Journal of Dairy Science

Milk urea concentration (MUC) is an indicator of dietary protein utilization and nitrogen use efficiency in dairy cows. We performed genome-wide association studies (GWAS) on MUC in early, mid, and late lactation in the Holstein (HOL) and Brown Swiss (BSW) dairy cattle breeds using imputed sequence variants. We identified 11 and 17 independent quantitative trait loci (QTL) for MUC across the three lactation stages in BSW and HOL, respectively. While many of these QTL have previously been reported for MUC and other dairy traits, our study provides evidence that some QTL exert lactation-stage specific effects. Our findings suggest that variants at the DGAT1 locus on BTA14 have pleiotropic effects on MUC and other dairy traits. This QTL showed an early lactation-specific association with MUC but impacted milk and fat yield across the entire lactation. We fine-mapped two QTL for MUC in early and mid-lactation in BSW on BTA9 (lead SNP: 9:21392941, Pcorrected = 1.1E-17) and BTA28 (lead SNP: 28:6518357; Pcorrected = 3E-11). We identified lncRNA ENSBTAG00000058688 and IBTK as positional and functional candidate genes for the BTA9 QTL, and KCNK1 as positional and functional candidate gene that harbors a highly significant missense variant for the BTA28 QTL. In conclusion, our results shed light on the genetic architecture of MUC and highlighted QTL harboring potential functional variants underpinning milk urea variation within and across breeds.

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.

Antimicrobial use (AMU) in agricultural systems is frequently linked to antimicrobial resistance (AMR). Yet, the scale at which AMU reshapes host-associated resistomes remains unclear. This gap arises, in part, from the scarcity of farm-level AMU data from commercial production systems. Here, we combine detailed AMU records from commercial dairy farms with metagenomic analyses of bovine fecal resistomes from calves, lactating cows, sick cows, and cull cows. At a broad level, resistome profiles were similar regardless of farm AMU. Resistance associated with historically common antibiotics, such as tetracyclines, was frequent on low- and high-AMU farms, indicating that some resistance classes are ubiquitous in dairy systems regardless of current AMU. In contrast, resistance to other drug classes varied systematically with AMU. Higher AMU was associated with increased resistance to aminoglycosides, {beta}-lactams, and macrolides, drug classes that are critical for treating mastitis and bovine respiratory disease. Resistance gene richness and diversity were highest in calves, underscoring the importance of accounting for host traits alongside AMU when evaluating resistance patterns. Together, these findings underscore the need for detailed, farm-level AMU data to understand how management practices shape AMR and to inform strategies for sustaining the effectiveness of existing antimicrobials in agricultural and public-health contexts.

Evidence suggests that increased local temperatures are associated with higher prevalence of antimicrobial resistance (AMR) in environmental bacteria. This study investigates the association between local climate and the proportion of antimicrobial-resistant Escherichia coli isolated from 2,766 farm environment samples from 53 English dairy farms. To do this, a non-linear Bayesian model that specifically accounts for decreased test sensitivity at low E. coli abundance was developed and used to estimate the proportion of isolates resistant to four antimicrobials (amoxicillin, cephalexin, streptomycin and tetracycline) from colony count data. Mean 7-day temperature and relative humidity at the farm location was modelled using a generalised additive model formulation. A higher proportion of E. coli isolates were resistant to cephalexin and streptomycin in samples collected from adult cow collecting yards, than heifer housing sheds. In contrast, a greater proportion of E. coli isolates from heifer housing sheds were resistant to amoxicillin and tetracycline. Evidence that local temperature is associated with an increase in the proportion of E. coli isolates resistant to streptomycin (20{degrees}C increase associated with a 5.0-fold increase; 95% CI: 1.03-33.0) and tetracycline (2.6-fold increase; 90% CI: 1.1-5.2) was observed. Additionally, relative humidity was associated with an increase in the proportion of isolates resistant to amoxicillin streptomycin and tetracycline. The influence of weather on the proportion of antimicrobial-resistant E. coli varied between samples collected from adult animals in collecting yards and heifers in housing sheds. These findings highlight the importance of considering weather conditions, sample characterises and seasonality when designing on-farm AMR surveillance systems. ImportanceUnderstanding how environmental conditions are associated with variability in AMR prevalence is critical for developing robust livestock AMR surveillance and anticipating the potential effects of climate change. The non-linear Bayesian modelling approach developed here adjusts for E. coli abundance associated variability in test sensitivity, enabling the influence of risk factors associated with the proportion of antimicrobial-resistant E. coli within samples to be more accurately estimated. Applying this approach to 2,766 faecal samples from 53 dairy farms in Southwest England indicated that the proportion of antimicrobial-resistant E. coli generally increased under warmer and wetter conditions. These findings suggest that environmental conditions can influence the prevalence of AMR E. coli in dairy farm environments and demonstrate the importance of accounting for weather related variability in livestock AMR surveillance. Adjusting for these associations in livestock AMR surveillance could improve the accuracy of modelling AMR trends and strengthen the assessment of climate-associated AMR risks.

