In this study, the concentrations of metals (arsenic (As), cadmium (Cd), copper (Cu), mercury (Hg) and lead (Pb)), and aflatoxin M1 were analysed in mare's milk samples taken from eight mares over a period of six months during lactation. The results showed that the concentrations of metals in milk occurred in the following order: Cu > Pb > Hg > Cd > As. Key findings of the study included the determined content of metals, depending on lactation stages and animal husbandry practices. Copper had the highest concentration among the metals analysed, while Cd and As were not detected. No statistically significant differences were found in the levels of heavy metals or aflatoxin M1 across different lactation stages. However, statistically significant differences in aflatoxin M1 concentrations were observed depending on the type of animal husbandry, illustrating the influence of environmental and husbandry conditions on milk contamination. The study concludes that there is no toxicological risk for consumers of Croatian Cold-Blooded mare's milk, which is an important finding for food safety and public health. The significance of this study lies in the provision of valuable data on the safety of mare’s milk, especially with regard to its possible contamination with toxic heavy metals and aflatoxin M1. The main objective was to determine the presence and concentrations of the listed contaminants, to evaluate the influence of lactation stage and husbandry, and to assess compliance with established safety standards.

Dairy cows typically respond to stressors by altering their behavior, such as reducing eating time (ET) and rumination time (RT). Although declines in milk yield (MY) have been extensively studied, models to quantify perturbations in ET and RT are still lacking. This study adopts a smoothing approach to identify and characterize perturbations in MY, ET, and RT in response to the main primary stressors, heat stress (HS), lameness (L), and mastitis (M), while evaluating the influences of parity and stage of lactation. A total of 350 Italian Simmental cows were monitored in farms equipped with automatic milking systems and accelerometers. Within this population, cows with a lactation period of at least 150 days were selected. A double-curve smoothing model (λ = 100 and λ = 10,000) was applied to calculate response and recovery times and to quantify production and feeding behavior losses. The results indicate that L causes the longest (30.6 d and 28.8 d, respectively) perturbations for both MY and ET. While L caused the greatest loss in milk production (14.7 kg), HS resulted in the greatest losses regarding feeding behavior (ET: 175.2 min and RT: 210.3 min). In general, M had a lower impact, likely due to the timeliness of treatments. Primiparous cows showed faster responses to stress but slower recovery times compared to multiparous ones. However, multiparous cows exhibited greater total MY losses. The method proved effective for quantifying resilience and opens new perspectives in health monitoring, allowing for the identification of both economic loss and each animal's capacity to cope with pathological and environmental events, improving the overall sustainability of the dairy farm.

Human milk composition varies in time to meet the evolving growth and developmental requirements of infants. While 24-hour (diurnal) variations in human milk composition for term-born infants have been reported, evidence concerning diurnal variation of preterm human milk composition remains inconclusive. To examine the presence of diurnal variations in macronutrient content in very preterm human milk. Milk samples were donated by mothers of very preterm infants (<30weeks gestation). Milk series (defined as sequential milk samples collected from one mother) consisted of 13 to 17 (median 15) samples, collected over three consecutive days. Milk macronutrient (fat, true protein and carbohydrates) content were measured using mid-infrared spectrophotometry (Miris HMA™). Rhythmicity analyses and logistic regression analyses were performed to explore associations between macronutrient rhythmicity and pregnancy duration (weeks), infants' sex, and lactational stage). Of the 22 milk series studied, 12 (55%) showed 24-hour rhythmicity in one or more macronutrients. Fat content showed rhythmicity in 41% of the series, with varying peak times. For carbohydrates, protein and calculated energy content, rhythmicity was only identified in 18%, 14% and 27% of the milk series, respectively. Longer pregnancy duration was associated with increased odds of rhythmicity (odds ratio 2.1 (95% confidence interval 1.02-4.21), p=0.04), but not with sex or stage of lactation. Over half of the preterm human milk samples exhibited diurnal macronutrient rhythmicity, mainly in fat levels. The observed rhythms had varying peak times, suggesting phase differences of the maternal rhythms.

