Journal of Dairy Science

Continuous video offers a dynamic view of dairy-cow behaviour, but its value for precision nutrition depends on alignment with physiological context. We developed a dairy digital-twin framework that fuses identity-associated behavioural records from an established video-analytics layer with body weight, milk production, milk fat, parity and days in milk. The 16-cow analytical cohort was monitored for up to 11 days in one tie-stall barn, yielding 153 cow-days after quality exclusions applied before model fitting. NRC (2001) expected dry matter intake provided a transparent physiological reference compatible with the daily records. In matched leave-one-cow-out analysis, adding video-derived feeding duration to body weight, fat-corrected milk and days in milk reduced RMSE from 2.015 to 1.763 kg DM/day, MAE from 1.267 to 1.159 kg DM/day and MAPE from 4.5% to 4.2%, while R{superscript 2} increased from 0.500 to 0.617. A secondary reduced index achieved RMSE 2.362 kg DM/day and MAPE 5.8% across held-out cows. Cow-level analysis delineated the operating domain: median per-cow MAPE was 4.15%, whereas the sole cow at 15 days in milk had MAPE 28.8%. Two independently recorded veterinary events were temporally concordant with unusual feeding trajectories, providing descriptive biological context. Because the endpoint was NRC-derived, these metrics quantify reference reconstruction rather than accuracy against observed intake. By converting continuous behavioural events into auditable cow-day states, the framework links physical animals to physiologically contextualized digital counterparts and establishes a scalable foundation for operator-focused dairy digital-twin decision support.

This study evaluated the potential of milk mid-infrared (MIR) spectroscopy, combined with routinely available on-farm variables, for predicting serum metabolic, immune, and inflammatory biomarkers in early-lactation cows. Data included 5,936 blood samples from 4,442 cows across 23 Australian dairy herds, with paired milk MIR spectra and serum measurements for up to 14 biomarkers. Prediction models were developed using partial least squares regression and evaluated using nested 10-fold random cross-validation and leave-one-herd-out validation. The results show that while basic herd-test data, including milk fat, protein, and lactose concentration, as well as on-farm variables, including DIM, calving age, breed, and herd could predict serum biomarkers, combining MIR spectra with these on-farm variables produced the best overall performance. In random cross-validation, blood urea nitrogen (BUN) was predicted most accurately (R2 = 0.78), while {beta}-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) showed moderate accuracy (R2 = 0.56 and 0.44, respectively). BUN also showed the strongest external validation performance, with leave-one-herd-out R2 = 0.58 and comparable accuracy for predicting records collected after 70 days in milk (R2 = 0.65). BHB and NEFA had moderate leave-one-herd-out accuracy but did not transfer beyond early lactation. Most other biomarkers showed low or inconsistent external validation performance. Overall, MIR spectroscopy combined with on-farm variables shows promise for routine prediction of BUN, BHB and NEFA, which can be used for monitoring and genetic evaluation of, for example, ketosis and energy deficit. Initial random cross-validation results for glucose, bilirubin and cholesterol were promising, but more data is needed to improve the prediction accuracy and robustness of the predictions. HighlightsO_LIMilk MIR can predict several serum biomarkers in early-lactation dairy cows. C_LIO_LIMIR-predicted blood urea nitrogen shows the greatest accuracy and robustness. C_LIO_LIMIR-predicted {beta}-hydroxybutyrate and nonesterified fatty acids show moderate accuracy. C_LIO_LIMost mineral, hepatic, and inflammatory biomarkers had limited accuracy. C_LIO_LIRoutine MIR phenotyping is most promising for BUN, BHB, and NEFA. C_LI SummaryMilk mid-infrared (MIR) spectroscopy and on-farm variables are evaluated as a high-throughput tool to predict health-related serum biomarkers in early-lactation dairy cows. The data include 5,936 paired blood and milk samples from 4,442 cows across 23 Australian dairy herds and up to 14 serum biomarkers. Prediction models are developed using partial least squares regression with nested random cross-validation and leave-one-herd-out validation. Blood urea nitrogen (BUN) shows the greatest and most transferable prediction accuracy across herds and lactation stages. {beta}-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) are predicted with moderate accuracy, but only during early lactation. Random cross-validation results for glucose and bilirubin are promising, but larger datasets are needed for robust external validation. Most other mineral, hepatic, and inflammatory biomarkers show limited external prediction accuracy. These results indicate that MIR-based routine health phenotyping is most promising for BUN, BHB, and NEFA.

