Undeclared animal species in dry and wet novel and hydrolyzed protein diets for dogs and cats detected by microarray analysis.

BACKGROUND: Although the European Pet Food Industry Federation (FEDIAF) stated that labels must be accurate and provide detailed information on the ingredients, mislabeling of pet food has been documented by several authors. This phenomenon is of particular concern when related to products used as elimination diets for the diagnosis of adverse food reaction (AFR) in dogs and cats because the presence of undeclared ingredients may negatively interfere with the trial and prevent the veterinarian from making an appropriate diagnosis. The aim of this study was to shed light upon the problem of contamination and mislabeling in both dry and wet novel protein diets (NPDs) and hydrolyzed protein diets (HPDs) using a microarray-based commercial kit which tests for the presence of 19 animal species. RESULTS: Of the 40 analyzed products (9 dry NPDs, 22 wet NPDs, 6 dry HPDs and 3 wet HPDs), ten presented a content that correctly matched the label, while five did not contain the declared animal species, twenty-three revealed the presence of undeclared animal species, and two had a vague label that did not allow the evaluation of its accuracy. The most frequently contaminants identified in both dry and wet pet foods were pork, chicken and turkey. The presence of undeclared animal species was higher in dry than wet pet foods; furthermore, a lower number of contaminating animal species was identified in HPDs than NPDs (4 vs 10), and a lower number of contaminated HPDs (6 out of 9, 67%) than contaminated NPDs was detected (24 out of 31, 77%). Thirteen out of 14 brands tested presented at least one mislabeled product. CONCLUSIONS: Mislabeling seems to be a widespread issue in pet foods used as elimination diets. Contamination can occur in all types of products used for the purpose, although dry NPDs are the main issue. Due to the high risk of contamination, particular attention should be given to both the selection of raw material suppliers and the production process.

Metagenomic analysis of rumen microbial population in dairy heifers fed a high grain diet supplemented with dicarboxylic acids or polyphenols.

BACKGROUND: The aim of this study was to investigate the effects of two feed supplements on rumen bacterial communities of heifers fed a high grain diet. Six Holstein-Friesian heifers received one of the following dietary treatments according to a Latin square design: no supplement (control, C), 60 g/day of fumarate-malate (organic acid, O) and 100 g/day of polyphenol-essential oil (P). Rumen fluid was analyzed to assess the microbial population using Illumina sequencing and quantitative real time PCR. RESULTS: The P treatment had the highest number of observed species (P < 0.10), Chao1 index (P < 0.05), abundance based coverage estimated (ACE) (P < 0.05), and Fisher's alpha diversity (P < 0.10). The O treatment had intermediate values between C and P treatments with the exception of the Chao1 index. The PCoA with unweighted Unifrac distance showed a separation among dietary treatments (P = 0.09), above all between the C and P (P = 0.05). The O and P treatments showed a significant increase of the family Christenenellaceae and a decline of Prevotella brevis compared to C. Additionally, the P treatment enhanced the abundance of many taxa belonging to Bacteroidetes, Firmicutes and Tenericutes phyla due to a potential antimicrobial activity of flavonoids that increased competition among bacteria. CONCLUSIONS: Organic acid and polyphenols significantly modified rumen bacterial populations during high-grain feeding in dairy heifers. In particular the polyphenol treatment increased the richness and diversity of rumen microbiota, which are usually high in conditions of physiological rumen pH and rumen function.

Confirmation of protein biomarkers of corticosteroids treatment in veal calves sampled under field conditions.

In veal calf production, growth promoters are still illicitly used. Surveillance of misuse of such molecules is necessary to preserve human health. Methods currently adopted for their analysis are based on liquid chromatography-tandem mass spectrometry, but their efficacy can be affected by undetectable residual concentrations in biological matrices due to treatments at low-dosage or based on unknown anabolic compounds. The development of screening methods to identify the indirect biological effects of administration of growth promoters can improve the efficiency of drug residue monitoring. To this purpose, an integrated approach has been used to further validate the set of protein biomarkers defined in a previous controlled study to detect the use of corticosteroids through the changes caused in muscle protein expression. The thymus morphology of 48 samples collected under field conditions was evaluated to assess the presence of potential corticosteroids treatment. Animals were divided on the basis of their thymus characteristics in negative or suspected for illegal corticosteroids treatment. Drug residue analyses were performed on the liver, giving a satisfactory correlation with the histological examination (∼85%). Finally, the proteomics analysis of muscle protein extracts was carried out by 2D differential in gel electrophoresis, and proteins that were differentially expressed between the two animal groups (p value <0.01) were selected for MALDI-MS/MS analysis. This approach allowed us to identify 29 different proteins, and our findings indicate that the altered protein expression pattern can be used as an indirect method for the detection of illicit corticosteroids administration. A subset of the identified proteins was already reported in a previous controlled study, proving that these biomarkers can be used to develop a screening assay to improve the tools currently available for the detection of corticosteroids abuse in bovine meat production.

