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Background: Milk fever (MF), a metabolic disorder in dairy cows characterized by low blood calcium concentrations postpartum, is well‐recognized clinically. However, comprehensive data on the alteration of metabolites associated with this condition remains sparse. Hypothesis: Delineate serum metabolite profiles and metabolic pathways preceding, coinciding with, and after the onset of MF. Animals: Twenty‐six cows, including 20 healthy cows and 6 cows initially affected by MF. Because of culling, the number of MF‐affected cows decreased to 4 at MF week, +4 weeks, and +8 weeks postpartum. Methods: A nested case‐control longitudinal study was conducted, with blood samples collected at −8 and −4 weeks prepartum, MF week, and +4 and +8 weeks postpartum. Serum analysis utilized direct injection/liquid chromatography/tandem mass spectrometry (DI/LC/MS/MS) techniques. Results: Key findings included the identification of diverse metabolites such as hexose, amino acids, phosphatidylcholines, lysophosphatidylcholines, and sphingomyelin, which varied between studied groups (P <.05). The most marked metabolic alterations were observed 4 weeks prepartum. In total, 42, 56, 38, 29, and 24 metabolites distinguished the MF group at the respective time points (P <.05). Additionally, 33 metabolic pathways, including amino acid, antioxidant metabolism, fatty acid degradation, and carbohydrate processing, were impacted (P <.05). Conclusions and Clinical Importance: Metabolic disruptions in dairy cows begin several weeks before the clinical manifestation of MF and persist up to 8 weeks postpartum. These findings emphasize the complexity of MF, extending beyond only hypocalcemia and indicate the necessity for preemptive monitoring in dairy herd management. [ABSTRACT FROM AUTHOR]

Abstract Background Milk fever (MF), a metabolic disorder in dairy cows characterized by low blood calcium concentrations postpartum, is well‐recognized clinically. However, comprehensive data on the alteration of metabolites associated with this condition remains sparse. Hypothesis Delineate serum metabolite profiles and metabolic pathways preceding, coinciding with, and after the onset of MF. Animals Twenty‐six cows, including 20 healthy cows and 6 cows initially affected by MF. Because of culling, the number of MF‐affected cows decreased to 4 at MF week, +4 weeks, and +8 weeks postpartum. Methods A nested case‐control longitudinal study was conducted, with blood samples collected at −8 and −4 weeks prepartum, MF week, and +4 and +8 weeks postpartum. Serum analysis utilized direct injection/liquid chromatography/tandem mass spectrometry (DI/LC/MS/MS) techniques. Results Key findings included the identification of diverse metabolites such as hexose, amino acids, phosphatidylcholines, lysophosphatidylcholines, and sphingomyelin, which varied between studied groups (P

This preliminary study explored potential serum biomarkers for predicting the onset of milk fever (MF), a bovine parturient disease with hypocalcemia. We conducted two-dimensional gas chromatography mass spectrometry-based metabolomics in 8 and 17 pregnant Holstein cows that did and did not develop MF 3 weeks later, respectively. In principal component analysis (PCA) applied to a dataset containing 1,498 metabolites, serum metabolites exhibited highly similar chemical profiles between cows with and without MF. PCA with a limited dataset of metabolites containing fatty acids, which had significantly different values between the groups and/or correlation coefficients of >0.5 for the serum calcium concentration, distinguished the two groups. These suggest the possibility of developing serum biomarkers for predicting bovine MF. [ABSTRACT FROM AUTHOR]

Milk fever is a metabolic disorder that predominantly affects dairy animals during the periparturient period and within four weeks of calving. Milk fever is primarily attributed to a decrease in the animal's serum Ca2+ levels. Clinical milk fever occurs when Ca2+ concentration drops below 1.5 mM (6 mg/dL). Without prompt intervention, clinical milk fever leads to noticeable physical symptoms and health complications including coma and fatality. Subclinical milk fever is characterized by Ca2+ levels between 1.5 and 2.12 mM (6–8.48 mg/dL). Approximately 50% of multiparous dairy cows suffer from subclinical milk fever during the transition to lactation. The economic impact of milk fever, both direct and indirect, is substantial, posing challenges for farmers. To address this issue, we developed a low-cost electrochemical sensor that can measure bovine serum calcium levels on-site, providing an opportunity for early detection of subclinical and clinical milk fever and early intervention. This calcium sensor is a scalable solid contact ion sensing platform that incorporates a polymeric calcium-selective membrane and ionic liquid-based reference membrane into laser-induced graphene (LIG) electrodes. Our sensing platform demonstrates a sensitivity close to the theoretical Nernstian value (29.6 mV/dec) with a limit of detection of 15.6 μM and selectivity against the species in bovine serum. Moreover, our sensor can detect Ca2+ in bovine serum with 91% recovery. [Display omitted] • Low cost calcium sensor is developed by modification of laser engraved carbon electrodes with a calcium sensing membrane. • A liquid-junction free ion-liquid doped reference membrane is deposited on a laser-induced graphene electrode for development of a liquid-junction free portable reference electrode. • Bovine serum calcium levels can be measured on-site with more than 90% accuracy. • Accessible and low cost platform is developed for early on-site diagnosis of milk fever, allowing timely intervention [ABSTRACT FROM AUTHOR]

This preliminary study explored potential serum biomarkers for predicting the onset of milk fever (MF), a bovine parturient disease with hypocalcemia. We conducted two-dimensional gas chromatography mass spectrometry-based metabolomics in 8 and 17 pregnant Holstein cows that did and did not develop MF 3 weeks later, respectively. In principal component analysis (PCA) applied to a dataset containing 1,498 metabolites, serum metabolites exhibited highly similar chemical profiles between cows with and without MF. PCA with a limited dataset of metabolites containing fatty acids, which had significantly different values between the groups and/or correlation coefficients of >0.5 for the serum calcium concentration, distinguished the two groups. These suggest the possibility of developing serum biomarkers for predicting bovine MF.