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This paper examines the relationship between theatre and podcasts in Italy, to provide an overview of the different configurations of audio drama in relation to the characteristics of the new medium. It focuses on the period between 2020 and the present, when podcasting began to be widely used as an ‘autonomous’ and ‘independent’ medium. The examples presented refer to different productions, intending to analyze various forms and highlight those that deviate from the radio tradition to align themselves with the logic of the podcast and contemporary storytelling.

Over recent decades, there was a substantial evolution in the productive management of dairy animals worldwide with a consequent boost in individual milk yield. This evolution positioned the milk production as the central metabolic priority around which all other physiological functions are coordinated and partially minimised. This shift underscores the crucial role of effectively managing stressful phases in intensive dairy farming systems, also highlighting the resilience exhibited by the animals. Indeed, monitoring the nutritional and health status becomes paramount, aiming for an early detection of (sub)clinical health impairments. Given the mammary gland’s centrality in high-yielding dairy breeds, it’s unsurprising that the milk matrix provides insights about udder itself but also systemic metabolic function. The emerging field of milk phenomics explores links between milk components and animal health, holding great promise for studying dairy cow resilience. The use of infrared spectroscopy on milk to predict indicators and complex traits at the herd level is a promising approach. In the dairy sector, the available infrared instruments mainly implement the Fourier transform infrared (FTIR) spectroscopy. This method is widely employed in milk recording schemes worldwide for animal monitoring and breeding purposes. In addition, visible and near-infrared (NIR) spectroscopy is increasingly integrated into milking systems for daily on-farm monitoring of milk quality and animals’ physiological status. This review examines the topic of milk phenomics together with potential and challenges of infrared spectroscopy to predict indicators and complex traits related to health and nutritional disorders exploiting the biological bonds that exist between milk and blood in dairy animals.HIGHLIGHTS Milk is a valuable source of information for assessing nutritional and health proxies in dairy animals. Infrared spectroscopy is used within routine milk recording systems for the determination of major components, but other useful applications exist. This review summarises research on milk phenomics carried out by mean of infrared spectroscopy to predict complex traits related to animals’ health and nutritional disorders.

This study aimed at evaluating the environmental impact (EI) of herds representative of the Italian heavy pig production system to investigate the EI variation associated with farm management (FM), diet formulation (DF) and animal response (AR) variables. Data originated from 8 breeding farms, which included the sows and preweaning piglets (Site1) and the post-weaned piglets (7.5–30 kg body weight – BW, Site2) and 10 growing–fattening farms, dealing with 30–170 kg BW pigs (Site3). A cradle-to-farm gate Life Cycle Assessment was used, with 1 kg BW gain (BWG) as functional unit. Impact categories were global warming (GWP), acidification (AP) and eutrophication (EP) potentials and land occupation (LO). Whole-production cycle EI (Site123, 0–170 kg BW) was obtained summing up EIs of 0–30 and 30–170 kg BW animals. Impacts were analysed with one- or two-way PERMANOVA to test the effect of FM, DF and AR variables. The Site123-related EI averaged nearly 3.1 kg CO2-eq (GWP), 50 g SO2-eq (AP), 22 g PO4-eq (EP) and 4.9 m2/y (LO) per kg BWG. Site3 contributed nearly 80% of the whole impact. Regarding Site1, GWP resulted mitigated by increasing sow productivity. Site2 EI resulted mitigated by decreasing feed conversion ratio and increasing average daily gain, whereas Site3 EI by increasing feed self-sufficiency and decreasing dietary crude protein and mortality. In perspective, given the relevance of Site3 on the whole-pig system EI, a deeper integration between the farm agronomical management and the growing–finishing pigs’ diets formulation would support the environmental sustainability of heavy pig operations.

