Search Results (757)

As a dual-purpose (meat and fat) coarse-wool sheep breed in Xinjiang, the Pishan Red sheep exhibits year-round estrus and excellent reproductive performance. The aim of this study was to systematically estimate the genetic parameters of growth traits in Pishan Red sheep at each stage from 0 to 12 months of age, and to provide a scientific basis for optimizing early selection indices for this breed. Year of birth, type of birth, and sex were included as fixed effects, while maternal genetic effects and individual additive genetic effects were treated as random effects. A multi-trait animal model was constructed using DMU 6.0 software to analyze the genetic parameters. The results showed that for growth traits at 0 months of age, heritability ranged from 0.09 to 0.64, genetic correlations from –0.03 to 0.84, and phenotypic correlations from 8.2 × 10⁻³ to 0.32. Among these, the direct heritability of body weight was 0.18, and the maternal heritability was 0.21, while cannon circumference was identified as a high-heritability trait. At 2 months of age, heritability ranged from 0.04 to 0.69, genetic correlations from −0.78 to 0.96, and phenotypic correlations from 0.036 to 0.44. Body weight, body length, and cannon circumference were high-heritability traits. At 6 months of age, heritability ranged from 0.04 to 0.71, genetic correlations from −0.32 to 0.70, and phenotypic correlations from −0.13 to 0.54. Body weight was a medium-heritability trait, while chest width and cannon circumference were high-heritability traits. At 12 months of age, heritability ranged from 0.07 to 0.48, genetic correlations from −0.04 to 0.87, and phenotypic correlations from 0.28 to 0.72. Body weight was a medium-heritability trait, whereas body height, body length, cannon circumference, and heart girth were high-heritability traits. Both body weight and cannon circumference exhibited high heritability throughout the 0–12 month period and can therefore serve as key selection indices for early breeding in this breed. The findings of this study provide essential local baseline data for the genetic improvement, breeding program design, and genetic evaluation of Pishan Red sheep. Full article

Continuous and objective monitoring of livestock behavior plays a key role in precision farming, animal welfare assessment, and reproductive management. This study proposes a non-invasive framework for sheep behavior and reproductive activity monitoring that integrates wearable actigraphy, machine learning, and a cloud-based data processing architecture. Tri-axial accelerometer data were collected at 30 Hz using collar-mounted ActiGraph sensors under real farming conditions. Raw acceleration signals were processed without temporal aggregation, preserving full temporal resolution that includes axis-specific acceleration, vector magnitude, and delta magnitude features. Several supervised learning models were evaluated for behavior classification, including BLSTM, LSTM, CNN–BLSTM, Random Forest, and Support Vector Machine, targeting behaviors such as standing, walking, grazing, lying, flehmen, and mating. The results indicate that both deep learning and classical machine learning approaches achieve high classification performance, with Random Forest obtaining an overall accuracy of 0.82, while deep sequential models effectively capture temporal patterns and behavioral transitions. Furthermore, a scalable cloud architecture is introduced to automate data ingestion, preprocessing, inference, storage in InfluxDB, and visualization through an interactive web application. The proposed framework supports continuous monitoring and offers practical tools for precision livestock management. Full article

This study evaluated the effects of forage source on the longissimus dorsi muscle metabolomic profiles of Dumont and Mongolian sheep. A total of 24 male sheep, including Dumont sheep (DS) and Mongolian sheep (MS), were assigned to a 2 × 2 factorial design with two breeds and two forage sources: alfalfa hay (AH) and corn straw (CS). The four groups were DSAH, DSCS, MSAH, and MSCS, with six lambs per group. Untargeted metabolomics was used to characterize muscle metabolic profiles after a 90-day feeding period. Stable metabolomic separations were mainly observed between forage treatments within each breed, namely DSAH vs. DSCS and MSAH vs. MSCS, whereas breed comparisons under the same forage condition showed limited separation and weaker model stability. OPLS-DA combined with univariate analysis identified 101 and 100 differential metabolites in the DSAH vs. DSCS and MSAH vs. MSCS comparisons, respectively. Pathway enrichment analysis indicated that forage-associated metabolic differences were mainly related to amino acid metabolism, lipid metabolism, and energy metabolism. AH feeding was associated with broader changes in muscle metabolic pathways than CS feeding, particularly in pathways related to nutrient utilization and lipid-related metabolism. These findings suggest that the forage source is closely associated with muscle metabolic variation in fattening lambs, while possible breed-related differences in metabolic responsiveness require further validation. Full article

