Influence of different milking methods on milk quality based on somatic cell count and basic composition.

INTRODUCTION AND OBJECTIVE: Correlations between the number of milk somatic cells (SCC), the number of microorganisms, and the content of basic components of milk were studied on five farms (F1-F5) with cows of the same breed, but with different milking systems. MATERIAL AND METHODS: From each farm, 50 Holstein Friesien milk samples were collected once a month (250 samples/month; n=3,000) during March 2022 - February 2023. Samples from farms F1 and F5 were tested for fat, protein, lactose, no fat dry matter content (FTIR spectroscopy), for the SCC (Fossomatic 7), and for the differential cells (Vetscan DC-Q). RESULTS: The highest fat content was confirmed on farm F5 (3.85 ± 1.70%) and F4 (3.82 ± 0.21%) with automatic milking system (AMS). However, from the point of view of protein content, these farms showed slightly lower values (<0.05). F1 did not meet the minimum required amount for fat content (2.84 ± 0.81%) set by the legislation of the Slovakia. The comparison shows that there is not much difference in cell size between healthy cells and mastitis cells. The average size of healthy cells was approximately 8.77 ± 0.49 µm. In the monitored period, the average values determined were at the level of 292,000/mL (5.46 ± 0.72 log10 SCC) in cow milk samples, while for the rest of the year, the values remained at 256,000/mL (5.40 ± 0.80 log10 SCC). F1 was categorized as a positive farm with a high TLC (total milk leucocyte count) concentration (5.58 log10 cells/mL, 406.65 ± 53.80 × 103 cells/mL) and a predominant NEU fraction (61%). Farms F2, F4, and F5 were classified as negative farms (TLC was 4.70 ± 0.26 log10 cells/ml). CONCLUSIONS: According to the results, the size of SCCs in healthy milk does not differ from SCCs found in mastitis milk. From the results, it can be concluded that the transition to the latest generation of robotic milking method can positively affect milk production and its quality.

Influence of production level, number, and stage of lactation on milk quality in compost barn systems.

This study evaluated the influence of milk production, number of lactations, and days in milk (DIM) on the quality and composition of milk from dairy cows housed in a compost barn (CB) system. The study was carried out using a six-year database, counting 31,268 observations from 2,037 cows of European breeds. Multiparous cows showed higher fat and protein production. Lactose showed high levels for primiparous and the initial stage of lactation (4.65%) and was negatively influenced by somatic cell count (SCC). Milk urea nitrogen was higher (14.01%) from 106 to 205 days in milk, and the other components were higher at >305 days. Therefore, the solids content was higher in the first and second lactations due to the high contents of lactose, fat, and milk protein, but lactose was reduced over lactations. In contrast, high DIM increased SCC and concentrated solids due to lower milk production. The effect of milk production, stage, and lactation order on the composition and milk quality of herds housed in CB showed the same pattern as in other production systems.

Exploring the impact of biosecurity measures on somatic cell score in mountain dairy farms considering the CLASSYFARM system.

Biosecurity plays a crucial role in preventing the introduction of infectious diseases to a herd as well as the spread of diseases within or between animals and herds. In particular, biosecurity measures are crucial for maintaining animal health and reducing the need for the application of antibiotic substances for fighting the rising antibiotic resistance. The object of this cross-sectional study was to investigate the presence of biosecurity measures and their association with milk quality parameters, with a special focus on somatic cell count (SCC) - an indicator for udder health -, in small-scale mountain dairy farms. Therefore, for the very first time, the CLASSYFARM system was considered, which is a computer platform integrated into the Italian national veterinary portal, that processes a significant amount of data from various sources collected in the field or from other information systems (e.g. animal welfare, health status, biosecurity, antimicrobial use, slaughterhouse information). A total of 169 dairy farms were included in the study. Biosecurity measures, based on 15 questions required in the CLASSYFARM welfare assessment protocol, as well as information about husbandry systems, milking systems and pasture practices were gathered and combined with milk yield data, provided by the South Tyrolean dairy association. Farms only scored 44.00 points on average in a scoring system from 0.00 to 100.00 points that was be able to summarize 15 different biosecurity measures in one index. Our results show a clear negative correlation (-0.713) between the biosecurity index and somatic cell score (SCS) indicating that a higher level of biosecurity, which reflects the presence of biosecurity measures within a farm, is associated with lower SCC levels. Furthermore, we found significant correlations between SCS and milk production (-0.629), confirming that udder health is linked to higher milk production. Fat, protein, and the fat-to-protein ratio showed a positive correlation with SCS (0.281, 0.146, 0.106), likely to be caused by a concentration shift effect (dilution effect). Husbandry system, breed, milking system, and pasture practices seem to have an impact as well, but the main factor was the biosecurity score. This study highlights the importance of implementing biosecurity measures for ensuring animal health and thus productivity and quality in milk production, even in small-scale farms, which are characterized by limited structure availability and smaller herds compared to big dairy enterprises in the lowlands.

