Ability of milk pH to predict subclinical mastitis and intramammary infection in quarters from lactating dairy cattle

Sialic Acid Receptor Specificity in Mammary Gland of Dairy Cattle Infected with Highly Pathogenic Avian Influenza A(H5N1) Virus

In March 2024, the US Department of Agriculture's Animal and Plant Health Inspection Service reported detection of highly pathogenic avian influenza (HPAI) A(H5N1) virus in dairy cattle in the United States for the first time. One factor that determines susceptibility to HPAI H5N1 infection is the presence of specific virus receptors on host cells; however, little is known about the distribution of the sialic acid (SA) receptors in dairy cattle, particularly in mammary glands. We compared the distribution of SA receptors in the respiratory tract and mammary gland of dairy cattle naturally infected with HPAI H5N1. The respiratory and mammary glands of HPAI H5N1-infected dairy cattle are rich in SA, particularly avian influenza virus-specific SA α2,3-gal. Mammary gland tissues co-stained with sialic acids and influenza A virus nucleoprotein showed predominant co-localization with the virus and SA α2,3-gal. HPAI H5N1 exhibited epitheliotropism within the mammary gland, and we observed rare immunolabeling within macrophages.

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.

Staphylococcal mastitis in dairy cows

Bovine mastitis is one of the most common diseases of dairy cattle. Even though different infectious microorganisms and mechanical injury can cause mastitis, bacteria are the most common cause of mastitis in dairy cows. Staphylococci, streptococci, and coliforms are the most frequently diagnosed etiological agents of mastitis in dairy cows. Staphylococci that cause mastitis are broadly divided into Staphylococcus aureus and non-aureus staphylococci (NAS). NAS is mainly comprised of coagulase-negative Staphylococcus species (CNS) and some coagulase-positive and coagulase-variable staphylococci. Current staphylococcal mastitis control measures are ineffective, and dependence on antimicrobial drugs is not sustainable because of the low cure rate with antimicrobial treatment and the development of resistance. Non-antimicrobial effective and sustainable control tools are critically needed. This review describes the current status of S. aureus and NAS mastitis in dairy cows and flags areas of knowledge gaps.

Multi-criteria decision analysis for supporting the selection of subclinical mastitis screening tests to use in large- and small-scale dairy farms in Türkiye

The production of high-quality and safe milk is closely associated with the udder health of dairy cows. While there are many mastitis diagnostic tests/methods available, choosing the most appropriate diagnostic test for a sustainable udder health control program could be a challenge. This study was aimed at selecting tests for the screening of subclinical mastitis on small- and large-scale dairy farms in Türkiye, using multi-criteria decision-making methods. An integrated approach employing the analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) together was used to select subclinical mastitis screening tests for on-farm use. While the AHP determines the weights of the evaluation criteria, the TOPSIS provides a final ranking. Nine different subclinical mastitis screening (SCM) methods (DeLaval somatic cell counter, PortaSCC test, California mastitis test (CMT), rapid culture, portable/hand-held electrical conductivity meter, infrared thermography, leukocyte esterase strip test, milk pH, UdderCheck test) were analyzed on the basis of five selection criteria (the market availability of the test, the diagnostic accuracy of the test, the cost of the test, the cow-side use of the test, and the practicality of the test). The selection criteria were determined based on literature review and stakeholder input. The weighting of the criteria with the AHP was based on the pairwise comparison of the criteria by stakeholders. The criteria were weighted from 1 to 9 according to their relative importance as follows: "1: equally important," "3: moderately important," "5: strongly important," "7: very strongly important," "9: extremely important," and "2, 4, 6, 8: intermediate values." Final ranking of SCM tests with the TOPSIS was based on the stakeholder evaluations of fulfillment of the criteria by the alternatives. The most appropriate screening test for both large- and small-scale dairy farms was determined to be the CMT. The CMT is a very useful, easy to perform, and low-cost tool for detecting subclinical mastitis. Being a major element of udder health control programs, the CMT, if regularly used on dairy farms in Türkiye, would enable the culling of chronically infected animals and the reduction of mastitis-associated economic losses. Furthermore, regular CMTs would contribute to reducing milk SCC and improving milk quality. In conclusion, multi-criteria decision-making methods not only provide a systematic approach that may assist both veterinarians and farmers in deciding on the best choice among the different tests available for the screening of subclinical mastitis but also offer potential benefits to policymakers, researchers, and other industry stakeholders.