Use of dicarboxylic acids and polyphenols to attenuate reticular pH drop and acute phase response in dairy heifers fed a high grain diet.

BACKGROUND: The aim of this study was to determine the ability of two feed additives, a fumarate-malate (FM) and a polyphenol-essential oil mixture (PM), in attenuating the drop of ruminal pH and the metabolic and immune response resulting from an excessively high grain diet. Six heifers were used in a 3 × 3 Latin square experiment and fed a low starch (LS) diet for 14 d, followed by a high starch (HS) diet for 8 d (NDF 33.6%, starch 30.0% DM). In the last 5 days of each period, barley meal was added to decrease rumen pH. During HS feeding all animals were randomly assigned to one of the following three dietary treatments: no supplement/control (CT), a daily dose of 60 g/d of FM, or 100 g/d of PM. Reticular pH was continuously recorded using wireless boluses. On d 21 of each period, rumen fluid was collected by rumenocentesis (1400 h), together with blood (0800 h) and fecal samples (0800, 1400, and 2100 h). RESULTS: The correlation coefficient of pH values obtained using the boluses and rumenocentesis was 0.83. Compared with CT and PM, the FM treatment led to a lower DMI. Nadir pH was lowest during CT (5.40, 5.69, and 5.62 for CT, FM and PM, respectively), confirming the effectiveness of both supplements in reducing the pH drop caused by high grain feeding. This result was confirmed by the highest average time spent daily below 5.6 pH (199, 16 and 18 min/d) and by the highest acetate to propionate ratio of the CT fed heifers. The PM decreased the concentrations of neutrophils (2.9, 3.2, and 2.8 10(9)/L) and acute phase proteins: SAA (37.1, 28.6 and 20.1 µg/mL), LBP (4.1, 3.8, and 2.9 µg/mL), and Hp (675, 695 and 601 µg/mL). Free lipopolysaccharides (LPS) were detected in blood and feces, but their concentrations were not affected by treatments, as the remaining blood variables. CONCLUSIONS: Data suggest that both additives could be useful in attenuating the effects of excessive grain feeding on rumen pH, but the PM supplement was more effective than FM in reducing the inflammatory response compared to CT.

Food safety and hygiene lessons in the primary school: implications for risk-reduction behaviors.

OBJECTIVE: This study describes an effective educational program to improve children's knowledge about characteristics of microorganisms and food contamination, and their personal hygiene behaviors. MATERIALS AND METHODS: Between November 2011 and March 2012, a health campaign, targeted at fifth-grade students of 12 public primary compulsory schools, was conceived. Participants were divided into two classes, a theoretical class and a practical class based on two different teaching approaches. To address children's knowledge and behaviors on the program topics and to monitor the effectiveness of the health campaign on changing pre-existent concepts and habits, pre- and post-intervention questionnaires were administered both to students and parents. Poisson and binomial mixed models were performed. RESULTS: Two hundred forty-nine children were enrolled. Results show an overall improvement in children's knowledge both for the practical and theoretical classes (incident risk ratios [IRRs]: 1.2, 95% confidence interval (CI) 1.1-1.2, p<0.001 and 1.1, 95% CI 1.0-1.1, p<0.001, post- versus pre-intervention). The same effect was observed for children's behavior, comparing post- versus pre-intervention for both groups (IRRs were 3.4, 95% CI 2.2-5.2, p<0.001 and 3.2 95% CI 1.9-5.5, p<0.001). CONCLUSION AND APPLICATIONS: The methodology described in this article might be usefully adopted to conduct food safety classes, contributing to the amelioration of children's awareness on food related risks and leading to significant benefit for primary prevention.

