Concentrations of blood and milk ketone bodies, blood isopropanol and plasma glucose in dairy cows in relation to the degree of hyperketonaemia and clinical signs

Serum metabolomic analysis of the dose-response effect of dietary choline in overweight male cats fed at maintenance energy requirements

Choline participates in methyl group metabolism and has been recognized for its roles in lipid metabolism, hepatic health and muscle function in various species. Data regarding the impacts of choline on feline metabolic pathways are scarce. The present study investigated how choline intake affects the metabolomic profile of overweight cats fed at maintenance energy. Overweight (n = 14; body condition score:6-8/9) male adult cats were supplemented with five doses of choline in a 5x5 Latin Square design. Cats received a daily dose of choline on extruded food (3620 mg choline/kg diet) for three weeks at maintenance energy requirements (130 kcal/kgBW0.4). Doses were based on body weight (BW) and the daily recommended allowance (RA) for choline for adult cats (63 mg/kg BW0.67). Treatment groups included: Control (no additional choline, 1.2 x NRC RA, 77 mg/kg BW0.67), 2 x NRC RA (126 mg/kg BW0.67), 4 x NRC RA (252 mg/kg BW0.67), 6 x RA (378 mg/kg BW0.67), and 8 x NRC RA (504 mg/kg BW0.67). Serum was collected after an overnight fast at the end of each treatment period and analyzed for metabolomic parameters through nuclear magnetic resonance (NMR) spectroscopy and direct infusion mass spectrometry (DI-MS). Data were analyzed using GLIMMIX, with group and period as random effects, and dose as the fixed effect. Choline up to 8 x NRC RA was well-tolerated. Choline at 6 and 8 x NRC RA resulted in greater concentrations of amino acids and one-carbon metabolites (P < 0.05) betaine, dimethylglycine and methionine. Choline at 6 x NRC RA also resulted in greater phosphatidylcholine and sphingomyelin concentrations (P < 0.05). Supplemental dietary choline may be beneficial for maintaining hepatic health in overweight cats, as it may increase hepatic fat mobilization and methyl donor status. Choline may also improve lean muscle mass in cats. More research is needed to quantify how choline impacts body composition.

Characterization of ketolactia in dairy cows during early lactation

Fourier transform infrared spectroscopy (FTIR) allows for the determination of milk acetone (mACE) and β-hydroxybutyrate (mBHB) concentrations, providing a potential herd monitoring tool for hyperketolactia, defined as elevated milk ketone bodies. The study aim was to characterize mACE and mBHB concentration dynamics during early lactation in Polish Holstein-Friesian cows. Milk samples (n = 3,867,390) were collected within 6 to 60 days in milk (DIM) over a 4-yr period (April 1, 2013 to March 31, 2017) from approximately 21,300 dairy herds (average 38.7 cows/herd). Fixed effects of parity, DIM, and their interaction on mACE and mBHB concentrations were determined using a mixed model with a herd-year-season fixed effect and random cow effect. Published hyperketolactic mACE (≥0.15 mmol/L) and mBHB (≥0.10 mmol/L) threshold concentrations were used to classify study milk samples into ketolactia groups of normal (mACE <0.15 mmol/L and mBHB <0.10 mmol/L) and hyperketolactic (HYKL; either mACE ≥0.15 mmol/L or mBHB ≥0.10 mmol/L). Additionally, HYKL samples were categorized into subpopulations as having elevated mBHB and mACE (HYKL_ACEBHB, mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L), only elevated mBHB (HYKL_BHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), or only elevated mACE (HYKL_ACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L). Effects of parity, DIM, ketolactia group or subpopulation, and their interactions on mACE and mBHB concentrations were also determined using the mixed model that included ketolactia group or subpopulation as an independent variable. Across all data, mACE and mBHB concentrations were influenced by effects of parity, DIM, and their interaction as well as parity, DIM, ketolactia group or subpopulation, and their interactions. For all samples, mACE and mBHB concentrations decreased with increasing DIM, with mACE concentration declining more rapidly compared with mBHB. In the data set, 68% and 32% of all samples were defined as normal or HYKL, respectively. Among HYKL samples, mACE was elevated soon after calving and declined over time. In contrast, mBHB started lower after calving and increased reaching peak concentrations around 30 DIM, and then decreased. Within HYKL samples, 50.8, 41.3, and 7.9% were categorized as HYKL_ACEBHB, HYKL_BHB, and HYKL_ACE respectively. Between 6 and 21 DIM, 11.3% of HYKL were classified as HYKL_ACE. Primiparous cows had greater (14.8%) HYKL_ACE samples in this time period. In conclusion, this study has characterized mACE and mBHB concentrations during early lactation and determined effects of parity, DIM, and their interaction. Using published criteria interpreting mACE and mBHB concentrations, it was intriguing to identify a unique population of samples having elevated mACE without mBHB in early lactation, especially in primiparous cows. Further research is needed to determine if this sample population represents an unhealthy metabolic status that adversely affects cow health and performance.

Insulin receptor substrate in brain-enriched exosomes in subjects with major depression: on the path of creation of biosignatures of central insulin resistance

Insulin signaling is critical for neuroplasticity, cerebral metabolism as well as for systemic energy metabolism. In rodent studies, impaired brain insulin signaling with resultant insulin resistance (IR) modulates synaptic plasticity and the corresponding behavioral functions. Despite discoveries of central actions of insulin, in vivo molecular mechanisms of brain IR until recently have proven difficult to study in the human brain. In the current study, we leveraged recent technological advances in molecular biology and herein report an increased number of exosomes enriched for L1CAM, a marker predominantly expressed in the brain, in subjects with major depressive disorder (MDD) as compared with age- and sex-matched healthy controls (HC). We also report increased concentration of the insulin receptor substrate-1 (IRS-1) in L1CAM⁺ exosomes in subjects with MDD as compared with age- and sex-matched HC. We found a relationship between expression of IRS-1 in L1CAM⁺ exosomes and systemic IR as assessed by homeostatic model assessment of IR in HC, but not in subjects with MDD. The increased IRS-1 levels in L1CAM⁺ exosomes were greater in subjects with MDD and were associated with suicidality and anhedonia. Finally, our data suggested sex differences in serine-312 phosphorylation of IRS-1 in L1CAM⁺ exosomes in subjects with MDD. These findings provide a starting point for creating mechanistic framework of brain IR in further development of personalized medicine strategies to effectively treat MDD.

Predicting Subclinical Ketosis in Dairy Cows Using Machine Learning Techniques

Simple Summary

The maintenance of cows in good health and physical condition is an important component of dairy cattle management. One of the major metabolic disorders in dairy cows is subclinical ketosis. Due to financial and organizational reasons it is often impossible to test all cows in a herd for ketosis using standard blood examination method. Using milk data from test-day records, obtained without additional costs for breeders, we found diagnostic models identifying cows-at-risk of subclinical ketosis. In addition, to select the best models, we present a general scoring approach for various machine learning models. With our models, breeders can identify dairy cows-at-risk of subclinical ketosis and implement appropriate management strategies and prevent losses in milk production.