Pregnancy modulates the endometrial immune responses to establish maternal immune tolerance, and nuclear factor kappa B (NF-{kappa}B) subunits and I{kappa}B family are involved in the maternal innate and adaptive immune responses. It, nevertheless, is unclear if early pregnancy regulates the expression of NF-{kappa}B subunits and inhibitor of NF-{kappa}B (I{kappa}B) family in the ovine endometrium. In this study, ovine endometria were sampled at day 16 of the estrous cycle (N16), and at days 13, 16, and 25 of pregnancy (P13, P16, and P25), and mRNA and protein expression of NF-{kappa}B subunits and I{kappa}B family was analyzed by RT-qPCR, western blot, and immunohistochemistry. The results revealed that the expression of all NF-{kappa}B subunits was decreased at P25 compared with N16 both in mRNA and protein expression, but the expression of B cell leukemia-3, I{kappa}B, I{kappa}B kinase {gamma}, and I{kappa}B{delta} was increased at P25 compared with N16 both in mRNA and protein expression. I{kappa}B{beta}, however, was downregulated during early pregnancy, and the expression of I{kappa}B{varepsilon} and I{kappa}B{zeta} was decreased at P13 and P16 compared with N16 and P25 both in mRNA and protein expression. In summary, early pregnancy changed the expression of NF-{kappa}B subunits and I{kappa}B family in the ovine endometrium both in mRNA and protein expression, which may be essential for maternal immune tolerance and embryo implantation.

A tightly regulated inflammatory response occurs during and following parturition; however, excessive or prolonged inflammation negatively affects herd health and productivity. The gut microbiota plays an important role in host immunity and metabolism and undergoes substantial changes during the transition period. However, the relationship between systemic inflammation, measured by serum acute-phase proteins, and gut microbial dynamics during early lactation remains poorly understood. We investigated fecal microbiota dynamics in relation to systemic inflammation in early postpartum dairy cows. Fecal and blood samples were collected from 71 Holstein cows on days 1 and 3 in milk (DIM). The V3-V4 region of the 16S rRNA gene was sequenced and microbial diversity, differential abundance, and microbial interaction networks were evaluated. Inflammatory status, defined by fibrinogen, haptoglobin, and their combined classification, was associated with significant alterations in fecal microbial composition during the immediate postpartum period, independent of body condition score, parity, DIM, and DNA extraction parameters. Differential abundance analyses revealed extensive taxonomic restructuring, while network analyses identified increased modularity, altered keystone taxa distribution, and greater compartmentalization of microbial interactions in animals with elevated inflammatory markers. Several taxa were consistently associated with inflammatory status across analytical approaches. Notably, Ruminococcaceae UCG-002 and Dielma were associated with inflammatory states, whereas Xylanibacter, Marvinbryantia, Akkermansia, and Oscillibacter were associated with non-inflammatory status. This study identifies an association between systemic inflammation and fecal microbiota composition in early transition dairy cows, providing a foundation for future microbiome-based biomarkers of inflammatory status. IMPORTANCESubclinical systemic inflammation during early postpartum can negatively affect dairy cow health and productivity, yet current monitoring relies on repeated blood sampling and transient inflammatory biomarkers. For the first time association of systemic inflammation, assessed using fibrinogen, haptoglobin, and their combined classification, with alterations in fecal microbial composition, microbial interaction networks, and keystone taxa distribution during the early postpartum period was established. Several bacterial taxa were consistently associated with either elevated or normal inflammatory states across differential abundance, network, and odds ratio analyses. Many of these taxa remain poorly characterized in dairy cattle, highlighting the need for future mechanistic studies. This study demonstrates that systemic inflammation during early postpartum is associated with measurable alterations in the fecal microbiota. This work provides a foundation for developing microbiome-based biomarkers for detecting and monitoring subclinical systemic inflammation in dairy cattle.