Effect of induced ruminal acidosis on blood variables in heifers.

BACKGROUND: Ruminal acidosis is responsible for the onset of different pathologies in dairy and feedlot cattle, but there are major difficulties in the diagnosis. This study modelled the data obtained from various blood variables to identify those that could indicate the severity of ruminal acidosis. Six heifers were fed three experimental rations throughout three periods. The diets were characterised by different starch levels: high starch (HS), medium starch (MS) and low starch, as the control diet (CT). Ruminal pH values were continuously measured using wireless sensors and compared with pH measurements obtained by rumenocentesis. Blood samples were analysed for complete blood count, biochemical profile, venous blood gas, blood lipopolysaccharide (LPS) and LPS-binding proteins (LBP). RESULTS: The regression coefficient comparing the ruminal pH values, obtained using the two methods, was 0.56 (P = 0.040). Feeding the CT, MS and HS led to differences in the time spent below the 5.8, 5.5 and 5.0 pH thresholds and in several variables, including dry matter intake (7.7 vs. 6.9 vs. 5.1 kg/d; P = 0.002), ruminal nadir pH (5.69 vs. 5.47 vs. 5.44; P = 0.042), mean ruminal pH (6.50 vs. 6.34 vs. 6.31; P = 0.012), haemoglobin level (11.1 vs. 10.9 vs. 11.4 g/dL; P = 0.010), platelet count (506 vs. 481 vs. 601; P = 0.008), HCO3(-) (31.8 vs. 31.3 vs. 30.6 mmol/L; P = 0.071) and LBP (5.9 vs. 9.5 vs. 10.5 µg/mL; P < 0.001). A canonical discriminant analysis (CDA) was used to classify the animals into four ruminal pH classes (normal, risk of acidosis, subacute ruminal acidosis and acute ruminal acidosis) using haemoglobin, mean platelet volume, ß-hydroxybutyrate, glucose and reduced haemoglobin. CONCLUSIONS: Although additional studies are necessary to confirm the reliability of these discriminant functions, the use of plasma variables in a multifactorial model appeared to be useful for the evaluation of ruminal acidosis severity.

Herd Level Yield Gap Analysis in a Local Scale Dairy Farming System: A Practical Approach to Discriminate between Nutritional and Other Constraining Factors.

This study performed a yield gap analysis to help farmers understand whether their constraints were mainly due to nutritional factors or management and health issues. Twenty-nine farms were periodically evaluated. Milk yield (MY), dry matter intake (DMI), total mixed ration (TMR) composition and homogeneity index (HI), TMR digestibility, income over feed cost (IOFC), and MY summer-winter ratio (SWR) were collected. Farms were divided and compared according to the average annual MY: Low (L), Medium (M) and High (H), characterised by <31.1, 31.1-36.7 and >36.7 kg/head/day. An ANOVA mixed model and a stepwise regression to assess the relationship between nutritional variables and MY were run. H farms showed higher IOFC (p < 0.001), DMI (p = 0.006), DDM (p < 0.001), digestible crude protein (DCP, p = 0.019), HI (p = 0.09), SWR (p = 0.041) and lower HI coefficient of variation (p = 0.04). The conversion of DDM into milk was higher in H and M farms. Stepwise regression for MY selected DDM and CP (R2 = 0.716, p < 0.05). M farms were mainly constrained by nutritional factors, whereas L farms were also affected by other factors such as those related to management and health.

Uncovering Patterns in Dairy Cow Behaviour: A Deep Learning Approach with Tri-Axial Accelerometer Data.

The accurate detection of behavioural changes represents a promising method of detecting the early onset of disease in dairy cows. This study assessed the performance of deep learning (DL) in classifying dairy cows' behaviour from accelerometry data acquired by single sensors on the cows' left flanks and compared the results with those obtained through classical machine learning (ML) from the same raw data. Twelve cows with a tri-axial accelerometer were observed for 136 ± 29 min each to detect five main behaviours: standing still, moving, feeding, ruminating and resting. For each 8 s time interval, 15 metrics were calculated, obtaining a dataset of 211,720 observation units and 15 columns. The entire dataset was randomly split into training (80%) and testing (20%) datasets. The DL accuracy, precision and sensitivity/recall were calculated and compared with the performance of classical ML models. The best predictive model was an 8-layer convolutional neural network (CNN) with an overall accuracy and F1 score equal to 0.96. The precision, sensitivity/recall and F1 score of single behaviours had the following ranges: 0.93-0.99. The CNN outperformed all the classical ML algorithms. The CNN used to monitor the cows' conditions showed an overall high performance in successfully predicting multiple behaviours using a single accelerometer.