Abstract

The diagnosis of subclinical ketosis in dairy cows based on blood ketone bodies is a challenging and costly procedure. Scientists are searching for tools based on results of milk performance assessment that would allow monitoring the risk of subclinical ketosis. The objective of the study was (1) to design a scoring system that would allow choosing the best machine learning models for the identification of cows-at-risk of subclinical ketosis, (2) to select the best performing models, and (3) to validate them using a testing dataset containing unseen data. The scoring system was developed using two machine learning modeling pipelines, one for regression and one for classification. As part of the system, different feature selections, outlier detection, data scaling and oversampling methods were used. Various linear and non-linear models were fit using training datasets and evaluated on holdout, testing the datasets. For the assessment of suitability of individual models for predicting subclinical ketosis, three β-hydroxybutyrate concentration in blood (bBHB) thresholds were defined: 1.0, 1.2 and 1.4 mmol/L. Considering the thresholds of 1.2 and 1.4, the logistic regression model was found to be the best fitted model, which included independent variables such as fat-to-protein ratio, acetone and β-hydroxybutyrate concentrations in milk, lactose percentage, lactation number and days in milk. In the cross-validation, this model showed an average sensitivity of 0.74 or 0.75 and specificity of 0.76 or 0.78, at the pre-defined bBHB threshold 1.2 or 1.4 mmol/L, respectively. The values of these metrics were also similar in the external validation on the testing dataset (0.72 or 0.74 for sensitivity and 0.80 or 0.81 for specificity). For the bBHB threshold at 1.0 mmol/L, the best classification model was the model based on the SVC (Support Vector Classification) machine learning method, for which the sensitivity in the cross-validation was 0.74 and the specificity was 0.73. These metrics had lower values for the testing dataset (0.57 and 0.72 respectively). Regression models were characterized by poor fitness to data (R² < 0.4). The study results suggest that the prediction of subclinical ketosis based on data from test-day records using classification methods and machine learning algorithms can be a useful tool for monitoring the incidence of this metabolic disorder in dairy cattle herds.

Predictive ability of host genetics and rumen microbiome for subclinical ketosis

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and β-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis. However, heritability estimates reported for milk BHB and acetone in several dairy cattle breeds were low. The rumen microbial community has been reported to play a significant role in host energy homeostasis and metabolic and physiologic adaptations. The current study aims at investigating the effects of cows' genome and rumen microbial composition on concentrations of acetone and BHB in milk, and identifying specific rumen microbial taxa associated with variation in milk acetone and BHB concentrations. We determined the concentrations of acetone and BHB in milk using nuclear magnetic resonance spectroscopy on morning milk samples collected from 277 Danish Holstein cows. Imputed high-density genotype data were available for these cows. Using genomic and microbial prediction models with a 10-fold resampling strategy, we found that rumen microbial composition explains a larger proportion of the variation in milk concentrations of acetone and BHB than do host genetics. Moreover, we identified associations between milk acetone and BHB with some specific bacterial and archaeal operational taxonomic units previously reported to have low to moderate heritability, presenting an opportunity for genetic improvement. However, higher covariation between specific microbial taxa and milk acetone and BHB concentrations might not necessarily indicate a causal relationship; therefore further validation is needed before considering implementation in selection programs.

Symposium review: Big data, big predictions: Utilizing milk Fourier-transform infrared and genomics to improve hyperketonemia management

Negative animal health and performance outcomes are associated with disease incidences that can be labor-intensive, costly, and cumbersome for many farms. Amelioration of unfavorable outcomes through early detection and treatment of disease has emphasized the value of improving health monitoring. Although the value is recognized, detecting hyperketonemia (HYK) is still difficult for many farms to do practically and efficiently. Increasing data streams available to farms presents opportunities to use data to better monitor cow and herd health; however, challenges remain with regard to validating, integrating, and interpreting data. During the transition to lactation period, useful data are presented in the form of milk production and composition, milk Fourier-transform infrared (FTIR) wavelength absorbance, cow management records, and genomics, which have been employed to monitor postpartum onset of HYK. Attempts to predict postpartum HYK from test-day milk and performance variables incorporated into multiple linear regression models have demonstrated sufficient accuracy to monitor monthly herd prevalence; however, they lacked the sensitivity and specificity for individual cow diagnostics. Subsequent artificial neural network prediction models employing FTIR data and milk composition variables achieved 83 and 81% sensitivity and specificity for individual cow diagnostics. Although these results fail to reach the diagnostic goals of 90%, they are achieved without individual cow blood samples, which may justify acceptance of lower performance. The caveat is that these models depend on milk analysis, which is traditionally done every 4 weeks. This infrequent sampling allows for a single diagnostic sample for about half of the fresh cows. Benefits to farms are greatly improved if postpartum cows can be milk-tested weekly. Additionally, this allows for close monitoring of somatic cell count and may open the door for use of other herd health monitoring tools. Future improvements in these models may be achievable by maximizing sensitivity at the expense of specificity and may be most economical in disorders for which the cost of treatment is less than that of mistreating (e.g., HYK). Genomic predictions for HYK may be improved by incorporating genome-wide associated SNP and further utilized for precision management of HYK risk groups. Development and validation of HYK prediction models may provide producers with individual cow and herd-level management tools.

Between- and within-herd variation in blood and milk biomarkers in Holstein cows in early lactation

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites' levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.

Predicting blood β-hydroxybutyrate using milk Fourier transform infrared spectrum, milk composition, and producer-reported variables with multiple linear regression, partial least squares regression, and artificial neural network

Prediction of postpartum hyperketonemia (HYK) using Fourier transform infrared (FTIR) spectrometry analysis could be a practical diagnostic option for farms because these data are now available from routine milk analysis during Dairy Herd Improvement testing. The objectives of this study were to (1) develop and evaluate blood β-hydroxybutyrate (BHB) prediction models using multivariate linear regression (MLR), partial least squares regression (PLS), and artificial neural network (ANN) methods and (2) evaluate whether milk FTIR spectrum (mFTIR)-based models are improved with the inclusion of test-day variables (mTest; milk composition and producer-reported data). Paired blood and milk samples were collected from multiparous cows 5 to 18 d postpartum at 3 Wisconsin farms (3,629 observations from 1,013 cows). Blood BHB concentration was determined by a Precision Xtra meter (Abbot Diabetes Care, Alameda, CA), and milk samples were analyzed by a privately owned laboratory (AgSource, Menomonie, WI) for components and FTIR spectrum absorbance. Producer-recorded variables were extracted from farm management software. A blood BHB ≥1.2 mmol/L was considered HYK. The data set was divided into a training set (n = 3,020) and an external testing set (n = 609). Model fitting was implemented with JMP 12 (SAS Institute, Cary, NC). A 5-fold cross-validation was performed on the training data set for the MLR, PLS, and ANN prediction methods, with square root of blood BHB as the dependent variable. Each method was fitted using 3 combinations of variables: mFTIR, mTest, or mTest + mFTIR variables. Models were evaluated based on coefficient of determination, root mean squared error, and area under the receiver operating characteristic curve. Four models (PLS-mTest + mFTIR, ANN-mFTIR, ANN-mTest, and ANN-mTest + mFTIR) were chosen for further evaluation in the testing set after fitting to the full training set. In the cross-validation analysis, model fit was greatest for ANN, followed by PLS and MLR. Diagnostic strength after cross-validation was poorest for MLR and was similar for ANN and PLS. Models that used mTest + mFTIR variables performed marginally better than models that used only mFTIR or mTest variables. These results suggest that blood BHB prediction models that use mFTIR + mTest variables may be useful additions to existing HYK diagnostic and management programs.