Risk prediction model of clinical mastitis in lactating dairy cows based on machine learning algorithms

Mastitis is the most common disease among dairy cows and is known to have negative effects on both animal welfare and the profitability of dairy farms. Early detection of clinical mastitis cases is considered the best option for preventing cows from developing mastitis. In this study, we developed clinical mastitis prediction models that only required inputting common indicators from the automatic milking system. We utilized multidimensional data from the cow mastitis database of Afimilk (China) Agricultural Technology Co., Ltd. to predict mastitis in dairy cows. All data were screened for the period of 0-150 days of lactation. The data included parity, lactation day, period, mean and standard deviation of milk yield, of electrical conductivity, and of lying time, which were taken as input features. The classification of whether cows suffer from clinical mastitis was determined as output. We analyzed 426 cows with clinical mastitis and 2087 healthy cows by using four machine learning algorithms: Decision Tree, Random Forest, Back Propagation neural networks, and Support Vector Machines. In these four algorithms, the accuracy ranged from 94% to 98%, while the running times varied widely from seconds to minutes. The decision tree prediction model achieved an accuracy of 98% and the precision rate for healthy cows was 99%, while for mastitis cows it was 97%. Machine learning algorithms have played an important role in predicting cow mastitis, with the Decision Tree algorithm showing great performance and higher accuracy in our research.

Variations in Composition, Antioxidant Profile, and Physical Traits of Goat Milk within the Semi-Intensive Production System in Mountainous Areas during the Post-Weaning to End-of-Lactation Period

Dairy products from mountain-origin milk are known for their superior composition and quality. This study aimed to examine changes in composition, nutritional quality, and antioxidant properties of milk from semi-intensively managed goats in mountainous regions during the post-weaning to end-of-lactation period. Bulk tank milk samples from 10 farms were collected bi-weekly in the period from March to September. The farms were situated in regions with an average altitude of 772.20 m above sea level. The results revealed significant variations in milk composition, with fluctuations in fat, protein, lactose, and total solids. Milk yield per doe showed seasonal differences, with the highest yield in April and the lowest in September. Fatty acid composition exhibited changes throughout the sampling period, with variations in polyunsaturated fatty acids. Nutritional indices, such as the atherogenicity index and thrombogenicity index, remained within the recommended values. Antioxidant properties, including total phenolic content, DPPH, FRAP, and ABTS, showed significant differences, with higher values toward the end of the study. Milk pH, electrical conductivity, brix value, and refractive index also exhibited variations, while density and freezing point remained relatively stable. The study provided valuable information that can be used to develop breeding and feeding plans to achieve uniform milk quality in mountainous regions.

Comparison of an image cytometry somatic cell count analyzer to a flow cytometry analyzer

The objective of this study was to evaluate the performance of a small footprint benchtop somatic cell counter based on image cytometry (LactiCyte HD; Page and Pedersen International Ltd., Hopkinton, MA) against a flow cytometer employed at a regional dairy herd improvement (DHI) laboratory. Milk samples collected during monthly DHI testing were split into 2 samples. One sample was evaluated using flow cytometry (Bentley SomaCount FCM; Bentley Instruments, Chaska, MN) at the regional DHI laboratory, whereas the other was evaluated using image cytometry at 2 different image levels (full number of images, 16 pictures per slide; half number of images, 8 pictures per slide). Mean bias of the image cytometer at 16 images was -15,500 cells/mL, whereas at 8 images the bias was 21,800 cells/mL. When considering only cell counts ≤400,000 cells per mL, the bias for both imaging resolutions was positive, meaning the image cytometer read higher than the flow cytometer. Both imaging resolutions (16 and 8) had a concordance correlation coefficient greater than 0.95. Considering ≥200,000 cells/mL to be indicative of subclinical mammary gland infection, the sensitivity and specificity of the image cytometer at 16 images were 92.0% and 91.7%, whereas the sensitivity and specificity of the analyzer at 8 images were 92.0% and 85.7%, respectively. Method precision (repeatability; coefficients of variation) were calculated at 3 different somatic cell counts (100,000, 200,000, and 400,000 cells/mL) where each sample was run repeatedly 12 times. When analyzed at the full number of images the coefficients of variation were 16.9%, 11.7%, and 10.9% for 100,000, 200,000, and 400,000 cells/mL, respectively. Analysis at half the number of images resulted in coefficients of variation of 18.9%, 24.8%, and 8.7% for 100,000, 200,000, and 400,000 cells/mL. We conclude that the image cytometer is an acceptable somatic cell count analyzer for on-farm use for applications such as screening cows for microbiological testing, and that precision is superior when the analysis is performed at the full number of images allowed by the instrument.