The use of stem cells in the treatment of mastitis in dairy cows.

Mastitis is a multifactorial inflammatory disease. The increase in antibiotic resistance of bacteria that cause mastitis means that cattle breeders would prefer to reduce the use of antibiotics. Recently, therapies using mesenchymal stem cells (MSCs) from various sources have gained significant interest in the development of regenerative medicine in humans and animals, due to their extraordinary range of properties and functions. The aim of this study was to analyze the effectiveness of an allogeneic stem cells derived from bone marrow (BMSC) and adipose tissue (ADSC) in treating mastitis in dairy cattle. The research material consisted of milk and blood samples collected from 39 Polish Holstein-Friesian cows, 36 of which were classified as having mastitis, based on cytological evaluation of their milk. The experimental group was divided into subgroups according to the method of MSC administration: intravenous, intramammary, and intravenous + intramammary, and according to the allogeneic stem cells administered: BMSC and ADSC. The research material was collected at several time intervals: before the administration of stem cells, after 24 and 72 h, and after 7 days. Blood samples were collected to assess hematological parameters and the level of pro-inflammatory cytokines, while the milk samples were used for microbiological assessment and to determine the somatic cells count (SCC). The administration of allogeneic MSCs resulted in a reduction in the total number of bacterial cells, Staphylococcus aureus, bacteria from the Enterobacteriaceae group, and a systematic decrease in SCC in milk. The therapeutic effect was achieved via intravenous + intramammary or intramammary administration.

[Investigations of a controlled, decision tree based procedure for Selective Dry Cow Treatment in Bavarian dairy farms]. / Untersuchungen zu einem kontrollierten, entscheidungsbaumbasierten Verfahren des Selektiven Trockenstellens in Bayerischen Milchviehbetrieben.

OBJECTIVE: Four parameters of a decision tree for Selective Dry Cow Treatment (SDCT), examined in a previous study, were analyzed regarding their efficacy in detecting cows for dry cow treatment (DCT, use of intramammary antimicrobials). This study set out to review wether all parameters (somatic cell count [SCC≥ 200 000 SC/ml 3 months' milk yield recordings prior dry off (DO)], clinical mastitis history during lactation [≥1 CM], culturing [14d prior DO, detection of major pathogens] and California-Mastitis-Test [CMT, > rate 1/+ at DO]) are necessary for accurate decision making, whether there are possible alternatives to replace culturing, and whether a simplified model could replace the decision tree. MATERIAL AND METHODS: Records of 18 Bavarian dairy farms from June 2015 to August 2017 were processed. Data analysis was carried out by means of descriptive statistics, as well as employing a binary cost sensitive classification tree and logit-models. For statistical analyses the outcomes of the full 4-parameter decision tree were taken as ground truth. RESULTS: 848 drying off procedures in 739 dairy cows (CDO) were included. SCC and CMT selected 88.1%, in combination with CM 95.6% of the cows that received DCT (n=494). Without culturing, 22 (4.4%) with major pathogens (8x Staphylococcus [S.] aureus) infected CDO would have been misclassified as not needing DCT. The average of geometric mean SCC (within 100 d prior DO) for CDO with negative results in culturing was<100 000 SC/ml milk, 100 000-150 000 SC/ml for CDO infected with minor pathogens, and ≥ 150 000 SC/ml for CDO infected with major pathogens (excluding S.aureus). Using SCC during lactation (at least 1x > 200 000 SC/ml) and positive CMT to select CDO for DCT, contrary to the decision tree, 37 CDO (4.4%) would have been treated "incorrectly without" and 43 CDO (5.1%) "unnecessarily with" DCT. Modifications were identified, such as SCC<131 000 SC/ml within 100 d prior to DO for detecting CDO with no growth or minor pathogens in culturing. The best model for grading CDO for or against DCT (CDO without CM and SCC<200 000 SC/ml [last 3 months prior DO]) had metrics of AUC=0.74, Accuracy=0.778, balanced Accuracy=0.63, Sensitivity=0.92 and Specificity=0.33. CONCLUSIONS: Combining the decision tree's parameters SCC, CMT and CM renders suitable selection criteria under the conditions of this study. When omitting culturing, lower thresholds for SCC should be considered for each farm individually to select CDO for DCT. Nonetheless, the most accurate model could not replace the full decision tree.