Genetic parameter estimation for milk β-hydroxybutyrate and acetone in early lactation and its association with fat to protein ratio and energy balance in Korean Holstein cattle

Objective

The objective of this study was to estimate the genetic parameters for milk β-hydroxybutyrate (BHBA), acetone (Ac), fat protein ratio (FPR), and energy balance (EB) using milk test day records and investigate the effect of early lactation FPR and EB on milk ketone body concentrations.

Methods

Total 262,940 test-day records collected from Korea Animal Improvement Association during the period of 2012 to 2016 were used in this study. BHBA and Ac concentrations in milk were measured by Fourier transform infrared spectroscopy (FTIR). FPR values were obtained using test day records of fat and protein percentage. EB was calculated using previously developed equation based on parity, lactation week, and milk composition data. Genetic parameters were estimated by restricted maximum likelihood procedure based on repeatability model using Wombat program.

Results

Elevated milk BHBA and Ac concentrations were observed during the early lactation under the negative energy balance. Milk FPR tends to decrease with the decreasing ketone body concentrations. Heritability estimates for milk BHBA, Ac, EB, and FPR ranged from 0.09 to 0.14, 0.23 to 0.31, 0.19 to 0.52, and 0.16 to 0.42 respectively at parity 1, 2, 3, and 4. The overall heritability for BHBA, Ac, EB and FPR were 0.29, 0.32, 0.58, and 0.38 respectively. A common pattern was observed in heritability of EB and FPR along with parities.

Conclusion

FPR and EB can be suggested as potential predictors for risk of hyperketonemia. The heritability estimates of milk BHBA, Ac, EB, and FPR indicate that the selective breeding may contribute to maintaining the milk ketone bodies at optimum level during early lactation.

Predicting hyperketonemia by logistic and linear regression using test-day milk and performance variables in early-lactation Holstein and Jersey cows

Although cowside testing strategies for diagnosing hyperketonemia (HYK) are available, many are labor intensive and costly, and some lack sufficient accuracy. Predicting milk ketone bodies by Fourier transform infrared spectrometry during routine milk sampling may offer a more practical monitoring strategy. The objectives of this study were to (1) develop linear and logistic regression models using all available test-day milk and performance variables for predicting HYK and (2) compare prediction methods (Fourier transform infrared milk ketone bodies, linear regression models, and logistic regression models) to determine which is the most predictive of HYK. Given the data available, a secondary objective was to evaluate differences in test-day milk and performance variables (continuous measurements) between Holsteins and Jerseys and between cows with or without HYK within breed. Blood samples were collected on the same day as milk sampling from 658 Holstein and 468 Jersey cows between 5 and 20 d in milk (DIM). Diagnosis of HYK was at a serum β-hydroxybutyrate (BHB) concentration ≥1.2 mmol/L. Concentrations of milk BHB and acetone were predicted by Fourier transform infrared spectrometry (Foss Analytical, Hillerød, Denmark). Thresholds of milk BHB and acetone were tested for diagnostic accuracy, and logistic models were built from continuous variables to predict HYK in primiparous and multiparous cows within breed. Linear models were constructed from continuous variables for primiparous and multiparous cows within breed that were 5 to 11 DIM or 12 to 20 DIM. Milk ketone body thresholds diagnosed HYK with 64.0 to 92.9% accuracy in Holsteins and 59.1 to 86.6% accuracy in Jerseys. Logistic models predicted HYK with 82.6 to 97.3% accuracy. Internally cross-validated multiple linear regression models diagnosed HYK of Holstein cows with 97.8% accuracy for primiparous and 83.3% accuracy for multiparous cows. Accuracy of Jersey models was 81.3% in primiparous and 83.4% in multiparous cows. These results suggest that predicting serum BHB from continuous test-day milk and performance variables could serve as a valuable diagnostic tool for monitoring HYK in Holstein and Jersey herds.

Evaluation of a point-of-care electrochemical meter to detect subclinical ketosis and hypoglycaemia in lactating dairy cows

OBJECTIVES

To evaluate and validate a hand-held electrochemical meter (Precision Xtra®) as a screening test for subclinical ketosis and hypoglycaemia in lactating dairy cattle.

DESIGN

Method comparison study using a convenience sample.

PROCEDURE

Blood samples were collected into plain tubes from the coccygeal vessels of 181 Holstein cows at 2-4 weeks of lactation during summer in Iran. Blood β-hydroxybutyrate concentration (BHB) and glucose concentration were immediately measured by the electrochemical meter after applying 20 μL of blood to the reagent strip. Passing-Bablok regression and Bland-Altman plots were used to determine the accuracy of the meter against laboratory reference methods (BHB dehydrogenase and glucose oxidase).

RESULTS

Serum BHB ranged from 0.1 to 7.3 mmol/L and serum glucose ranged from 0.9 to 5.1 mmol/L. Passing-Bablok regression analysis indicated that the electrochemical meter and reference methods were linearly related for BHB and glucose, with a slope estimate that was not significantly different from 1.00. Clinically minor, but statistically significant, differences were present for the intercept value for Passing-Bablok regression analysis for BHB and glucose, and bias estimates in the Bland-Altman plots for BHB and glucose.

CONCLUSION

The electrochemical meter provided a clinically useful method to detect subclinical ketosis and hypoglycaemia in lactating dairy cows. Compared with other method validation studies using the meter, we attributed the improved performance of the electrochemical meter to application of a fixed volume of blood (20 μL) to the reagent strip, use of the meter in hot ambient conditions and use of glucose oxidase as the reference method for glucose analysis.

