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Feed costs and carcass yields affect the profitability and sustainability of sheep production. Therefore, it is crucial to select animals with a higher feed efficiency and high‐quality meat production. This study focuses on the impact of dietary and genetic factors on production traits such as feed efficiency, carcass quality, and meat quality. Diets promote optimal sheep growth and development and provide sufficient protein can lead to higher‐quality meat. However, establishing an optimized production system requires careful consideration and balance of dietary parameters. This includes ensuring adequate protein intake and feeding diets with higher intestinal absorption rates to enhance nutrient absorption in the gut. The study identifies specific genes, such as Callipyge, Calpastatin, and Myostatin, and the presence of causal mutations in these genes, as factors influencing animal growth rates, feed efficiency, and meat fatty acid profiles. Additionally, variants of other reported genes, including PIGY, UCP1, MEF2B, TNNC2, FABP4, SCD, FASN, ADCY8, ME1, CA1, GLIS1, IL1RAPL1, SOX5, SOX6, and IGF1, show potential as markers for sheep selection. A meta‐analysis of reported heritability estimates reveals that residual feed intake (0.27 ± 0.07), hot carcass weight (0.26 ± 0.05), dressing percentage (0.23 ± 0.05), and intramuscular fat content (0.45 ± 0.04) are moderately to highly heritable traits. This suggests that these traits are less influenced by environmental factors and could be improved through genetic selection. Additionally, positive genetic correlations exist between body weight and hot carcass weight (0.91 ± 0.06), dressing percentage (0.35 ± 0.15), and shear force (0.27 ± 0.24), indicating that selecting for higher body weight could lead to favorable changes in carcass quality, and meat quality. [ABSTRACT FROM AUTHOR]

Rotavirus group A (RVA) is the most important cause of acute diarrhoea and severe dehydration in young mammals. Infection in livestock is associated with significant mortality and economic losses and, together with wildlife reservoirs, acts as a potential source of zoonotic transmission. Therefore, molecular surveillance of circulating RVA strains in animal species is necessary to assess the risks posed to humans and their livestock. An RVA molecular epidemiological surveillance study on clinically diseased livestock species revealed high prevalence in cattle and pigs (31 per cent and 18 per cent, respectively) with significant phylogenetic diversity including a novel and divergent ovine artiodactyl DS-1-like constellation G10-P[15]-I2-R2-C2-M2-A11-N2-T6-E2-H3. An RVA gene reassortment occurred in an RVA asymptomatic pig and identified as a G5-P[13] strain, and a non-structural protein (NSP)2 gene had intergenomically reassorted with a human RVA strain (reverse zoonosis) and possessed a novel NSP4 enterotoxin E9 which may relate to the asymptomatic RVA infection. Analysis of a novel sheep G10-P[15] strain viral protein 4 gene imparts a putative homologous intergenic and interspecies recombination event, subsequently creating the new P[15] divergent lineage. While surveillance across a wider range of wildlife and exotic species identified generally negative or low prevalence, a novel RVA interspecies transmission in a non-indigenous pudu deer (zoo origin) with the constellation of G6-P[11]12-R2-C2-M2-A3-N2-T6-E2-H3 was detected at a viral load of 11.1 log10 copies/gram. The detection of novel emerging strains, interspecies reassortment, interspecies infection, and recombination of RVA circulating in animal livestock and wildlife reservoirs is of paramount importance to the RVA epidemiology and evolution for the One Health approach and post-human vaccine introduction era where highly virulent animal RVA genotypes have the potential to be zoonotically transmitted. [ABSTRACT FROM AUTHOR]

