JDS communications最新文献

{"title":"Water soaking improves pizza bake properties of fat-free mozzarella cheese shreds","authors":"Suresh Sutariya ,&nbsp;Prafulla Salunke","doi":"10.3168/jdsc.2025-0879","DOIUrl":"10.3168/jdsc.2025-0879","url":null,"abstract":"<div><div>Fat-free mozzarella is valued for its low-calorie, low-fat nutrition, but suffers from poor melting, excessive browning, and rubbery texture when baked, limiting its appeal. This study builds on prior findings that soaking fat-free mozzarella shreds in water improves pizza baking performance. The research evaluates the effects of soaking on frozen-thawed shreds and on leftover pizza after refrigeration and microwave reheating, using rheometer-based analysis. Results show that soaking lowers the melting temperature and enhances flowable texture, with improvements persisting after freeze-thaw cycles and reheating. Hydrating shreds thus consistently improves performance of fat-free mozzarella pizza.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 128-133"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying data anomalies in milk component measurements from partial-day milking records","authors":"Xiao-Lin Wu ,&nbsp;Malia J. Caputo ,&nbsp;Chip Donatone ,&nbsp;Asha M. Miles ,&nbsp;Baldwin Ransom L. VI ,&nbsp;Steven Sievert ,&nbsp;Jay Mattison ,&nbsp;John B. Cole ,&nbsp;Javier Burchard ,&nbsp;João Dürr","doi":"10.3168/jdsc.2025-0825","DOIUrl":"10.3168/jdsc.2025-0825","url":null,"abstract":"<div><div>High-quality milk and milk component data are crucial for accurate genetic evaluations and effective herd management. However, data recording errors can compromise the validity of downstream decisions. In a recent study, we proposed using intraclass correlation coefficients as a herd-level metric to assess the consistency of milk components from single milkings, thereby effectively identifying farms with potential data quality concerns. A key challenge, however, is whether potentially erroneous records can be detected at the cow-day level. In this study, we introduce a novel metric—individual-level intraclass correlations—to assess data consistency at the cow-day level and evaluate its performance against 3 commonly used anomaly-detection methods. We further introduce a 2-step approach to estimate percentile thresholds for flagging outliers. The results demonstrate the superior performance of this new metric over the conventional univariate and multivariate methods in identifying anomalies in correlated partial daily milk component data. In addition, the negative impact of data shuffling was examined. Together, these methods provide robust and practical tools for detecting suspect milk component records at the individual cow-day level.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 204-209"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an Internet of Things–based real-time greenhouse gas and weather monitoring system for precision dairy farming","authors":"Keshawa Dadallage ,&nbsp;Marina Madureira Ferreira ,&nbsp;Alejandra Zapata-Salazar ,&nbsp;Diego A. Ceballos ,&nbsp;Lav R. Khot ,&nbsp;Francisco A. Leal Yepes","doi":"10.3168/jdsc.2025-0862","DOIUrl":"10.3168/jdsc.2025-0862","url":null,"abstract":"<div><div>The environmental footprint of dairy production is one of the most pressing challenges faced by the industry globally. Our study aimed to develop and validate a cost-effective sensing solution for real-time monitoring of dairy farms' GHG emissions and microclimatic conditions. Each of the integrated sensing nodes was equipped with carbon dioxide (CO₂), methane (CH₄), and ammonia (NH₃) gas sensors, along with an all-in-one weather sensor. Sensing nodes were validated against gold-standard measurements using open-circuit respiration chambers with individual cows under controlled conditions. The CH₄ emissions (133.0 ± 22.5 ppm, mean ± SD) showed an overall correlation (r = 0.46) with the gold-standard respiration chamber (166.0 ± 32.8 ppm) across all 3 d. However, the correlation changed over time, with a strong correlation on d 1 (r = 0.62), a moderate correlation on d 2 (r = 0.35), and a weak correlation on d 3 (r = 0.11). In contrast, sensor node quantified CO₂ emissions (905 ± 779 ppm) showed