Effects of a combination butaphosphan and cyanocobalamin product and insulin on ketosis resolution and milk production

The objective of this study was to determine the effects of butaphosphan-cyanocobalamin (B+C), glargine insulin, and propylene glycol on resolution of ketosis and average daily milk yield after treatment. Cows from 16 herds in Ontario, Canada, and 1 herd in Michigan were tested at weekly intervals between 3 and 16 DIM. Ketosis was defined as blood β-hydroxybutyrate (BHB) ≥1.2 mmol/L. All ketotic cows were given a baseline treatment of 3 d of 300 g of propylene glycol orally. Animals were then randomly assigned to treatment with 3 doses of either 25 mL of B+C or 25 mL of saline placebo and 1 dose of either 2 mL (200 IU) of glargine insulin or 2 mL of saline placebo in a 2 × 2 factorial arrangement. Outcomes of interest on all farms were ketosis cure (blood BHB <1.2 mmol/L 1 wk postenrollment), maintenance of ketosis cure (blood BHB <1.2 mmol/L 1 and 2 wk postenrollment), and blood BHB concentrations at 1 and 2 wk postenrollment. Milk weights were collected daily in 1 large freestall herd. Repeated measures ANOVA was used to evaluate blood BHB concentrations 2 wk after treatment and milk production for 30 d after treatment. Poisson regression was used to examine the effect of treatment on cure and maintenance of cure. Due to a regulatory delay causing temporary unavailability of B+C in Canada, data were analyzed in 2 sets of models: one for insulin and the corresponding placebo (n = 620) and one for the full trial (n = 380). Animals with blood glucose concentrations ≤2.2 mmol/L at the time of ketosis diagnosis were 2.1 times more likely (95% CI = 1.2 to 3.7) to be cured if treated with B+C. Animals in lactation 3 or higher that had blood glucose concentrations <2.2 mmol/L at enrollment produced 4.2 kg/d (95% CI = 1.4 to 7.1) more milk if treated with insulin versus placebo and 2.8 kg/d (95% CI = 0.9 to 4.7) more milk if treated with B+C versus placebo. Animals in lactation 3 or higher with blood glucose ≥2.2 mmol/L that were treated with insulin produced 2.3 kg/d (95% CI = 0.3 to 4.4) less milk than untreated controls. No interaction was observed between treatments. This evidence suggests that B+C and insulin may be beneficial for ketosis treatment in animals with blood glucose <2.2 mmol/L at ketosis diagnosis. It also suggests that blood glucose concentration may be an important predictor of success of ketosis treatment.

Genetic Parameters of Milk β-Hydroxybutyric Acid and Acetone and Their Genetic Association with Milk Production Traits of Holstein Cattle

This study was conducted to estimate the genetic parameters of β-hydroxybutyrate (BHBA) and acetone concentration in milk by Fourier transform infrared spectroscopy along with test-day milk production traits including fat %, protein % and milk yield based on monthly samples of milk obtained as part of a routine milk recording program in Korea. Additionally, the feasibility of using such data in the official dairy cattle breeding system for selection of cows with low susceptibility of ketosis was evaluated. A total of 57,190 monthly test-day records for parities 1, 2, and 3 of 7,895 cows with pedigree information were collected from April 2012 to August 2014 from herds enrolled in the Korea Animal Improvement Association. Multi-trait random regression models were separately applied to estimate genetic parameters of test-day records for each parity. The model included fixed herd test-day effects, calving age and season effects, and random regressions for additive genetic and permanent environmental effects. Abundance of variation of acetone may provide a more sensitive indication of ketosis than many zero observations in concentration of milk BHBA. Heritabilities of milk BHBA levels ranged from 0.04 to 0.17 with a mean of 0.09 for the interval between 4 and 305 days in milk during three lactations. The average heritabilities for milk acetone concentration were 0.29, 0.29, and 0.22 for parities 1, 2, and 3, respectively. There was no clear genetic association of the concentration of two ketone bodies with three test-day milk production traits, even if some correlations among breeding values of the test-day records in this study were observed. These results suggest that genetic selection for low susceptibility of ketosis in early lactation is possible. Further, it is desirable for the breeding scheme of dairy cattle to include the records of milk acetone rather than the records of milk BHBA.

Evaluation of an Electrochemical Point-of-Care Meter for Measuring Glucose Concentration in Blood from Periparturient Dairy Cattle

BACKGROUND

The Precision Xtra(®) meter is a promising low cost electrochemical point-of-care unit for measuring blood glucose concentration ([gluc]) in cattle blood. The meter uses an algorithm that assumes the intra-erythrocyte [gluc] equals the plasma [gluc] on a molal basis, and that the hematocrit is similar in humans and cattle.

OBJECTIVES

The primary objective was to determine the accuracy of the meter for measuring plasma [gluc] in dairy cattle. Secondary objectives were to characterize the influence of hematocrit and sample temperature on the measured value for [gluc].

ANIMALS

A total of 106 periparturient Holstein-Friesian cattle.

METHODS

Blood and plasma samples (1,109) were obtained and Deming regression and Bland-Altman plots were used to determine the accuracy of the meter against the reference method (plasma hexokinase assay). Multivariable regression and linear regression were used to determine the effect of hematocrit and sample temperature on the plasma [gluc] measured by the meter.

RESULTS

Intra-erythrocyte [gluc] was 18% of plasma [gluc] on a molar basis. Sample temperature had a significant linear effect on plasma [gluc] as measured by the meter for 3/5 plasma samples when measured [gluc] > 160 mg/dL.

CONCLUSIONS AND CLINICAL IMPORTANCE

The meter utilizes an algorithm that is optimized for human blood and is inaccurate when applied to bovine blood. Until a cattle-specific algorithm is developed, we recommend using plasma as the analyte instead of blood and calculating plasma [gluc] using the equation: [gluc] = 0.66 × [gluc]p-meter + 15, where [gluc]p-meter is the value reported by the meter. If blood is measured, then we recommend using the equation: [gluc] = 0.90 × [gluc]b-meter + 15.

Polymorphisms within the APOBR gene are highly associated with milk levels of prognostic ketosis biomarkers in dairy cows

Essentially all high-yielding dairy cows experience a negative energy balance during early lactation leading to increased lipomobilization, which is a normal physiological response. However, a severe energy deficit may lead to high levels of ketone bodies and, subsequently, to subclinical or clinical ketosis. It has previously been reported that the ratio of glycerophosphocholine to phosphocholine in milk is a prognostic biomarker for the risk of ketosis in dairy cattle. It was hypothesized that this ratio reflects the ability to break down blood phosphatidylcholine as a fatty acid resource. In the current study, 248 animals from a previous study were genotyped with Illumina BovineSNP50 BeadChip, and genome-wide association studies were carried out for the milk levels of phosphocholine, glycerophosphocholine, and the ratio of both metabolites. It was demonstrated that the latter two traits are heritable with h2 = 0.43 and h2 = 0.34, respectively. A major quantitative trait locus was identified on cattle chromosome 25. The APOBR gene, coding for the apolipoprotein B receptor, is located within this region and was analyzed as a candidate gene. The analysis revealed highly significant associations of polymorphisms within the gene with glycerophosphocholine as well as the metabolite ratio. These findings support the hypothesis that differences in the ability to take up blood phosphatidylcholine from low-density lipoproteins play an important role in early lactation metabolic stability of dairy cows and indicate APOBR to contain a causative variant.