A study was performed to determine if targeted metabolic profiling of cattle sera could be used to establish a predictive tool for identifying hormone misuse in cattle. Metabolites were assayed in heifers (n = 5) treated with nortestosterone decanoate (0.85 mg/kg body weight), untreated heifers (n = 5), steers (n = 5) treated with oestradiol benzoate (0.15 mg/kg body weight) and untreated steers (n = 5). Treatments were administered on days 0, 14, and 28 throughout a 42 day study period. Two support vector machines (SVMs) were trained, respectively, from heifer and steer data to identify hormone-treated animals. Performance of both SVM classifiers were evaluated by sensitivity and specificity of treatment prediction. The SVM trained on steer data achieved 97.33% sensitivity and 93.85% specificity while the one on heifer data achieved 94.67% sensitivity and 87.69% specificity. Solutions of SVM classifiers were further exploited to determine those days when classification accuracy of the SVM was most reliable. For heifers and steers, days 17-35 were determined to be the most selective. In summary, bioinformatics applied to targeted metabolic profiles generated from standard clinical chemistry analyses, has yielded an accurate, inexpensive, high-through-put test for predicting steroid abuse in cattle.

As global pig health diseases, porcine respiratory disease complex (PRDC) and porcine circovirus‐associated disease (PCVAD) generate substantial economic losses despite pigs been vaccinated against the primary causative virus, highlighting the importance of understanding virome interactions and specifically co‐factor infections. Established primary endemic pathogens for PRDC include porcine circovirus 2 (PCV2), porcine reproductive and respiratory syndrome virus (PRRSv) and swine influenza virus (SIV), and PCV2 aetiology in interaction with other co‐infecting viruses can result in PCVAD. Porcine parvovirus (PPV) 1 is a well‐characterized virus with an available vaccine preventing reproductive failure in sows. However, whilst novel PPV 2 to 7 viruses have been identified since 2001, their viral pathogenic potential in clinical and subclinical disease remains to be determined. Therefore, this study has sought to develop a better understanding of their potential role as associated co‐infections in PRDC and PCVAD by examining archival samples for the presence of PCV2 and the novel parvoviruses PPV2‐4 from clinically diseased pigs across production age stages. Epidemiologically, the novel PPV2 was found to be the most prevalent within the fattener age group with PPV2‐4 statistically associated with pig respiratory disease and enteric ulcers. Additionally, statistical modelling by latent class analysis (LCA) on veterinary pathology scored pigs found a clustering co‐factor association between PPV2 and PCV2, suggesting the novel PPV may be involved in PRDC and PCVAD. Phylogenetic analysis of novel PPVs revealed the PPV2 capsid evolution to be diverged from the original strains with a low nucleotide homology of 88%–96% between two distinct clades. These findings determine that novel PPV 2–4 viruses are statistically associated as co‐infectors in a diseased pig population, and significantly detected PPV2 clustering co‐infection frequency with PCV2 in PRDC and PCVAD diseased pigs through LCA analysis. [ABSTRACT FROM AUTHOR]

A fully integrated system that combines extended gate field-effect transistor (EGFET)-based potentiometric biosensors and electrochemical impedance spectroscopy (EIS)-based biosensors has been demonstrated. This integrated configuration enables the sequential measurement of the same immunological binding event on the same sensing surface and consequently sheds light on the fundamental origins of sensing signals produced by FET and EIS biosensors, as well as the correlation between the two. Detection of both the bovine serum albumin (BSA)/anti-BSA model system in buffer solution and bovine parainfluenza antibodies in complex blood plasma samples was demonstrated using the integrated biosensors. Comparison of the EGFET and EIS sensor responses reveals similar dynamic ranges, while equivalent circuit modeling of the EIS response shows that the commonly reported total impedance change (DZtotal) is dominated by the change in charge transfer resistance (Rct) rather than surface capacitance (Csurface). Using electrochemical kinetics and the Butler-Volmer equation, we unveil that the surface potential and charge transfer resistance, measured by potentiometric and impedance biosensors, respectively, are, in fact, intrinsically linked. This observation suggests that there is no significant gain in using the FET/EIS integrated system and leads to the demonstration that low-cost EGFET biosensors are sufficient as a detection tool to resolve the charge information of biomolecules for practical sensing applications. [ABSTRACT FROM AUTHOR]