Evaluation of Cow-Side Meters to Determine Somatic Cell Count in Individual Cow Quarter and Bulk-Tank Milk Samples

Intramammary infections, which cause mastitis, can increase treatment and labor costs, decrease milk production, and affect milk quality. Meters that measure quarter somatic cell count (SCC) could be used to make more informed dry cow therapy decisions. The objective of this study was to compare the RT-10 iPhone adapter (RT-10; Dairy Quality Inc., Newmarket, ON, Canada), DeLaval Cell Counter (DSCC; DeLaval, Gurnee, IL, USA), Porta Check Quick Test (PortaCheck, White City, OR, USA), California Mastitis Test (ImmuCell, Portland, ME USA), pH meter (Hanna Instruments, Smithfield, RI, USA), electrical conductivity meter (OHAUS, Parsippany, NJ, USA), and the dual laser infrared temperature thermometer (Klein Tools, Lincolnshire, IL, USA) for measuring SCC in individual Holstein mammary quarters in comparison to a reference standard, the Fourier Transform Spectrometer 600 Combi System (Combi; Bentley Instruments, Chaska, MN, USA). Meters were evaluated using 658 individual cow quarter samples and 100 bulk-tank samples to measure SCC. Individual quarter milk samples from 160 cows from four commercial dairy herds were collected just before dry off and tested within 4 h of collection. To test bulk-tank SCC, 100 bulk-tank milk samples (25 mL) were collected from UC Davis Veterinary Medicine Teaching and Research Milk Quality Lab. Meter SCC values were regressed on observed Combi SCC. Goodness of fit was then evaluated by partitioning the mean square predicted error (MSPE). For individual quarter SCC, RT-10 had the highest coefficient of determination (R² = 0.86), lowest MSPE, and highest proportion of MSPE due to random variation (96%). Both the RT-10 and DSCC had the highest sensitivity and specificity for identifying quarter SCC above and below 200,000 cells/mL. For bulk-tank SCC, DSCC had the highest coefficient of determination (R² = 0.45), lowest MSPE, and highest proportion of MSPE due to random variation (80%). The RT-10 and DSCC could be used to measure individual quarter SCC to determine which cows to treat at dry off potentially reducing antibiotic use.

Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers

Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.

Risk factors associated with subclinical mastitis and its effect on physico-mineral features of camel milk

This study was carried out to determine the risk factors implicated in camel subclinical mastitis as well as the physico-mineral features of camel milk, there by examining the effect of this disease on those parameters. Milk samples were obtained from 125 lactating multiparous she-camels (aged 10-12 years) during early lactation from December 2020 to April 2021. The samples were screened for the presence of subclinical mastitis using the somatic cell count (SCC) test. In total, 73 (58.4%) samples showed the presence of subclinical mastitis, whereas the remaining 52 (41.6%) samples showed negative results for subclinical mastitis. Standard methods were used to appreciate the pH and mineral composition of the milk samples, such as Ca, Na, Cl, and K contents. In camels, unhygienic udder condition was identified as the major risk factor for the incidence of subclinical mastitis. Calf mortality and increased herd size were associated with a higher prevalence of subclinical mastitis. Tick infestations were also significantly associated with increased disease risk. Use of antisuckling devices, increase in milk yield, and weakness of body condition were identified as main risk factors and were primarily associated with the disease. However, udder lesions and deformities, milking frequency, and owner visits had no significant influence on the occurrence of subclinical mastitis. The overall mean pH value was 6.54 ± 0.01 and the mean values of Ca, Na, Cl, and K contents were 148.24 ± 2.55, 53.83 ± 1.52, 124.99 ± 1.80, and 240.22 ± 3.80 mg/100 g, respectively. When the level of milk from healthy animals and that from camels with subclinical mastitis (SCC > 2.4 × 10⁵) were compared, it showed that Na and Cl contents were significantly increased (p < 0.05) with the increase in SCC (56.52 vs.50.07 and 128.26 vs.120.40 mg/100 g, respectively). In contrast, there were no notable changes (p > 0.05) in the Ca, K, and pH values. In conclusion, udder hygiene, calf mortality, herd size, tick infestations, use of antisuckling devices, higher milk yield, and body condition were identified as the major risk factors that predispose the camels to subclinical mastitis. Furthermore, an increase in the Na and Cl levels in camel milk was observed along with udder inflammation. Consequently, the elevated Na and Cl levels in milk can be a sign of subclinical mastitis in camels.