Insect proteins represent a promising and more sustainable alternative to soybean meal in swine nutrition. However, high dietary inclusion levels often result in reduced animal performance, indicating that factors other than crude protein concentration should be considered. This study evaluated the protein quality and degradability of feed-grade defatted black soldier fly (BSF) meal in comparison with a conventional organic protein core for post-weaning piglets. Protein content, amino acid composition, reactive lysine, Maillard reaction markers, buffering capacity, and protein hydrolysability were determined. Our results showed that defatted BSF meal exhibited a protein content and amino acid profile comparable to those of the protein core but contained substantially higher levels of free amino acids. Accounting for free amino acids reduced the estimated lysine damage from 18.4% to 10.4%, highlighting the importance of considering free amino acids when determining reactive lysine. In addition, BSF meal exhibited a higher buffering capacity and lower protein degradability than the protein core. These findings provide new insights into the nutritional limitations of feed-grade BSF meal and suggest that a more accurate assessment of reactive lysine, together with dietary strategies to reduce buffering capacity, may improve its utilization in post-weaning piglet diets.

Livestock welfare models are developed under controlled experimental conditions but deployed across farms, breeds, management systems and label regimes, where reliability remains uncertain. We introduce the Protocol-Driven Transfer Evaluation (PDTE) framework, which treats the adaptation protocol, comprising label mapping, objective design, domain alignment, model selection, calibration and threshold policy, as the experimental variable and evaluates transfer through animal-level external validation with uncertainty quantification. We apply PDTE to a bovine welfare task involving transfer of a facial pain representation from postoperative beef cattle to dairy cows under shifts in breed, sex, production system, clinical etiology, recording environment and label fidelity. Using an author-collected Canadian Holstein and Jersey dataset with an independent eight-cow test cohort, direct source-domain transfer was weak, with sequence AUC 0.418 and cow-level AUC 0.400. PDTE identified two failure modes under weak supervision: threshold collapse, in which adaptation converges to a single prediction class, and calibration-induced collapse, in which score ranking is preserved while decision behavior deteriorates. Across protocols, objective design dominated performance. Class-balanced focal adaptation achieved stable operating behavior (sequence AUC 0.611; cow-level AUC 0.667), while a target-only model attained comparable performance without source initialization (sequence AUC 0.596; paired p = 0.984), indicating that protocol design and operating-point choices contributed more than pretraining under weak-label conditions. Animal-level uncertainty remained substantial, with a bootstrap 95% confidence interval of 0.20 to 1.00, exceeding the transfer effect. These findings show that transferability limits cannot be inferred from source-domain performance alone and require protocol-controlled, uncertainty-aware evaluation in livestock AI.

This study examines the effects of rural out-migration and remittance inflows on food consumption outcomes among rural households in the Tigray region of Ethiopia. Utilizing household survey data collected from 521 rural households across three distinct Weredas (districts) (Tahtay Maichew, Kola Tembien, and Kilte-awlaelo). A Binary Probit model was employed to identify factors influencing migration decisions, while an Endogenous Switching Regression (ESR) model was used to estimate the impact of migration on food consumption outcomes while controlling for selection bias and unobserved heterogeneity. Food security was measured using the Food Consumption Score (FCS) and dietary diversity indicators. The empirical results reveal that severe food insecurity is widespread, with over 60% of all surveyed households falling into the "Poor" food consumption category. Descriptive baseline comparisons show that migration and remittance transfers marginally shift the raw average FCS upward from 23.86 to 25.48. However, this impact is profoundly nuanced: remittances serve as an immediate consumption-smoothing safety net but run parallel to a "labor-lost" constraint that reduces own-production capacities, forcing households to rely increasingly on market purchases for staple foods. The findings reveal that migration creates short-term labor shortages in agricultural production; however, remittance inflows substantially improve household food consumption frequencies, particularly for pulses, vegetables, and other nutrient-rich foods. After accounting for self-selection bias and unobserved traits, the rigorous ESR estimates indicate that migration increases the Food Consumption Score of participating households by an average Treatment Effect on the Treated (ATT) of 10.75 points, shifting them into more secure dietary tiers. Moreover, remittances help households mitigate the adverse effects of drought and other shocks by relaxing liquidity constraints and supporting both food purchases and agricultural investments. The study recommends establishing target food security safety nets for non-remittance households, promoting scale-appropriate labor-saving agricultural technologies, expanding traditional communal labor-sharing innovations, and boosting irrigation and agricultural input support programs to enhance rural food security and livelihood resilience.