a weaker correlation (r = 0.019, 2,461 ± 346 ppm), indicating the need for further improvements to the sensing node. A wireless network of calibrated sensing nodes was deployed in 3 different locations within a dairy farm: dry cow pen (DCP), feed bunk (FB), and freestall beds (FSB) at a research dairy farm. The CH₄ emissions were greater in the DCP (12.5 ± 6.65 ppm) compared with FB (2.80 ± 0.61 ppm) and FSB (2.34 ± 0.62 ppm). The CO₂ emissions at the FB were greater (1,498 ± 1,020 ppm) compared with the DCP (534 ± 222 ppm) and FSB (724 ± 517 ppm). The NH₃ emissions were highest in the FSB (4.24 ± 0.91 ppm) compared with DCP (2.93 ± 1.35 ppm) and FB (1.10 ± 0.44 ppm). The differences in GHG emissions across the different areas of the dairy farm may be influenced by ambient temperature, humidity, housing conditions, and manure management practices. Our sensing nodes may provide a low-cost, scalable sensing network that can offer a practical solution for continuous GHG monitoring.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 185-190"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential energy partitioning occurs in response to high- and low-energy diets in Holstein cows during late lactation","authors":"Thiago O. Cunha ,&nbsp;Tanya L. France ,&nbsp;Sebastian I. Arriola Apelo ,&nbsp;Kenneth.F. Kalscheur ,&nbsp;Elizabeth A. French ,&nbsp;Mateus Z. Toledo ,&nbsp;Milo C. Wiltbank ,&nbsp;Laura L. Hernandez","doi":"10.3168/jdsc.2025-0891","DOIUrl":"10.3168/jdsc.2025-0891","url":null,"abstract":"<div><div>This study evaluated the impact of high-energy (HE) or low-energy (LE) diets during late lactation and the responsiveness of body condition changes to diet during the dietary treatment period. Sixty-six multiparous Holstein cows were blocked by parity and expected date of parturition and randomly assigned to HE (1.74 Mcal/kg DM) or LE (1.50 Mcal/kg DM) diets at 150 d of gestation to achieve high or average BCS by dry-off (233 d of gestation). Surprisingly, not all cows within dietary treatment groups were responsive to the diet based on BCS at dry-off. To determine the underlying physiology responsible for this observation, we classified cows as responsive (R) or nonresponsive to diet (NR) within each dietary treatment: HE (HE-R, &gt;0.25 increase in BCS [28/35]; HE-NR, ≤0.25 BCS [7/35]) or LE (LE-R ≤0.25 increase in BCS [27/31]; LE-NR &gt;0.25 BCS increase [4/31]). Feed intake did not differ within the HE-R and HE-NR subgroups or between the LE-R and LE-NR subgroups. During the dietary treatment period, cumulative ECM was greater in HE-NR than HE-R cows (3,304 vs. 2,236 ± 151 kg). In contrast, LE-NR produced less ECM than LE-R cows (1,622 ± 229 vs. 2,068 ± 77 kg) during the dietary treatment period. Circulating insulin concentrations were similar among subgroups at study enrollment (9.2 ± 1.1 mU/mL); however, dry-off insulin concentrations differed among subgroups (HE-R 17 ± 3.0; HE-NR 5.4 ± 2.0 mU/mL; LE-R 10.2 ± 2.0; LE-NR 23.6 ± 4.0 mU/mL). One week before parturition, circulating insulin concentrations converged and were no longer different among subgroups, averaging 12.5 ± 2 mU/mL. Our data suggest that circulating insulin concentration is involved in regulating the response to dietary treatment during late lactation.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 296-301"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory analysis of associations between postpartum body condition changes measured by an automated 3-dimensional camera and reproductive outcomes measured by in-line milk progesterone analysis","authors":"Alessandro Frizza ,&nbsp;Erminio Trevisi ,&nbsp;Luca Cattaneo","doi":"10.3168/jdsc.2025-0773","DOIUrl":"10.3168/jdsc.2025-0773","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Our objective was to evaluate the associations of postpartum BCS changes, as predicted by automatic monitoring using 3-dimensional (3D) camera technology after calving, with milk yield and reproductive outcomes assessed both from in-line milk progesterone analysis and conventional methods in Holstein dairy cows in a retrospective observational study. Cows calving in a commercial farm during a whole year (n = 123; 53 primiparous and 70 multiparous) were