Quarter-level analyses of the associations among subclinical intramammary infection and milk quality, udder health, and cheesemaking traits in Holstein cows

In this study, we investigated associations among subclinical intra-mammary infection (IMI) and quarter-level milk composition, udder health indicators, and cheesemaking traits. The dataset included records from 450 Holstein cows belonging to three dairy herds. After an initial screening (T0) to identify animals infected by Streptococcus agalactiae, Streptococcus uberis, Staphylococcus aureus, and Prototheca spp., 613 quarter milk samples for 2 different sampling times (T1 and T2, 1 mo after T1) were used for analysis. Milk traits were analyzed using a hierarchical linear mixed model including the effects of days in milk, parity and herd, and bacteriological and inflammatory category [culture negative with somatic cell count (SCC) <200,000 cells/mL; culture negative with SCC ≥200,000 cells/mL; or culture positive]. All udder health indicators were associated with increased SCC and IMI at both sampling times. The largest effects were detected at T2 for milk lactose (-7% and -5%) and milk conductivity (+9% and +8%). In contrast, the increase in differential SCC (DSCC) in samples with elevated SCC was larger at T1 (+17%). Culture-negative samples with SCC ≥200,000 cells/mL had the highest SCC and greatest numbers of polymorphonuclear-neutrophils-lymphocytes and macrophages at both T1 and T2. Regarding milk cheesemaking ability, samples with elevated SCC showed the worst pattern of curd firmness at T1 and T2. At T2, increased SCC and IMI induced large decreases in recoveries of nutrients into the curd, in particular recovered protein (-14% and -16%) and recovered fat (-12% and -14%). Different behaviors were observed between Strep. agalactiae and Prototheca spp., especially at T2. In particular, samples that were positive for Strep. agalactiae had higher proportions of DSCC (+19%) compared with negative samples with low SCC, whereas samples that were positive for Prototheca spp. had lower DSCC (-11%). Intramammary infection with Prototheca spp. increased milk pH compared with culture-negative samples (+3%) and negative samples that had increased SCC (+2%). The greatest impairment in curd firmness at 30 min from rennet addition was observed for samples that were positive for Prototheca spp. (-99% compared with negative samples, and -98% compared with negative samples with high SCC). These results suggest that IMI caused by Prototheca spp. have detrimental effects on milk technological traits that deserve further investigation of the mechanisms underlying animals' responses to infection.

Effect of mastitis incidence on litter size, litter weight, and milk composition of rabbit does

This study aimed to examine the effect of mastitis incidence on the litter size, litter birth weight, and milk composition of Hycole does on a commercial rabbit farm during their third and fourth parity. At third parity does were assigned to the "No mastitis" (n = 30) and "Mastitis" (n = 28) groups on the basis of visible abscesses in the mammary gland area. The microbiological analysis revealed the presence of different pathogenic bacteria. At third parity, "Mastitis" females had fewer kits than the "No mastitis" group, and the average birth weight was lower. On day 2 of the third lactation, "Mastitis" does produced significantly less milk daily compared with the "No mastitis" group. A significant effect on the incidence of mastitis on the litter size and litter weight during the growth of kits up to the 35th day was also observed. The effect of the incidence of mastitis on milk chemical composition was limited. At the fourth parity, the litter characteristics and daily milk yield were leveled in "Mastitis" and "No mastitis" females. To conclude, our study showed that mastitis negatively affects litter size, birth weight, and daily milk yield in the current parity. However, early detection and proper treatment allowed to obtain good reproductive results and healthy kits in the next parity.

