Adrenal responsiveness to a low-dose ACTH challenge in early and late lactating dairy cows.

To improve the evaluation of the chronic stress conditions, the adrenal responsiveness to low dose ACTH stimulation, in different lactation stages, was checked in 56 multiparous dairy cows from 2 herds (25-350 days in milk). Cows were retrospectively ranked in 3 stages: early (150 DIM) lactation. Herd B (vs. herd A) showed higher basal cortisol and frequency of inflammation. Early stage (vs. others) showed higher basal cortisol, bilirubin, ceruloplasmin and haptoglobin, as well as lower ones of cholesterol and lower rise of plasma cortisol during ACTH challenge (P<0.001). Cortisol peak was also correlated negatively with ceruloplasmin, bilirubin, ROM, and positively with cholesterol, vitamin A and E. Both, basal cortisol and cortisol response to ACTH, are associated to inflammation but in opposite way: basal cortisol positively and cortisol response negatively. This latter results are likely due to lower transcortin synthesis, that could be ensued in early lactating cows suffering inflammation

Circulating amino acids in blood plasma during the peripartal period in dairy cows with different liver functionality index

The liver functionality index (LFI) measures the changes of albumin, cholesterol, and bilirubin concentrations between 3 and 28 d postpartum. This composite index, based on variables with direct relevance to liver-specific plasma protein synthesis (albumin), hepatic/intestinal lipoprotein synthesis (cholesterol), and clearance of breakdown products of heme catabolism (bilirubin), provides a tool for evaluating manifestations of hepatic disease. Both energy and protein metabolism are likely to be affected by various physiological challenges in this period but have not been tested systematically. The present study was conducted to profile AA in cows with high or low LFI during the peripartal period and relate this to production outcomes. Eighteen multiparous cows were used from −21 through 28 d around parturition and divided retrospectively into the high or low LFI group. Blood samples were obtained on −21, −14, −7, 1, 3, 7, 10, 14, 17, 21, and 28 d relative to calving, and biomarkers and AA in plasma were measured. Grouping based on LFI resulted in 8 cows with high LFI (HLFI) and 10 cows with low LFI (LLFI). Although the temporal response in dry matter intake (DMI, 16.3 kg/d) and body condition score (2.56) did not differ, cows with high compared with low LFI had greater overall milk production (37.9 vs. 32.9 kg/d) although energy-corrected milk yield did not differ (42.6 vs. 38.7 kg/d). As expected, cows grouped as LLFI had lower cholesterol and albumin but greater bilirubin after calving compared with HLFI animals. Despite similar temporal responses in DMI between groups, concentrations of total AA were greater in HLFI, particularly after calving. Although concentrations of total essential AA (EAA) and branched-chain AA did not differ with LFI status, cows in HLFI had greater concentrations of Thr and Ile postpartum. Nearly all plasma AA concentrations followed the general trend of a nadir at 1 d after calving followed by a gradual increase to prepartal levels before 28 d. Glycine was the only AA exhibiting a gradual increase in concentration through the transition, with a maximum at 7 d postpartum followed by a gradual decrease. We detected no effect of LFI status on plasma Lys, which decreased markedly from −21 d to calving, followed by an increase to prepartal values by d 7. In contrast, concentrations of Met and His decreased markedly between −21 and 10 d and did not reach prepartal values by 28 d. The marked decrease in Gln concentration after calving regardless of LFI might compromise immune function during this period. Overall, the results indicate the existence of an association among inflammation, liver function postpartum, and AA plasma concentrations, irrespective of temporal differences in DMI. Cows with better indices of liver function produced more milk and maintained greater concentrations of total AA and some EAA such as Thr and Ile. Whether these AA played a direct role in the greater milk production remains to be determined

The effect of a single, early-life administration of a probiotic on piglet growth performance and faecal microbiota until weaning