Development of a prototypic, field-usable diagnostic tool for the detection of gram-positive cocci-induced mastitis in cattle.

BACKGROUND: Bovine mastitis is one of the most widespread diseases affecting cattle, leading to significant losses for the dairy industry. Currently, the so-called gold standard in mastitis diagnosis involves determining the somatic cell count (SCC). Apart from a number of advantages, this method has one serious flaw: It does not identify the etiological factor causing a particular infection, making it impossible to introduce targeted antimicrobial therapy. This can contribute to multidrug-resistance in bacterial species. The diagnostic market lacks a test that has the advantages of SCC and also recognizes the species of pathogen causing the inflammation. Therefore, the aim of our study was to develop a lateral flow immunoassay (LFIA) based on elongation factor Tu for identifying most prevalent Gram-positive cocci responsible for causing mastitis including Streptococcus uberis, Streptococcus agalactiae and Staphylococcus aureus. RESULTS: As a result, we showed that the assay for S. uberis detection demonstrated a specificity of 89.02%, a sensitivity of 43.59%, and an accuracy of 80.3%. In turn, the second variant - assay for Gram-positive cocci reached a specificity of 95.59%, a sensitivity of 43.28%, and an accuracy of 78.33%. CONCLUSIONS: Our study shows that EF-Tu is a promising target for LFIA and we have delivered evidence that further evaluation could improve test parameters and fill the gap in the mastitis diagnostics market.

Cows with diverging haplotypes show differences in differential milk cell count, milk parameters and vaginal temperature after S. aureus challenge but not after E. coli challenge.

BACKGROUND: In dairy cattle, mastitis causes high financial losses and impairs animal well-being. Genetic selection is used to breed cows with reduced mastitis susceptibility. Techniques such as milk cell flow cytometry may improve early mastitis diagnosis. In a highly standardized in vivo infection model, 36 half-sib cows were selected for divergent paternal Bos taurus chromosome 18 haplotypes (Q vs. q) and challenged with Escherichia coli for 24 h or Staphylococcus aureus for 96 h, after which the samples were analyzed at 12 h intervals. Vaginal temperature (VT) was recorded every three minutes. The objective of this study was to compare the differential milk cell count (DMCC), milk parameters (fat %, protein %, lactose %, pH) and VT between favorable (Q) and unfavorable (q) haplotype cows using Bayesian models to evaluate their potential as improved early indicators of differential susceptibility to mastitis. RESULTS: After S. aureus challenge, compared to the Q half-sibship cows, the milk of the q cows exhibited higher PMN levels according to the DMCC (24 h, p < 0.001), a higher SCC (24 h, p < 0.01 and 36 h, p < 0.05), large cells (24 h, p < 0.05) and more dead (36 h, p < 0.001) and live cells (24 h, p < 0.01). The protein % was greater in Q milk than in q milk at 0 h (p = 0.025). In the S. aureus group, Q cows had a greater protein % (60 h, p = 0.048) and fat % (84 h, p = 0.022) than q cows. Initially, the greater VT of S. aureus-challenged q cows (0 and 12-24 h, p < 0.05) reversed to a lower VT in q cows than in Q cows (48-60 h, p < 0.05). Additionally, the following findings emphasized the validity of the model: in the S. aureus group all DMCC subpopulations (24 h-96 h, p < 0.001) and in the E. coli group nearly all DMCC subpopulations (12 h-24 h, p < 0.001) were higher in challenged quarters than in unchallenged quarters. The lactose % was lower in the milk samples of E. coli-challenged quarters than in those of S. aureus-challenged quarters (24 h, p < 0.001). Between 12 and 18 h, the VT was greater in cows challenged with E. coli than in those challenged with S. aureus (3-h interval approach, p < 0.001). CONCLUSION: This in vivo infection model confirmed specific differences between Q and q cows with respect to the DMCC, milk component analysis results and VT results after S. aureus inoculation but not after E. coli challenge. However, compared with conventional milk cell analysis monitoring, e.g., the global SCC, the DMCC analysis did not provide refined phenotyping of the pathogen response.

The determination of mastitis severity at 4-level using Milk physical properties: A deep learning approach via MLP and evaluation at different SCC thresholds.

