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Simple Summary: In this study, we tested the antioxidant capacity of three natural products (quercetin, bromelain, and Lentinula edodes) and their combination. A new feed supplement based on the combination was formulated and evaluated in a randomized control trial in kennel adult female dogs. The three ingredients tested together showed a high antioxidant capacity. Additionally, the new formulation showed anti-inflammatory and immunomodulatory effects, indicating a potential for use in improving gastrointestinal health and psycho-physical conditions in dogs. Oxidative stress causes several pathological conditions in humans and animals, including gastrointestinal disorders. The aim of this study was to analyze the antioxidant capacity of three natural powdered raw materials containing quercetin, bromelain, and Lentinula edodes and develop a new feed supplement for dogs using a combination of them. The total phenolic content (TPC), antioxidant activity, DPPH (2,2-diphenyl-1-picrylhydrazyl), and ABTS (2,2′-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt) of the extracts, either individually or in combination, were evaluated colorimetrically. The effects of this supplement on healthy adult dogs' nutritional, inflammatory, and stress status were evaluated. American Staffordshire Terrier adult female dogs (n = 30) were randomly assigned to a control (n = 15) or a treated (n = 15) group. The supplement was added as powder to the food of the treated dogs once daily for 28 days. There was no significant difference in the body weight and body condition scores between the initial and final phases of the experiment. At the end of our study, a significant decrease in fecal calprotectin, cortisol, indole/skatole, and N-methylhistamine and a significant increase in short-chain fatty acids were observed as compared to the control group. In conclusion, this natural feed supplement can be used to improve gastrointestinal health and psycho-physical conditions in dogs. [ABSTRACT FROM AUTHOR]

The aim of this study was to quantify some environmental (individual herds, herd productivity, milking system, and season) and animal factors [individual animals, breed, days in milk (DIM) and parity] on the variability of the log-10 transformation of somatic cell count (LSCC) and differential somatic cell count (DSCC) on individual bovine milk. A total of 159,360 test-day records related to milk production and composition were extracted from 12,849 Holstein-Friesian and 9,275 Simmental cows distributed across 223 herds. Herds were classified into high and low productivity, defined according to the average daily milk net energy output (DMEO) yielded by the cows. Data included daily milk yield (DYM; kg/d), milk fat, protein, lactose, SCC, and DSCC, and information on herds (i.e. productivity, milking system). The daily production of total and differential somatic cells in milk was calculated and then log-10 transformed, obtaining DLSCC and DLDSCC, respectively. Data were analyzed using a mixed model including the effects of individual herd, animal, repeated measurements intra animal as random, and herd productivity, milking system, season, breed, DIM, parity, DIM × parity, breed × season, DIM × milking system and parity × milking system as fixed factors. Herds with a high DMEO were characterized by a lower content of LSCC and DSCC, and higher DLSCC and DLDSCC, compared to the low DMEO herds. The association between milking system and somatic cell traits suggested that the use of the automatic milking systems would not allow for a rapid intervention on the cow, as evidenced by the higher content of all somatic cell traits compared to the other milking systems. Season was an important source of variation, as evidenced by high LSCC and DSCC content in milk during summer. Breed of cow had a large influence, with Holstein-Friesian having greater LSCC, DSCC, DLSCC, and DLDSCC compared to Simmental. With regard to DIM, the variability of LSCC was mostly related to that of DSCC, showing an increase from calving to the end of lactation, and suggesting the higher occurrence of chronic mastitis in cows toward the end of lactation. All the somatic cell traits increased across number of parities, possibly because older cows may have increased susceptibility to intramammary infections. [ABSTRACT FROM AUTHOR]

A dataset of 177 individual nitrogen balances from dry and lactating cows was split in two independent groups: training dataset (n = 130) and challenge dataset (n = 47). The training dataset was used to develop multiple linear regressions (MLR) and artificial neural networks (ANN) aimed at predicting the urinary excretion of total (NURI) and that of purine derivative nitrogen (PDN). Input variables for the prediction of NURI were crude protein (CP) intake, effective degradability of non-protein dry matter (DM), neutral detergent fiber (NDF) content of the diet, live weight and milk yield. Live weight, total carbohydrate intake, the ratio of non-protein DM degraded to CP degraded and milk yield corrected for DM intake were entered to predict PDN. The regression between predicted and observed values for the training dataset showed a better statistical accuracy of ANN than did MLR models, especially for PDN. The evaluation of the two models on the challenge dataset showed similar determination coefficients, either when predicting total nitrogen excretion (0.623 and 0.614 for ANN and MLR, respectively) or PDN (0.688 and 0.666, for ANN and MLR, respectively). Moreover, both approaches were affected by a tendency to under-predict both targets at high levels of NURI and PDN. However, with the ANN approach, it is possible to study the response of the model to modifications of individual inputs by the so-called response analysis. This unique feature could be used to study the effect of different physiological situations as well as providing hypotheses for additional research. KEY WORDS: * modeling * neural networks * nitrogen excretion * purine derivatives * cows