A meta-analysis was conducted to quantify production responses to chromium (Cr) supplementation and better understand variables that affect this response. Multivariate random and mixed effects models were used to develop and fit all models. The response variable was described by the mean difference of milk yield, ECM, DMI, and milk fat and protein yields between cows that received Cr supplementation and cows in the control group. Treatment means from 28 studies were used to assemble a database of studies designed specifically to investigate the effects of supplementing Cr on dairy cows. Of the 93 treatment means, 38 means fed the Cr starting in the dry period. Overall, Cr supplementation increased production, and the mean difference is affected by stage of lactation (characterized by DIM in our analysis), Cr source (Cr-methionine, Cr-propionate, Cr-chelate, Cr-picolinate, Cr-yeast), and dose (0-19 mg/d). The models for milk yield, milk fat, and milk protein suggest the greatest response for Cr supplementation between a 6 to 7 mg/d supplementation rate. However, the greatest response for DMI was predicted to be at a supplementation rate of 9 mg/d. The models suggest peak mean differences in yields of milk, ECM, fat, and protein at approximately 100 DIM with supplementation of Cr starting at pre- or postcalving. Although the production of ECM maximizes at approximately 100 DIM there is still a benefit in production to feeding Cr up to 168 to 186 DIM, depending on the Cr source.

Composition and biology of human milk.

Studying changes in plasma EAA concentration and profile may provide a foundation for precision protein nutrition strategies for feeding dairy cows. Using data from a systematic review, Letelier et al. (2022a) identified 2 EAA concentration and profile clusters that differed in performance (DMI, daily milk energy output, fat yield and protein yield) and measures of feed and N use efficiency. However, controlled trials are necessary to evaluate these findings with individual cow-level data. We hypothesized that the EAA concentration and profile at the group level obtained from the literature would result in comparable performance and efficiency measures when evaluated at the individual level. Hence, this study aimed to evaluate the clusters identified in the review of Letelier et al. (2022a) using a supervised machine learning model to determine whether the differences in performance and efficiencies between clusters were consistent when assessed with an independent empirical dataset. These data were from a study of 62 cows stratified in 4 lactation stages (early, mid-early, mid-late, and late) fed diets of 13.6%, 15.2%, 16.7%, or 18.3% CP (DM basis) for 8 wk. A random forest algorithm was trained for cluster identification using data from the review published by Letelier et al. (2022a), with Arg, His, Ile, Leu, Lys, Met, Phe, Thr, and Val concentration and profile (i.e., the molar proportion in total plasma EAA concentration) as features and clusters as outputs. A leave-one-trial-out cross-validation approach evaluated the model's classification ability, achieving accuracy, precision, recall, and F1 score of 84.4%, 87.3%, 85.7%, and 86.5% for cluster 1, and 84.4%, 80.5%, 82.5%, and 81.5% for cluster 2, respectively. The model was then retrained using the entire 62-cow dataset. The EAA concentration and profile were assessed in wk 4 and 8, where 33 and 38 cows were classified as cluster 1, and 29 and 24 as cluster 2, respectively. Cows in cluster 2 exhibited greater concentrations of Arg (11.8%), His (24.5%), Ile (18.4%), Leu (38.8%), Lys (16%), Met (14.4%), Phe (15.2%), Trp (4.5%), and Val (26.3%) than cows in cluster 1. In addition, cluster 2 cows were determined to have 2.53% greater DMI (28.4 ± 0.23 vs. 27.7 ± 0.22 kg/d) and 2.34% greater ECM yield (42.8 ± 0.51 vs. 43.8 ± 0.54 kg/d), but 2.81% lower N use efficiency (100 × milk true protein N/N intake; 28.5% ± 0.42% vs. 27.7% ± 0.44%) than cows in cluster 1. The was no difference in feed efficiency and milk component concentration between clusters. These findings confirm that the group-level responses previously observed between EAA-based clusters and measures of dairy cow performance also exist at the individual cow level. However, research with larger datasets is needed to clarify the nature of the relationship between EAA-based clusters and measures of performance, feed efficiency, and N use efficiency.