Abstract Background Various blood metabolites are known to be useful indicators of health status in dairy cattle, but their routine assessment is time-consuming, expensive, and stressful for the cows at the herd level. Thus, we evaluated the effectiveness of combining in-line near infrared (NIR) milk spectra with on-farm (days in milk [DIM] and parity) and genetic markers for predicting blood metabolites in Holstein cattle. Data were obtained from 388 Holstein cows from a farm with an AfiLab system. NIR spectra, on-farm information, and single nucleotide polymorphisms (SNP) markers were blended to develop calibration equations for blood metabolites using the elastic net (ENet) approach, considering 3 models: (1) Model 1 (M1) including only NIR information, (2) Model 2 (M2) with both NIR and on-farm information, and (3) Model 3 (M3) combining NIR, on-farm and genomic information. Dimension reduction was considered for M3 by preselecting SNP markers from genome-wide association study (GWAS) results. Results Results indicate that M2 improved the predictive ability by an average of 19% for energy-related metabolites (glucose, cholesterol, NEFA, BHB, urea, and creatinine), 20% for liver function/hepatic damage, 7% for inflammation/innate immunity, 24% for oxidative stress metabolites, and 23% for minerals compared to M1. Meanwhile, M3 further enhanced the predictive ability by 34% for energy-related metabolites, 32% for liver function/hepatic damage, 22% for inflammation/innate immunity, 42.1% for oxidative stress metabolites, and 41% for minerals, compared to M1. We found improved predictive ability of M3 using selected SNP markers from GWAS results using a threshold of > 2.0 by 5% for energy-related metabolites, 9% for liver function/hepatic damage, 8% for inflammation/innate immunity, 22% for oxidative stress metabolites, and 9% for minerals. Slight reductions were observed for phosphorus (2%), ferric-reducing antioxidant power (1%), and glucose (3%). Furthermore, it was found that prediction accuracies are influenced by using more restrictive thresholds (−log10(P-value) > 2.5 and 3.0), with a lower increase in the predictive ability. Conclusion Our results highlighted the potential of combining several sources of information, such as genetic markers, on-farm information, and in-line NIR infrared data improves the predictive ability of blood metabolites in dairy cattle, representing an effective strategy for large-scale in-line health monitoring in commercial herds.

ABSTRACT: The clinical relevance of avian metapneumovirus (aMPV) is growing in the poultry sector, especially in broiler farming, where no vaccination is administered in Italy. Given the naïve status of the birds, a serological survey was conducted in a densely populated area of Northern Italy, to evaluate aMPV circulation. Seven farms were selected and sampled in summer/fall, then sampling was repeated in the following season (winter/spring) to assess a possible seasonal effect. In each farm, fifteen birds were blood sampled towards the end of the cycle and sera were analyzed with an ELISA test. Clinical signs were reported in 5 out of 7 farms, although all farms were positive at both sampling points, except for one, which was negative at the first sampling. The seroprevalence within farm ranged from 26.6% to 100%, and antibody titres appear to increase with age. No seasonality effect was evidenced, whereas a farm effect was more distinct. aMPV circulation appears wide in Northern Italian farms, with different clinical outcomes that could be modulated by intrinsic characteristics of the farms. In absence of vaccination, serological monitoring can be a useful tool for viral entrance monitoring, although sampling timing should be evaluated in order to spot seroconversion after late infections.

Abstract Background Metabolic disturbances adversely impact productive and reproductive performance of dairy cattle due to changes in endocrine status and immune function, which increase the risk of disease. This may occur in the post-partum phase, but also throughout lactation, with sub-clinical symptoms. Recently, increased attention has been directed towards improved health and resilience in dairy cattle, and genomic selection (GS) could be a helpful tool for selecting animals that are more resilient to metabolic disturbances throughout lactation. Hence, we evaluated the genomic prediction of serum biomarkers levels for metabolic distress in 1353 Holsteins genotyped with the 100K single nucleotide polymorphism (SNP) chip assay. The GS was evaluated using parametric models best linear unbiased prediction (GBLUP), Bayesian B (BayesB), elastic net (ENET), and nonparametric models, gradient boosting machine (GBM) and stacking ensemble (Stack), which combines ENET and GBM approaches. Results The results show that the Stack approach outperformed other methods with a relative difference (RD), calculated as an increment in prediction accuracy, of approximately 18.0% compared to GBLUP, 12.6% compared to BayesB, 8.7% compared to ENET, and 4.4% compared to GBM. The highest RD in prediction accuracy between other models with respect to GBLUP was observed for haptoglobin (hapto) from 17.7% for BayesB to 41.2% for Stack; for Zn from 9.8% (BayesB) to 29.3% (Stack); for ceruloplasmin (CuCp) from 9.3% (BayesB) to 27.9% (Stack); for ferric reducing antioxidant power (FRAP) from 8.0% (BayesB) to 40.0% (Stack); and for total protein (PROTt) from 5.7% (BayesB) to 22.9% (Stack). Using a subset of top SNPs (1.5k) selected from the GBM approach improved the accuracy for GBLUP from 1.8 to 76.5%. However, for the other models reductions in prediction accuracy of 4.8% for ENET (average of 10 traits), 5.9% for GBM (average of 21 traits), and 6.6% for Stack (average of 16 traits) were observed. Conclusions Our results indicate that the Stack approach was more accurate in predicting metabolic disturbances than GBLUP, BayesB, ENET, and GBM and seemed to be competitive for predicting complex phenotypes with various degrees of mode of inheritance, i.e. additive and non-additive effects. Selecting markers based on GBM improved accuracy of GBLUP.