Characterization of intestinal microbiota in normal weight and overweight Border Collie and Labrador Retriever dogs.

Obesity in dogs is an emerging issue that affects canine health and well-being. Its development is ascribed to several factors, including genetic predisposition and dietary management, and recent evidence suggests that intestinal microbiota may be involved as well. Previous works have shown obesity to be linked to significant changes in gut microbiota composition in humans and mice, but only limited information is available on the role played by canine gut microbiota. The aim of this exploratory study was to investigate whether composition of canine faecal microbiota may be influenced by overweight condition and breed. All the enrolled companion dogs were young adults, intact, healthy, and fed commercial extruded pet food; none had received antibiotics, probiotics or immunosuppressant drugs in the previous six months. Labrador Retriever (LR) and Border Collie (BC) were chosen as reference breeds and Body Condition Score (BCS) on a 9-point scale as reference method for evaluating body fat. The faecal microbial communities of 15 lean (BCS 4-5/9; 7 LRs and 8 BCs) and 14 overweight (BCS > 5/9; 8 LRs and 6 BCs) family dogs were analysed using 16S rRNA gene sequencing. Moreover, for each dog, the daily intake of energy (kcal/d) and dietary macronutrients (g/d) were calculated according to an accurate feeding history collection. Firmicutes and Bacteroidetes resulted the predominant phyla (51.5 ± 10.0% and 33.4 ± 8.5%, respectively) in all dogs. Bioinformatic and statistical analysis revealed that no bacterial taxon differed significantly based on body condition, except for genus Allisonella (p < 0.05); BC gut microbiota was richer (p < 0.05) in bacteria belonging to phyla Actinobacteria (family Coriobacteriaceae in particular) and Firmicutes (Allobaculum and Roseburia genera). No remarkable differences were recorded either for diversity indices (i.e., alpha diversity, p > 0.10) or for divergence within the sample set (i.e., beta diversity, p > 0.05). PERMANOVA tests performed on single factors demonstrated the tendency of dietary protein to influence the recruited dogs' microbiota beta-diversity at amplicon sequence variant level (p = 0.08). In conclusion, the faecal microbiota of dogs involved in this exploratory study showed no major variations based on body condition. However, our findings suggested that certain bacterial taxa previously acknowledged in obesity-related studies may be detected in dissimilar amounts depending on canine breed.

Protein expression changes in skeletal muscle in response to growth promoter abuse in beef cattle.

The fraudulent treatment of cattle with growth promoting agents (GPAs) is a matter of great concern for the European Union (EU) authorities and consumers. It has been estimated that 10% of animals are being illegally treated in the EU. In contrast, only a much lower percentage of animals (<0.5%) are actually found as being noncompliant by conventional analytical methods. Thus, it has been proposed that methods should be developed that can detect the use of the substances via the biological effects of these substances on target organs, such as the alteration of protein expression profiles. Here we present a study aimed at evaluating if a correlation exists between the treatment with GPAs and alterations in the two-dimensional electrophoresis (2DE) protein pattern obtained from the biceps brachii skeletal muscle from mixed-bred cattle. After image analysis and statistical evaluation, protein spots that differentiate between treated and control groups were selected for analysis by mass spectrometry. A set of proteins could be defined that accurately detect the use of glucocorticoids and ß(2)-agonists as growth promoters through the changes caused in muscle differentiation. As a further validation, we repeated the analysis using an independent set of samples from a strain of pure-bred cattle and verified these proteins by Western blot analysis.

Assessment of the Effectiveness of a Portable NIRS Instrument in Controlling the Mixer Wagon Tuning and Ration Management.