The study objective was to assess the methane (CH4)-mitigating potential (CH4-MP) of an Asparagopsis taxiformis variety (Brominata; Blue Ocean Barns) and evaluate its effects on cow health when fed at increasing dietary inclusion rates (IR) in dairy cows. This paper reports data on the CH4-MP and production performance. In this study, 48 late-lactation cows (mean DIM = 386) blocked by parity were assigned randomly to receive 1 of 4 freeze-dried and pelletized Brominata IR treatments: 0% (CTL), 0.30% (standard IR [SIR]), 0.45% (SIR1.5), and 0.60% of DM (SIR2.0), with mean bromoform concentrations of 0, 17.4, 26.1, and 34.8 mg/kg of DM, respectively. The study consisted of a 10-d baseline measurement period (P1), a 4-wk IR ramp-up phase (P2), and a subsequent 9-wk response measurement period (P3). The pelletized Brominata was mixed uniformly into the TMR delivered daily to individual cows. The CH4 emissions were measured daily using the GreenFeed system (C-Lock Inc., Rapid City, SD). Milk composition, BW, and body condition scores were recorded once every 2 wk. The feces samples were collected directly from the rectum every 8 h over 2 consecutive days during the last week of P3 to determine the apparent total-tract digestibility of nutrients. Orts were examined periodically during P3 to assess pellet refusals. Treatment effects were analyzed using the MIXED procedure of SAS with the REPEATED option. The model included fixed effects of IR, time (in weeks), the treatment × time interaction, parity, the covariate effect of P1 measurements, and the random effect of cow. The DMI decreased linearly with increasing IR. The DMI decreases of SIR1.5 (32.4%) and SIR2.0 (46.5%) were sustained throughout P3, whereas that of SIR became negligible after the fourth week of P3. The pellet refusals revealed sorting against Brominata pellets, resulting in 37% to 43% lower Brominata concentrations in ingested DM compared with the treatment IR. The mean CH4 production decreased by 50%, 70%, and 77%, and CH4 yield decreased by 41%, 56%, and 59% compared with the CTL in response to SIR, SIR1.5, and SIR2.0, respectively. The CH4 yield reduction of SIR gradually decreased from the second week of P3 onward and became negligible in the last week, whereas SIR1.5 and SIR2.0 sustained it at 66% until the sixth week and then experienced a reduction to 36%. Consistently, the bromoform concentration (mg/g) in freeze-dried Brominata declined during P3, reaching a 23% reduction by the final 2 wk, primarily due to variability among harvested batches. Milk yield, milk component yields, and milk fat content decreased linearly with increasing Brominata IR. Compared with CTL, only SIR2 decreased those responses, except for milk fat yield, which was also decreased by SIR1.5. The nutrient digestibility had cubic relationships with IR, such that the DM, OM, and CP digestibility of SIR1.5 was lower than that of SIR but similar to that of CTL and SIR2.0. The results demonstrate that Brominata is highly effective in reducing enteric CH4 emissions of dairy cows. However, it is crucial to address palatability concerns and managing variability in bromoform concentration to sustain this efficacy under current feeding conditions in late lactation and possibly in other lactation stages.

Colostrum-specific amino acids and lipids elevating lutein bioaccessibility at the micellization stage relative to mature milk and infant formula.