ABSTRACT: The considerable increase in the production capacity of individual cows owing to both selective breeding and innovations in the dairy sector has posed challenges to management practices in terms of maintaining the nutritional and metabolic health status of dairy cows. In this observational study, we investigated the associations between milk yield, composition, and technological traits and a set of 21 blood biomarkers related to energy metabolism, liver function or hepatic damage, oxidative stress, and inflammation or innate immunity in a population of 1,369 high-yielding Holstein-Friesian dairy cows. The milk traits investigated in this study included 4 production traits (milk yield, fat yield, protein yield, daily milk energy output), 5 traits related to milk composition (fat, protein, casein, and lactose percentages and urea), 11 milk technological traits (5 milk coagulation properties and 6 curd-firming traits). All milk traits (i.e., production, composition, and technological traits) were analyzed according to a linear mixed model that included the days in milk, the parity order, and the blood metabolites (tested one at a time) as fixed effects and the herd and date of sampling as random effects. Our findings revealed that milk yield and daily milk energy output were positively and linearly associated with total cholesterol, nonesterified fatty acids, urea, aspartate aminotransferase, γ-glutamyl transferase, total bilirubin, albumin, and ferric-reducing antioxidant power, whereas they were negatively associated with glucose, creatinine, alkaline phosphatase, total reactive oxygen metabolites, and proinflammatory proteins (ceruloplasmin, haptoglobin, and myeloperoxidase). Regarding composition traits, the protein percentage was negatively associated with nonesterified fatty acids and β-hydroxybutyrate (BHB), while the fat percentage was positively associated with BHB, and negatively associated with paraoxonase. Moreover, we found that the lactose percentage increased with increasing cholesterol and albumin and decreased with increasing ceruloplasmin, haptoglobin, and myeloperoxidase. Milk urea increased with an increase in cholesterol, blood urea, nonesterified fatty acids, and BHB, and decreased with an increase in proinflammatory proteins. Finally, no association was found between the blood metabolites and milk coagulation properties and curd-firming traits. In conclusion, this study showed that variations in blood metabolites had strong associations with milk productivity traits, the lactose percentage, and milk urea, but no relationships with technological traits of milk. Specifically, increasing levels of proinflammatory and oxidative stress metabolites, such as ceruloplasmin, haptoglobin, myeloperoxidase, and total reactive oxygen metabolites, were shown to be associated with reductions in milk yield, daily milk energy output, lactose percentage, and milk urea. These results highlight the close connection between the metabolic and innate immunity status and production performance. This connection is not limited to specific clinical diseases or to the transition phase but manifests throughout the entire lactation. These outcomes emphasize the importance of identifying cows with subacute inflammatory and oxidative stress as a means of reducing metabolic impairments and avoiding milk fluctuations.

ABSTRACT: Mastitis is one of the most significant diseases in dairy cows and causes several economic losses. Somatic cell count (SCC) is often used as an indirect diagnostic tool for mastitis, especially for subclinical mastitis (SCM) where no symptoms or signs can be detected. Streptococcus agalactiae is one of the main causes of contagious mastitis, and Prototheca spp. is an alga-inducing environmental mastitis that is not always correlated with increased milk SCC. The aim of this study was to evaluate the changes in the metabolomic profile of blood in relation to subclinical intramammary infection (IMI) in dairy cows. In addition, differences resulting from the etiologic agent causing mastitis were also considered. Forty Holstein-Friesian dairy cows in mid and late lactation were enrolled in this cross-sectional design study. Based on the bacteriological examination of milk, the animals were divided into 3 groups: group CTR (control group; n = 16), group A (affected by SCM with IMI caused by Strep. agalactiae; n = 17), and group P (affected by SCM with IMI caused by Prototheca spp.; n = 7). Blood samples from the jugular vein were collected in tubes containing clot activator; the serum aliquot was stored until metabolomic analysis by 1H-nuclear magnetic resonance spectroscopy. Statistical analysis was conducted by fitting a linear model with the group as the fixed effect and SCC as the covariate. Forty-two metabolites were identified, and among them 10 were significantly different among groups. Groups A and P showed greater levels of His and lactose and lower levels of acetate, Asn, and dimethylamine compared with group CTR. Group A showed high levels of Val, and group P showed high levels of Cit and methylguanidine, as well as lower levels of 3-hydroxybutyrate, acetone, allantoin, carnitine, citrate, and ethanol. These metabolites were related to ruminal fermentations, energy metabolism, urea synthesis and metabolism, immune and inflammatory response, and mammary gland permeability. These results suggest systemic involvement with subclinical IMI and that the metabolic profile of animals with SCM undergoes changes related to the etiological agent of mastitis.