Prevalence of subclinical ketosis in dairy cattle in the Southwestern Iran and detection of cutoff point for NEFA and glucose concentrations for diagnosis of subclinical ketosis

Subclinical ketosis (SCK) is simply a condition marked by increased levels of circulating ketone bodies without the presence of the clinical signs of ketosis. Subclinical ketosis can cause economic losses through decreased milk production and association with preparturient diseases. Limited information is available regarding the prevalence of SCK in dairy herds in Southwestern Iran. The objectives of this study were (i) determination of the cutoff point of nonesterified fatty acids (NEFAs) and glucose concentrations for diagnosis of SCK using receiver operating characteristic (ROC) analysis, and (ii) determination of prevalence of subclinical ketosis in apparently healthy dairy cattle in Southwestern Iran. From October to December 2009, a total of 100 clinically healthy multiparous Holstein cows (3-8 years old) were randomly selected from 16 dairy herds around Kazerun, Fars Province, Iran. The cows had two-six lactations, with body weight ranging from 500 to 650 kg. Blood samples for each cow were taken at 2, 4 and 6 weeks post parturition and 3-4h after the morning feeding. The optimal cutoff point was set, by the ROC method, to >0.26 mmol/L for NEFA, and < 2.26 mmol/L for glucose with corresponding 82.54% sensitivity and 91.89% specificity for NEFA and 44.44% sensitivity and 78.38% specificity for glucose. Cows with BHB concentrations higher than 1200 μmol/L were classified as having SCK. In 2, 4 and 6 weeks post parturition 63%, 68% and 59% of the tested cows were subclinically ketotic. Overall, 97% of tested cows (97/100) were considered subclinically ketotic in at least one sample period. Thirty percent of tested cows (30/100) suffered from subclinical ketosis in all of the 2, 4 and 6 weeks postpartum. The results suggest that, a cut-off point of 0.26 mmol/L for NEFA concentrations can be used during early lactation for diagnosis of subclinical ketosis and making management decisions for prevention and treatment. Glucose cannot be a good criterion for diagnosis of SCK and it does not appear to be useful for monitoring subclinical ketosis.

Increased blood concentration of isopropanol in ketotic dairy cows and isopropanol production from acetone in the rumen

To evaluate acetone and isopropanol metabolism in bovine ketosis, the blood concentrations of isopropanol, acetone, plasma 3-hydroxybutyrate (3-HB) and other metabolites were analyzed in 12 healthy controls and 15 ketotic dairy cows including fatty liver and inferior prognosis after laparotomy for displaced abomasum. In ruminal fluid taken from 6 ketotic cows, ruminal isopropanol and acetone were also analyzed. Ketotic cows showed higher concentrations of isopropanol, acetone, 3-HB and nonesterified fatty acid, and higher activities of aspartate transaminase and gamma-glutamyl transferase than control cows. Blood samples had higher concentration of isopropanol accompanied by increased acetone. In the ketotic cows, acetone was detected not only in blood but also in ruminal fluid, while higher ruminal isopropanol did not necessarily accompany its elevation in the blood. Using 2 steers with rumen cannula, all ruminal content was emptied and then substituted with artificial saliva to evaluate the importance of ruminal microbes in isopropanol production. Under each condition of intact and emptied rumen, acetone was infused into the rumen and blood isopropanol was analyzed. The elevation in the blood isopropanol concentration after acetone infusion was markedly inhibited by the emptying. Here, increased blood concentrations of isopropanol and acetone were observed in ketotic cows, and the importance of ruminal microbes in isopropanol production was confirmed.

Bovine subclinical ketosis in dairy herds in Iran

Subclinical ketosis (SCK) is defined as elevated concentrations of ketone bodies in the absence of clinical signs of ketosis. It is an important metabolic disease in dairy cattle during early lactation and is associated with losses in milk production and several other periparturient diseases. Limited information is available regarding the prevalence of SCK in dairy herds in Iran. The objectives of this study were (i) to determine the incidence of SCK in the dairy herds in Kerman province of Iran using serum beta-hydroxybutyrate (BHB) concentrations, and (ii) to investigate the relationship between serum concentrations of BHB and glucose of cows with SCK. In the present study, 90 multiparous Holstein cows (4-6 years old) from 11 commercial dairy herds were evaluated 3-4 weeks after calving. The distribution of blood BHB concentrations seemed to suggest a cut-off point of 1200 micromol/L between cows with and without SCK. At this cut-off point, 14.4% of tested cows (13/90) were classified as subclinically ketotic, with the prevalence rate within herd ranging from 10% to 20%. Cows with SCK were detected in all the investigated dairies except one. Blood glucose concentrations in cows with SCK were significantly lower (p < or = 0.05) than in cows without SCK, and serum BHB and glucose concentration were inversely correlated (r = -0.43, p < or = 0.05). The results suggest that, using a cut-off of 1200 micromol/L, BHB concentrations can be used during early lactation for diagnosis and to make management decisions for prevention and treatment.

Quarter health, milking interval, and sampling time during milking affect the concentration of milk constituents

Eleven Danish Holstein cows were used to examine the effects of quarter health (healthy vs. unhealthy), milking interval (12 vs. 6 h), and sampling time during milking on the concentration of 8 milk constituents [acetone, beta-hydroxybutyrate (BHBA), N-acetyl-beta-D-glucosaminidase (NAGase), somatic cell count (SCC), urea, fat, protein, and lactose]. The selection criterion was that each cow should have 2 or 3 healthy and 1 or 2 unhealthy quarters. Foremilk was collected before attaching the teat cups of the milking machinery, and thereafter, milk samples were collected automatically from each quarter every 45 s during milking. Compared with milk from healthy quarters, milk from unhealthy quarters had a higher concentration of BHBA, NAGase, SCC, and protein during the entire milking, whereas urea was higher in the last part of the milking process. Healthy quarters had a higher content of acetone and lactose during the whole milking, whereas fat was higher in the first part of the milking process. When the cows were milked at the 6-h interval, all milk constituents except lactose and protein were higher during the whole (NAGase, SCC, and urea) or part of the milking (acetone, BHBA, and fat) compared with when cows were milked at the 12-h interval. Lactose was higher in the first part of the milking at the 12-h compared with the 6-h interval, whereas protein was not affected by milking interval. beta-Hydroxybutyrate, NAGase, SCC, and fat increased during the milking process, whereas acetone, urea, protein, and lactose decreased. Foremilk was remarkably different for all constituents, except acetone, and should not be used as a representative milk sample to achieve the true level of a milk constituent. If these milk constituents are to be used in an inline management system, these effects should be taken into account.