Current research aims to generate an alternative model to classical methods in the determination of subclinical mastitis at 4 levels (healthy, suspicious, subclinical, and clinical). For this purpose, multilayer perceptron (MLP) artificial neural networks (ANN) was developed as test model. 5 variables from the physical properties of milk somatic cell count (SCC), electrical conductivity (EC), pH, density, and temperature at fore milking (TFM) were included in the model in the classification of mastitis. Model performance was validated on test data (%25) and compared with the multinomial logistic regression (MNLR). MLP model has shown a satisfactory performance with an accuracy of 95.14% and - 141 of AIC score better than the control model (MNLR) of 80.27% and - 133 AIC despite using higher number of parameters (104). Since the main problem is to diagnose subclinical mastitis, which does not cause any visible symptoms, it was important to distinguish between absolute subclinical (suspicious excluded positives) and absolute healthy (suspicious included positives) ones. Therefore, optimum cut-off threshold was evaluated for these two different scenarios with only variable SCC the gold standard indicator of subclinical mastitis and results were compared in the interpretation of model performance. The results show that the 5-variable MLP model exhibits a high sensitivity of 93.22% (AUC = 0.95 for healthy ones) at low cutoff thresholds as well. New studies should provide a better understanding by evaluating economics, sustainability, animal welfare and health aspects together to determine the optimal threshold value.

Cow-level risk factors associated with the increase in somatic cell count and the occurrence of subclinical mastitis in Brazilian Holstein and Jersey dairy cows.

Mastitis, a multifactorial disease influenced by both cow and herd-level factors, results in significant losses throughout the dairy chain. We aimed to evaluate the relationship between milking frequency (MF), parity order (PO), days in milk (DIM), and milk yield (MY) on somatic cell count (SCC) and the odds of a cow having subclinical mastitis (SCM) in Brazilian Holstein and Jersey dairy cows. Our dataset consisted of 747,520 test-day records from 52,954 cows, including 49,089 Holstein cows and 3865 Jersey cows and 498 herds. The SCC was evaluated using a generalized linear mixed model, whereas SCM occurrence was evaluated using a logistic regression model. A case of SCM was defined when a cow had >200×103 cells/mL. Our results indicated that the SCC increases with higher PO and DIM and decreases in cows milked three times a day and those with higher MY in both breeds (>40 and >25 L/d for Holstein and Jersey, respectively). Increasing MF from two to three times a day reduced the chances of a Holstein and Jersey cow having SCM by 10 and 20 %, respectively. For Holstein and Jersey cows, those with ≥quadriparous had 3.9 times and 2.2 times higher chances, respectively, of having SCM compared to primiparous cows. Cows with >305 DIM had 2.0 times greater chances of having SCM for both, Holstein and Jersey cows, compared to cows with ≤105 DIM. Holstein cows yielding ≥40 L/d had a 75 % lower chance of having SCM compared to those yielding <20 L/d, while Jersey cows with ≥25 L/d had a 60 % lower chance compared to those yielding <15 L/d. In conclusion, higher PO and DIM pose risks, whereas a MF of three times a day and higher MY are protective factors against increases in SCC and SCM occurrence in Brazilian Holstein and Jersey cows.

Genetic parameters for novel mastitis traits defined by combining test-day somatic cell score and differential somatic cell count in the first lactation of Japanese Holsteins.

In this study, we aimed to improve current udder health genetic evaluations by addressing the limitations of monthly sampled somatic cell score (SCS) for distinguishing cows with robust innate immunity from those susceptible to chronic infections. The objectives were to (1) establish novel somatic cell traits by integrating SCS and the differential somatic cell count (DSCC), which represents the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells and (2) estimate genetic parameters for the new traits, including their daily heritability and genetic correlations with milk production traits and SCS, using a random regression test-day model (RRTDM). We derived 3 traits, termed ML_SCS_DSCC, SCS_4_DSCC_65_binary, and ML_SCS_DSCC_binary, by using milk loss (ML) estimates at corresponding SCS and DSCC levels, thresholds established in previous studies, and a threshold established from milk loss estimates, respectively. Data consisted of test-day records collected during January 2021 through March 2022 from 265 herds in Hokkaido, Japan. From these records, we extracted records between 7 to 305 d in milk (DIM) in the first lactation to fit the RRTDM. The model included the random effect of herd-test-day, the fixed effect of year-month, fixed lactation curves nested with calving age groups, and random regressions with Legendre polynomials of order 3 for additive genetic and permanent environmental effects. The analysis was performed using Gibbs sampling with Gibbsf90+ software. The averages (ranges) of the daily heritability estimates over lactation were 0.086 (0.075-0.095) for SCS, 0.104 (0.073-0.127) for ML_SCS_DSCC, 0.137 (0.014-0.297) for SCS_4_DSCC_65_binary, and 0.138 (0.115-0.185) for ML_SCS_DSCC_binary; the heritability curve for SCS_4_DSCC_65_binary was erratic. Genetic correlations within the trait decreased as the DIM interval widened, especially for those integrating DSCC, indicating that these traits should be analyzed using RRTDM rather than repeatability models. The averages (ranges) of genetic correlations with milk yield over lactation were 0.01 (-0.22 to 0.28) for SCS, -0.05 (-0.40 to 0.13) for ML_SCS_DSCC, -0.08 (-0.17 to 0.09) for SCS_4_DSCC_65_binary, and -0.08 (-0.22 to 0.27) for ML_SCS_DSCC_binary. Compared with SCS, the newly defined traits exhibited slightly stronger negative genetic correlations with milk yield. Especially in late lactation stages, the genetic correlation between ML_SCS_DSCC and milk yield was significantly below zero, with a posterior median of -0.40. Furthermore, the new traits showed positive correlations with SCS, having estimates varying from 0.68 to 0.85 for ML_SCS_DSCC, 0.14 to 0.47 for SCS_4_DSCC_65_binary, and 0.61 to 0.66 for ML_SCS_DSCC_binary, depending on DIM. Considering that ML_SCS_DSCC and ML_SCS_DSCC_binary have relatively high heritability (compared with SCS) and favorable genetic correlations with milk production traits and SCS, their incorporation into breeding programs appears promising. Nevertheless, their genetic relationships with (sub)clinical mastitis require further investigation.