ABSTRACT: Better understanding of the molecular mechanisms behind bovine mastitis is fundamental for improving the management of this disease, which continues to be of major concern for the dairy industry, especially in its subclinical form. Disease severity and progression depend on numerous aspects, such as livestock genetics, and the interaction between the causative agent, the host, and the environment. In this context, epigenetic mechanisms have proven to have a role in controlling the response of the animal to inflammation. Therefore, in this study we aimed to explore genome-wide DNA methylation of milk somatic cells (SC) in healthy cows (n = 15) and cows affected by naturally occurring subclinical mastitis by Streptococcus agalactiae (n = 12) and Prototheca spp. (n = 11), to better understand the role of SC methylome in the host response to disease. Differentially methylated regions (DMR) were evaluated comparing: (1) Strep. agalactiae-infected versus healthy; (2) Prototheca-infected versus healthy, and (3) mastitis versus healthy and (4) Strep. agalactiae-infected versus Prototheca-infected. The functional analysis was performed at 2 levels. To begin with, we extracted differentially methylated genes (DMG) from promoter DMR, which were analyzed using the Cytoscape ClueGO plug-in. Coupled with this DMG-driven approach, all the genes associated with promoter-methylated regions were fed to the Pathifier algorithm. From the DMR analysis, we identified 1,081 hypermethylated and 361 hypomethylated promoter regions in Strep. agalactiae-infected animals, while 1,514 hypermethylated and 358 hypomethylated promoter regions were identified in Prototheca-infected animals, when compared with the healthy controls. When considering infected animals as a whole group (regardless of the pathogen), we found 1,576 hypermethylated and 460 hypomethylated promoter regions. Both pathogens were associated with methylation differences in genes involved in pathways related to meiosis, reproduction and tissue remodeling. Exploring the whole methylome, in subclinically infected cows we observed a strong deregulation of immune-related pathways, such as nuclear factor kB and toll-like receptors signaling pathways, and of energy-related pathways such as the tricarboxylic acid cycle and unsaturated fatty acid biosynthesis. In conclusion, no evident pathogen-specific SC methylome signature was detected in the present study. Overall, we observed a clear regulation of host immune response driven by DNA methylation upon subclinical mastitis. Further studies on a larger cohort of animals are needed to validate our results and to possibly identify a unique SC methylome that signifies pathogen-specific alterations.

ABSTRACT: In this study we wanted to investigate the associations between naturally occurring subclinical intramammary infection (IMI) caused by different etiological agents (i.e., Staphylococcus aureus, Streptococcus agalactiae, Streptococcus uberis, and Prototheca spp.), in combination with somatic cell count (SCC), on the detailed milk protein profile measured at the individual mammary gland quarter. An initial bacteriological screening (time 0; T0) conducted on individual composite milk from 450 Holstein cows reared in 3 herds, was performed to identify cows with subclinical IMI. We identified 78 infected animals which were followed up at the quarter level at 2 different sampling times: T1 and T2, 2 and 6 wk after T0, respectively. A total of 529 quarter samples belonging to the previously selected animals were collected at the 2 sampling points and analyzed with a reversed phase HPLC (RP-HPLC) validated method. Specifically, we identified and quantified 4 caseins (CN), namely αS1-CN, αS2-CN, κ-CN, and β-CN, and 3 whey protein fractions, namely β-lactoglobulin, α-lactalbumin, and lactoferrin (LF), which were later expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, % N). Data were analyzed with a hierarchical linear mixed model with the following fixed effects: days in milk (DIM), parity, herd, SCC, bacteriological status (BACT), and the SCC × BACT interaction. The random effect of individual cow, nested within herd, DIM and parity was used as the error term for the latter effects. Both IMI (i.e., BACT) and SCC significantly reduced the proportion of β-CN and αS1-CN, ascribed to the increased activity of both milk endogenous and microbial proteases. Less evident alterations were found for whey proteins, except for LF, which being a glycoprotein with direct and undirect antimicrobial activity, increased both with IMI and SCC, suggesting its involvement in the modulation of both the innate and adaptive immune response. Finally, increasing SCC in the positive samples was associated with a more marked reduction of total caseins at T1, and αS1-CN at T2, suggesting a synergic effect of infection and inflammation, more evident at high SCC. In conclusion, our work helps clarify the behavior of protein fractions at quarter level in animals having subclinical IMI. The inflammation status driven by the increase in SCC, rather the infection, was associated with the most significant changes, suggesting that the activity of endogenous proteolytic enzymes related to the onset of inflammation might have a pivotal role in directing the alteration of the milk protein profile.