Incidence of subclinical ketosis in cows supplemented with a monensin controlled-release capsule in Holstein cattle, Florida, USA

The objective of this study was to determine the effect of a monensin controlled-release capsule on the proportion of cows with subclinical ketosis (SK). During July to August 2001, 300 cows dried-off 50-70 days before expected parturition were randomly assigned to either a treatment (n = 150, oral capsule, 335 mg/d of monesin for 95 d) or control group (no capsule, n = 150). At 14 days postpartum, a milk sample was obtained and evaluated for beta-hydroxybutyrate (BHBA) using a semi-quantitative ketone test strip. In a sub-sample of 50 cows per group a blood sample was taken and analyzed for BHBA using an ELISA kit. Milk BHBA > or = 200 micromol/L was used as the cut-off value for diagnosis of SK. The incidence of SK based on the milk test was statistically different between groups (P < or = 0.05) with a value of 26.6% for control and 14.5% for cows treated with monensin, respectively. Cows treated with monensin were 0.68 times less likely to give a positive result for milk BHBA than non-treated cows (0.53-0.80; 95% CI). Serum BHBA concentrations did not differ between groups (0.81 +/- 0.09 mmol/L versus 0.70 +/- 0.07 mmol/L for controls and treated, respectively; P > 0.05). However, for each incremental increase in serum BHBA of 0.1 mmol/L occurrence of SK increased 52% (OR = 1.52; 1.21-1.91; 95% CI).

Predicting Risk of Ketosis in Dairy Cows Using In-Line Measurements of β-Hydroxybutyrate: A Biological Model

Automated monitoring of individual cows to determine health status is a potentially valuable management tool, especially in large dairy herds. Herein is described the rationale, structure, and functionality of a biological model to predict risk of ketosis in individual cows using in-line measurements of the ketone body beta-hydroxybutyrate (BHBA) in milk. The model also uses acceleration in milk yield, body fatness at calving, diseases in current lactation, and incidences of ketosis in earlier lactations as additional risk factors for ketosis. However, the model is designed to function merely on the basis of milk BHBA in the absence of other data. Values of milk BHBA are smoothed using a state space model before these are used in calculations in the biological part of the model. The model is designed to be updated each time a new BHBA measurement or a disease occurrence is available and then uses previous and current data. Outputs of the model are the risk of ketosis (value between 0 and 1, where 0 = no risk and 1 = clinical ketosis) and how many days until the next milk sample should be taken and analyzed for BHBA. At higher risks for ketosis, more frequent milk sampling is the recommended output. Test examples from cows for which BHBA has been measured extensively were used to show the functionality of the model. The model performed equally well when reductions in sampling frequency were applied, and it was also relatively robust to the addition of up to +/- 2 residual SD of random noise in the BHBA values. This model has the potential to provide the basis for a useful disease monitoring and management tool. However, thorough validation awaits a much larger dataset and testing of the model under a variety of on-farm situations.

Phenotypic and Genetic Influences on Test-Day Measures of Acetone Concentration in Milk

The objectives of this study were to estimate heritability of acetone concentration in milk, based on monthly samples of milk obtained as part of a routine milk testing program, and to evaluate the feasibility of using such data in a genetic evaluation program for selection against ketosis incidence. Milk samples were collected from January to December of 1999 in herds enrolled in the Ontario Dairy Herd Improvement Association, and acetone concentration was measured using an inline chemical procedure. The original data included more than 50,000 records. Because ketosis is generally a problem during early lactation, only the single test with the fewest days in milk was retained. In addition, data were retained only for cows with pedigree information. The final data set included 10,375 records. Among these data, only 6.56% had detectable levels of acetone. Acetone data were log-transformed prior to statistical analysis. Simple ANOVA indicated that herd, parity number, days in milk, and month of test had significant effects on acetone concentration. Acetone levels increased with lactation number and were higher in early lactation. Three approaches were applied for genetic analysis. First, REML was used with a simple linear animal model. Then, a separate procedure used data augmentation and Gibbs Sampling to obtain continuously distributed underlying values for records with zero acetone concentration, and these data were analyzed with both an animal and sire model. Heritability of acetone concentration was less than 1% for all 3 analyses. Herd effects accounted for about 5% of the phenotypic variance. Low estimates of heritability were due either to low actual levels of genetic variance or inability to detect all of the genetic variance present, due to infrequent recording during the early part of the lactation. Genetic evaluation based on recording of acetone concentration on a monthly basis seems of little use as a selection tool to decrease incidence of ketosis.

Concentrations of ketones in milk in early lactation, and reproductive performance of dairy cows

Samples of blood and milk were taken from clinically ketotic cows at 12-hour intervals before and after treatment The concentration of beta-hydroxybutyrate was determined in plasma and milk, and the concentration of acetone was determined in milk. Measurement of milk acetone had the optimal combination of sensitivity, specificity and positive predictive value to identify ketotic cows and was subsequently used in a comparison of the fertility of ketotic and normal cows. Two samples of milk were taken approximately two weeks apart, between 12 and 60 days after calving, from 410 cows on three farms and the concentration of acetone in the milk was measured. Thirty cows with milk acetone concentrations of at least 0.4 mmol/litre were compared with paired control cows with milk acetone concentrations less than 0.3 mmol/litre. The ketotic cows had a significantly longer calving-to-conception interval and a significantly higher culling rate due to a failure to conceive (P<0.05).

Variability of Acetone in Milk in a Large Low-Production Dairy Herd: a Longitudinal Case Study

The objective of this study was to relate acetone in milk with cow and management factors in one low producing dairy herd (5260 kg milk per 305-day lactation). Milk acetone was measured in regular monthly milk samples one to three times within 100 days of lactation in 4433 lactations (2639 cows, 7800 measurements) from one herd over a period of 32 months (1988-91). Associations between milk acetone and cow factors and surrogate measures of management were evaluated by variance components of multiple fixed effect models. Lactation stage, calendar month of study, production groups and milk yield were strong, and percentage milk fat and parity were weak predictors of milk acetone. There was a trend of increasing body weight loss from the first to the second month of lactation with increasing milk acetone level. A substantial increase in milk production in 1991 was accompanied by an almost twofold rise in milk acetone. It was concluded that environmental parameters had strong relationships with milk acetone even in this low-producing herd.

Determination of acetone in cow milk by Fourier transform infrared spectroscopy for the detection of subclinical ketosis

Fourier transform infrared analysis (FTIR) was used in combination with partial least squares regression (PLS) to predict the concentration of acetone in milk. FTIR spectra were compared with results of a gas-chromatographic head space method. Principal component analysis of whole spectra (3000 to 1000 cm(-1)) suggested to reduce the spectrum of analysis for acetone to 1450 to 1200 cm(-1). A second derivative was applied to the spectra to remove baseline effects and further enhance the spectral features. Full cross-validation was used to compare the reference with predicted acetone concentrations of samples not included in model development. PLS applied to the full spectral range resulted in a complex 19-factor model with a cross-validation error of 0.22 mM. After reducing the spectrum and taking the second derivative, we obtained a model with seven factors that yielded a cross-validation error of 0.21 mM. This compares favorably with a previously reported model with 20 factors and an error of 0.25 mM. Using PLS predictions to identify cows with subclinical ketosis resulted in 95 to 100% sensitivity and 96 to 100% specificity when the threshold for subclinical ketosis was 0.4 to 1.0 mM. The corresponding positive predictive values were > or = 76% and the negative predictive values > 98% throughout an assumed range of subclinical ketosis prevalence of 10 to 30%.