Meat condemnation at slaughterhouses reflects the rate of animal diseases, economic losses, and potential public health risks. In northern Nigeria, however, longitudinal and model-based assessments of condemnation patterns using routine abattoir data remain limited. This study aimed to quantify species- and disease-specific meat condemnation rates, examine short-term temporal variation during the study period, and identify predictors of condemnation at the Sokoto State Main Abattoir. A retrospective panel analysis of aggregated abattoir data with repeated temporal observations was conducted using abattoir meat inspection records from January to June 2025. Condemnation rates per 1000 animals slaughtered were calculated by species, disease category, and month. Short-term temporal variation within the study period and associated factors were evaluated using negative binomial regression with an offset for slaughter volume. These rates reflect the number of condemned organs recorded relative to the number of animals slaughtered, as multiple organs may be condemned from a single animal during post-mortem inspection. Model adequacy was assessed through dispersion diagnostics, multicollinearity checks, residual analyses, sensitivity analyses, and predictive calibration using observed versus model-predicted rates. A total of 317,685 animals were slaughtered during the study period, with 1628 condemnation cases, corresponding to an overall condemnation rate of 5.12 per 1000 animals slaughtered (95% CI: 4.88–5.38). Condemnation rates varied markedly by species, with camels exhibiting the highest monthly rates (140.05 per 1000 animals slaughtered), followed by cattle (51.80 per 1000 animals slaughtered), sheep (40.62 per 1000 animals slaughtered), and goats (22.19 per 1000 animals slaughtered) during the study period. Disease-specific analyses identified contagious bovine pleuropneumonia, fascioliasis, hydatidosis, and tuberculosis-like lesions as major contributors to condemnation. Temporal patterns demonstrated non-linear monthly variation, with elevated rates in mid-study months. The final negative binomial model showed good calibration, with close agreement between observed and predicted rates across species and diseases. Meat condemnation at the Sokoto State abattoir demonstrates substantial heterogeneity by species, disease, and time. Priority conditions such as contagious bovine pleuropneumonia (CBPP), fascioliasis, hydatidosis, and tuberculosis-like lesions warrant targeted control efforts. These findings reinforce the value of routinely collected abattoir data as a practical and robust component of animal health surveillance in resource-limited settings. Full article

Despite growing interest in human–animal interactions in livestock, limited information is available on whether differences in routine human contact in the home flock have lasting effects on sheep behaviour and physiological stress responses after transfer to a new herd. This study evaluated behavioural and cortisol related responses in 191 Polish Mountain sheep from five farms that were seasonally combined into one traditional Carpathian grazing flock. Before grazing, farms were classified according to selected characteristics of farmer contact with sheep, including, time spent with the flock, handling style, consistency of interaction, and farmer behaviour towards the animals. Sheep behavioural responses during milking were assessed by the shepherd and an independent observer using a five point scale in two observation periods and serum cortisol concentration was measured in ten sheep per farm. Behavioural scores were analysed using a cumulative link mixed model, with evaluator and season as fixed effects and farm and sheep identity nested within the farm as random effects. Descriptive mean behavioural scores ranged from 2.18 to 4.38, and mean cortisol concentrations ranged from 2.49 to 4.86. Farm level patterns suggested that sheep from farms with more favourable human contact tended to show calmer behaviour during milking and lower cortisol concentrations. These findings indicate that routine human contact in the home flock may be associated with later behavioural and physiological responses under communal grazing conditions. Full article

While most existing studies addressing greenwashing emphasize governmental regulation, they often overlook the role of public participation. This study examines how managers’ risk preferences affect enterprise decision-making under public scrutiny. In this study, an agent-based simulation model incorporating enterprises, media, and consumers is established on the basis of signaling theory and the wolf-sheep model. The conclusions are as follows: (1) Both positive and negative public opinion can curb greenwashing behavior in building material enterprises, but negative public opinion intensity is more effective in this context. (2) Regardless of whether building material enterprises operate in positive or negative public opinion scenarios, constraining managers’ risk preferences consistently serves as an effective internal mechanism for curbing greenwashing behavior. (3) The effectiveness of constraint managers’ risk preferences in suppressing greenwashing behavior is influenced by the external public opinion scenario, with its inhibitory effect being more pronounced under negative public opinion scenarios. This study incorporates public opinion as a key external factor and integrates dynamic managers’ risk preferences into a behavioral simulation framework. It expands the theoretical understanding of greenwashing decision-making mechanisms and offers practical implications for regulatory enforcement and enterprise governance. Full article