Cross-national alignment of branded food databases is essential for international nutritional epidemiology but lacks standardized methods. Existing approaches - including food ontologies, domain-specific fine-tuned language models, and manual expert mapping - require either substantial infrastructure or do not scale to thousands of items. We propose an unsupervised evaluation framework for large language model (LLM)-based food database alignment that requires no ground-truth labels. Using the Japan Branded Food Database (JBFD; 9,519 items, 71 mid-level categories) and USDA FoodData Central (448 categories) as a case study, we introduce two complementary metrics: weighted centroid distance (nutritional proximity between matched category pairs) and dominant category share (structural consistency of category-level assignments). We then conducted a systematic ablation study across eight input conditions (A-H), varying combinations of product name, nutrient profile, and semantic category label. Results showed that nutrient-only inputs yielded poor structural consistency despite low centroid distances, while semantic category labels achieved the highest dominant category share (89.3%) but introduced circularity due to their LLM-derived origin. Among circularity-free conditions, product name combined with minimal nutrient information (energy, protein, salt; condition E) achieved the best balance of centroid distance (0.471) and dominant category share (65.8%). Model comparison across Claude Haiku, Sonnet, and Opus confirmed that NO_MATCH rates were consistent across model sizes (12-14%), suggesting that prompt design contributes more to alignment quality than model scale. These findings provide practical guidance for input design in LLM-based food database alignment without ground-truth annotation.Sonnet 4.6

Fresh produce encounters pathogens at various stages of production and supply, with the harvesting process serving as one of these stages. To evaluate contamination associated with harvesting, we systematically swabbed zone 1 harvester surfaces and quantified Bacteroidales as a fecal biomarker using quantitative polymerase chain reaction (qPCR). Baseline contamination was dominated by non-detects, with occasional low-level detections (<25 copies/cm2) near the assay limit of detection (LoD). Detection occurred more frequently post-harvest (overall [~]4% pre-harvest and 10% post-harvest), while microbial loads remained low, indicating that harvesting primarily affected the likelihood of low-level contamination rather than increasing contamination abundance. Additionally, we developed and field-deployed a portable loop- mediated isothermal amplification (LAMP) assay for rapid harvester hygiene assessment and benchmarked its field performance against qPCR. Together, these results support a practical molecular tool for monitoring fecal contamination and informing cleaning and sanitization decisions.

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

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.