Ketone bodies in milk and blood of dairy cows: relationship between concentrations and utilization for detection of subclinical ketosis

The objective of this study was to investigate the relationship between the concentrations of the different ketone bodies in milk and blood and to evaluate these concentrations for the detection of subclinical ketosis. A total of 60 multiparous cows were used. Concentrations of acetone, acetoacetate, and beta-hydroxybutyrate were analyzed quantitatively in blood and milk, and the Ketolac strip test was used for semiquantitative determination of beta-hydroxybutyrate in milk. Cows were defined subclinically ketotic when their concentration of blood beta-hydroxybutyrate was over 1200 micromol/L. High correlation coefficients were observed between blood acetone and blood acetoacetate, and between blood and milk acetone. On the contrary, concentrations of milk and blood beta-hydroxybutyrate were poorly correlated with the other concentrations of ketone bodies. The Ketolac strip test overestimated the concentrations of beta-hydroxybutyrate in milk. For the detection of subclinical ketosis, the best sensitivity-specificity combination was obtained with the determination of acetoacetate in blood or milk, with threshold concentrations of 125 and 50 micromol/L, respectively. Determination of beta-hydroxybutyrate in the milk via an enzymatic analysis or via the Ketolac strip test provided valuable results, with threshold concentrations of 70 and 100 micromol/L, respectively. The simplicity of use of the Ketolac strip test makes it a valuable way to investigate subclinical ketosis.

Prediction of energy balance in high yielding dairy cows with test-day information

This study used a previously developed model to predict herd mean energy balance of the first 12 wk of lactation from test-day information. The predictions were compared with calculated energy balance based on feed analysis and to changes in body weight. Seven independent feeding trials including 43 diets (519 lactations, 254 cows; 1987 to 1996) were used. Conventional diets were discriminated from nonconventional diets by significant differences between mean calculated energy balance of subtrial diets versus control diets. The total difference between group means of predicted minus calculated energy balance was positive throughout the observed lactation period. It was lowest (5 to 9 MJ of net energy for lactation) during negative energy balance of the conventional diets in wk 2 to 7 when 18 to 50% of the total difference was due to random variation. Because of this difference, both predicted and calculated energy balances were compared to body weight change as a reference for true energy balance. Body weight change was adjusted for rumen fill. While calculated energy balance tended to be negative at times when cows gained weight, predicted energy balance was positive. Cows fed nonconventional diets gained weight, while calculated energy balance was extremely negative, whereas predicted energy balance based on test-day information was positive. We concluded that the prediction difference was relatively small when standard rations were used, and that nonconventional rations biased predicted energy balance to a lesser extent than calculated energy balance. Estimating energy balance based on test-day information appears feasible.

Mixed ruminal microbes of cattle produce isopropanol in the presence of acetone but not 3-D-hydroxybutyrate

The objective was to evaluate the ability of mixed rumen microbes to synthesize isopropanol from acetone or 3-D-hydroxybutyrate. Rumen fluid from seven mature, nonpregnant, dry Holstein cows was incubated with starch or cellulose and additions of acetone, 3-D-hydroxybutyrate, or saline. Rumen fluid was analyzed for isopropanol after 0, 3, 6, and 9 h. No isopropanol was present in any sample at 0 h, and none was present in incubations containing saline or 3-D-hydroxybutyrate at any subsequent time. Incubations that included acetone produced small amounts of isopropanol from 0 to 3 and 3 to 6 h and significantly larger amounts from 6 to 9 h. With starch as the energy substrate, production from 6 to 9 h was 3.8 micromol/min per liter of rumen fluid and 3.7 micromol/min per liter with cellulose as the energy substrate; however, these values did not differ significantly. Mixed rumen microbes could synthesize isopropanol from acetone but not from 3-D-hydroxybutyrate, and rumen microbial metabolism of acetone was the likely source of plasma isopropanol seen in ketotic ruminants.

First ovulation and ketone body status in the early postpartum period of dairy cows

The effect of ketone body status on occurrence of first ovulation during early lactation was assessed in 84 multiparous dairy cows under field conditions. Animals were equally distributed across 8 farms and were controlled by the same herd fertility monitoring program. Cows were visited twice antepartum and 6 times postpartum at weekly intervals between 5:30 and 8:30 AM. On these occasions, body condition scores and milk yields were measured, blood and milk samples were taken, cows were gynecologically examined, and parameters of reproduction were determined. The onset of first ovulation was specified by milk progesterone determination and rectal palpation. Cows starting postpartum ovarian cyclicity within or after 30 d were classified as early and late responders (ER and LR, respectively). Resumption of the estrous cycle within 30 d postpartum is considered optimal under practical conditions, and classification based on this threshold value resulted in groups of equal size and equal distribution of ER + LR cows within farms. Ketone bodies measured were beta-hydroxybutyrate in serum and acetoacetate and acetone in serum and milk. Blood serum and milk ketone body concentrations during the first 6 wk of lactation were higher in LR than in ER, whereas plasma glucose and nonesterified fatty acid and milk fat, protein and urea concentrations did not differ between groups. Maximal concentrations of ketone bodies from parturition to first ovulation were better predictors of the onset of the estrous cycle than mean or minimal concentrations over the same period. Milk acetone and serum beta-hydroxybutyrate concentrations provided the most reliable information with regard to resumption of ovarian activity of all ketone bodies.

Subclinical ketosis in lactating dairy cattle

Subclinical ketosis is an important and common condition of early-lactation dairy cattle. It is associated with losses in milk production and increased risk of periparturient disease. Prevention depends on several factors, including proper transition-cow nutrition, management of body condition, and the use of certain feed additives such as niacin, propylene glycol, and ionophores. All currently available cowside tests for subclinical ketosis have certain limitations in their use. Effective monitoring schemes for subclinical ketosis can be developed, however, and these may be useful in many herd health programs.

Screening of dairy cows for ketosis by use of infrared spectroscopy and multivariate calibration

A fast and inexpensive method of screening ketosis in cows is presented. This method is based on the determination of acetone in bovine milk by using Fourier transform infrared spectroscopy combined with multivariate calibration. Only samples with a naturally increased acetone content could be used in the calibration step; samples containing added acetone did not produce an acceptable calibration equation. On test samples ranging from 0.0 to 2.8 mM acetone, an R2 of 0.81 and an accuracy (root mean square error of prediction) of 0.27 mM were obtained. This accuracy was sufficient to classify the cows into two groups: healthy and possibly ketotic. No false negatives were determined for the present data set.