Toxoplasmosis, caused by the obligate intracellular parasite T. gondii, is one of the most prevalent parasitic infections worldwide, affecting approximately one-third of the global population. Despite decades of intensive research, no effective human vaccine exists. The only commercially available vaccine, Toxovax, is restricted to veterinary use in sheep and is unsuitable for human application due to safety concerns. Beyond summarizing the literature, this review offers a critical appraisal of why translation has stalled and where the field should focus next. Live-attenuated vaccines remain the most immunogenic in preclinical models but face significant translational barriers for human use. Key antigenic targets include surface antigens (SAG), dense granule antigens (GRA), rhoptry proteins (ROP), and microneme proteins (MIC). Protective immunity relies critically on Th1-type immune responses characterized by interferon-gamma production. Major obstacles include the parasite’s complex life cycle, strain diversity, and difficulty achieving sterile immunity. Subunit and mRNA-based platforms offer more favorable safety profiles and established clinical precedents, representing the most viable pathway toward a human vaccine. Recent advances in CRISPR/Cas9 gene editing and emerging mRNA vaccine platforms offer promising new directions. This review advances the field in three ways. (i) It prioritizes mRNA and adjuvanted subunit formulations targeting multistage conserved antigens as the most realistic near-term human candidates. (ii) It identifies the limited targeting of bradyzoite-stage biology as a principal, under-addressed gap. (iii) It argues that future development must be differentiated into three complementary One Health goals—prevention of congenital disease in humans, reduction in tissue-cyst burden in livestock, and interruption of environmental transmission by vaccinating cats. In practice, a veterinary-first deployment strategy is the most immediate and impactful pathway to reducing the human and zoonotic burden of toxoplasmosis. Full article

Somatic cell count (SCC) in milk is widely used as an indicator of intramammary infections in dairy sheep and is routinely monitored by the dairy industry as a marker of milk quality. This study aimed to evaluate the effect of SCC levels on milk production, composition, colour, coagulation properties, and cheese-making ability in Manchega dairy sheep. A total of 752 individual milk samples were analysed. To normalise SCC distribution, the somatic cell score (SCS) was calculated and samples were classified into SCS classes. Increasing SCS significantly reduced daily milk yield and lactose content, increased milk pH, and decreased lightness (L*). Higher SCS was also associated with impaired coagulation properties, including longer rennet clotting time (RCT) and curd firming rate (k₂₀), as well as reduced curd firmness (A₃₀, A₆₀). Similar effects were observed for modelled coagulation parameters, with delayed RCTeq and reduced kCF and CFp. Regarding cheese-making ability, SCS significantly affected curd humidity and protein recovery, whereas no significant effects were detected for dry curd yield or fat recovery. Overall, elevated somatic cell counts were associated with a reduction in the technological quality of Manchega sheep milk, particularly affecting coagulation behaviour and curd characteristics. These results underline the importance of controlling SCC levels in dairy sheep systems for both udder health monitoring and maintaining milk suitability for cheese-making. Full article

Background/Objectives: Rebamipide is a gastroprotective agent with poor aqueous solubility and rapid gastrointestinal clearance, leading to reduced therapeutic efficiency. This study aimed to enhance the solubility, mucoadhesion, and sustained oral delivery of Rebamipide through the development of a deep eutectic mixture (DEM)-based bioadhesive controlled-release granule formulation. Methods: In silico hydrogen-bonding interactions between Rebamipide, malonic acid, and urea were analyzed using CCDC tools. A thermodynamically stable DEM (1:3:1) was prepared and incorporated into bioadhesive granules using chitosan and HPMC. Physicochemical characterization was conducted using FTIR, DSC, TGA, and PXRD. Solubility, in vitro dissolution, ex vivo mucoadhesion (sheep gastric mucosa), and in vivo gastric retention (BaSO₄-loaded granules in rats) were evaluated. Results: The optimized DEM significantly enhanced Rebamipide solubility (10.08 mg/mL vs. 0.045 mg/mL). Solid-state analyses confirmed hydrogen-bond formation and reduced crystallinity. DEM granules exhibited sustained drug release over 24 h (99.7 ± 0.8%) with improved dissolution efficiency compared to the marketed tablet (Mucosta®, 100 mg; T₅₀%: 5.03 h vs. 0.82 h). Kinetic modeling indicated non-Fickian anomalous transport (n = 0.47). The bioadhesive force of DEM granules (0.29 ± 0.02 N) was significantly higher than that of the pure drug and physical mixture. In vivo radiographic studies confirmed prolonged gastric retention. Conclusions: The DEM-based bioadhesive granule system effectively improves solubility, dissolution rate, mucoadhesion, and gastric retention of Rebamipide. This approach represents a promising platform for once-daily gastroretentive oral delivery, pending further pharmacokinetic evaluation. Full article