Anthelmintic resistance in cyathostomins is escalating worldwide, threatening equine health and highlighting the need for sustainable, ecology based parasite control strategies. Chicory (Cichorium intybus, Puna II) has emerged as a promising antiparasitic forage, yet its broader effects on the equine holobiont, parasites, microbiota, and host physiology remain poorly understood. We conducted a 32 day longitudinal grazing trial in young horses to assess how chicory affects parasitological outcomes, gut microbial ecology, nemabiome composition, behaviour, and host physiological and immune responses. Twenty-six naturally infected Anglo-Arabian horses were monitored weekly, with 13 grazing a chicory-based sward and 13 grazing a permanent pasture. Clinical parameters, body weight, and serum biochemistry remained stable across treatments, indicating that chicory was well tolerated. Immune profiles showed limited variation, although IL 10 increased in chicory fed horses, suggesting subtle immune modulation. Behavioural observations revealed no signs of discomfort and indicated slightly enhanced social interactions in the chicory group. Chicory grazing produced a marked reduction in cyathostomin egg excretion, accompanied by species specific shifts in nemabiome composition. Several cyathostomin taxa, including Cylicocyclus ashworthi, C. leptostomus, and C. nassatus, declined in chicory fed horses, whereas certain Cylicostephanus spp increased, indicating differential sensitivity rather than uniform suppression. Concomitantly, chicory induced profound ecological changes in the gut microbiota, including reduced alpha diversity, increased beta dispersion, and destabilised individual microbial trajectories. Several bacterial lineages, particularly Oscillospiraceae, Clostridiaceae, Lachnospiraceae, and Bacteroidales, were differentially enriched, reflecting a functional reorganisation of the intestinal ecosystem. Together, these findings demonstrate that chicory reduces parasite fitness, reshapes nemabiome composition, and alters gut microbial ecology while maintaining host physiological stability. Chicory thus emerges as a promising ecological tool for parasite control, capable of modulating the equine holobiont in ways that complement and potentially reduce reliance on conventional anthelmintic strategies. However, because its effects on gut microbial ecology remain uncertain, and may include shifts resembling dysbiosis, future studies are needed to monitor microbial dynamics more closely and clarify the long term ecological consequences of chicory grazing.

PurposeBacterial vaginosis (BV) is associated with disruption of the vaginal microbiome and extracellular matrix (ECM) remodeling, yet the contribution of host proteases to this process remains unclear. This study investigated whether expression and activity of cathepsins K, L, S, and V differ by BV diagnosis and community state type (CST). We hypothesized that BV and BV associated CSTs would exhibit increased expression and activity of collagen and elastin-degrading cathepsins. MethodsVaginal fluid samples were collected and classified by BV diagnosis and CST. Cathepsin expression was evaluated by Western blotting to distinguish inactive and active enzyme forms. Proteolytic activity was assessed using multiplex cathepsin zymography. Statistical analyses compared cathepsin expression and activity across diagnoses and CSTs. Principal component analysis and linear regression were performed to assess associations between cathepsin activity, microbial diversity, and CST. ResultsProcathepsin K expression was significantly increased in BV-positive and CST IV samples, while total cathepsin L expression was significantly elevated in samples with Nugent-intermediate scores. Cathepsins S and V showed variation in inactive and active forms in Nugent-intermediate and CST III samples. In contrast, total cathepsin activity, including cathepsins K and V, did not significantly differ across BV diagnoses or CSTs. Overall, cathepsin activity varied between individuals rather than by clinical classification. ConclusionsCathepsin expression and maturation state differ by microbiome composition, suggesting that the vaginal microbiome may regulate post-translational processing of cathepsins. As a result, cathepsin activity appears to be regulated at the individual level rather than strictly by BV diagnosis or CST. These findings link vaginal microbiome composition to ECM remodeling and potential adverse reproductive outcomes.

Assigning glycemic index (GI) values to food composition databases is a critical bottleneck in nutritional epidemiology. We developed an in-context learning approach using large language models (LLMs), in which a structured knowledge system (termed a skill) loads GI reference databases ([~]11,000 entries), expert decision rules, and error-correction heuristics into the models context window ([~]300,000 tokens). The LLM performs GI assignments without scripted logic, functioning simultaneously as a semantic matching engine, numerical reasoning system, and expert curator. We validated this approach in two experiments. In Validation Study 1, the skill predicted the expert-curated US National GI Database (9,428 foods) using only European reference data, achieving within {+/-}10 agreement of 73.7% without manual review - compared with 31.3% retention of previously published cosine-similarity approach. In Validation Study 2, the skill was augmented with US GIDB and applied to 1,157 European food descriptions classified using the EFSA FoodEx2 system, achieving ICC = 0.79 with the expert (weighted {kappa} = 0.65; triplicate ICC = 0.88). We then applied the skill prospectively to extend US dietary GI and GL surveillance to two additional NHANES cycles (2019-2023), identifying a continued decline in energy-adjusted glycemic load. Reproducibility was assessed through triplicate runs (temperature = 0, pinned model version). The skill architecture is described in sufficient detail to inform future applications of in-context learning for nutritional database construction. STATEMENT OF SIGNIFICANCEThis paper introduces a fundamentally new approach to glycemic index (GI) database construction. Rather than using programmatic text-matching algorithms followed by extensive manual curation, we demonstrate that a large language model (LLM), when loaded with the complete GI reference literature and formalized expert decision rules, can perform one-shot GI assignments at accuracy levels comparable to human expert ratings (ICC = 0.79 with expert, weighted {kappa} = 0.65 for GI category agreement). The approach is validated across two independent food databases spanning US and European food supplies. The method reduces the time required to assign GI values to a new national food database from months of expert labor to hours of computation, while maintaining reproducibility through a structured, versionable skill architecture. This has immediate practical implications for enabling GI-based dietary surveillance and epidemiologic research in countries that currently lack GI databases or need to update existing databases.