Naturally occurring variation in the bovine mannose receptor C-type 1 gene (MRC1) may shape macrophage responses to Mycobacterium (M.) bovis, a key driver of bovine tuberculosis (bTB). We identified four coding region SNPs in MRC1 across Bos taurus (Holstein Friesian, Brown Swiss) and Bos indicus (Boran, Sahiwal) cattle breeds, including a non-synonymous variant, rs380943118 (c.2963G>A; Ser988Asn) in C-type lectin-like domain (CTLD) 6, most prevalent in Sahiwal cattle. Structural modelling suggested that the S988N substitution, which is spatially separated from the monosaccharide binding site of CTLD4, might indirectly affect glycan binding, perhaps through a conformational change in the receptor. Monocyte-derived macrophages upregulated MR expression during differentiation, with heterozygous (G/A) animals showing higher MR expression and increased uptake of GFP-M. bovis BCG, although differences were not statistically significant. Anti-CD206 blockade did not inhibit BCG internalization, either indicating that this specific antibody did not bind to a CTLD involved in ligand binding or that MR is not the sole entry receptor. These results highlight naturally occurring MRC1 polymorphisms that may influence MR structure and macrophage function, providing a foundation for future studies to assess their role in bTB susceptibility.

Abstract The gayal (Bos frontalis) is an endangered semi-domesticated bovine species renowned for its high-quality beef. However, its semi-feral lifestyle, ongoing habitat fragmentation, and extensive genetic introgression from sympatric local cattle have led to dramatic population decline and severe erosion of purebred genetic integrity, posing substantial challenges to its conservation and utilization. To address the urgent demand for rapid, non-invasive, and field-compatible germplasm identification, we developed an integrated artificial intelligence (AI) framework that predicts genomic admixture composition from external morphological images. We constructed a comprehensive dataset comprising 6,245 morphological images and matched genomic sequences from 52 gayals maintained at the Yunnan Provincial Gayal Conservation Farms. Following a preliminary evaluation of nine deep learning models, five were incorporated into a anatomical segment-based multi-modal pipeline, among which Inception_V3 delivered the optimal overall performance. To enhance simultaneous extraction of local fine-grained features and global structural information, we further designed an innovative HybridInceptionViT model by integrating the multi-scale Inception module with the Vision Transformer (ViT) framework. This hybrid model significantly outperformed the baseline Inception_V3, boosting the accuracy of phenotype-derived prediction against genomic admixture estimate from 69.69% to 87.87% (absolute error <15%). This study establishes a practical, low-cost "phenotype-to-genotype" tool for rapid on-site gayal germplasm screening, offering a scalable strategy for the conservation and breeding management of endangered livestock, and holds broad application prospects for agricultural and livestock production systems.

Dairy-free foods must reproduce diverse functions of dairy, from foam stabilization in a latte to acid-gel structure in yogurt and melt-stretch behavior in mozzarella. Public consumer benchmarks rarely compare these categories under a common protocol. Here we analyze data from the NECTAR Taste of the Industry 2026 study, a blinded, randomized, in-person evaluation of commercial dairy-free products and dairy benchmarks. The full study included 2,183 consumers and 112 products across ten categories, with 3,220 product evaluations and 79,027 recorded survey responses, including 35,762 product-linked responses. The ten categories included barista milk, butter, cheddar, cream cheese, creamer, ice cream, fluid milk, mozzarella, sour cream, and Greek style yogurt. Within each category, we compare a dairy benchmark with the dairy-free product selected post hoc as the category leader. Participants rated overall liking, flavor, texture and mouthfeel, appearance, similarity to dairy, and purchase intent on seven-point scales and completed check-all-that-apply questions. In exploratory category-specific equivalence tests using a chosen margin of {+/-}0.05 points, barista milk, creamer, and fluid milk meet this margin. Mozzarella has the largest paired deficit of -1.46 points (unadjusted, p < 0.001), followed by Greek style yogurt and butter; all three remain significant after Holm correction across the ten primary comparisons. Descriptive penalty analysis associates off-flavor, artificial or chemical notes, stale or cardboard notes, bitter taste, and lingering aftertaste with the largest reductions in liking. Together, these results establish the first open sensory benchmark for dairy and dairy-free products, demonstrate that sensory parity is already achievable in several beverage categories, and identify the product categories and sensory attributes that offer the greatest opportunities for future innovation.

