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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]

Objectives: This study investigated metabolic changes associated with bovine leukemia virus (BLV) infection in dairy cows, focusing on pre-parturition alterations. Methods: Metabolite identification in serum and urine samples was performed using a targeted metabolomics method, employing the TMIC Prime kit in combination with flow injection analysis and liquid chromatography–tandem mass spectrometry. Results: Of 145 cows examined, 42 (28.9%) were BLV-seropositive. Around 38% of infected cows showed high somatic cell counts indicative of subclinical mastitis, with 15 experiencing additional health issues such as ketosis, milk fever, and lameness. Despite these conditions, no significant differences in milk yield or composition were observed between the infected and control groups. Metabolomic analysis conducted at −8 and −4 weeks prepartum revealed significant metabolic differences between BLV-infected and healthy cows. At −8 weeks, 30 serum metabolites were altered, including sphingomyelins, lysophosphatidylcholines, amino acids, and acylcarnitines, suggesting disruptions in membrane integrity, energy metabolism, and immune function indicative of early neoplastic transformations. By −4 weeks, the number of altered metabolites decreased to 17, continuing to reflect metabolic disruptions in cows with leukemia. Multivariate analysis highlighted distinct metabolic profiles between infected and control cows, identifying key discriminating metabolites such as choline, aspartic acid, phenylalanine, and arginine. Urine metabolomics revealed significant prepartum shifts in metabolites related to glucose, asymmetric dimethylarginine, and pyruvic acid, among others. Conclusions: The research confirmed metabolomics' efficacy in defining a BLV infection metabolic profile, elucidating leukosis-associated metabolic disruptions. This approach facilitates the identification of BLV-infected cows and enhances understanding of infection pathophysiology, providing a foundation for advanced management and intervention strategies in dairy herds. The study underscores the profound impact of leukosis on metabolic processes and highlights urine metabolomics' utility in non-invasively detecting BLV infection, offering the potential for improved herd health management. [ABSTRACT FROM AUTHOR]

The aquaculture industry has been growing rapidly over the past few decades to meet future animal protein demands. However, intensive aquaculture industry faces challenges such as growth abnormalities, high mortality rates, water quality and intestinal health deterioration. Administering probiotics can serve as a nutritional strategy to enhance the immune system and growth performance of fish influxes of gut microbiota. This study aimed to evaluate the impact of two dietary probiotic strains L. mesenteroides and L. lactis on the growth performance, immunity, and gut microbiota of Nile tilapia (Oreochromis niloticus). Fish were fed with basal and experimental diet supplemented by both L. mesenteroides and L. lactis bacteria at 106 cell/g for 8 weeks. Feeding a combination of L. mesenteroides and L. lactis resulted in significant improvements in feed utilization parameters (PER and FER) (P < 0.001), alternative complement pathway activity, intestinal lactic acid bacteria count (P < 0.012), mucus secretion (P < 0.002) and peroxidase activity (P < 0.001) compared to the control groups. Serum lysozyme activity also exhibited a significant increase in the L. mesenteroides and L. lactis dietary group (P < 0.011) compared to the control and single probiotic supplemented diet groups. Furthermore, Nile tilapia fed the L. mesenteroides and L. lactis supplemented diet showed enhanced growth performance metrics (weight gain, final weight and specific growth rate) compared to those fed control and single probiotic supplemented diets (P < 0.022). Additionally, superoxide dismutase activity was significantly elevated in the L.mesenteroides and L. lactis supplemented diet groups compared to the control and single L.mesenteroides supplemented diet groups (P < 0.017). These findings strongly indicate that a dietary combination of L. mesenteroides and L. lactis probiotics could function as a beneficial immunostimulant feed supplement in Nile tilapia aquaculture. [ABSTRACT FROM AUTHOR]

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings. [ABSTRACT FROM AUTHOR]

Fast and easily repeatable methods for commissioning procedures for brachytherapy (BT) treatment planning systems (TPS) are needed. Radiochromic film dosimetry with gamma analysis is widely used in external beam quality assurance (QA) procedures and planar film dosimetry is also increasingly used for verification of the dose distribution in BT applications. Using the gamma analysis method for comparing calculated and measured dose data could be used for commissioning procedures of the newly developed TG-186 and MBDCA calculation algorithms. The aim of this study was dosimetric verification of the calculation algorithm used in TPS when the CT/MRI ring applicator is used.