Peste des Petits Ruminants (PPR) is a highly contagious viral disease of small ruminants and remains a major threat to food security and rural livelihoods across Africa, the Middle East, and Asia. In the Mediterranean, uneven outbreak reporting and intense spatial clustering hinder the identification of regions where environmental and anthropogenic conditions favor disease occurrence. This study applied an interpretable machine-learning ecological niche modeling framework to characterize PPR spatial suitability in North Africa. A merged outbreak dataset (n = 744) was compiled from the Food and Agriculture Organization (FAO) EMPRES-i and the World Animal Health Information System (WAHIS) databases for 2005–2026. Outbreak locations were linked to environmental and anthropogenic predictors, spatially thinned, and paired with randomly sampled pseudo-absences at a 1:1 ratio. After correlation-based screening and Boruta feature selection, four classifiers were compared under five-fold spatial block cross-validation: a generalized linear model (GLM), a support vector machine (SVM), Random Forest (RF), and extreme gradient boosting (XGBoost). All models showed good discriminatory performance. Random Forest (RF) and extreme gradient boosting (XGBoost) yielded the highest area under the receiver operating characteristic curve value (AUC = 0.94). Random Forest achieved the highest specificity, XGBoost achieved the highest sensitivity, and the support vector machine showed the most even sensitivity–specificity tradeoff among the machine-learning classifiers. Sheep density, mean diurnal temperature range, temperature seasonality, and human population density were consistently the dominant drivers. Predicted PPR suitability based on reported outbreaks was concentrated along the North African coastal belt and low across most arid inland regions. These findings suggest that passive surveillance is likely to be most informative in coastal production systems where host density, environmental suitability, and reporting opportunity overlap. At the same time, areas of lower reported-outbreak suitability should not be interpreted as disease-free and may require complementary active surveillance approaches. Full article

Livestock manure resources are abundant in the upper Yellow River basin on the eastern Tibetan Plateau, where rapeseed (Brassica napus L.) is grown under cold, short-season alpine conditions. To identify a suitable organic fertilizer substitution proportion, a two-year randomized complete block field experiment was conducted on Chestnut soil (Kastanozem) to compare mineral fertilization with 25%, 50%, 75%, and 100% replacement of mineral N by an organic fertilizer produced from composted cattle and sheep manure under equal total N, P, and K inputs. Grain yield was highest at 50% substitution, increasing by about 14% relative to mineral fertilization (p < 0.05), whereas 100% substitution slightly reduced yield. Increasing manure inputs enlarged soil organic carbon and total nutrient pools, but these increases were not accompanied by proportional increases in plant-available nutrients. Compared with mineral fertilization, 50% substitution increased available N, P, and K by about 18%, 34%, and 10%, respectively, and also increased the proportions of total N, P, and K present in available forms. Activities of the measured extracellular enzymes were generally 12–72% higher under 50% substitution than under mineral fertilization. A piecewise structural equation model indicated that yield improvement was associated mainly with greater nutrient uptake and recovery efficiency. Overall, moderate substitution best balanced nutrient accumulation, nutrient availability, efficiency, and productivity under the tested alpine conditions. Full article

Small ruminant lentiviruses are longstanding viral infections affecting sheep and goats worldwide, resulting in reduced efficiency and economic losses. In Portugal, updated epidemiological data are scarce. The aim of this study was to assess the seroprevalence and risk factors for SRLV in Portugal. The study was conducted in Portuguese flocks of ovine and caprine species. Flocks were randomly chosen, and producers were invited to answer a questionnaire. The indirect ELISA test, ID Screen^® MVV/CAEV Indirect, was made to detect infection. We collected samples from 59 flocks, of which 55.93% (CI 95%: 43.26–68.60%) had at least one positive animal. Of these flocks, 1302 individual samples presented a seroprevalence of 32.95% (CI 95%: 30.08–35.81%). Regarding the risk factor analysis, the multivariable mixed-effects logistic regression model at the individual level identified variables with increased odds of SRLV seropositivity. Caprine species (OR = 2.47; CI 95%: 1.01–6.03), non-autochthonous breed (OR = 2.95; CI 95%: 1.23–7.06), animals older than two years old (OR = 1.95; CI 95%: 1.29–2.94), dairy aptitude (OR = 8.15; CI 95%: 2.53–26.24), unknown serostatus of newly acquired animals (OR = 9.41; CI 95%: 2.93–30.23) and participation in livestock competitions (OR = 4.25; CI 95%: 1.42–12.73) were significantly associated with increased odds of seropositivity. SRLV has been confirmed in both regions of Portugal studied, with a significant regional disparity that is likely attributable to differences in management practices. The identification of risk factors specific to each production system is crucial for the development and implementation of voluntary control programs. Full article