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.

Background: Iron deficiency (ID) affects up to 40% of pregnant women in the third trimester, even in highly resourced and iron-supplemented populations, with adverse consequences for maternal health and long-term offspring development. Psychological stress may compromise iron status through hypothalamic-pituitary-adrenocortical (HPA) axis dysregulation and inflammation, but no study has directly examined cortisol in relation to iron status across human pregnancy. Objective: This longitudinal study examined associations between HPA function and maternal iron status across pregnancy and tested whether IL-6 and CRP mediated the relationship between cortisol and ferritin across gestation. Methods: One hundred sixty-eight pregnant Black women with Medicaid insurance completed up to four laboratory assessments across pregnancy. Salivary cortisol was measured before and in response to the Trier Social Stress Test, yielding basal and reactive cortisol indices. Serum ferritin, IL-6, and CRP were collected at each visit. Trimester-specific regression models examined cortisol reactivity in relation to ferritin; linear mixed-effects models with moderated mediation tested whether basal cortisol predicted ferritin via inflammation. Results: Higher cortisol reactivity was associated with lower ferritin specifically in the third trimester (std. {beta} = -0.197, p = .004). Higher basal cortisol predicted a steeper IL-6 rise across gestation (p = .002), and IL-6 was positively associated with ferritin (b = 0.236, p = .006), consistent with inflammatory iron sequestration. The indirect effect of basal cortisol on ferritin via IL-6 was statistically significant, and higher basal cortisol was negatively associated with cortisol reactivity in the third trimester. No pathway was observed through CRP. Conclusion: Greater cortisol reactivity predicted lower third-trimester ferritin, a pattern that suggests cumulative iron depletion, atypically sustained HPA reactivity in late pregnancy, or both. To our knowledge, this is the first prospective study linking cortisol reactivity to iron status across human pregnancy, identifying maternal stress physiology as a novel target for understanding and addressing gestational iron deficiency.

To evaluate the international interoperability of food composition databases, we assessed the compatibility of seven national food composition tables with USDA FoodData Central (FDC) using the LLM-based matching method reported previously (Nakagawa and Yamamoto, 2026). Databases from four English-speaking countries (Canada, United Kingdom, Australia, and New Zealand), South Korea, and Japan were compared with 8,158 USDA FDC entries (SR Legacy and Foundation Foods, excluding Survey/FNDDS). Match rates varied by country (62.0-89.7%) and food category. After excluding six USDA categories unsuitable for cross-national comparison, 45.2% of the remaining 6,290 entries were not matched by any country. Canada showed the highest concordance, reflecting shared North American food supply. Japan and South Korea showed similar low coverage for vegetables and spices. These findings suggest that while USDA FDC represents a practical foundation for a globally comprehensive food composition database given its breadth, systematic incorporation of country-specific foods and classification schemes will be necessary to achieve true international interoperability.