The castor bean tick (Ixodes ricinus) is a widespread European ectoparasite and vector of multiple diseases that can impair cattle health and productivity. This study evaluated whether a single application of a gel microencapsulated acaricide (α-cypermethrin and permethrin) reduces I. ricinus infestation in dairy cows and affects milk yield. Twenty cows were allocated to treated and control groups; treated animals received one spray at the start of the grazing season, and tick counts were recorded daily for 196 days with monthly milk-yield measurements. Two activity peaks were observed (June and September-October) with reduced abundance in July-August; all control cows were parasitised, with daily counts of 1-18 ticks (median = 2). During the first month after treatment, the acaricide reduced tick numbers by around 80% versus controls (p < 0.001); efficacy declined over the ensuing months, and differences were negligible after about five months. No adverse effect on milk yield was detected (p = 0.38), and seasonal variation (p < 0.0001) and lactation stage (p < 0.001) were the primary determinants of production. Primiparous and young cows, as well as cows in mid-to-late lactation, tended to show higher levels of tick infestation. A single application of the gel microencapsulated product provided a significant reduction in tick burden during the first month after treatment in grazing dairy cows, without a negative impact on milk production, supporting its use in endemic areas.

Although Lys has been widely used in dairy cows, its effects on lactational performance are inconsistent, and the potential interfering factors have not been systematically investigated. Thirty-three reviewed publications from PubMed, Web of Science, and Google Scholar databases up to March 31, 2025, were pooled to calculate the weighted mean differences (WMD) and CI for continuous variables using a stratified 3-level meta-analysis with a random-effects model. A moderator analysis was used to evaluate the influences of cow breed, lactational stage, dietary MP supply, basal diet type, and other additions, as well as methods, dosage, and duration of administration, on the effects of supplemental Lys. Results showed that Lys supplementation increased the milk yield (WMD = 0.52 kg/d, [0.30, 0.74]), milk protein yield (WMD = 0.03 kg/d, [0.02, 0.04]), milk protein concentration (WMD = 0.05%, [0.03, 0.07]), and milk fat yield (WMD = 0.02 kg/d, [0.01, 0.03]) in dairy cows. The positive effects of Lys supplementation on milk yield and milk fat yield were more prominent in dairy cows of Holstein breed, in cows fed an MP-adequate diet, in cows fed a corn silage-based diet, or in administration through feeding rumen-protected Lys compared with the respective other groups. The response of milk protein yield in dairy cows was greater when Lys was supplemented in early lactation (WMD = 0.04 kg/d, [0.02, 0.06]). Lysine supplementation along with Met significantly increased the milk yield (WMD = 1.09 kg/d, [0.53, 1.64]), whereas sole Lys addition had greater effects on milk protein concentration (WMD = 0.06%, [0.03, 0.09]). Regression analysis showed that the optimal dosage and duration of Lys supplementation for milk yield, milk protein yield, and milk fat yield were 203, 208, and 204 g/d (6.8%, 6.9%, and 6.8% of MP) and 90, 85, and 43 d, respectively. These findings collectively provide practical guidelines for Lys application in improving the lactational performance in dairy cows.

Lactation decline in sheep is accompanied by extensive mammary gland remodeling, primarily involving extracellular matrix (ECM) reorganization. Here, we integrated single-cell RNA sequencing data from peak (PL) and late lactation (LL) stages to delineate the cellular and molecular mechanisms underlying this process. We identified nine immune cell subtypes and observed marked stage-specific changes in their abundance, highlighting a dynamic immune landscape during lactation regression. Notably, fibroblasts emerged as pivotal stromal regulators, exhibiting high expression of ECM-related genes and mediating collagen restructuring. Ligand-receptor interaction analysis revealed that fibroblasts maintained robust communication with endothelial and immune cells via FGF and FN1 signaling pathways, orchestrating ECM remodeling and structural stabilization. Metabolic profiling further implicated fibroblast-driven valine, leucine, and isoleucine degradation in supporting ECM dynamics. Cross-species comparisons revealed conserved transcriptional programs in fibroblasts and endothelial cells between sheep and humans, underscoring their evolutionarily conserved roles in ECM remodeling and angiogenesis. The study uncovers a fibroblast-driven regulatory network governing postpartum ECM remodeling, providing theoretical insights into the development and reconstruction of mammary tissue, and laying a foundation for investigating lactation dynamics and tissue regression across species.

Environmental and lifestyle factors affecting nickel concentrations in human colostrum: A cross-sectional study in Poznań, Poland.