As natural and anthropogenic hazards intensify, improving the performance of reinforced-concrete (RC) infrastructure within a resilience-oriented assessment framework while limiting environmental burdens has become an important challenge for sustainable construction. In this context, this study proposes an OpenBIM-based digital-twin methodology to compare two equivalent RC structural scenarios: a conventional solution and an alternative incorporating unprocessed waste sheep wool fibres into cementitious materials. Using an IFC-based model of a high-rise building, the workflow enables automated extraction of structural quantities and a consistent building-scale assessment of material use, environmental impacts, and circularity indicators. Laboratory evidence from the literature is translated into element-level performance criteria through a dual-factor selection strategy based on key structural properties and secondary indicators related to cracking and post-cracking behaviour. The results show that the wool-fibre alternative enables the incorporation of a relevant amount of waste wool into the structure while causing only negligible increases in embodied energy and carbon emissions relative to the conventional RC scenario. The selected formulations also maintain or improve the governing mechanical and serviceability-related factors, indicating potential benefits in crack control, toughness, and repairability. Overall, this methodology provides a reproducible pathway for linking laboratory-scale material innovation with building-scale digital assessment, supporting more sustainable and performance-aware decision-making in RC construction. Full article

Canestrato di Castel del Monte (CCM) is a traditional sheep cheese from the Abruzzo region of Italy, strongly linked to local pastoral practices and characterized by high cultural and commercial value. Ensuring its authenticity is therefore essential to protect both producers and consumers. In this study, Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with chemometric modelling was investigated for the classification of traditional sheep cheeses. A dataset of approximately 2000 spectra obtained from Canestrato di Castel del Monte (CCM), low-ripening CCM, and Pecorino Toscano was analyzed using different modelling strategies. Partial Least Squares Discriminant Analysis (PLS-DA) and Sequential Preprocessing through Orthogonalization combined with Linear Discriminant Analysis (SPORT-LDA) were first applied to simultaneously separate the three categories. Subsequently, a class-modelling approach based on Soft Independent Modelling of Class Analogy (SIMCA) was used to authenticate CCM and low-ripening cheeses. The discriminant models achieved excellent classification performance: accuracies close to 100% for CCM and low-ripening CCM and around 95% for Pecorino Toscano. SIMCA provided reliable rejection of non-target samples, although with lower sensitivity compared to discriminant approaches. Overall, the results demonstrate that ATR-FTIR spectroscopy coupled with appropriate chemometric modelling represents a powerful strategy for the authentication and classification of traditional sheep cheeses. Full article

Large animal models are a critical component of the preclinical evaluation of mechanical cardiac implants, enabling assessment of safety and performance under physiological conditions that cannot be adequately reproduced in vitro. Choosing a suitable animal model is important for both scientifically valid and ethically responsible preclinical evaluation. However, interspecies differences between animal models and humans pose significant challenges for relevant translation of preclinical findings to clinical outcomes. This narrative review provides a comprehensive overview of commonly used large animal models (sheep, goats, pigs, and calves) for the preclinical assessment of mechanical cardiac implants, including prosthetic heart valves, ventricular assist devices, and total artificial hearts. We summarize key anatomical and physiological characteristics that influence device implantation, chronic follow-up, and translational value. Emphasis is placed on three critical outcome domains for preclinical evaluation of mechanical cardiac implants: calcification, thrombogenicity, and hemodynamic performance. Species- and age-dependent differences in calcification are reviewed, identifying juvenile sheep as a worst-case model for early manifestation and detection of graft mineralization. Interspecies differences in coagulation biology are examined, showing attenuated platelet responses in sheep and closer similarity between porcine and human platelet behavior, supporting pigs as the preferred thrombogenicity model. Hemodynamic evaluation strategies in acute and chronic large-animal studies are discussed, with particular emphasis on circulatory demands influenced by somatic growth and on device adaptability under varying loading conditions. Overall, this review provides practical, outcome-driven guidance for large animal model selection and experimental design in mechanical cardiac implant research, while identifying key limitations, knowledge gaps, and the need for standardized reporting to improve the translational reliability of preclinical studies. Based on the findings presented in this review, we conclude that there is no single animal model capable of evaluating all relevant aspects of a device. Instead, different animal models provide distinct advantages depending on the outcomes of interest. Full article