automatically evaluated for BCS with a 3D camera (DeLaval Body Condition Scoring system) daily on a 5-point scale up to 120 DIM and retrospectively classified into tertiles based on BCS change from calving to 30 DIM. The resulting groups had high (HI), intermediate (IN), and low (LO) BCS change. Milk yield and milking frequency were collected daily from the automatic milking system (VMS V310, DeLaval), which also automatically evaluated milk progesterone concentration every 2 to 3 d on average. These data were used to characterize luteal activity, with progesterone concentrations peaking during luteal phases and reaching a nadir around estrus events, thus allowing identification of the resumption of cyclicity. Pregnancy outcomes were evaluated up to 200 DIM with logistic regressions and time-to-event data with Cox's proportional hazard models. Continuous data were analyzed with ANOVA, with repeated measures mixed models when appropriate. The models included the effects of BCS tertile and parity. Body condition score loss averaged −0.47, −0.30, and −0.09 for HI, IN, and LO, respectively, ranging from −0.78 to −0.36 in HI, from −0.35 to −0.25 in IN, and from −0.24 to 0.41 in LO. Cows with minimal BCS loss (LO) were thinner (BCS = 3.23 ± 0.29) at calving than cows with greater BCS loss (HI and IN, BCS = 3.38 ± 0.25 and 3.37 ± 0.23, respectively). The BCS nadir was lower in HI compared with IN and LO, although the time to the nadir did not differ. The HI cows tended to have later commencement of luteal activity (i.e., DIM of the first of at least 2 consecutive samples with milk progesterone ≥5 ng/mL; +8 d vs. IN and LO), calculated based on progesterone profiles, but a similar percentage of cows (∼95% overall) resumed ovarian cyclicity before the end of voluntary waiting period (75 DIM). The proportion of cows pregnant at the first artificial insemination (AI) did not differ, but LO cows tended to have increased likelihood of pregnancy at the second AI compared with IN. The cumulative proportion of pregnant cows at the first and second AI tended to be greater in LO compared with HI and IN, and the proportion of pregnant cows up to 200 DIM was greater in LO. Compared with LO, the HI and IN cows had reduced hazard of pregnancy up to 200 DIM. Milk yield was 4 and 3 kg/d lower in LO compared with HI and IN. Automated BCS and progesterone monitoring showed that greater BCS loss in the first 28 DIM was associated with delayed cyclicity and reduced reproductive performance, whereas minimal loss was ","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 290-295"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analysis of supplemental methionine effects on plasma amino acid concentrations in dairy cows","authors":"G.I. Zanton","doi":"10.3168/jdsc.2025-0804","DOIUrl":"10.3168/jdsc.2025-0804","url":null,"abstract":"<div><div>Increasing metabolizable Met (mMet) through feeding supplemental rumen-protected Met to dairy cows is a common component of balancing rations for Met. Changes in plasma Met (pMet) brought about by this practice may affect the metabolism of other AA, resulting in changes in the concentration of other plasma AA (pAA). The objective of this meta-analysis was to evaluate the changes in pAA when lactating dairy cows were provided supplemental mMet. Literature studies were identified that fed cows a control diet and the control diet supplemented with Met as either rumen-protected Met or through infusion to increase pMet. There were 41 studies feeding 60 control and 78 Met treatments that met the selection criteria and entered into the final analysis. Responses entering the meta-analysis were calculated as Met-supplemented cow pAA − control cow pAA and analyzed as weighted mean differences or standardized weighted mean differences where the weighting term was the inverse variance and robust variance estimation was conducted to account for the hierarchical structure of the data. Regression was also conducted where pAA were regressed against pMet weighted by the inverse variance and including the random effect of study and experiment-within-study. Mean pMet in control cows was 19.9 µ<em>M</em>, which increased with supplementation by 11.3 µ<em>M</em>. Sulfur-containing pAA