This study examined the correlations between key biomarkers of energy and lipid metabolism (beta-hydroxybutyrate, glucose, lipoproteins) and haematological and biochemical blood parameters in Brown Swiss cows kept under year-round housing in a naturally ventilated barn. The relevance of this research is due to the increasing frequency of metabolic disorders and heat stress in high-yielding dairy cattle, which is exacerbated by seasonal fluctuations in microclimatic conditions. The investigation of the diagnostic value of blood biomarkers is considered promising for the early detection of metabolic stress and for improving the effectiveness of animal welfare monitoring. The study involved second-lactation cows (n = 50) at one of the largest Brown Swiss dairy complexes in central Ukraine. Representative groups of cows were randomly formed for each season, ensuring similar productivity and stage of lactation. Protein, lipid, carbohydrate and mineral metabolism, as well as haematopoietic indices, were investigated. Environmental conditions (temperature, humidity, temperature–humidity index) were assessed using data from the nearest meteorological station. Correlations between blood parameters were determined using Spearman’s correlation coefficient. Data processing and statistical analysis were performed using Statistica 12 (StatSoft Inc., USA), with significance accepted at p ≤ 0.05. The results showed that beta-hydroxybutyrate was significantly negatively correlated with liver enzyme activity (ALT, r = –0.465, p &lt; 0.05; AST, r = –0.321, p &lt; 0.05). Glucose was negatively correlated with total calcium (r = –0.742, p &lt; 0.05), Ca/P ratio (r = –0.561, p &lt; 0.05), haematocrit (r = –0.472, p &lt; 0.05), total lipoproteins (r = –0.512, p &lt; 0.05) and albumins (r = –0.283, p &lt; 0.05), but positively correlated with inorganic phosphorus (r = 0.309, p &lt; 0.05), MCH (r = 0.333, p &lt; 0.05) and MCHC (r = 0.385, p &lt; 0.05). Lipoproteins showed positive correlations with total calcium (r = 0.532, p &lt; 0.05), carotene (r = 0.399, p &lt; 0.05), haematocrit (r = 0.417, p &lt; 0.05), Ca/P ratio (r = 0.294, p &lt; 0.05) and negative correlations with AST (r = –0.302, p &lt; 0.05) and MCHC (r = –0.306, p &lt; 0.05). The identified significant correlations between the principal biomarkers and haematological parameters reflect the integrated regulatory mechanisms of homeostasis. The findings confirm the utility of simultaneous monitoring of beta-hydroxybutyrate, glucose and lipoproteins in blood for assessing metabolic adaptation and the risk of disorders in contemporary dairy cow management systems.

This study systematically analyzed the dynamic changes of milk fat globule membrane (MFGM) proteins in breast milk across different lactation stages. Using data-independent acquisition (DIA)-based quantitative proteomics, a total of 6445 MFGM proteins were identified. The total amount of MFGM proteins showed a significant decline over time. Bioinformatics analysis of differentially expressed proteins revealed that breast milk MFGM not only provides nutritional support but also plays multifunctional roles in regulating infant immunity, neurodevelopment, and gut health. Colostrum, rich in immuno-related proteins such as lactoferrin and IgA, facilitates gut microbiota colonization and establishes the newborn immune barrier. Transitional milk and mature milk progressively shift toward nutritional support and health maintenance, aligned with infant developmental stages. Through comprehensive analytical approaches, this study thoroughly elucidated the dynamic patterns of functional components in breast milk, providing a reference for optimizing the precise nutritional formulation of infant formula.