The Brown Swiss (BS) cattle breed is one of the major Swiss dairy breeds. Intensive selection and the widespread use of few elite sires in artificial insemination have increased inbreeding and the occurrence of deleterious recessive alleles in the homozygous state. Analyzing life trajectories in large, genotyped cohorts can identify hidden recessive disorders that are difficult to detect using traditional case-control association testing. Long-read DNA sequencing enables precise detection of causal alleles, including structural variants. This study aimed to (1) identify cryptic recessive loci affecting rearing performance in Swiss BS cattle, (2) evaluate their impact on survival, (3) characterize the associated phenotype, (4) identify the causal variant using long-read whole-genome sequencing, and (5) assess its functional impact. Using Homozygous Haplotype Enrichment/Depletion (HHED) mapping, we identified a risk haplotype (BH39) on chromosome 15 spanning from 16,276,819 bp to 16,446,984 bp that was associated with increased juvenile mortality within the first 180 days of life when present in the homozygous state. The BH39 occurred at a frequency of approximately 4.5% in Swiss BS cattle and 5.3% in German and Austrian BS cattle, and homozygous carriers exhibited a significantly reduced first-year survival rate. Five females homozygous for BH39 underwent clinical examination. They all showed recurrent respiratory disease, impaired growth, poor body condition, rough hair coat, and brown-discolored teeth. Pathological examination revealed bronchopneumonia and eosinophilic enteritis. Clinicopathological findings indicated failure to thrive and immunodeficiency. Long-read WGS of two BH39 homozygous calves revealed a private homozygous coding variant that was in high linkage disequilibrium with BH39. The identified structural variant was an insertion of a large transposable element (10.4 kb ERVK[2-1-LTR]) into the third exon of ALKBH8 (NM_001080341.2 c.267_268indel). Full-length RNA sequencing of cerebellum and liver from a homozygous calf revealed that the endogenous retrovirus (ERV) insertion introduces a cryptic transcription termination signal, truncating ALKBH8 mRNA. This study demonstrates that exploring population-scale genomic data and mining thousands of life-history records, followed by veterinary follow-up evaluations and molecular genetic analyses, provides an effective strategy for identifying cryptic recessive disorders that shorten the lifespan of cattle. The findings provide strong evidence that the ERV insertion into the coding sequence of ALKBH8 represents a loss-of-function variant that causes a previously undescribed recessive disorder that results in increased rearing loss. Interpretive summaryWe identified a recessive disorder in Brown Swiss cattle that causes retarded growth, recurrent infections, immunodeficiency, and increased mortality during the first year of life. Using population-scale genomic data, clinical investigations, and long-read sequencing, we linked the disorder to an exonic transposable element insertion disrupting ALKBH8. The identification of the causal variant now enables direct genetic testing and the implementation of genome-based mating strategies to avoid carrier-by-carrier matings and, consequently, prevent the birth of affected homozygous offspring. We demonstrate the utility of integrating large-scale breeding records, veterinary phenotyping, and advanced genomics to identify hidden defects affecting livestock health and productivity.

Micronutrient deficiencies are prevalent in Madagascar, where diets rely heavily on starchy staples and access to animal-source foods is limited. Small dried fish (SDF) are widely available, yet their nutritional value and health risks remain poorly documented. We combined market surveys, taxonomic identification, and micronutrient and heavy metal analyses of nine SDF types collected along National Road 7. The samples encompassed 33 fish families, were dominated by small pelagic species (Clupeidae and Engraulidae), and were appreciated by consumers. A daily portion (5 g for infants; 10 g for young children and women of childbearing age) contributed substantially to Recommended Nutrient Intakes (RNIs). Across samples and groups, SDF were rich (>30% of RNI) in selenium and, for infants and young children, in calcium. All samples were a source of (>15% of RNI), or rich in, phosphorus, whereas iron contributions were more variable but often substantial. Several samples exceeded 100% of RNIs for selenium, calcium, iron, or manganese in infants and young children, and some were also sources of magnesium and, less frequently, zinc. Vitamin A was absent from sun-dried samples but detected in a smoked freshwater type. Heavy metal concentrations varied markedly, and portions of several types led to estimated exposures to inorganic arsenic or cadmium exceeding reference values, whereas freshwater species and some pelagic types showed a more favorable nutrition-risk balance. Overall, SDF are affordable, nutrient-dense foods with strong potential to alleviate micronutrient deficiencies in Madagascar, while highlighting the need for type-specific guidance to balance nutritional benefits and contamination risks.