Metataxonomic analysis and host proteome response in dairy cows with high and low somatic cell count: a quarter level investigation.

Host response to invasive microbes in the bovine udder has an important role on the animal health and is essential to the dairy industry to ensure production of high-quality milk and reduce the mastitis incidence. To better understand the biology behind these host-microbiome interactions, we investigated the somatic cell proteomes at quarter level for four cows (collected before and after milking) using a shotgun proteomics approach. Simultaneously, we identified the quarter microbiota by amplicon sequencing to detect presence of mastitis pathogens or other commensal taxa. In total, 32 quarter milk samples were analyzed divided in two groups depending on the somatic cell count (SCC). The high SCC group (>100,000 cell/mL) included 10 samples and significant different proteome profiles were detected. Differential abundance analysis uncovers a specific expression pattern in high SCC samples revealing pathways involved in immune responses such as inflammation, activation of the complement system, migration of immune cells, and tight junctions. Interestingly, different proteome profiles were also identified in quarter samples containing one of the two mastitis pathogens, Staphylococcus aureus and Streptococcus uberis, indicating a different response of the host depending on the pathogen. Weighted correlation network analysis identified three modules of co-expressed proteins which were correlated with the SCC in the quarters. These modules contained proteins assigned to different aspects of the immune response, but also amino sugar and nucleotide sugar metabolism, and biosynthesis of amino acids. The results of this study provide deeper insights on how the proteome expression changes at quarter level in naturally infected cows and pinpoint potential interactions and important biological functions during host-microbe interaction.

Mechanism of transepithelial migration of lymphocytes into the milk in porcine mammary glands.

Lymphocytes in the colostrum play many important roles during lactation, including protecting newborn piglets against infections. The lymphocytes constantly enter the mammary gland from the mother's bloodstream before and during lactation. However, little is known about the mechanism of transport of maternal lymphocytes across the mammary glands into the milk (lumen). In this study, the maternal lymphocytes were detected in sow colostrum by immunofluorescent staining and fluorescence-activated cell sorting and lymphocytes were observed transmigrating into the breast acinar lumen. Furthermore, immunohistochemical staining revealed that CD3+ T, γδ+ T, and IgA+ B cells were primarily located at the base area of the mammary gland. Meanwhile, more lactating alveoli and blood capillaries were distributed in this area. Finally, a mammary epithelial cell (EpH4-Ev)/T cell co-culture system was established to explore the mechanism of lymphocyte transmigration across the mammary epithelial cells. The expression of CCL2 and CCL28 in EpH4-Ev cells, which facilitated the transmigration of lymphocytes, significantly increased in the presence of prolactin. Our results provide a better understanding of the concept of lactogenic immunity and pave the way for vaccination strategies for the induction of lactogenic immunity in pregnant swine.

Active cargo loading into extracellular vesicles: Highlights the heterogeneous encapsulation behaviour.