The objective of the present study is to evaluate the effects of lactation stage, age, somatic cell count (SCC), and daily milk yield on plasmin-plasminogen (PL-PG) system activity and physicochemical milk traits in intensively reared Chios and Frizarta ewes. A total of 52 purebred ewes (26 ewes per breed and farm) were randomly selected and prospectively monitored during the 3rd, 5th, and 6th month post-lambing. Daily milk yield and body condition score (BCS) were recorded, and individual milk samples were collected for the assessment of PL-PG activities using enzymatic assays, SCC, electrical conductivity (EC), refractive index (RI), and pH. Correlation analysis and mixed linear regression models were used for the assessment of the effects. Lactation stage significantly affected PL-PG system traits in both breeds, but in opposite direction; plasmin and plasminogen plus plasmin declined toward late lactation in Chios ewes, whereas it increased in Frizarta ewes. Lower SCC was associated with reduced plasmin system activity in Chios ewes, whereas no effect was observed in Frizarta ewes. The plasminogen-to-plasmin ratio remained stable across lactation, breeds, and SCC classes, indicating coordinated regulation of the system. BCS was positively associated with plasmin activity during late lactation, suggesting a stage-dependent metabolic modulation. EC and pH were closely associated with SCC, while RI mainly reflected compositional variation. Our findings underline that, although the PL-PG system is primarily affected by lactation stage and mammary health status in sheep, there are breed-specific regulatory patterns which should be further investigated.

The aim of this study was to characterize the physiological variation of somatic cell count (SCC) and milk somatic cell subsets in relation to total bacterial count and milk production parameters, in mastitis-free local Greek ewes. To this end, we studied the SCC, daily milk yield and composition, milk somatic cell subset distribution and total bacterial count in the milk of first and second parity Frizarta ewes, at different lactation stages. As there is a total lack of evidence for differential milk somatic cell distribution in local Greek ewes, we chose to study the Frizarta breed, one of the most promising local sheep breeds, extensively reared in Western Greece, highly productive and well adapted to geoclimatic conditions. Partial correlation analysis was performed between SCC and somatic cell subtype populations with milk yield, composition and total bacterial count. Total SCC in Frizarta ewes ranged between 35 and 74×103 cells/ml and was significantly influenced by lactation stage and parity number. Neutrophils and lymphocytes were the most abundant immune cell types followed by mammary epithelial cells and macrophages. A positive association of bacterial count with neutrophils and macrophages and a negative association with lymphocytes were observed. Finally, a negative association between total bacterial count with daily milk yield was detected. Our data forms the basis for understanding how parity and stage of lactation affects different immune and epithelial cell populations in the milk of healthy Frizarta ewes and can be used in future studies investigating the effect of the health status on differential cell count in ewe milk.

Background and aimsThe macronutrient composition of donor human milk (DHM) can vary substantially due to several factors such as maternal age, diet, and lactation duration. However, consistent macronutrient levels in DHM facilitate the administration of the required amounts to preterm infants. The current pooling strategy at most human milk banks combines milk from different batches from a single donor. This study aims to stabilize the macronutrient quality of DHM by pooling milk from different donors by utilizing machine learning prediction and optimisation techniques.MethodsThe current pooling strategy is compared with a new theoretical approach that pools milk batches from up to 5 donors. To predict the crude protein and energy content, we used the following variables: body mass index, the donor’s diet (vegetarian or non-vegetarian), maternal age, full-term or preterm delivery, lactation stage, and volume pumped. These predictions are then used within an optimisation model to create milk pools that minimize the deviations from the target macronutrient levels (1.0 g protein/100 mL and 70 kcal/100 mL).ResultsThe prediction model is based on 2236 created single-donor pools from 480 donors. Random forest regression models provided the most accurate predictions of macronutrient content. The new pooling strategy using multiple donors shows reduced deviations from target values compared to the current single-donor approach (average total absolute deviation 0.402 versus 0.664).ConclusionThis study proves the potential of data-driven methods to improve operational efficiency in human milk banks, and improving the consistency of donor human milk.

