequent recovery of body reserves were less intense for primiparous cows than for multiparous cows. Loss of body condition scores was higher and more prolonged for cows of higher dairy merit. The minimum body condition score occurred at 3 mo after calving for the worst yielding cows and at 4 mo after calving for the best yielding cows; the highest yielding cows had twice the loss in body condition as the lowest yielding cows. General equations are presented as a proposed guideline to examine changes in body condition score of Holstein cows of different parities and dairy merit.

Background The prognostic relevance of left atrial (LA) morphological and functional variables, including those derived from speckle tracking echocardiography (STE), has been little investigated in veterinary medicine. Objectives To assess the prognostic value of several echocardiographic variables, with a focus on LA morphological and functional variables in dogs with myxomatous mitral valve disease (MMVD). Animals One‐hundred and fifteen dogs of different breeds with MMVD. Methods Prospective cohort study. Conventional morphologic and echo‐Doppler variables, LA areas and volumes, and STE‐based LA strain analysis were performed in all dogs. A survival analysis was performed to test for the best echocardiographic predictors of cardiac‐related death. Results Most of the tested variables, including all LA STE‐derived variables were univariate predictors of cardiac death in Cox proportional hazard analysis. Because of strong correlation between many variables, only left atrium to aorta ratio (LA/Ao > 1.7), mitral valve E wave velocity (MV E vel > 1.3 m/s), LA maximal volume (LAVmax > 3.53 mL/kg), peak atrial longitudinal strain (PALS < 30%), and contraction strain index (CSI per 1% increase) were entered in the univariate analysis, and all were predictors of cardiac death. However, only the MV E vel (hazard ratio [HR], 4.45; confidence interval [CI], 1.76‐11.24; P < .001) and LAVmax (HR, 2.32; CI, 1.10‐4.89; P = .024) remained statistically significant in the multivariable analysis. Conclusions and Clinical Importance The assessment of LA dimension and function provides useful prognostic information in dogs with MMVD. Considering all the LA variables, LAVmax appears the strongest predictor of cardiac death, being superior to LA/Ao and STE‐derived variables.