The adoption of the mixer wagon and total mixed ration aimed to decrease dysmetabolic diseases and improve feed efficiency in dairy cows. Differences between theoretical and eaten diets are imputable to errors in diet preparation or cow feed sorting. We proposed a method to measure the chemical composition and particle size distribution of the ration and determined its peNDF content through a portable Near Infra-Red spectrophotometer that allowed the calculation of two indexes: the homogeneity and the sorting indexes. In a cohort of 19 Italian Holstein breeding farms, we studied the correlation of these indexes with the mixer wagon settings. Determination coefficients in the validation (Rv2) for dry matter, crude protein, aNDF, and starch were 0.91, 0.54, 0.86, and 0.67, respectively. The ration fractions (%, w/w of wet weight) retained by the 3.8 and 1.8 mm sieves, and the bottom showed Rv2 of 0.46, 0.49, and 0.53, respectively. The homogeneity index regressed negatively with the mixer wagon load fullness (R2 = 0.374). The homogeneity-binary classification showed an odds ratio of 1.72 for dry matter and 0.39 for aNDF (p < 0.05). The sorting-binary classification showed an odds ratio of 2.54 for aNDF (p < 0.05). The studied farms showed low peNDF values (median = 17.9%).

Machine Learning to Detect Posture and Behavior in Dairy Cows: Information from an Accelerometer on the Animal's Left Flank.

The aim of the present study was to develop a model to identify posture and behavior from data collected by a triaxial accelerometer located on the left flank of dairy cows and evaluate its accuracy and precision. Twelve Italian Red-and-White lactating cows were equipped with an accelerometer and observed on average for 136 ± 29 min per cow by two trained operators as a reference. The acceleration data were grouped in time windows of 8 s overlapping by 33.0%, for a total of 35,133 rows. For each row, 32 different features were extracted and used by machine learning algorithms for the classification of posture and behavior. To build up a predictive model, the dataset was split in training and testing datasets, characterized by 75.0 and 25.0% of the observations, respectively. Four algorithms were tested: Random Forest, K Nearest Neighbors, Extreme Boosting Algorithm (XGB), and Support Vector Machine. The XGB model showed the best accuracy (0.99) and Cohen's kappa (0.99) in predicting posture, whereas the Random Forest model had the highest overall accuracy in predicting behaviors (0.76), showing a balanced accuracy from 0.96 for resting to 0.77 for moving. Overall, very accurate detection of the posture and resting behavior were achieved.

Effectiveness of Stocking Density Reduction on Mitigating Lameness in a Charolais Finishing Beef Cattle Farm.

This study aimed at assessing whether a reduction in stocking density (SKD) would mitigate lameness and positively affect the performance and health of Charolais bulls in an Italian commercial farm. Bulls were distributed in groups of 10 or 8 animals/pen for high (HD) or low density (LD) corresponding to an individual space of 3.5 or 4.7 m2, respectively. Bulls were fitted with collars that measured rumination time and activity. Three 8-h observational sessions were conducted to record behaviors. Data about health conditions were collected daily. No differences were found in the animals' performance. However, performance results might have been impaired by the culling rate experienced during the trial, which prevented from keeping a consistent SKD. Behaviors did not differ between groups, except for rumination time, which was higher for LD bulls during the third observation (p < 0.05). However, rumination time, recorded by collars, did not vary among treatments. There were no differences in the percentage of sick or lame bulls, but the percentage of animals treated repeatedly due to relapse was higher for the HD group (p < 0.05). It was concluded that a larger space allowance could improve the health of bulls kept on fully slatted floors.

The Effects of Decreasing Dietary Crude Protein on the Growth Performance, Feed Efficiency and Meat Quality of Finishing Charolais Bulls.

This study aimed to evaluate the effect of decreasing dietary crude protein (CP) on the performance of finishing Charolais bulls in the Italian rearing system. Animals were fed two diets, differing only in the CP level (low protein (LP), 13.5% CP versus control (CON), 15.0% CP). Dry matter (DM) intake (DMI) and animals' weights were recorded to obtain average daily gain (ADG) and feed conversion rate (FCR). Feed and fecal samples were collected to evaluate digestibility of diet components. Daily cost of the ration (DRC), feed cost per kg of daily weight gain (CDG) and daily gross margin (DGM) were calculated to analyze the possible benefits of decreasing the protein level. Meat quality analyses were also conducted. Higher DMI (10.6 versus 10 kg/d; p < 0.05) and ADG (1.47 versus 1.36 kg/d; p < 0.05) were observed for CON. No differences in FCR or digestibility were found. Even if the DRC was lower (p < 0.05) for the LP diet (2.26 versus 1.97 €; CON versus LP), no difference was reported for CDG and DGM. Meat lightness and redness were significantly lower and higher in the LP, respectively. To conclude, the CP requirement in these rearing conditions appeared to be higher than 13.5%.