Cys and homocysteine as well as Lys were increased with increasing pMet whereas Gln, Glu, His, Ile, Leu, Tyr, and Val decreased with increasing pMet. The pAA Arg, Gly, Orn, Ser, Tau, and Trp responded curvilinearly to pMet with the predicted response in Arg, Orn, Tau, and Trp reaching a peak and Gly and Ser a nadir at intermediate concentrations of pMet. Milk protein yield increased in association with greater pMet, but responses to supplemental Met appeared to be limited by the reduction of other pAA, as higher responses to pMet were observed at higher levels of dietary CP. These results imply that concentration changes in pAA should be considered during diet formulation when feeding supplemental mMet to support increased milk protein production.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 146-151"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting individual dry matter intake in Holstein × Gyr cows using behavior-monitoring sensor, phenotypic, and weather data with supervised machine learning","authors":"Camila S. da Silva ,&nbsp;Tadeu E. da Silva ,&nbsp;Anna L.L. Sguizatto ,&nbsp;Andreia F. Machado ,&nbsp;Abias S. Silva ,&nbsp;João H.C. Costa ,&nbsp;Mariana M. Campos ,&nbsp;Domingos S.C. Paciullo ,&nbsp;Carlos A.M. Gomide ,&nbsp;Mirton J.F. Morenz","doi":"10.3168/jdsc.2025-0850","DOIUrl":"10.3168/jdsc.2025-0850","url":null,"abstract":"<div><div>Accurate estimation of DMI is essential for optimizing nutrition, efficiency, and economic performance in modern dairy herds. However, most existing equations to estimate DMI are designed for herd-level predictions in purebred Holstein cows. This study evaluated the accuracy and precision of machine learning (ML) algorithms to predict daily individual DMI in Holstein × Gyr crossbred lactating cows using a supervised and integrative approach that combined behavior monitoring data, cow phenotypes, and weather features. Data from 31 cows were individually and consecutively collected over 18 d. Twenty-two cows (71% of the dataset) were used to train 4 linear regression models (multiple linear, ridge, lasso, and elastic net) and 3 ensemble algorithms (random forest, gradient boosting, and extreme gradient boosting) through leave-one-group-out cross-validation, with the number of folds equal to the number of cows (<em>k</em> = 22). The remaining 9 cows were used as an external test set. Among all algorithms, Gradient boosting achieved the best overall performance, yielding moderate precision (R² = 0.68) and accuracy (root mean squared error = 1.60 kg/d) metrics on test data. Our results indicate that gradient boosting is more suitable for capturing complex nonlinear relationships underlying daily DMI compared with the other models evaluated. Further advancements in ML-based DMI prediction should consider integrating intra- and interindividual variability in feeding behavior and accounting for animal-specific effects.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 179-184"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decreasing the computing time of approximated reliabilities of genomic estimated breeding values in the single-step genomic best linear unbiased predictor using different core sizes for the algorithm for proven and young","authors":"S.N. Sanchez-Sierra ,&nbsp;Matias Bermann ,&nbsp;Natascha Vukasinovic ,&nbsp;Miguel A. Sánchez-Castro ,&nbsp;Ignacy Misztal ,&nbsp;Daniela Lourenco","doi":"10.3168/jdsc.2025-0892","DOIUrl":"10.3168/jdsc.2025-0892","url":null,"abstract":"<div><div>The single-step genomic best linear unbiased predictor (ssGBLUP) along with the algorithm for proven and young (APY) are used to compute GEBV in livestock populations with extensive genomic data. Calculating GEBV reliabilities is computationally expensive, particularly with many genotyped animals, because it requires inverting the left-hand side of the mixed model equations. However, reliabilities in ssGBLUP models can be approximated by leveraging the sparse structure of the APY. The primary computational bottleneck of the algorithm lies in a matrix multiplication step, which scales quadratically with the size of the core set. This study aimed to decrease the computing time for approximating GEBV reliabilities in ssGBLUP