Extracellular vesicles (EVs) have demonstrated unique advantages in serving as nanocarriers for drug delivery, yet the cargo encapsulation efficiency is far from expectation, especially for hydrophilic chemotherapeutic drugs. Besides, the intrinsic heterogeneity of EVs renders it difficult to evaluate drug encapsulation behaviour. Inspired by the active drug loading strategy of liposomal nanomedicines, here we report the development of a method, named "Sonication and Extrusion-assisted Active Loading" (SEAL), for effective and stable drug encapsulation of EVs. Using doxorubicin-loaded milk-derived EVs (Dox-mEVs) as the model system, sonication was applied to temporarily permeabilize the membrane, facilitating the influx of ammonium sulfate solution into the lumen to establish the transmembrane ion gradient essential for active loading. Along with extrusion to downsize large mEVs, homogenize particle size and reshape the nonspherical or multilamellar vesicles, SEAL showed around 10-fold enhancement of drug encapsulation efficiency compared with passive loading. Single-particle analysis by nano-flow cytometry was further employed to reveal the heterogeneous encapsulation behaviour of Dox-mEVs which would otherwise be overlooked by bulk-based approaches. Correlation analysis between doxorubicin auto-fluorescence and the fluorescence of a lipophilic dye DiD suggested that only the lipid-enclosed particles were actively loadable. Meanwhile, immunofluorescence analysis revealed that more than 85% of the casein positive particles was doxorubicin free. These findings further inspired the development of the lipid-probe- and immuno-mediated magnetic isolation techniques to selectively remove the contaminants of non-lipid enclosed particles and casein assemblies, respectively. Finally, the intracellular assessments confirmed the superior performance of SEAL-prepared mEV formulations, and demonstrated the impact of encapsulation heterogeneity on therapeutic outcome. The as-developed cargo-loading approach and nano-flow cytometry-based characterization method will provide an instructive insight in the development of EV-based delivery systems.

Development of an advanced flow cytometry based high-resolution immunophenotyping method to benchmark early immune response in dairy cows.

The determination of the somatic cell count of a milk sample is one of the most common methods to monitor udder health of a dairy cow. However, this procedure does not take into account the fact that cells in milk present a great variety of different cell types. The objective of our study was to establish a high-resolution differential cell count (HRDCC) by means of flow cytometry in blood and milk. We were able to detect ten subpopulations among the three main populations of immune cells and to determine their viability. Additionally, blood samples were analyzed for common laboratory biomarkers, i.e. differential blood counts, haptoglobin levels and several metabolic parameters. In this first feasibility study, we used three different vaccines to stimulate the immune system of five healthy cows each. Samples were collected shortly before, in between and after the vaccinations. Using multivariate statistical methods we saw a diagnostic benefit when HRDCCs were included compared to only the standard laboratory parameters. The impacts of all three vaccinations on the immune system were visible in blood HRDCCs as well as in milk HRDCCs. Cluster of Differentiation 8+ (CD8+) T cells, B cells and monocyte/macrophage subpopulations were among the most important and statistically relevant parameters for all treatments in both biofluids. Moreover, in one of the treatment groups intermediate monocytes showed a significant increase after both vaccinations. Although the use of HRDCC in blood or milk was shown to be highly relevant for early systemic diagnostic, to confirm these subpopulations further investigations in cows of different breed, lactation stage or health status are required.

Genome-Wide Association Studies for Milk Somatic Cell Score in Romanian Dairy Cattle.

Mastitis is one of the most frequently encountered diseases in dairy cattle, negatively affecting animal welfare and milk production. For this reason, contributions to understanding its genomic architecture are of great interest. Genome-wide association studies (GWAS) have identified multiple loci associated with somatic cell score (SCS) and mastitis in cattle. However, most of the studies have been conducted in different parts of the world on various breeds, and none of the investigations have studied the genetic architecture of mastitis in Romanian dairy cattle breeds up to this point in time. In this study, we report the first GWAS for SCS in dairy cattle breeds from Romania. For GWAS, we used an Axiom Bovine v3 SNP-chip (>63,000 Single Nucleotide Polymorphism -SNPs) and 33,330 records from 690 cows belonging to Romanian Spotted (RS) and Romanian Brown (RB) cattle. The results found one SNP significantly associated with SCS in the RS breed and 40 suggestive SNPs with -log10 (p) from 4 to 4.9 for RS and from 4 to 5.4 in RB. From these, 14 markers were located near 12 known genes (AKAP8, CLHC1, MEGF10, SATB2, GATA6, SPATA6, COL12A1, EPS8, LUZP2, RAMAC, IL12A and ANKRD55) in RB cattle, 3 markers were close to ZDHHC19, DAPK1 and MMP7 genes, while one SNP overlapped the HERC3 gene in RS cattle. Four genes (HERC3, LUZP2, AKAP8 and MEGF10) associated with SCS in this study were previously reported in different studies. The most significant SNP (rs110749552) associated with SCS was located within the HERC3 gene. In both breeds, the SNPs and position of association signals were distinct among the three parities, denoting that mastitis is controlled by different genes that are dependent according to parity. The current results contribute to an expansion in the body of knowledge regarding the proportion of genetic variability explained by SNPs for SCS in dairy cattle.