Beta-hydroxybutyrate levels in peripheral blood and ketone bodies supplemented in culture media affect the in vitro chemotaxis of bovine leukocytes

The role of ketone bodies on chemotactic capacities of leukocytes was characterized in two experiments. Experiment I was performed to investigate the association between serum beta-hydroxybutyrate concentrations (BHB) and in vitro chemotaxis of leukocytes. Cows were divided into low-BHB, medium-BHB, and high-BHB ones and classified according to their BHB. Leukocytes from high-BHB cows had a significantly lower chemotactic differential than leukocytes from low-BHB cows (p < 0.01). The effect of adding ketone bodies into in vitro chemotaxis cultures on leukocytes chemotaxis was studied in Experiment II. Either individual or a combination of commercial ketone bodies - sodium salts of BHB (BHBA), lithium salt of acetoacetate (ACAC), and acetone (Acetone) - were diluted in culture media and divided into eight concentrations corresponding to concentrations of bovine subclinical and clinical ketosis. For leukocytes from medium- and high-BHB cow, the chemotactic indexes of leukocytes were reduced by ACAC and Acetone. Chemotactic differentials of cultures with ACAC and acetone supplementation from both sources of leukocytes were significantly lower than that of the control culture (p < 0.05). For leukocytes from high-BHB cows, chemotactic indexes were suppressed in a ketone-body environment. In conclusion, leukocytes from naturally-occurring ketotic cows have lower chemotactic differentials than those from non-ketotic cows, and a chemotactic capacity indicated by a chemotactic differential is impaired when leukocytes migrate in an environment with ketone bodies in vitro.

Energy metabolism in cochlear outer hair cells in vitro

ATP levels in outer hair cells in vitro were measured using the luciferin/luciferase method. Hair cells were isolated from the guinea pig cochlea and maintained for 2 h in a balanced salt solution with 5.5 mM glucose. Ten to 20 cells sufficed for a robust and reproducible luminescence signal, indicating an ATP content of 6.2 +/- 0.4 fmol/cell. This ATP concentration is similar to that found in cultures of other cell types and agrees well with the classical measurements in freeze-dried preparations. The ATP levels were reduced by the following treatments: (1) the omission of glucose in the culture medium lowered ATP levels by 28%; (2) the inhibition of glycolysis by 2-deoxyglucose lowered ATP levels by 66%; (3) the inhibition of oxidative phosphorylation by carbonyl cyanide m-chlorophenylhydrazine (CCCP) lowered ATP levels by 75%, and (4) the inhibition of both pathways reduced the ATP content to non-detectable levels. Acetoacetate was able to restore ATP levels partially when glycolysis was inhibited. These results suggest that (1) the major pathway of ATP synthesis in outer hair cells is the aerobic metabolism of glucose; (2) endogenous energy stores (e.g. glycogen) can maintain ATP levels in the absence of glucose; and (3) ketone bodies may be alternative energy sources.

A new quick-test for semiquantitative determination of beta-hydroxybutyric acid in bovine milk

A new test strip for semiquantitative determination of beta-hydroxybutyric acid (BHB) in bovine milk has been tested in experimental investigations in three lactating cows. After intraruminal administration of butyric acid, the following parameters were determined during 7 hours: milk concentrations of BHB (quantitatively and semiquantitatively) and acetone (quantitatively), BHB concentration in blood and urine (quantitatively), acetone + acetic acid concentration in urine (semiquantitatively). The new quick-test proved to be highly sensitive and even subclinical or physiological levels of BHB in milk could be determined. It seems to be suitable not only for the diagnosis of clinically manifest ketosis in dairy cows, but also for the control of the energy metabolism on a herd basis and as an indicator of ketogenic feedstuffs in the ration.

Influence of feeding intensity on blood concentrations of glucose, ketone bodies and free fatty acids in nutritionally adapted dairy cows fed 24 times daily

Concentrations of acetoacetate, D-3-hydroxybutyrate, glucose and free fatty acids were determined in blood from 3 Jersey cows during a 5-months period. The cows were fed an identical complete feed every hour, from ad libitum intake to maintenance level, for 28 days at each of the following levels of intake: 170, 138, 102, 53 and 37 g organic matter per kg bodyweight0.75 (metabolic bodyweight). Throughout the experimental period, the cows were in negative energy balance, which was reflected in an average weight loss of 640 g per day. None of the metabolites differed from reference values for healthy lactating cows. The concentration of D-3-hydroxybutyrate decreased linearly with the level of feeding and reflected a decreased ruminal production of butyrate. The high feeding frequency to lactating cows may be considered an essential factor in the prevention of ketosis.

Clinical ketosis

A diagnosis of primary ketosis is based on clinical signs, clinical pathology, and ruling-out disorders that cause secondary ketosis. Various treatments can be used alone or in combination during the management of clinical ketosis. A treatment should be based on drugs with a mechanism of action that will eliminate the pathogenesis of the clinical signs observed.

Subclinical ketosis in dairy cows

Subclinical ketosis is defined as a preclinical stage of ketosis. The peak prevalence of subclinical ketosis occurs during the fourth week of lactation. Herd-related factors, breed, parity, and season are other important determinants. Subclinical ketosis can be revealed by determining levels of plasma glucose, plasma NEFA and blood, and milk or urine ketone body concentration. There are theoretical and practical advantages of using milk ketone bodies. Most authors are agreed on approximate lower and upper borderlines for subclinical ketosis. The risk of an outbreak of clinical symptoms has been evaluated by some authors. Most authors have found significant negative relationships between energy balance and ketone body concentration. Some disagreement may be attributable to the fact that the diets used in different experiments can have different glucogenic potential, even if the energy content is the same. This affects the relationship between energy balance and ketone body concentration, as the ketone body level is influenced by both the energy balance and plasma glucose. Feeding silage with high butyric acid content increases the risk of subclinical ketosis. There are indications that cows with the highest milk yield directly after calving are at greatest risk for developing ketosis. Increased ketone body level secondarily reduces milk production, a decrease that has been quantified by some authors. Subclinical ketosis causes delayed reproductive functions return to normal after calving, increased intervals from calving to first and last service, and an increased frequency of ovarian cysts. The routine determination of milk acetone levels in control programs can be used to evaluate the status of individual cows, to indicate the energy feeding in early lactation at a herd level, and to evaluate sires for breeding. The heritability and the tendency toward a positive genetic correlation between milk acetone and milk yield have also been discussed, as have aspects of nutritional prevention. Factors such as energy- and protein-rich roughage, tasty high-energy concentrates, suitable feeding during the dry period, and division of the concentrates into at least four meals are considered to be important.