The establishment and maintenance of a balanced gut microbiota in early life play a pivotal role in pigs. This study aims to evaluate the effect of the administration of a single early-life probiotic on piglet faecal microbiota and growth performance until weaning. Forty-eight hours after birth (d0), 820 piglets were allocated into 4 groups (205 piglets/16 litters/group) and orally inoculated as follows: 1) Control (CO: 4 mL of pure water); 2) Saccharomyces (SA: 4 mL containing a total of 1 × 1010 CFU of Saccharomyces cerevisiae var. boulardii CNCM-1079; 3) Enterococcus (EF: 4 mL containing a total of 1 × 1010 CFU of Enterococcus faecium lactiferm WS200); 4) a mix of the two probiotics at the same doses (SAEF). At d7 and d18, the piglets were weighed, and faeces from the piglets (18 piglets/group from 6 sows/group) and their mothers were analysed for a microbial profile by sequencing the v3-v4 regions of the 16S rRNA gene. Data were arranged in a 2x2 factorial design. The probiotic supplement improved piglet ADG in the periods d7-d18 (p &lt;.0001) and d0-d18 (p &lt;.05). From d7 to d18, the SA group tended to have lower mortality than the CO group (p =.08). The probiotic supplement significantly affected the microbial beta diversity at d7 (p &lt;.05). The SA probiotic favoured the colonisation of Erysipelatoclostridium and Christensenella, and the EF probiotic the colonisation of Lachnospiraceae. These results highlighted that the administration of a single early-life probiotic supplement could improve piglet performance and shape the faecal microbial profile.Highlights A single dose of E. faecium or S. cerevisiae improved piglet performance in the pre-weaning period. The early administration of probiotics shaped the faecal microbial profile of the piglets and contributed to improved growth performance

Determination of Free Amino Acids in Milk, Colostrum and Plasma of Swine via Liquid Chromatography with Fluorescence and UV Detection

Amino acids are ubiquitous components of mammalian milk and greatly contribute to its nutritional value. The compositional analysis of free amino acids is poorly reported in the literature even though their determination in the biological fluids of livestock animals is necessary to establish possible nutritional interventions. In the present study, the free amino acid profiles in mature swine milk, colostrum and plasma were assessed using a targeted metabolomics approach. In particular, 20 amino acids were identified and quantified via two alternative and complementary reversed-phase HPLC methods, involving two stationary phases based on core-shell technology, i.e., Kinetex C18 and Kinetex F5, and two detection systems, i.e., a diode array detector (DAD) and a fluorescence detector (FLD). The sample preparation involved a de-proteinization step, followed by pre-chromatographic derivatization with 9-fluorenylmethylchloroformate (FMOC-Cl). The two optimized methods were validated for specificity, linearity, sensitivity, matrix effect, accuracy and precision and the analytical performances were compared. The analytical methods proved to be suitable for free amino acid profiling in different matrices with high sensitivity and specificity. The correlations among amino acid levels in different biological fluids can be useful for the evaluation of physio-pathological status and to monitor the effects of therapeutic or nutritional interventions in humans and animals

Transfer of mycotoxins from lactation feed to colostrum of sows

Studies regarding the transfer of mycotoxins from sow feed to colostrum are scarce. A sample of in-house produced lactation feed and one of colostrum were collected from two or three sows per farm (total 49) from 19 farms. The feed contents of aflatoxins (AFs), fumonisins (FUs), deoxynivalenol (DON) and zearalenone (ZEA) were assessed using ELISA and confirmed by liquid chromatography-mass spectrometry (LC-MS), The values were very low (10, 12, 17 and 2 positive samples for AFs, FUs, DON and ZEA, respectively), except for two samples (one AF, one DON). Based on feed values, colostrum samples from 13 farms were tested for at least one mycotoxin (Total 35). Aflatoxins were not found in any sample. A signal for FUs was observed in 5 of 11 colostra, despite low feed values; DON was frequently present in the colostrum (10/14). On the farm where the feed exceeded the DON suggested limits, a higher colostrum content was seen, 10.9 µg/kg, approximately 1/69 of the value showing toxicity in young pigs. The absence of reference values for neonate pigs, and the risk of higher and longer ingestion of DON by sows suggested considering routine checks of sow feed; more research on DON transfer and toxicity in piglets is needed

Biomarkers of inflammation, metabolism, and oxidative stress in blood, liver, and milk reveal a better immunometabolic status in peripartal cows supplemented with Smartamine M or MetaSmart