Background/ObjectivesThe integration of large language model (LLM)-based AI tools into veterinary clinical practice is rapidly increasing; however, no systematically derived taxonomy of veterinary AI query patterns has been established. This study aimed to develop and refine an exploratory taxonomy of veterinary AI query patterns across clinical stages through a structured expert-panel review process. MethodsAn exploratory cross-sectional expert panel study was conducted. 5,372 real-world query logs from a veterinary clinical AI chatbot deployed over eight months were analyzed using AI-assisted inductive coding to derive an initial taxonomy. The taxonomy was refined through literature review and subsequently reviewed by an expert panel of 38 veterinary professionals via structured online survey across five clinical stages. ResultsA taxonomy of 3 categories and 21 subtypes was established: Clinical Support Queries (Types A-H), Evidence-Based Research Queries (Types I-L), and Terminology and Drug Reference Queries (Types M-U). Type B (Differential Reasoning) had the highest overall frequency (57/188 first-choice responses), while Type D (Clinical Decision Support) was dominant immediately post-consultation (55.3%). Veterinary professionals with [&ge;]10 years of experience showed a higher frequency of Type G (Evidence Search) preference than those with <10 years of experience (18 vs. 4), while university-affiliated professionals demonstrated a distinct pattern dominated by Type G. ConclusionsTo our knowledge, no published study has previously established a veterinary-specific, clinical-stage-sensitive exploratory taxonomy of AI query patterns; this study addresses that gap. The findings provide a foundational framework for designing context-aware, stage-adaptive veterinary AI systems and benchmark evaluation tools.

Beef cattle farming plays a crucial role in the livestock-related economies of both Italy and Argentina. Although both countries have grazing systems of meat production, the heterogeneity of those systems leads to different parasitological scenarios regarding epidemiology and the presence of resistance to commonly used anthelmintic drugs. Considering ivermectin (IVM) is the most widely used anthelmintic for treating gastrointestinal nematode (GIN) infections in cattle, the current studies evaluated the efficacy of ivermectin (IVM) given subcutaneously (SC) to both young calves and adult cows in ten (10) commercial cattle farms from Italy (A to E) and Argentina (F to J). The work was complemented with the assessment of the IVM plasma exposure and disposition kinetics both in young and adult animals. While adult cows and young calves were included in the study performed in Italy (Campania region), only calves aged 8-14 months old were selected to perform the efficacy trials in Argentina (central area of the Buenos Aires province). Fifteen (15) calves/cows naturally infected with GINs were treated with IVM (0.2 mg/kg) in each of the Farms. The therapeutic response (efficacy) was determined at 14 days after treatment by the faecal egg count reduction test. Six (6) adult cows and eight (8) young calves treated with IVM were randomly selected to perform the pharmacokinetic (PK) study with blood samples being taken 2 h and 21 days post-treatment. Drug concentrations were measured by HPLC. Similar IVM PK trends were obtained for both adult and young cattle. The IVM systemic exposure (expressed as AUC) obtained for adult cattle (380{+/-}158 ng.d/mL) was similar to that observed in calves group (313{+/-}85.5 ng.d/mL). No statistical differences between animals from both ages were observed for the most representative PK parameters (P>0.05). Surprisingly, while in Argentina IVM resistance was present in all the farms evaluated (90% CI = 0%-95%), in Italy a fully susceptible nematode population was presented in three farms (90% CI = 96%-100%) and only a very low level of IVM resistance was detected in the rest of the farms (90% CI = 92%-98%). Whereas Cooperia spp. and Haemonchus spp. were identified as the principal genera exhibiting resistance to IVM in Argentina, Cooperia spp., Ostertagia spp., and Oesophagostomum spp. were reported to display low levels of resistance under the Italian field scenario. In conclusion, IVM can be safely and effectively used in both young and adult cattle with similar disposition kinetic patterns. While its therapeutic response is failing under the conditions investigated in the Argentinian farms, its efficacy remains notably high in the Italian region under study. However, the use of IVM, as well any other active antiparasitic principle, should always be preceded by a diagnostic assessment of the nematode populations resistance status.