by reducing the size of the core set in APY without compromising the precision of the reliability approximations. Reliabilities were approximated for a single-trait model for calf respiratory disease in Holsteins (h² = 0.042). A dataset comprising 4,563,070 animals in the pedigree, 1,629,592 genotypes, and 1,585,306 records was used for the study. Core sets of varying sizes (25k, 20k, 15k, 10k, and 5k) were evaluated. Approximated reliabilities obtained with a core set size of 25k were used as a comparison benchmark. Correlations between approximated reliabilities obtained with different core sizes and the benchmark ranged from 0.94 to 1.00, whereas the intercept and slope of the regression of the benchmark reliabilities on the smaller core reliabilities ranged from −0.16 to 0.38 and from 0.64 to 1.15, respectively. Computing times varied significantly, with the fastest approximation (55.02 min) achieved using a 5k core, compared with 171.27 min for the 25k core benchmark. This represents a 3.1-fold reduction in computing time and a 2.1-fold reduction in memory usage when comparing the 25k core size with the 5k core size. Additionally, more substantial savings can be obtained as the number of traits increases. Having fewer genotyped animals in the APY core is a reasonable approach to accelerate GEBV reliability calculations; however, changes in the approximated reliabilities occur, underscoring the trade-off between computational efficiency and the accuracy of the approximations.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 222-226"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of incubation with endocannabinoids on the expression of endocannabinoid and inflammatory components following an ex vivo lipopolysaccharide challenge in leukocytes of dairy cows","authors":"P. dos Santos Silva ,&nbsp;Y. Butenko ,&nbsp;L. Hubner ,&nbsp;B. Shattenstein ,&nbsp;M. Zachut","doi":"10.3168/jdsc.2025-0866","DOIUrl":"10.3168/jdsc.2025-0866","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The endocannabinoid system (ECS) is involved in regulating immune functions in leukocytes. An inflammatory stimulus, specifically LPS, can modulate the activity of endocannabinoids (eCB) receptors, and eCB within the leukocytes can further exert either pro- or anti-inflammatory effects on the immune function of these cells. The effects of exogenous eCB on the cellular inflammatory responses of bovine leukocytes are largely unexplored; therefore, we aimed to evaluate the effects of incubation with the main eCB &lt;em&gt;N&lt;/em&gt;-arachidonoylethanolamide (AEA/anandamide) or 2-arachidonyglycerol (2-AG) on gene expression of eCB and inflammatory mediators following an ex vivo LPS challenge in dairy cow leukocytes. To this end, whole blood from mid-lactation dairy cows (n = 6) were subjected to ex vivo incubation with eCB (control [CTL], AEA at 0.29 µ&lt;em&gt;M&lt;/em&gt;, or 2-AG at 0.26 µ&lt;em&gt;M&lt;/em&gt;) for 2 h, followed by stimulation with or without LPS (10 ng/mL) for an additional 2 h. Overall, there were 6 treatments for cells from each cow: CTL, AEA, and 2-AG without LPS stimulation, and CTL+LPS, AEA+LPS, and 2-AG+LPS. Subsequently, RNA was extracted from leukocytes and assayed for gene expression levels via real-time quantitative PCR. First, we examined the main effects of LPS stimulation across eCB treatments: LPS decreased expression of the eCB receptors cannabinoid receptor 2 (&lt;em&gt;CNR2&lt;/em&gt;), G protein-coupled receptor 55 (&lt;em&gt;GPR55&lt;/em&gt;), and peroxisome proliferator-activated receptor gamma (&lt;em&gt;PPARG&lt;/em&gt;). Furthermore, LPS increased expression of the eCB enzymes N-acyl phosphatidylethanolamine phospholipase D (&lt;em&gt;NAPEPLD&lt;/em&gt;) and monoglyceride lipase (&lt;em&gt;MGLL&lt;/em&gt;) while reducing the expression of diacylglycerol lipase B (&lt;em&gt;DAGLB&lt;/em&gt;) compared with non-LPS-stimulated groups. Then, we examined the main effects of eCB treatments on gene expression: incubation with AEA increased expression of cannabinoid receptor 1 (&lt;em&gt;CNR1&lt;/em&gt;) in leukocytes, whereas 2-AG increased the expression of the &lt;em&gt;CNR2&lt;/em&gt; and tended to increase &lt;em&gt;GPR55&lt;/em&gt;. In addition, 