Occurrence and aetiology of subclinical mastitis in water buffalo in Bangladesh.

Subclinical mastitis (SCM) in water buffalo is a production disease associated with decreased milk yield and impaired milk quality and safety. Water buffalo is an important livestock species in Bangladesh, but information about the occurrence and aetiology of SCM in this species is scarce. A cross-sectional study was conducted as part of the Udder Health Bangladesh Programme to (i) determine the occurrence of SCM and bulk milk somatic cell count (SCC) in water buffalo in Bangladesh, (ii) identify pathogens causing SCM and (iii) evaluate penicillin resistance in isolated staphylococci strains. Sixteen buffalo farms in the Bagerhat and Noakhali regions of Bangladesh were selected for study and a bulk milk sample was collected from each farm. In addition, 299 udder quarter milk samples were collected from 76 animals. The bulk milk samples were assessed by direct SCC and the quarter milk samples by California mastitis test (CMT). The occurrence of SCM calculated at quarter and animal level was 42.5 and 81.6%, respectively. Milk samples from 108 CMT-positive quarters in 48 animals and 38 randomly selected CMT-negative quarters in 24 animals were investigated using bacteriological culture. Estimated mean bulk milk SCC was 195 000 cells/ml milk (range 47 000- 587 000 cells/ml milk). On culture, estimated quarter-level intramammary infection (IMI) was 40.4%. The identity of isolated bacteria was confirmed by MALDI-TOF mass spectrometry. Non-aureus staphylococci (NAS) were the most common pathogens (24.7%) and, among 36 NAS tested, 36.1% were resistant to penicillin. Thus there was high occurrence of SCM on the study farms, with relatively high penicillin resistance in NAS. Further studies are needed to identify underlying risk factors and develop an udder health control strategy for water buffalo in Bangladesh.

Variations in the levels of acute-phase proteins and lactoferrin in serum and milk during bovine subclinical mastitis.

Variations in the levels of acute phase proteins and lactoferrin in serum and milk for diagnosis of subclinical mastitis in dairy cows are described in this research paper. Milking animals from two organized dairy farms in Kerala, India, were screened by California Mastitis Test (CMT), Electrical Conductivity test (EC) and Somatic Cell Count (SCC) test to identify animals affected with sub clinical mastitis (SCM). The concentrations of acute phase proteins (APP) Haptoglobin (Hp), C- reactive protein (CRP), Albumin, Lactoferrin (Lf) and α- 1 acid glycoprotein (AGP) in milk and Hp, Albumin, Serum Amyloid A (SAA) and CRP in the serum of 40 normal cows and 40 cows affected with sub clinical mastitis were assessed. Solid phase ELISA was employed for assessment of all parameters except the albumin levels, for which spectrophotometry was used. The values of Hp in milk; and SAA, AGP and Lf in serum, were significantly elevated in the group with sub clinical mastitis. Such variations were found to be independent of the specific bacterial organism causing the disease. These results show that significant variations exist in the levels of acute phase proteins Hp, AGP and Lf in milk, and SAA in serum of animals affected with subclinical bovine mastitis that are not affected by specific bacterial etiology.

Extensive countrywide field investigation of somatic cell counts and total bacterial counts in bulk tank raw milk in goat herds in Greece.

Dairy goat farming is an important sector of the agricultural industry in Greece, with an annual total milk production exceeding 450 000 l and accounting for over 25% of all goat milk produced in the European Union; this milk is used mainly for cheese production. Despite the importance of goat milk for the agricultural sector in Greece, no systematic countrywide investigations in the bulk-tank milk of goats in Greece have been reported. Objectives were to investigate somatic cell counts (SCC) and total bacterial counts (TBC) in raw bulk-tank milk of goat herds in Greece, study factors influencing SCC and TBC therein and evaluate their possible associations with milk content. Throughout Greece, 119 dairy goat herds were visited for milk sampling for somatic cell counting, microbiological examination and composition measurement. Geometric mean SCC and TBC were 0.838 × 106 cells ml-1 and 581 × 103 cfu ml-1, respectively. Multivariable analyses revealed annual frequency of check-ups of milking system and total milk quantity per goat (among 53 variables) to be significant for increased SCC; no factor emerged (among 58 variables) to be significant for increased TBC. Negative correlation of SCC with total protein was found; mean total protein content in the bulk-tank milk in herds with SCC >0.75 × 106 cells ml-1 was 5.1% lower and in herds with SCC >1.5 × 106 cells ml-1, it was 7.8% lower.