The exponential increase in the number of genotyped animals, combined with the availability of high-density SNP chips has introduced computational challenges for routine genomic evaluations, particularly during the construction of the genomic relationship matrix. Although higher-density SNP panels can facilitate the identification of causal mutations, their use substantially increases computational requirements without a proportional gain in genomic prediction performance. To optimize computational efficiency while maintaining accuracy of genomic predictions, this study compared five SNP selection strategies (i.e., random sampling, random sampling with inclusion of informative SNPs, linkage disequilibrium (LD)-based pruning, a Shannon entropy-based machine learning approach, and [[EQUATION]]-based prioritization) to develop reduced-density panels for Nellore cattle. Using high-density (HD) genotype data comprising 437,650 SNPs from 304,782 animals (after quality control) as reference, three reduced-density panels (25K, 45K, and 65K SNPs) panels were tested across five traits (i.e., Age at first calving, Stayability, Weaning weight, Yearling weight, Muscling) with diverse genetic architectures. Genomic estimated breeding values (GEBVs) derived from these reduced panels were compared to those obtained from the HD reference panel using Pearsons correlations, under both genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) methods. In the GBLUP model, prediction accuracy generally improved with increased marker density. Random selection with and without the informative SNPs consistently yielded the highest accuracies, whereas the [[EQUATION]]-based approach showed the lowest agreement with the HD reference across all densities. In contrast, ssGBLUP demonstrated strong robustness to marker reduction, producing uniformly high correlations {approx}1.00) across all SNP densities and selection strategies. These findings indicate that optimized low-density SNP panels maintain prediction accuracy comparable to HD panels, offering a cost-effective tool for large-scale genomic evaluations.

ProblemComplement, a system of over 30 interacting proteins, functions as a critical immune mediator at mucosal surfaces including the intestine, airway, and nasal mucosae, where it orchestrates complement-dependent cytotoxicity (CDC), complement-dependent phagocytosis (CDP), and inflammatory responses. While complement components have been detected at low levels in genital tract fluids, including cervical mucus, the physiologic dynamics of complement in the female reproductive tract remain poorly characterized. Notably, systematic quantification of complement component levels across the menstrual cycle has not been conducted, limiting our understanding of how hormonal fluctuations may influence complement-mediated protection at the vaginal mucosa. Method of studyTen healthy women of reproductive age were recruited to provide paired samples of cervical mucus (CM) and serum (S) during each phase of the menstrual cycle: follicular, ovulatory, and luteal. Samples were analyzed using bead-based multiplex assays to quantify 13 primary complement components. ResultsAll 13 complement proteins tested were detectable in CM and S; C3b/iC3b was the predominant complement component in CM followed by C4 and C3. In contrast, C4 was the dominant component in S followed by C1q and C3. There were significantly higher levels of C2 in CM during the follicular phase of the menstrual cycle vs. the ovulatory phase (1.15{+/-}0.80 vs 0.24{+/-}0.22{micro}g/mL), C4b (0.56{+/-}0.35 vs 0.22{+/-}0.36 {micro}g/mL), C5a (1.45{+/-}1.09 vs 0.38{+/-}0.48 {micro}g/mL) In contrast, no differences were found in serum complement levels were during the menstrual cycle. Complement concentrations were on average 308-fold (median= 84) lower in CM than in S, except for C3b/iC3b which was only 5 to 7.5-fold lower in CM, and C2 which was higher in CM at the luteal and follicular phases. Midcycle cervical mucus was capable of inducing complement-mediated hemolysis at about 1/3 the potency of serum. ConclusionCervical mucus contains detectable and functional levels of complement proteins. These normative values can provide a foundation for future studies on immune mechanisms in the FRT.

Background Indias maternal nutrition profile is undergoing a dual-direction shift, with persistent undernutrition coexisting alongside rising overweight and micronutrient deficiencies. Despite national efforts through Integrated Child Development Services (ICDS) and the National Health Mission (NHM), maternal dietary diversity remains suboptimal in India. Frontline health workers (FLWs) play a central role in delivering nutrition counselling; however, gaps remain between knowledge and its translation into practice, highlighting the need to strengthen training, applied competencies, and health system support within primary care settings. Objective To assess knowledge, attitudes, and practices (KAP) regarding maternal nutrition counselling among FLWs and to explore contextual factors influencing counselling delivery. Methods A sequential explanatory mixed-methods study was conducted in Udupi, Karnataka, India. In phase one, 46 FLWs- Accredited Social Health Activists (ASHA), Community Health Officers (CHO), and Primary Health Care Officers (PHCO) completed a validated Knowledge, Attitudes, and Practices (KAP) questionnaire. Data were analysed using descriptive statistics, Kruskal-Wallis test, Spearman correlation, and exploratory multiple linear regression. In phase two, one focus group discussion with 21 participants was conducted and analysed using reflexive thematic analysis. Results FLWs demonstrated moderate KAP scores (37.50 {+/-} 5.09), with lower scores observed in dietary diversity knowledge and counselling practices. CHOs and PHCOs had significantly higher knowledge (p < 0.001) and practice scores (p = 0.002) compared to ASHAs, while attitudes were similar across cadres. Knowledge was positively associated with practice ({rho} = 0.389, p = 0.008). Exploratory regression indicated that cadre and knowledge were associated with practice, while attitude was not statistically significant. Qualitative findings suggested that counselling was largely protocol-based and constrained by workload, limited counselling tools, economic barriers, and cultural food practices. Conclusion Despite positive attitudes towards maternal nutrition counselling, frontline health workers demonstrated gaps in knowledge and counselling practices. Mixed-methods findings suggest that counselling delivery is shaped by both provider competencies and health-system constraints, highlighting the need for implementation-focused strategies to strengthen maternal nutrition counselling in routine antenatal care.