The bovine milk microbiome is a complex and dynamic microbial ecosystem, comprising both commensal and pathogenic bacteria. Its composition is shaped by endogenous factors, including udder physiology, lactation stage, and health status, particularly mastitis, as well as by exogenous factors, such as housing conditions, farm infrastructure, milking practices, and post-milking processing. Mastitis not only alters milk quality but also induces persistent dysbiosis that may persist even after clinical recovery, highlighting the need for continuous microbiome monitoring to ensure milk safety. Advances in molecular and metagenomic techniques have enabled the detection of microbial taxa that are difficult to identify using traditional culture-based methods. However, challenges remain due to low microbial biomass, reagent contamination, and the inability to distinguish live from dead bacteria, all of which complicate accurate characterization. Environmental contamination from skin, air, and equipment, along with microbial shifts during transport, storage, pasteurization, and product separation, further modulate microbial communities. While mastitis-related changes in milk microbiota have been extensively studied, the effects of other bovine diseases and systemic health conditions remain largely unexplored, constituting a critical knowledge gap. Understanding the factors that shape milk microbial communities is essential for ensuring dairy product safety, optimizing herd management, and developing microbiome-based innovations in milk production.

We evaluated the milk biomarkers cathelicidin (Cath), haptoglobin (Hp), milk serum amyloid A (M-SAA), N-acetyl-β-D-glucosaminidase (NAGase), lysozyme (LZ), and the half-udder milk somatic cell count (H-SCC), for their potential association with intramammary infections (IMI) in dairy goats across lactation stages. Half-udder milk from 105 goats was collected during early (39 ± 13 days in milk, DIM), mid (136 ± 12 DIM), and late (269 ± 12 DIM) lactation stages and analyzed for bacteriological culture (BC), H-SCC, and potential biomarker reactivity. Predictive performance was evaluated with BC as the outcome, and Dairy Herd Improvement records provided contextual production data. Cath positivity, assessed by western blot, showed the strongest association with positive BC in early lactation and performed well also in mid-lactation. A dynamic H-SCC threshold was reliably correlated with positive BC in early and mid-lactation. Hp positivity, assessed by Western blot, was associated with BC in mid-lactation, while NAGase, assessed by enzymatic assay, showed no consistent association. M-SAA, assessed by ELISA, suffered technical limitations due to a lack of dilution linearity, and LZ, assessed by enzymatic assay, showed no association with BC. Our data suggest stage-dependent associations and support further validation of Cath, Hp, and SCC as potential components of combined diagnostic panels, particularly in early and mid-lactation. However, a semi-quantitative Western blot assessment for Cath and Hp, as well as technical limitations for M-SAA, warrant cautious interpretation and further analytical validation.

Mastitis is a multifactorial disease that affects mammalian health, productivity, and public health. However, it remains considerably understudied in goats compared to cattle in Ethiopia. A cross-sectional study was conducted in selected districts of Northeastern of Amhara region between September 2024 and May 2025. The study aimed to determine the prevalence of mastitis in goats, identify the causative bacteria, and assess the associated risk factors. The detection of mastitis in goats was performed using a physical examination and the California mastitis test. Bacterial isolation and identification were performed according to established standard protocols. Statistical analysis was conducted using Stata 17 software. Among the 397 lactating goats examined, the overall mastitis prevalence at the goat level was 24.74%, comprising 2.52% clinical mastitis (CM) and 22.22% subclinical mastitis (SCM). At the udder halves level, the prevalence was 16.60%, with 1.39% CM and 15.21% SCM. Multivariable logistic regression analysis showed significant associations between goat mastitis and several factors: lactation stage (OR = 1.92; 95% CI: 1.89–6.30), district (OR = 3.47; 95% CI: 1.01–3.65), parity (OR = 2.73; 95% CI: 1.11–6.67), and previous history of mastitis (OR = 13.6; 95% CI: 4.64–40.15), all with p-values less than 0.05. Staphylococcus, E. coli, Enterococcus, and Klebsiella were identified in CM and SCM suspected cases at prevalence of 39.83%, 10.17%, 4.5%, and 2.4%, respectively. This study identified mastitis as significant production challenge-affecting goats in the study area. The findings revealed a considerable disease burden and a wide variety of bacteria, which indicates the importance of routine monitoring and the implementation of effective prevention and control measures.