The 3 branched-chain AA (BCAA), Val, Leu, and Ile, are essential AA used by tissues as substrates for protein synthesis and energy generation. In addition, BCAA are also involved in modulating cell signaling pathways, such as nutrient sensing and insulin signaling. In our previous study, dietary BCAA supplementation was shown to improve protein synthesis and glucose homeostasis in transition cows. However, a more detailed understanding of the changes in metabolic pathways associated with an increased BCAA availability is desired to fine-tune nutritional supplementation strategies. Multiparous Holstein cows (n = 20) were enrolled 28 d before expected calving and assigned to either the BCAA treatment (n = 10) or the control group (n = 10). Cows assigned to BCAA were fed 550 g/d of rumen-protected BCAA mixed with 200 g/d of dry molasses from calving until 35 DIM, whereas the cows assigned to the control were fed only 200 g/d of dry molasses. Serum samples were collected on d 10 before expected calving, as well as on d 4 and d 21 postpartum. Milk samples were collected on d 14 postpartum. From a larger cohort, we selected 20 BCAA-supplemented cows with the greatest plasma urea nitrogen concentration, as an indicator for greater BCAA availability, for the metabolomics analysis herein. Serum and milk samples were subjected to a liquid chromatography-mass spectrometry-based assay, detecting and measuring the abundance of 241 serum and 211 milk metabolic features, respectively. Multivariable statistical analyses revealed that BCAA supplementation altered the metabolome profiles of both serum and milk samples. Increased abundance of serum phosphocholine and glutathione and of milk Val, Ile, and Leu, and decreased abundance of milk acyl-carnitines were associated with BCAA supplementation. Altered phosphocholine and glutathione abundances point to altered hepatic choline metabolism and antioxidant balance, respectively. Altered milk acyl-carnitine abundances suggest changes in mammary fatty acid metabolism. Dietary BCAA supplementation was associated with a range of alterations in serum and milk metabolome profiles, adding to our understanding of the role of BCAA availability in modulating dairy cow protein, lipid, and energy metabolism on a whole-body level and how it affects milk composition.

Essential amino acids (EAA) are critical for multiple physiological processes. Branched-chain amino acid (BCAA) supplementation provides energy substrates, promotes protein synthesis, and stimulates insulin secretion in rodents and humans. Most dairy cows face a protein and energy deficit during the first weeks postpartum and utilize body reserves to counteract this shortage. The objective was to evaluate the effect of rumen-protected BCAA (RP-BCAA; 375 g of 27% l-leucine, 85 g of 48% l-isoleucine, and 91 g of 67% l-valine) with or without oral propylene glycol (PG) administration on markers of liver health status, concentrations of nonesterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) in plasma, and liver triglycerides (TG) during the early postpartum period in dairy cows. Multiparous Holstein cows were enrolled in blocks of 3 and randomly assigned to either the control group or 1 of the 2 treatments from calving until 35 d postpartum. The control group (n = 16) received 200 g of dry molasses per cow/d; the RP-BCAA group (n = 14) received RP-BCAA mixed with 200 g of dry molasses per cow/d; the RP-BCAA plus PG (RP-BCAAPG) group (n = 16) received RP-BCAA mixed with 200 g of dry molasses per cow/d, plus 300 mL of PG, once daily from calving until 7 d in milk (DIM). The RP-BCAA and RP-BCAAGP groups, on average (± standard deviation), were predicted to receive a greater supply of metabolizable protein in the form of l-Leu 27.4 ± 3.5 g/d, l-Ile 15.2 ± 1.8 g/d, and l-Val 24.2 ± 2.4 g/d compared with the control cows. Liver biopsies were collected at d 9 ± 4 prepartum and at 5 ± 1 and 21 ± 1 DIM. Blood was sampled 3 times per week from calving until 21 DIM. Milk yield, dry matter intake, NEFA, BHB, EAA blood concentration, serum chemistry, insulin, glucagon, and liver TG and protein abundance of total and phosphorylated branched-chain ketoacid dehydrogenase E1α (p-BCKDH-E1α) were analyzed using repeated measures ANOVA. Cows in the RP-BCAA and RP-BCAAPG groups had lower liver TG and lower activities of aspartate aminotransferase and glutamate dehydrogenase during the first 21 DIM, compared with control. All cows, regardless of treatment, showed an upregulation of p-BCKDH-E1α at d 5 postpartum, compared with levels at 21 d postpartum. Insulin, Met, and Glu blood concentration were greater in RP-BCAA and RP-BCAAPG compared with control during the first 35 DIM. Therefore, the use of RP-BCAA in combination with PG might be a feasible option to reduce hepatic lipidosis in dairy cows during early lactation.

