Assessing the Usefulness of Interleukin-8 as a Biomarker of Inflammation and Metabolic Dysregulation in Dairy Cows

The study aimed to evaluate interleukin-8 (IL-8) as a biomarker for udder inflammation in dairy cows and to explore its associations with various metabolic parameters indicative of systemic inflammation and metabolic dysregulation. Dairy cows (multiparous) were categorized into five somatic cell count (SCC) classes: Class I (<100,000 cells/mL; n = 45), Class II (100,000-200,000 cells/mL; n = 62), Class III (201,000-400,000 cells/mL; n = 52), Class IV (401,000-1,000,000 cells/mL; n = 73), and Class V (>1,000,000 cells/mL; n = 56). The study quantified IL-8 levels and analyzed their correlations with NEFAs (non-esterified fatty acids), BHBA (beta-hydroxybutyrate), GGTP (gamma-glutamyltransferase), and AspAT (aspartate aminotransferase). IL-8 concentrations demonstrated a significant and progressive increase across the SCC classes, establishing a strong positive correlation with SCC (p < 0.01). Additionally, IL-8 levels exhibited positive correlations with GGTP (p < 0.01) and AspAT (p < 0.01), indicating that elevated IL-8 is associated with increased hepatic enzyme activities and potential liver dysfunction. Furthermore, IL-8 showed significant positive correlations with NEFAs (p < 0.01) and BHBA (p < 0.05), linking higher IL-8 levels to metabolic disturbances such as ketosis and negative energy balance. Variations in metabolic parameters, including NEFAs, BHBA, GGTP, and AspAT, across the SCC classes underscored the association between elevated SCC levels and metabolic dysregulation in dairy cows. These findings highlight the interrelated nature of the inflammatory responses and metabolic disturbances in dairy cattle, emphasizing that an elevated SCC not only signifies udder inflammation but also correlates with systemic metabolic alterations indicative of ketosis and liver damage.

Identifying strategies to enhance the milking and operator efficiency of herringbone and rotary parlor systems in Ireland

International trends of increasing dairy herd sizes coupled with scarcity of labor has necessitated the enhancement of labor efficiency for dairy production systems. This study quantified the effects of infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors used on pasture-based farms in Ireland. Data from 592 milkings across 26 farms (16 herringbones and 10 rotaries) was used. The metrics of cows milked per hour (cows/h), cows milked per operator per hour (cows/h per operator) and liters of milk harvested per hour (L/h) described milking efficiency. The metrics of total process time per cow (TPT, s/cow), milk process time per cow (MPT, s/cow), work routine time (WRT, s/cow), cluster time (CT, s/cluster), and attachment time per cow (ATC, s/cow) described operator efficiency. Automations investigated were backing gates, cluster flush, plant wash, cluster removers (ACRs), feeders, entry gates, rapid-exit, and teat spray. Additional operator presence at milking was also investigated. Herringbone and rotary parlors were assigned to quartiles from their cows/h per operator values to examine infrastructure, automations, and management practices variations. Fourth quartile herringbones based on cows/h per operator values (Q4) averaged 93 cows/h per operator using average system sizes of 24 clusters with 5 parlor automations. Q4 rotaries averaged 164 cows/h per operator using average system sizes of 47 clusters and an average CT of 13 s/cluster. Cows/h per operator values for Q4 herringbone and rotary parlors were 82% and 54% higher, respectively, than values observed on Q1 parlors, indicating the considerable potential to improve efficiency. To determine if infrastructure, automations, or additional operators at milking significantly affected operator efficiencies, general linear mixed models were developed. For parlor infrastructure, additional clusters had greater significance on operator efficiencies (MPT) for herringbones (-1.3 s/cow) as opposed to rotaries (-0.2 s/cow). Hence, increases in system size was likely to result in improved efficiencies for herringbones but less so for rotaries. For automations, ACRs significantly reduced herringbone TPT, CT, and WRT values by 13.3 s/cow, 18.9 s/cluster, and 32.6 s/cow, respectively, whereas rapid-exit significantly lowered CT by 18.6 s/cluster. We found no significant effect on rotary TPT, MPT, CT, or WRT values from the use of automatic teat sprayers. An additional operator at milking was found to significantly reduce herringbone TPT but not MPT or CT. For rotaries, a second operator had no significant effect on TPT, MPT, CT, or WRT values. We documented strong negative correlations between operator efficiencies (TPT, MPT) and milking efficiency (cows/h) for both herringbone (-0.91, -0.84) and rotaries (-0.98, -0.89). Strong negative correlations between the herringbone automation count and TPT (-0.80), MPT (-0.72), and CT (-0.75) suggested highly automated parlors were likely to achieve greater operator efficiencies than less automated parlors. The strong negative correlation (-0.81) between rotary milking efficiency (cows/h) and CT suggested lower CT values (i.e., rotation speed) resulted in increased milking efficiency. In conclusion, our study quantified the effects of parlor infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors.