Bayesian estimation of diagnostic accuracy of somatic cell counts history and on-farm milk culture using Petrifilm® to identify quarters or cows that should be treated with antimicrobials in selective treatment protocols at dry off.

Bayesian latent class models were used to estimate the test accuracy (sensitivity (Se), specificity (Sp), and predictive values (NPV and PPV)) of cow-level somatic cell counts (SCC) data, quarter-level Petrifilm® on-farm milk culture, and quarter-level standard milk bacteriology for the identification of quarters that should possibly be treated with antimicrobials at dry off in dairy cows. Data of 282 cows from 9 dairy herds in Québec, Canada, with bulk tank SCC < 250,000 cells/mL were used. Estimated median herd-prevalence of infections that should be treated was 16.2 % (95 % credibility interval (CI): 11.0-22.7). Se and Sp estimates for quarter-milk culture using Petrifilm® were 82.2 % (95 %CI: 74.0-89.5) and 62.0 % (95 %CI: 58.6-65.6), respectively. Se and Sp for quarter-milk standard bacteriology were 67.4 % (95 %CI: 55.8-81.2) and 79.6 % (95 %CI: 76.4-83.0), respectively. Se and Sp of different SCC scenarios and thresholds were estimated. For first parity cows, using only the last Dairy Herd Improvement (DHI) test SCC with a threshold of 100,000 cells/mL appeared quite accurate, with Se, Sp, PPV, NPV and reduction of antimicrobial usage of 85.6 % (95 %CI: 69.6-95.6), 86.0 % (95 %CI: 80.0-91.7), 58.0 % (95 %CI: 42.3-74.2), 96.4 % (95 %CI: 91.3-99.0), and 75.3 % (95 %CI: 70.7-79.3), respectively. For cows of ≥ 2nd parity, using only the last DHI test SCC with a threshold of 200,000 cells/mL resulted in Se, Sp, PPV, NPV and reduction of antimicrobial usage of 75.3 % (95 %CI: 55.8-87.3), 84.0 % (95 %CI: 78.8-89.3), 47.2 % (95 %CI: 32.0-63.7), 94.7 % (95 %CI: 89.0-97.6), and of 77.0 % (95 %CI: 73.3-80.3), respectively. Adding quarter-level milk culture using Petrifilm® to cows identified as unhealthy using cow-level SCC data improved the test accuracy (mainly the PPV) and further reduced the use of antimicrobials. For instance, in ≥ 2nd parity cows, using only the last DHI SCC with a threshold of 200,000 cells/mL, adding a subsequent Petrifilm® test increased the reduction from 77.0 % (95 %CI: 73.3-80.3) to 89.5 % (95 %CI: 86.7-91.8). Considering the availability of SCC data, the easiness of using just the last DHI test, and the high NPV that could be achieved, producers may consider using just the last DHI test as a potential tool to identify cows that should be treated with antimicrobials at dry off. It may be used alone or in combination with quarter-level on-farm Petrifilm® milk culture on high SCC cows to further reduce the use of antimicrobials by identifying quarters that need to be treated.

Milk lymphocyte profile and macrophage functions: new insights into the immunity of the mammary gland in quarters infected with Corynebacterium bovis.

BACKGROUNDS: The present study explored the viability of bovine milk macrophages, their intracellular production of reactive oxygen and nitrogen species (RONS), and their phagocytosis of Staphylococcus aureus, as well as the profile of lymphocytes, from healthy udder quarters and udder quarters infected by Corynebacterium bovis. The study included 28 healthy udder quarters from 12 dairy cows and 20 udder quarters infected by C. bovis from 10 dairy cows. The percentages of macrophages and lymphocytes were identified by flow cytometry using monoclonal antibodies. Macrophage viability, RONS production, and S. aureus phagocytosis were evaluated by flow cytometry. RESULTS: Milk samples from quarters infected with C. bovis showed a lower percentage of macrophages but an increased number of milk macrophages per mL and a higher percentage of macrophages that produced intracellular RONS and phagocytosed S. aureus. No effect of C. bovis infection on macrophage viability was found. Udder quarters infected by C. bovis showed a higher percentage of T cells and CD4+ T lymphocytes, but no effect was found on the percentage of CD8+ CD4- T, CD8- CD4- T, or B lymphocytes. CONCLUSIONS: Thus, our results corroborate, at least in part, the finding that intramammary infections by C. bovis may offer protection against intramammary infections by major pathogens.