Application of culture, PCR, and PacBio sequencing for determination of microbial composition of milk from subclinical mastitis dairy cows of smallholder farms

Mastitis is a cow disease usually signalized by irritation, swelling, and soreness of the udder. It is characterized by physical, chemical, and biological changes in the udder and milk. The aim of this study was to detect and characterize pathogens causing subclinical mastitis (SCM) from the milk of dairy cows of small-scale farmers through culture and molecular techniques. Milk was collected from 32 cows belonging to 8 small-scale farmers around Harrismith District, South Africa. The results showed that screening of SCM by California mastitis test and somatic cell counts (SCC) was 21.87 and 25%, respectively. Culture methods revealed the presence of Staphylococcus aureus at 93% followed by Streptococci spp. and Escherichia coli at 36.4 and 13.3%, respectively. The PCR could only detect E. coli, while single-molecule real-time sequencing showed a total of 2 phyla, 5 families, 7 genera, and 131 species. Clostridiaceae was the most abundant family, while Romboutsia was the most abundant genus followed by Turicibacter spp. The present study has documented the occurrence of SCM causing pathogens in milk collected from cows of small-scale farmers in Harrismith, indicating that SCM may be present at higher levels than expected.

Technological interventions and advances in the diagnosis of intramammary infections in animals with emphasis on bovine population-a review

Mastitis, an inflammation of the udder, is a challenging problem in dairy animals accounting for high economic losses. Disease complexity, degree of economic losses and increasing importance of the dairy industries along with public health concerns envisages devising appropriate diagnostics of mastitis, which can offer rapid, accurate and confirmatory diagnosis. The various diagnostic tests of mastitis have been divided into general or phenotypic and specific or genotypic tests. General or phenotypic tests are those that identify general alterations, which are not specific to any pathogen. Genotypic tests are specific, hence confirmatory for diagnosis of mastitis and include specific culture, polymerase chain reaction (PCR) and its various versions (e.g. qRT-PCR), loop-mediated isothermal amplification, lateral flow assays, nucleotide sequencing, matrix-assisted laser desorption ionization time-of-flight mass spectrometry, and other molecular diagnostic methods. However, for highly specific and confirmatory diagnosis, pure cultures still provide raw materials for more sophisticated diagnostic technological interventions like PCR and nucleotide sequencing. Diagnostic ability of like infra-red thermography (IRT) has been shown to be similar to California mastitis test and also differentiates clinical mastitis from subclinical mastitis cases. As such, IRT can become a convenient and portable diagnostic tool. Of note, magnetic nanoparticles-based colorimetric biosensor assay was developed by using for instance proteolytic activity of plasmin or anti-S. aureus antibody. Last but not least, microRNAs have been suggested to be potential biomarkers for diagnosing bovine mastitis. This review summarizes the various diagnostic tests available for detection of mastitis including diagnosis through general and specific technological interventions and advances.

Hycole Doe Milk Properties and Kit Growth

Simple Summary

The rabbits used on the commercial rabbit farms for the production of rabbit fryers are crosses of synthetic lines, such as Hycole. The maternal rabbit lines are selected not only for high number of kits but also for high production of milk. The goal of the presented study is related to the lack of complex data on the quality of rabbit milk, though this milk determines the nutritional status of kits in the suckling period as well as body weight gains and survival of rabbit kits. There are data on the milk yield of rabbit does and the milk proximal chemical composition, but the hygienic quality of this milk (somatic cell count) and its relationship with milk yield, kits survival, and weight gains is an unanswered question. The presented findings show the significant relationship between litter size, which has a clear effect on the milk production, as well as litter weight. Also shown is that the day of lactation affected the physiochemical traits of rabbit milk.

Abstract

The level of production and the physiochemical traits of rabbit milk affect the growth and the mortality of bunnies during lactation. The goal of the study was to analyze the effect of litter size and day of lactation on the quality traits of rabbit milk, milk production, and associative traits. The study was conducted on 32 Hycole does and their litters. The rabbit milk pH ranged from 6.61 to 7.46. The colostrum was characterized by the highest content of total solids (31.54 and 31.80 g kg⁻¹) and fat content (15.73 and 15.9 g kg⁻¹). The milk from the beginning of the lactation was characterized by the highest level of somatic cell count (SCC) (523.67 and 536.57 10³ mL⁻¹), which gradually decreased to reach the lowest level on days 17 and 21 of lactation. The daily milk production was greater for does nursing 10 kits per litter compared to those nursing eight kits per litter (p < 0.001). The peak of milk production occurred on day 17 postpartum. To conclude, the litter size has a clear effect on milk production as well as litter weight and litter weight gains. It is also important to note that the day of lactation affected the physiochemical traits of rabbit milk.