2-AG increased the expression of fatty acid amide hydrolase (&lt;em&gt;FAAH&lt;/em&gt;) and tended to increase the expression of &lt;em&gt;NAPEPLD&lt;/em&gt;. As expected, LPS increased the expression of inflammatory markers; however, incubation with eCB had no discernible effects on these genes. Taken together, ex vivo exposure of dairy cow leukocytes to AEA or 2-AG, with or without stimulation with LPS, resulted in differential effects on the expression of eCB receptors and enzymes, but we did not detect effects of exogenous eCB on the expression of inflammatory genes following an LPS challenge. The findings of the present study provide the first reductionist step in understanding the relationship between the ECS and inflammatory responses in immune cells of dairy cows. The complexity of the regulation of immune function in leukocytes, and its potential interplay with eCB, requires further studies to comprehensively el","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 284-289"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential roles of colostrum microbiota in shaping calf gut microbiota and colostrum metabolites","authors":"Jalyn Hawkins ,&nbsp;Shelby Carpenter ,&nbsp;Himani Joshi ,&nbsp;Chuan-Yu Hsu ,&nbsp;Caleb Lemley ,&nbsp;Peixin Fan","doi":"10.3168/jdsc.2025-0883","DOIUrl":"10.3168/jdsc.2025-0883","url":null,"abstract":"<div><div>Colostrum provides vital nutrients and antibodies that are crucial for calf health and survival. It also contains microbes that may be vertically transmitted to calves and influence early gut microbiota development. These microbes in colostrum may also biologically function to produce unique metabolites that affect colostrum quality and calf growth. However, these colostrum components remain largely unexplored. The aim of this study was to identify colostrum-derived microbes capable of colonizing and persisting in the calf gut and to characterize colostrum metabolomics in relation to the colostrum microbiota. Colostrum samples were collected from 25 Holstein heifers, and fecal samples were collected from their individually housed Holstein-Angus crossbred offspring on d 4, 7, 14, and 30 after birth. Colostrum and fecal microbiota were analyzed using full-length 16S rRNA gene amplicon sequencing, whereas the untargeted metabolomics was performed using ultra-performance liquid chromatography MS. We identified 20% prevalent colostrum bacteria (15 species) were consistently detected in calf fecal samples across all time points, indicating their potential to colonize and persist in the early gut, although the relative abundance of these species in calf feces gradually decreased from d 4 to 30. Colostrum samples were classified into 3 distinct clusters based on the dominant species: <em>Streptococcus thermophilus</em>, <em>Lactococcus lactis</em>, and <em>Comamonas testosteroni</em>. Three colostrum samples from each cluster were selected as a focal group for the untargeted metabolomics analysis. We identified a total of 405 metabolites present in the colostrum samples. No significant differences in metabolomic profiles were observed among the 3 microbial clusters, indicating that colostrum microbiota were not the main drivers of metabolomic dynamics. However, 54 strong positive correlations were detected between bacterial species and metabolites, particularly between colostrum-calf feces shared species and microbial-derived metabolites. For example, 4-methylphenol was positively associated with <em>Bacteroides fragilis</em>, the most abundant bacterial species in calf feces on d 4. In addition, <em>Streptococcus uberis</em>, a pathogen associated with mastitis, exhibited the greatest number of strong negative correlations with metabolites. In conclusion, this study identified specific colostrum bacterial species with the potential to transmit and persist in the calf gut microbiota and to contribute to microbial metabolite production. Further research is warranted to evaluate the roles of these persistent microbes and their metabolites in shaping colostrum quality, calf growth, and health outcomes.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"7 2","pages":"Pages 302-308"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}