IntroductionPorcine circovirus 2 (PCV-2) is a key pathogen for the swine industry at a global level. Nine genotypes, differing in epidemiology and potentially virulence, emerged over time, with PCV-2a, -2b, and -2d being the most widespread and clinically relevant. Conversely, the distribution of minor genotypes appears geographically and temporally restricted, suggesting lower virulence and different epidemiological drivers. In 2022, PCV-2e, the most genetically and phenotypically divergent genotype, was identified in multiple rural farms in North-eastern Italy. Since rural pigs often have access to outdoor environment, the introduction from wild boars was investigated.MethodsThrough a molecular and spatial approach, this study investigated the epidemiology and genetic diversity of PCV-2 in 122 wild boars across different provinces of North-eastern Italy.ResultsMolecular analysis revealed a high PCV-2 frequency (81.1%, 99/122), and classified the majority of strains as PCV-2d (96.3%, 78/81), with sporadic occurrences of PCV-2a (1.2%, 1/81) and PCV-2b (2.5%, 2/81) genotypes. A viral flow directed primarily from domestic pigs to wild boars was estimated by phylogenetic and phylodynamic analyses.DiscussionThese findings attested that the genotype replacement so far described only in the Italian domestic swine sector occurred also in wild boars. and suggested that the current heterogeneity of PCV-2d strains in Italian wild boars likely depends more on different introduction events from the domestic population rather than the presence of independent evolutionary pressures. While this might suggest PCV-2 circulation in wild boars having a marginal impact in the industrial sector, the sharing of PCV-2d strains across distinct wild populations, in absence of a consistent geographical pattern, suggests a complex interplay between domestic and wild pig populations, emphasizing the importance of improved biosecurity measures to mitigate the risk of pathogen transmission.

ABSTRACT: Udder health has a crucial role in sustainable milk production, and various reports have pointed out that changes in udder condition seem to affect milk mineral content. The somatic cell count (SCC) is the most recognized indicator for the determination of udder health status. Recently, a new parameter, the differential somatic cell count (DSCC), has been proposed for a more detailed evaluation of intramammary infection patterns. Specifically, the DSCC is the combined proportions of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) on the total SCC, with macrophages (MAC) representing the remainder proportion. In this study, we evaluated the association between DSCC in combination with SCC on a detailed milk mineral profile in 1,013 Holstein-Friesian cows reared in 5 herds. An inductively coupled plasma–optical emission spectrometry was used to quantify 32 milk mineral elements. Two different linear mixed models were fitted to explore the associations between the milk mineral elements and first, the DSCC combined with SCC, and second, DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the proportion of PMN-LYM and MAC by SCC. We observed a significant positive association between SCC and milk Na, S, and Fe levels. Differential somatic cell count showed an opposite behavior to the one displayed by SCC, with a negative association with Na and positive association with K milk concentrations. When considering DSCC as count, Na and K showed contrasting behavior when associated with PMN-LYM or MAC counts, with decreasing of Na content and increasing K when associated with increasing PMN-LYM counts, and increasing Na and decreasing K when associated with increasing MAC count. These findings confirmed that an increase in SCC is associated with altered milk Na and K amounts. Moreover, MAC count seemed to mirror SCC patterns, with the worsening of inflammation. Differently, PMN-LYM count exhibited patterns of associations with milk Na and K contents attributable more to LYM than PMN, given the nonpathological condition of the majority of the investigated population. An interesting association was observed for milk S content, which increased with increasing of inflammatory conditions (i.e., increased SCC and MAC count) probably attributable to its relationship with milk proteins, especially whey proteins. Moreover, milk Fe content showed positive associations with the PMN-LYM population, highlighting its role in immune regulation during inflammation. Further studies including individuals with clinical condition are needed to achieve a comprehensive view of milk mineral behavior during udder health impairment.