This paper describes the design, fabrication, and validation of a paper-based diagnostic device for the rapid diagnosis of hypocalcemia in dairy cattle at the point-of-care (POC). The device incorporates a 3D printed calcium ion-selective membrane (ISM) as the sensing element for free—unbound—calcium in real bovine whole blood samples. With a linear response range of 100 mM to 97.7 μM, the sensor covers the clinically relevant concentrations of Ca²⁺ associated with both healthy cattle as well as those suffering from hypocalcemia. The components of the Ca²⁺ ion-selective electrodes were successfully translated to a paper-based device to provide a sensing platform that is simple to use, disposable, and low-cost, and is therefore well-situated for applications at the POC. The paper-based calcium sensor showed a Nernstian response between 10 mM and 100 μM and required only 12 μl of sample to perform a measurement, which can be accomplished in less than two minutes without the need for time-consuming separation steps. The performance of the paper-based Ca²⁺ sensor was validated using the commercially available epoc^® Blood Analysis System, which provided results within 5% of the data obtained with 3D printed Ca²⁺-ISM integrated paper-based device.

The objective of our study was to identify genomic regions associated with varying concentrations of non-esterified fatty acid (NEFA), β-hydroxybutyrate (BHB), and the development of hyperketonemia (HYK) in longitudinally sampled Holstein dairy cows. Our study population consisted of 147 multiparous cows intensively characterized by serial NEFA and BHB concentrations. To identify individuals with contrasting combinations in longitudinal BHB and NEFA concentrations, phenotypes were established using incremental area under the curve (AUC) and categorized as follows: Group (1) high NEFA and high BHB, group (2) low NEFA and high BHB), group (3) low NEFA and low BHB, and group (4) high NEFA and low BHB. Cows were genotyped on the Illumina Bovine High-density (777 K) beadchip. Genome-wide association studies using mixed linear models with the least-related animals were performed to establish a genetic association with HYK, BHB-AUC, NEFA-AUC, and the comparisons of the 4 AUC phenotypic groups using Golden Helix software. Nine single-nucleotide polymorphisms were associated with high longitudinal concentrations of BHB and further investigated. Five candidate genes related to energy metabolism and homeostasis were identified. These results provide biological insight and help identify susceptible animals thus improving genetic selection criteria thereby decreasing the incidence of HYK.

This study developed and evaluated an algorithm for processing thermal-RGB video feeds captured by an unmanned aerial vehicle (UAV) to automate heat stress monitoring in cattle housed in the drylots. The body surface temperature (BST) of individual cows was used as an indicator of heat stress. UAV data were collected using RGB and thermal infrared imagers, respectively, at 2 and 6.67 cm per pixel spatial resolution in Spring 2023 (dataset-1) and Summer 2024 (dataset-2). Study sites were two commercial drylots in Washington State. The custom algorithms were developed to: (1) detect and localize individual cows using a Mask R-CNN-based instance segmentation model combined with centroid tracking; and (2) extract BST by averaging the thermal-imagery pixels for each of the segmented cows. The algorithm showed higher detection accuracy with RGB images as input (F1 score: 0.89) compared to thermal (F1 score: 0.64). BST extraction with combined RGB and thermal imaging approach required corrections for alignment problems associated with differences in optics, imaging field of view, resolution, and lens properties. Consequently, thermal imaging-only approach was adopted for assessing real-time cow localization and BST estimation. Operating at one frame per second, algorithm successfully detected 72.4% and 81.65% of total cows in video frames from dataset-1 (38 s) and -2 (48 s), respectively. The mean absolute difference between algorithm output and ground truth (BST_GT) was 2.1 °C (dataset-1) and 3.3 °C (dataset-2), demonstrating satisfactory performance. With further refinements, this approach could be a viable tool for real-time heat stress monitoring in large-scale drylot production systems.