Measurement of urine pH and net acid excretion and their association with urine calcium excretion in periparturient dairy cows

Urine pH (U_pH) and net acid excretion (NAE) are used to monitor the degree of systemic acidification and predict the magnitude of resultant hypercalciuria when feeding an acidogenic ration to control periparturient hypocalcemia in dairy cattle. The objectives of this study were to evaluate the diagnostic performance of urine dipstick and pH paper for measuring U_pH, and to characterize the U_pH-NAE relationship and the association of urine Ca concentration ([Ca]) with U_pH and NAE. Urine samples (n = 1,116) were collected daily from 106 periparturient Holstein-Friesian cows fed an acidogenic ration during late gestation. Net acid excretion was measured by titration, and U_pH was measured by a glass-electrode pH meter (reference method), Multistix-SG urine dipsticks (Siemens Medical Solutions Inc., Ann Arbor, MI), and Hydrion pH paper (Micro Essential Laboratory Inc., Brooklyn, NY). Diagnostic performance was evaluated using Spearman correlation coefficient (r_s), Bland-Altman plots, and logistic regression. Urine pH measured by urine dipstick (r_s = 0.94) and pH paper (r_s = 0.96) were strongly associated with U_pH. Method-comparison studies indicated that the urine dipstick measured an average of 0.28 pH units higher, and pH paper 0.10 pH units lower, than U_pH. Urine [Ca] was more strongly associated with U_pH (r_s = -0.65) than NAE (r_s = 0.52). Goals for controlling periparturient hypocalcemia under the study conditions were U_pH <6.22 and <6.11, based on achieving urine [Ca] ≥5 mmol/L and estimated urinary Ca excretion ≥4 g/d, respectively. Urine pH was as accurate at predicting urine [Ca] as NAE when U_pH >6.11. We conclude that pH paper is an accurate, practical, and low-cost cow-side test for measuring U_pH and provides a clinically useful estimate of urine [Ca].

Seasonal variations in composition, properties, and heat-induced changes in bovine milk in a seasonal calving system

We determined seasonal variations in the composition and characteristics of bovine milk, as well as heat-induced changes in the physicochemical properties of the milk, in a typical seasonal-calving New Zealand herd over 2 full milking seasons. Fat, protein, and lactose contents varied consistently during the year in patterns similar to those of the lactation cycle. Seasonality also had significant effects on milk calcium, ionic calcium, fat globule size, buffering capacity, and ethanol stability, but not on casein micelle size. The ratio of casein to total protein did not vary significantly over the season, but late-season milk had the highest content of glycosylated κ-casein (G-κ-CN) and the lowest content of α-lactalbumin in both years. We observed significant between-year effects on protein, total calcium, ionic calcium, pH, and casein:total protein ratio, which might have resulted from different somatic cell counts in the 2 years. Compared with heating at 90°C for 6 min, UHT treatment (140°C for 5 s) induced greater dissociation of κ-casein, a similar extent of whey protein denaturation, a lower extent of whey protein-casein micelle association, and a larger increase in casein micelle size. Indeed, UHT treatment might have triggered significant dissociation of G-κ-CN, resulting in aggregation among the casein micelles and increased apparent mean casein micelle diameter. Seasonality had significant effects on the partitioning of G-κ-CN between the micelle and the serum phase, the extent of whey protein-casein micelle association under both heating conditions, and the casein micelle size of the UHT milk.

Evaluation of hand-held sodium, potassium, calcium, and electrical conductivity meters for diagnosing subclinical mastitis and intramammary infection in dairy cattle

Background

Subclinical mastitis (SCM) and intramammary infection (IMI) increase the sodium (Na) concentration and electrical conductivity (EC) and decrease the potassium (K) and calcium (Ca) concentrations in glandular secretions of lactating dairy cattle.

Hypothesis

Low‐cost portable Na, K, Ca, and EC meters are clinically useful cow‐side tests for diagnosing SCM and IMI.