The peripartal dairy cow experiences a state of reduced liver function coupled with increased inflammation and oxidative stress. This study evaluated the effect of supplementing basal diets with rumen-protected Met in the form of MetaSmart (MS) or Smartamine M (SM) (both from Adisseo Inc., Antony, France) during the peripartal period on blood and hepatic biomarkers of liver function, inflammation, and oxidative stress. Thirty-seven multiparous Holstein cows were fed the same basal diet from −50 to −21 d relative to expected calving [1.24 Mcal/kg of dry matter (DM); no Met supplementation]. From −21 d to calving, the cows received diets (1.54 Mcal/kg of DM) with no added Met (control, CON; n = 13), CON plus MS (n = 11), or CON plus SM (n = 13). From calving through 30 d in milk (DIM), the cows received the same postpartal diet (1.75 Mcal/kg of DM; CON), or CON plus MS or CON plus SM. Liver and blood samples were harvested at various time points from −21 to 21 d relative to calving. Preplanned contrasts of CON versus SM + MS during prepartum (−21 and −10 d before calving) and postpartum (7, 14, and 21 d after calving) responses were evaluated. Cows fed MS or SM compared with CON had lower overall concentrations of plasma ceruloplasmin and serum amyloid A (SAA). Compared with CON, Met-supplemented cows had greater overall plasma oxygen radical absorbance capacity. Liver concentrations of glutathione and carnitine also were greater overall with Met supplementation. Milk choline and liver phosphatidylcholine were lower overall in cows fed Met compared with controls. Liver tissue choline concentrations did not differ. Data indicate that supplemental Met enhanced de novo glutathione and carnitine synthesis in liver and, thus, increased antioxidant and β-oxidation capacity. The greater decrease of IL-6 after calving coupled with lower ceruloplasmin and SAA in Met-supplemented cows indicated a reduction in proinflammatory signaling within liver. The lower hepatic phosphatidylcholine in Met-supplemented cows might have been associated with greater assembly or export of very low density lipoproteins. Overall, biomarker analyses in blood and tissue indicate that the beneficial effect of feeding SM and MS on postpartal cow performance is due in part to a better immunometabolic status

Meat composition, from microscopy to chemistry by way of diagnostic imaging

MEAT COMPOSITION, FROM MICROSCOPY TO CHEMISTRY BY WAY OF DIAGNOSTIC IMAGING S.C. Modina1, E. Trevisi2, C. Bernardi1, M. Di Giancamillo3 1Department of Health, Animal Science and Food Safety, Universit\ue0 degli Studi di Milano, via Celoria 10, 20133 Milano, Italy 2Institute of Zootechnics, Faculty of Agriculture, Universit\ue0 Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy 3Department of Veterinary Science and Public Health, Universit\ue0 degli Studi di Milano, via Celoria 10, 20133 Milano, Italy E-mail: [email protected] The increasing demand of a real-time monitoring of food products has encouraged the application of non-invasive techniques. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) proved to be very accurate and valuable tools in estimating body and carcass composition in farm animals.1 CT has been successfully used for the characterization of food Italian products such as salami, providing a precise evaluation of fat percentage, also assessing its spatial distribution.2 Manzocco and colleagues demonstrated that MRI has great potential in monitoring the evolution of dry curing in S. Daniele hams.3In our experience, helical CT proved to be a fast tool in the classification of different meat cuts, deriving from adult cow and destined for the preparation of aircured products as \u201clean meat\u201d or \u201cfat meat\u201d, both in fresh and frozen samples. Histological studies confirmed that CT clearly distinguishes adipose and connective tissue infiltration within muscles and that semi-quantitative analysis of infiltration degree can be achieved. These data were further supported by the chemical analysis of meat samples corresponding to the same region of interest observed in both CT and histologic investigations; dry matter, crude proteins, crude fat and ash contents, calculated following standard international methods,4 varied in fact depending on the fat infiltrated extent, according with CT images. We finally observed that CT could be used in the evaluation of the same products at the end of ripening, without removing the outer envelope. These results are important for beef and meat industrial processing sector, suggesting that CT could be employed as an on-line instrument in abattoir and dry-cured meat industry in classifying the products at the beginning of the manufacturing even they are frozen. Moreover, it might represent a rapid and non-invasive technique for quality check at the end of the production line and for the assignment of the most appropriate nutritional and commercial value to different products. References 1. Scholz AM et al. Animal. 2015; 9: 1250 2. Frisullo P et al. Journal of Food Engineering. 2009; 94: 283 3. Manzocco L et al. Food Chem. 2013;141(3):2246 4. AOAC International 2012. Official Methods of Analysis. 19th ed. AOAC International Gaithersburg, M