Background The placenta serves a critical role in nutrient uptake and waste elimination for the developing fetus. The placenta is also responsible for the uptake and/or exchange of xenobiotics, including medications, between the maternal and fetal bloodstreams. An estimated 40-80% of women take medications or drugs during pregnancy for a variety of conditions. Very little is understood about fetal drug and nutrient exposure during pregnancy and how it may change over the course of fetal development. Objective This study aimed to characterize the abundance of transport proteins in placental tissue, which are important in modulating fetal nutrient and drug exposure, over the duration of pregnancy. Mass spectrometry-based global proteomic analysis revealed trends in the expression of thousands of proteins throughout gestation. Focusing on the membrane-associated proteome enabled an increased emphasis on the solute carrier and ATP-binding cassette families of transporter proteins that are critical for nutrient and xenobiotic transport across the maternal-fetal barrier. Study Design Using data-independent acquisition proteomics, relative abundance of proteins in placental tissue samples was profiled across all three trimesters of pregnancy (Trimester 1 = 16, Trimester 2 = 9, and Term = 9). Membrane fractions were generated to enrich membrane-associated proteins for proteomic analysis. Placental samples were grouped into randomized batches for membrane fraction generation and mass spectrometry analysis. Proteomic search results from each batch were imported into the R programming environment from Skyline, concatenated, and normalized as one data set for downstream analysis. Results A total of 6,331 proteins were detected across all samples with 4,210 proteins identified in every sample. Pathway analysis revealed that as gestational age increases, membrane-associated proteins involved in more complex metabolic pathways increase in relative abundance while those involved in extracellular remodeling events and simple organic ion transport tended to decrease. A total of 139 solute carrier and ATP-binding cassette transport proteins were identified in all samples, and 80 were identified in every sample. In general, membrane-associated proteins, including solute carrier and ATP-binding cassette transport proteins, were significantly enriched in placental tissue collected during early gestation compared to term placental tissue. Conclusion This study presents a comprehensive profiling of membrane-associated proteomic changes during gestation and identifies significant gestational age associated abundance changes at the protein level in several transport protein families. The application of data-independent acquisition global proteomic techniques enabled in-depth analysis of thousands of proteomic changes across pregnancy in a single experiment. These data provide critical information to support future studies into the understanding of fetal exposure to xenobiotics and nutrients circulating in the maternal bloodstream.

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.

Dietary protein restriction challenges the allocation of amino acids to growth and other physiological functions and therefore requires coordinated metabolic adaptation. Domestic pigs provide an informative system in which to study such responses, because nitrogen retention directly affects lean growth and can be quantified accurately under controlled feeding and housing conditions. Under reduced-protein diets, pigs differ in how effectively they retain nitrogen, and this variation has a genetic basis, making them well suited to investigate the molecular regulation of nitrogen use efficiency (NUE). Here, we characterise differential gene expression and enriched pathways in liver and skeletal muscle of more than 80 pigs with two divergent NUE phenotypes (high and low) maintained under the same protein-reduced, ad libitum dietary conditions. The two NUE phenotypes were clearly distinct at the transcriptomic level, with 177 differentially expressed genes in the liver and 133 in the muscle. In the liver, differential expression and enrichment analyses indicate reduced amino acid catabolism, lower inflammatory and detoxification activity, and a metabolic state that favours lipid processing and insulin-related regulation over the use of amino acids as energy sources. In skeletal muscle, they point to reduced lipid uptake, lower reliance on amino acid oxidation, and a greater emphasis on protein synthesis, translational regulation, mitochondrial energy metabolism, and growth-related processes. These gene-level patterns were supported and extended by pathway and gene-set enrichment analyses. Together, the results suggest that high and low-NUE pigs differ through coordinated, tissue-specific molecular adaptations. Overall, variation in NUE appears to reflect coordinated, tissue-specific differences in how nutrients are allocated between energy use, storage, and lean tissue growth.

Milk is a challenging matrix to extract sufficient microbial DNA from for downstream analysis. This study assessed fourteen DNA extraction protocols for their DNA outputs. An adaptation of the QIAGEN DNeasy PowerSoil kit, which increased initial sample volume and maintained all volume of lysate following bead beating proved most effective.