Metabolites from Plantago lanceolata (plantain) biomass have been linked with biological nitrification inhibition (BNI) in soil. After grazing, leaf metabolite chemistry is altered via digestion, and a suite of secondary metabolites are then delivered onto soil via dung and urine. The purpose of this study was to establish if urine from sheep grazed on plantain had BNI activity when added to pasture soil, and to identify the metabolite profile(s) that most likely contribute to the BNI effects observed. Groups of sheep (n=5) were grazed on one of nine different plantain cultivars in autumn and spring with analysis of leaf material, urine, soil incubation and BNI bioassay data used to identify potential metabolite candidates implicated with BNI. The urinary nitrogen and metabolite composition of sheep fed plantain varied significantly between cultivars and season. After 28 days of incubation, all soil microcosms treated with plantain-derived urine had up to 35% less nitrate than comparative ryegrass urine controls in both seasons, except one in autumn. The key phytochemistry associated with lower soil nitrate concentrations was phenylethanoid and iridoid glycosides resulting in a higher output of glucuronidated, methylated and sulfated secondary metabolites in the urine. Among 19 secondary metabolites identified in the urine, hydroxytyrosol-related metabolites as well as catechol glucuronide, 2-methoxyphenyl sulfate and guaiacol-{beta}-D-glucuronide appear to be the most likely target compounds with respect to the BNI effects observed. Variation in metabolites from different plantain cultivars affected the ratio of metabolite derivatives in urine, which ultimately affected soil nitrification rates. Cultivar phytochemistry is therefore an important consideration with respect to BNI under urine patches. HighlightsO_LISheep grazing different plantain cultivars had different urine compositions C_LIO_LIUrines elicited biological nitrification inhibition (BNI) in soil and in vitro C_LIO_LIDifferent BNI response was related to differential expression of urine metabolites C_LIO_LIKey urine metabolites associated with BNI are derived from glycosidic compounds C_LI

The maned wolf (Chrysocyon brachyurus) is a near-threatened canid species that suffers from gastrointestinal (GI) disease under human care. While the cause remains poorly understood, recent studies report that altered gut microbiota is linked to GI disease in the domestic dog. The goal of this study was to describe the relationship between gut bacteria and environmental factors, GI health, short chain fatty acid (SCFA) peaks, and genetic relatedness in maned wolves. Fresh fecal samples were collected twice from wolves (first collection n = 29; second collection n = 25) housed in six facilities in the United States. Fecal alpha-1 proteinase inhibitor (FA1PI), a biomarker for GI health in canids, and SCFA peaks were quantified. Information on diet, housing group and history of GI disease or inflammation was provided by the zoological facility for each wolf. We characterized gut microbiota using 16S rRNA gene amplicon sequencing with qPCR abundance corrections. We found that dietary fiber gross energy (GE), protein GE, and number of daily produce items influenced gut microbiota. Additionally, there was a negative relationship between dietary fiber GE and Fusobacterium sp. abundance, corroborating previous findings linking fiber to altered gut microbiome composition in canids. Lastly, fiber GE was negatively correlated with FA1PI, connecting fiber to GI health in the maned wolf. Findings from this study suggest that increasing dietary fiber GE changes the gut microbiome and may improve GI health in the maned wolf, highlighting important management decisions that can be considered to maintain a healthy zoo-managed maned wolf population. IMPORTANCEFindings from this study are important because gastrointestinal disease is a common health concern for maned wolves under human care, and the causes are not well understood. The current study found that diet, especially the amount of fiber gross energy, can affect gut bacteria and may support better gastrointestinal health. Diet alterations could be a practical tool for zoos to support management of gastrointestinal health issues in maned wolves. These findings also show the importance of carefully managing diets for a near-threatened species, since better gastrointestinal health may improve overall health and well-being and support reproduction. More research is needed to determine the best amount and type of fiber, but our results provide foundational information for improving care and supporting healthy zoo-managed maned wolf populations.