Animals

One hundred fifteen dairy cows at dry off and 92 cows within 4‐7 days postcalving.

Methods

Quarter foremilk samples were obtained and the somatic cell count (SCC) was measured using a DeLaval cell counter with SCM defined as SCC ≥ 200 000 cells/mL. Microbiological culture of foremilk samples was used to diagnose IMI. Cisternal milk Na, K, and Ca concentrations and EC were measured using portable ion‐selective meters. Logistic regression was used to determine the area under the receiver operating characteristic curve (AUC) and the optimal cut point was determined using Youden's index. Diagnostic test performance was evaluated by comparing the AUC and calculating the sensitivity, specificity, and positive likelihood ratio (+LR) at the optimal cut point for SCM and IMI.

Results

Diagnostic test performance was much better when the meters were used to diagnose SCM as compared to IMI. Cisternal milk Na concentration provided the most accurate method for identifying quarters with SCM or IMI. However, AUC was <0.90 and +LR was <10 for all diagnostic test evaluations.

Conclusions and Clinical Importance

Cisternal milk Na, K, and Ca concentrations and EC were not sufficiently predictive of SCM or IMI to be recommended as clinically useful diagnostic tests.

Pharmacokinetics and pharmacodynamics of intramammary cefquinome in lactating goats with and without experimentally induced Staphylococcus aureus mastitis

Values for pharmacokinetic variables are usually obtained in healthy animals, whereas drugs are frequently administered to diseased animals. This study investigated cefquinome pharmacokinetics in healthy goats and goats with experimentally induced mastitis. Five adult lactating goats received 75 mg of cefquinome intramammary infusion using a commercially available product into one udder half in healthy goats and goats with clinical mastitis that was induced by intracisternal infusion of 100 cfu of Staphylococcus aureus ATCC 29213 suspended in 5 ml of sterile culture broth. Cefquinome concentrations were determined in plasma and skimmed milk samples using high-performance liquid chromatography (HPLC). Pharmacodynamics was investigated using the California Mastitis Test and pH of milk. Experimentally induced mastitis significantly increased the California Mastitis Test score and pH, and decreased the maximal cefquinome concentration and shortened the half-life in milk when compared to healthy goats. In conclusion, mastitis facilitated the absorption of cefquinome from the mammary gland of lactating goats and induced marked changes in milk pH, emphasizing the importance of performing pharmacokinetic studies of antimicrobial agents in infected animals.

Clinical utility of urine specific gravity, electrical conductivity, and color as on-farm methods for evaluating urine concentration in dairy cattle

Background

Urine concentration (UC) provides clinically useful information concerning hydration status and renal function of animals.

Objectives

To characterize the clinical performance of urine specific gravity measured by optical refractometry (U_SG‐R) or Multistix‐SG urine reagent dipstick (U_SG‐D), urine electrical conductivity using an OAKTON Con 6 conductivity handheld meter (U_EC), urine color (U_Color) using a custom‐designed 8‐point color chart, and urine creatinine concentration (U_Creat) for assessing UC in dairy cattle.

Animals

20 periparturient Holstein‐Friesian cows.

Methods

Urine was obtained by perineal stimulation or urethral catheterization and urine osmolality (U_Osm, reference method), U_SG‐R, U_SG‐D, U_EC, U_Color, and U_Creat determined. Diagnostic test performance was evaluated using Spearman's rho and logistic regression to determine the area under the receiver operating curve (AUC) and optimal cut point for diagnosing hypohydration (U_Osm ≥800 mOsm/kg). P < .05 was considered significant.

Results

The best performing test for diagnosing hypohydration was U_SG‐R (AUC = 0.90) at an optimal cut point ≥1.030. The second‐best performing test was U_EC (AUC = 0.82) at a cut point of ≥23.7 mS/cm, followed by U_Creat (AUC = 0.76) at a cut point of ≥95.3 mg/dL, and U_Color (AUC = 0.74) at a cut point of ≥4 on an 8‐point scale. Urine specific gravity measured by dipstick performed poorly (AUC = 0.63).

Conclusions and Clinical Importance

U_SG‐R and U_EC provide practical and sufficiently accurate methods for measuring UC in dairy cattle. Urine color had moderate clinical utility as a no‐cost cow‐side method for assessing UC, whereas dipstick refractometry is not recommended for assessing UC.