Use of rumination and activity data as health status and performance indicators in beef cattle during the early fattening period.

The aim of this study was to measure the level of activity and rumination in young bulls and to assess whether these data can be used as indicators of health status and average daily weight gain (ADG). Two groups of animals (period 1: n=108 animals; period 2: n=106 animals) were fitted with sensors to measure daily activity and rumination, were weighed on arrival and at the end of the trial (70 days) and were checked twice daily to verify their health condition. Any clinical signs and therapies were recorded. The dishomogeneity index of rumination (DR), and the daily dishomogeneity indices of activity (DDA) and rumination (DDR), were calculated. Bulls had an ADG of 1.42±0.38kg/day and showed an average duration of daily rumination of 404±63min and an average activity of 474±46 bits, respectively. Animals characterised by low ADG had lower values of minimum daily rumination (P=0.01) and DDA (P<0.001), and a greater rumination range (P=0.007) and DR (P=0.003). Bovine respiratory disease and lameness were detected 31 and five times, respectively; among affected animals, the average daily activity, rumination and DDA were lower (P<0.05) at 3-6days before the onset of visible clinical signs, whereas DDR increased compared to the values when individuals were apparently healthy. The use of individual sensors appears promising for the early diagnosis of disease in beef cattle and for improving herd management.

Students' Consumption of Beverages and Snacks at School and Away from School: A Case Study in the North East of Italy.

In North-East Italy (the Veneto region), several public school nutrition policies have been developed to reduce the consumption of high-caloric snacks and beverages. However, little is known about whether the policies actually influence students' dietary behaviors. In order to address this point, a multi-center cross-sectional survey of 691 Italian students was conducted. Students completed the Beverage and Snack Questionnaire, which assesses the consumption of beverages and snacks at school and out of school. Three-level Poisson Models with random intercept with students (level 1 units) nested into classroom (level 2 units), and nested into schools (level 3 units), were used to examine the influence of the school setting vs. the out of school environment (independent variable) on students' consumption of sweet beverages, snacks, milk-based beverages, low-carbohydrate drinks, fruit, and vegetables (dependent variable) (p ≤ 0.05). The results showed a significantly higher consumption of sweet beverages, snacks, milk-based beverages, low-carbohydrate drinks, fruit, and vegetables out-of-the school, suggesting a school-protective association Thus, the policies aimed to limit or deny access to unhealthy foods in the school environment may play an important role in promoting more healthful dietary patterns for school children. Additional studies should be conducted to compare students' dietary behaviors between schools with nutrition policies to those without nutrition policies.

Direct detection of soil-bound prions.

Scrapie and chronic wasting disease are contagious prion diseases affecting sheep and cervids, respectively. Studies have indicated that horizontal transmission is important in sustaining these epidemics, and that environmental contamination plays an important role in this. In the perspective of detecting prions in soil samples from the field by more direct methods than animal-based bioassays, we have developed a novel immuno-based approach that visualises in situ the major component (PrP(Sc)) of prions sorbed onto agricultural soil particles. Importantly, the protocol needs no extraction of the protein from soil. Using a cell-based assay of infectivity, we also report that samples of agricultural soil, or quartz sand, acquire prion infectivity after exposure to whole brain homogenates from prion-infected mice. Our data provide further support to the notion that prion-exposed soils retain infectivity, as recently determined in Syrian hamsters intracerebrally or orally challenged with contaminated soils. The cell approach of the potential infectivity of contaminated soil is faster and cheaper than classical animal-based bioassays. Although it suffers from limitations, e.g. it can currently test only a few mouse prion strains, the cell model can nevertheless be applied in its present form to understand how soil composition influences infectivity, and to test prion-inactivating procedures.