Objectives: Estimate the prevalence and sociodemographic correlates of adolescent-reported food insecurity experiences from 2019-2021. Methods: Repeat cross-sectional data were collected in November-December 2019, 2020, and 2021 from adolescents aged 10-17 years living in the ten Canadian provinces (n = 11,057). The prevalence of ten items and five food insecurity subconstructs based on the 10-item Child Food Insecurity Experiences Scale was estimated. Weighted multinomial logistic regression assessed associations between sociodemographic characteristics and food insecurity experiences as a four-level (no, few, several, or many experiences) variable. Results: Across 2019-2021 among adolescents, the prevalence of worrying about food scarcity ranged between 18.4%-22.5%, worrying about parental/guardian ability to get food ranged between 22.8%-26.9%, and not being able to get the food they wanted ranged between 23.5%-26.1%. Close to or above one in four adolescents affirmed the uncertainty (range: 26.9%-29.9%) and compromised diet quality or preferences (range: 23.5%-26.1%) subconstructs. In 2021, adolescents identifying as Black had a higher relative risk ratio of few food insecurity experiences (adjusted relative risk ratio (ARRR): 2.04 [95% CI: 1.20, 3.47], p-value: <0.01) and adolescents identifying as Indigenous had a higher relative risk ratio of several food insecurity experiences (2.38 [1.10, 5.15], p-value 0.03) compared to adolescents identifying as White. The relative risk ratio of having few, several, or many food insecurity experiences also differed by age, sex-at-birth, perceived income adequacy, and region. Conclusion: The type and number of experiences reported underscores the value of directly measuring food insecurity. Interventions to mitigate food insecurity's adverse consequences are warranted.

Cattle harbor diverse bacterial communities across the gastrointestinal, respiratory, reproductive, mammary and other anatomical systems, but body-wide microbial biogeography remains poorly defined. To address this knowledge gap, we conducted a meta-analysis of publicly available bovine 16S rRNA gene amplicon sequencing data from 5,637 samples from 47 studies across six geographic regions and 27 anatomical sample types. Bacterial community structure differed significantly among sample types (PERMANOVA, R2 = 0.245, P = 0.0001), indicating spatial organization of bacterial communities across the bovine body, although study-level effects also contributed substantially to community variation. Communities were generally more similar within than between anatomical systems. Bacterial richness, diversity, taxonomic composition, and indicator taxa varied among sample types, with gastrointestinal, mammary-associated, ocular, and hoof microbiota exhibiting greater diversity than microbiota from liver, joint, and several reproductive samples. Distinct bacterial communities characterized the gastrointestinal, respiratory, reproductive, and mammary systems, as well as other anatomical sites. Despite these differences, several bacterial taxa were shared across multiple anatomical niches, particularly among male and female reproductive sites and among mammary-associated niches. This study provides a comprehensive body-wide characterization of bacterial biogeography in cattle and establishes a baseline for future studies of bovine microbial ecology and host-microbiome interactions.

Abstract Objective: This study aimed to assess the magnitude of undernutrition and associated factors among pregnant women attending public health facilities in the Goba district, Bale zone, Oromia Region, Ethiopia, 2022. Design: Institution-based, cross-sectional study design was used. Setting: The study was conducted in selected public health facilities from May to June 2022. Participants: The study population consisted of pregnant women who lived for at least 6 months in the study area and who attended antenatal care follow-up at selected public health facilities during the study period. Pregnant women who lived for less than six months in the study area and those who were critically ill were excluded from the study. Results: 487 respondents participated in this study with a 100% response rate. More than half (50.7%) of pregnant mothers were undernourished. The significant factors associated with maternal undernutrition during pregnancy in this study were mothers with no formal education (AOR = 5.050; 95% CI: 1.470- 17.346), a history of illness during pregnancy (AOR = 2.089; 95% CI: 1.246-3.504), and eating frequency of meals less than or equal to three times per day (AOR = 3.292; 95% CI: 1.040- 10.42). Poor nutritional knowledge (AOR = 5.588; 95% CI: 2.921-10.689), poor household (HH) wealth status (AOR = 4.774; 95% CI: 2.216- 10.285), and mothers who had >= 4 pregnancies were included (AOR = 0.852; 95% CI: 342-0.989). Conclusion: The magnitude of Undernutrition among pregnant women was 50.7%. Significant associations with Undernutrition were found in mothers with no formal education, poor dietary knowledge, a meal frequency of three or fewer times per day, a history of illness during pregnancy, lower and medium household wealth status, and those who had experienced four or more pregnancies while attending antenatal care (ANC) services at public health facilities.