Alternative Traits for Genetic Evaluation of Mastitis Based on Lifetime Merit

Genetic selection has achieved little progress in reducing mastitis incidence. Mastitis traits are problematic due to the lack of sensitivity of the data and reliance on clinical diagnosis, often missing subclinical cases, and/or on monthly somatic cell count (SCC) measurements. The current measure for mastitis is the lactation average of the somatic cells score (LSCS). We studied two datasets: (1) 148 heifers divided into non-intramammary infected, sub-clinically infected and clinical mastitis groups; (2) data from 89,601 heifers from Israeli Holsteins through the same period divided into "udder healthy" (UH) and "non-healthy" (UNH) by a threshold of SCC 120,000 cells/mL in all nine monthly milk recordings. In study 1, non-infected heifers had significantly (p < 0.05) more partum, production days and overall lifetime milk production compared to clinical and sub-clinically infected. In study 2, UH heifers (20.3%) had significantly higher (p < 0.01) lifetime milk, production days, and lactations. Subdividing datasets by sires, the same analyses detected differences in percentages of UH daughters between the sire groups. Lifetime milk production correlated (r = +0.83, p < 0.001) with udder health status. SCC threshold of less than 120,000 cells/mL during all first lactation measurements indicated healthy udder, providing a valuable insight that this dichotomous trait is advantageous for calculating lifetime net-merit index (NM$) over LSCS.

Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows

Use of selective dry cow antimicrobial therapy requires to precisely differentiate cows with an intramammary infection (IMI) from uninfected cows close to drying-off to enable treatment allocation. Milk somatic cell count (SCC) is an indicator of an inflammatory response in the mammary gland and is usually associated with IMI. However, SCC can also be influenced by cow-level variables such as milk yield, lactation number and stage of lactation. In recent years, predictive algorithms have been developed to differentiate cows with IMI from cows without IMI based on SCC data. The objective of this observational study was to explore the association between SCC and subclinical IMI, taking cognizance of cow-level predictors on Irish seasonal spring calving, pasture-based systems. Additionally, the optimal test-day SCC cut-point (maximized sensitivity and specificity) for IMI diagnosis was determined. A total of 2,074 cows, across 21 spring calving dairy herds with an average monthly milk weighted bulk tank SCC of ≤200,000 cells/mL were enrolled in the study. Quarter-level milk sampling was carried out on all cows in late lactation (interquartile range = 240-261 d in milk) for bacteriological culturing. Bacteriological results were used to define cows with IMI, when ≥1 quarter sample resulted in bacterial growth. Cow-level test-day SCC records were provided by the herd owners. The ability of the average, maximum and last test-day SCC to predict infection were compared using receiver operator curves. Predictive logistic regression models tested included parity (primiparous or multiparous), yield at last test-day and a standardized count of high SCC test-days. In total, 18.7% of cows were classified as having an IMI, with first parity cows having a higher proportion of IMI (29.3%) compared with multiparous cows (16.1%). Staphylococcus aureus accounted for the majority of these infections. The last test-day SCC was the best predictor of infection with the highest area under the curve. The inclusions of parity, yield at last test-day, and a standardized count of high SCC test-days as predictors did not significantly improve the ability of last test-day SCC to predict IMI. The cut-point for last test-day SCC which maximized sensitivity and specificity was 64,975 cells/mL. This study indicates that in Irish seasonal pasture-based dairy herds,with low bulk tank SCC control programs, the last test-day SCC (interquartile range days in milk = 221-240) is the best predictor of IMI in late lactation.

Mastitis: Impact of Dry Period, Pathogens, and Immune Responses on Etiopathogenesis of Disease and its Association with Periparturient Diseases

Mastitis is an inflammation of the mammary gland initiated by pathogenic bacteria. In fact, mastitis is the second most important reason for the culling of cows from dairy herds, after infertility. In this review we focus on various forms of mastitis, including subclinical and clinical mastitis. We also stress the importance of the dry-off period as an important time when pathogenic bacteria might start their insult to the mammary gland. An important part of the review is the negative effects of mastitis on milk production and composition, as well as economic consequences for dairy farms. The two most important groups of bacteria that are involved in infection of the udder, Gram-negative and Gram-positive bacteria, are also discussed. Although all cows have both innate and adaptive immunity against most pathogens, some are more susceptible to the disease than others. That is why we summarize the most important components of innate and adaptive immunity so that the reader understands the specific immune responses of the udder to pathogenic bacteria. One of the most important sections of this review is interrelationship of mastitis with other diseases, especially retained placenta, metritis and endometritis, ketosis, and laminitis. Is mastitis the cause or the consequence of this disease? Finally, the review concludes with treatment and preventive approaches to mastitis.

Use of a culture-independent on-farm algorithm to guide the use of selective dry-cow antibiotic therapy

An algorithm using only computer-based records to guide selective dry-cow therapy was evaluated at a New York State dairy farm via a randomized field trial. DairyComp 305 (Valley Ag Software, Tulare, CA) and Dairy Herd Improvement Association test-day data were used to identify cows as low risk (cows that might not benefit from dry-cow antibiotics) or high risk (cows that will likely benefit). Low-risk cows were those that had all of the following: somatic cell count (SCC) ≤200,000 cells/mL at last test, an average SCC ≤200,000 cells/mL over the last 3 tests, no signs of clinical mastitis at dry-off, and no more than 1 clinical mastitis event in the current lactation. Low-risk cows were randomly assigned to receive intramammary antibiotics and external teat sealant (ABXTS) or external teat sealant only (TS) at dry-off. Using pre-dry-off and postcalving quarter-level culture results, low-risk quarters were assessed for microbiological cure risk and new infection risk. Groups were also assessed for differences in first-test milk yield and linear scores, individual milk weights for the first 30 d, and culling and mastitis events before 30 d in milk. A total of 304 cows and 1,040 quarters in the ABXTS group and 307 cows and 1,058 quarters in the TS group were enrolled. Among cows to be dried, the proportion of cows that met low-risk criteria was 64% (n = 611/953). Of cultures eligible for bacteriological cure analysis (n = 171), 93% of ABXTS cured, whereas 88% of TS cured. Of the non-cures, 95% were contributed by the minor pathogens coagulase-negative staphylococci (n = 19/20). These organisms also accounted for 57.5% of new infections (n = 77/134). We found no statistical differences between treatment groups for new infection risk (TS = 7.3% quarters experiencing new infections; ABXTS = 5.5%), milk production (ABXTS = 40.5 kg; TS = 41.2 kg), linear scores (ABXTS = 2.5; TS = 2.7), culling events (ABXTS, n = 18; TS, n = 15), or clinical mastitis events (ABXTS, n = 9; TS, n = 5). Results suggest that the algorithm used decreased dry-cow antibiotic use by approximately 60% without adversely affecting production or health outcomes.

Current management practices and interventions prioritised as part of a nationwide mastitis control plan

The objectives of this study were to report performance and management data taken from a sample of UK dairy farms that have participated in the Agriculture and Horticulture Development Board Dairy Mastitis Control Plan (DMCP) and to identify important mastitis prevention practices that are not currently widely implemented. A total of 234 UK dairy herds were included in the study from which farm management and udder health data were collected. Herds were grouped according to their mastitis epidemiology and could be classed as (i) environmental dry period (EDP) (i.e. environmental pathogen with majority of infections being acquired during the dry period), (ii) environmental lactation (EL), (iii) contagious dry period (CDP) or (iv) contagious lactation (CL). The results of this study showed that many mastitis-related management practices that are generally considered to be important were not widely performed. A better understanding of those practices not widely adopted by UK dairy farmers at present may aid practitioners in identifying and overcoming potential barriers to improved mastitis control.

Udder infections with Staphylococcus aureus, Streptococcus dysgalactiae, and Streptococcus uberis at calving in dairy herds with suboptimal udder health

Udder infections with Staphylococcus aureus, Streptococcus dysgalactiae, and Streptococcus uberis are common causes of bovine mastitis. To study these pathogens in early lactation, a 12-mo longitudinal, observational study was carried out in 13 herds with suboptimal udder health. The aims of the study were to investigate the occurrence of these pathogens and to identify if presence of the 3 pathogens, and of genotypes within the pathogens, differed with respect to herd, season, and parity. Quarter milk samples, collected at calving and 4 d in milk (DIM), were cultured for the 3 pathogens. Genotyping of staphylococcal and streptococcal isolates was performed using spa typing and pulsed-field gel electrophoresis, respectively. For each of the 3 pathogens, cows with an udder infection at calving or 4 DIM were allocated to 1 of 4 infection types: cleared (pathogen present only at calving), persistent (pathogen present in the same quarter at calving and 4 DIM), new (pathogen present only at 4 DIM), or cleared/new (pathogen present in 1 quarter at calving and in another quarter at 4 DIM). Associations between season or parity and overall occurrence of pathogens or infection types were determined using univariable mixed-effect logistic-regression models and the Fisher's exact test, respectively. The most commonly occurring pathogen was Staph. aureus, followed by Strep. dysgalactiae and Strep. uberis. Persistent infections were the most common infection type among Staph. aureus-infected cows, whereas cleared infections were the most common among Strep. dysgalactiae- and Strep. uberis-positive cows. The proportion of cows with persistent Staph. aureus infections and the proportion of cows having a Strep. uberis infection at calving or 4 DIM were higher in the multiparous cows than in primiparous cows. Infections with Strep. dysgalactiae were less common during the early housing season than during the late housing or pasture seasons, whereas persistent Strep. uberis infections were less common during the pasture season than during the late housing season. The relative occurrence of the 3 pathogens, infection types of each pathogen, and genotype diversity of each pathogen throughout the year or in different seasons and parities varied among the herds, indicating that underlying factors predisposing for udder infections at calving differ between herds. Genotyping of bacterial isolates gave important insight into how such infection patterns differed within and between herds. These findings emphasize the need to choose preventive strategies for each individual herd.