This study aimed to assess the environmental impact (cradle-to-farm gate LCA) of milk production of cereal-based dairy farms in northern Italy and to analyse which traits related to farm management (MAN_F), lactating cows’ ration composition (DIET_F), and animal responses (ANI_F) could be identified as main determinants to address specific mitigation strategies. Data originated from 28 dairy farms. The functional unit was 1 kg of fat- and protein-corrected milk (FPCM). Impact categories were global warming (GWP), acidification (AP) and eutrophication (EP) potentials and land occupation (LO). Impact values were analysed with a linear model to test separately the effects of MAN_F, DIET_F and ANI_F variables. One kg FPCM was associated with an average impact of 1.10 kg CO2-eq (GWP), 17.1 g SO2-eq (AP), 6.0 g PO4-eq (EP), and 1.3 m2/y (LO). Regarding MAN_F, GWP and LO linearly decreased with increasing values of stocking rate and feed self-sufficiency (FSS), whereas minimum EP was found for intermediate FSS values (50% DM). Regarding DIET_F, GWP linearly decreased at increasing levels of dietary inclusion of cereal silages, whereas AP and EP linearly decreased at decreasing dietary crude protein (CP) content values. Among ANI_F, GWP and EP were quadratically associated with milk yield (MY), evidencing the lowest values at intermediate MY (9100 ± 477 kg FPCM/cow per 305d-lactation). The GWP, AP and EP decreased with decreasing age at first calving. These results can contribute at drawing good practices for farmers and consultants to promote more environmentally sustainable dairy production while supporting farm functioning and farmers’ income.HIGHLIGHTS Farm and animal determinants of Life Cycle Assessment of cereal-based dairy farms were studied. Mitigation effects can be achieved by operating on farm organisation, cow’s diet, and animal responses. Good practices for farmers and consultants can be proposed for a better dairy production sustainability.

The use of sexed semen to produce replacement heifers in dairy farms allows many cows to be inseminated with bulls of beef breeds with the aim of improving meat production. The major dairy and beef breeds are undergoing rapid genetic improvement as a result of more efficient selection methods, necessitating evaluation of the quality of meat produced by beef × dairy crosses obtained using current genetics. As part of a larger project, we carried out quantitative and qualitative evaluations of the veal and beef produced from crossbred calves produced by dairy farms that use sexed semen to obtain purebred replacement heifers. A total of 231 bull-calves were reared in the dairy farms or in specialised fattening farms, slaughtered, and sampled for meat quality analysis. These comprised: 104 crossbred calves, mainly from Belgian Blue sires and Holstein dams, which were intensively fattened for veal production; 84 beef × dairy crossbred calves, destined for beef production on the dairy farm of origin (12 calves) or in a specialised intensive fattening centre (72 calves); 26 purebred Charolais and 17 beef crosses from suckler cows, included for comparison, which were fattened in the same fattening centre and fed the same diet as the beef × dairy crosses. Veal and beef meat differed in all quality traits; the beef produced by dairy farmers was better than the beef produced by specialised fatteners in terms of cooking losses and tenderness, even though these animals were much older and weighed less at slaughter. There were minor differences in the quality traits of veal between the various beef × dairy breed combinations. In the case of intensive beef production, minor differences were observed between Belgian Blue-sired crosses from Brown Swiss cows (lipid content and shear force of meat) and Belgian Blue-sired crosses from crossbred cows (haem iron, lightness, yellowness, and hue) in comparison with crosses from Holstein cows. The beef of young bulls from suckler cows (Charolais and crosses) had a lower pH, dry matter and lipid contents, slightly higher cholesterol and haem iron contents, and higher cooking losses than meat from beef × dairy crosses. Taking into account the results from the entire project, we conclude that the combined use of sexed semen for pure-breeding and conventional beef semen for terminal crossbreeding improves meat production from dairy herds, both quantitatively and qualitatively.HIGHLIGHTS The meat from beef × dairy crossbred calves was found to have valuable qualitative characteristics. With regard to veal production, the meat quality characteristics of crossbred calves did not differ appreciably between breed combinations. With regard to intensive beef production, the meat from beef × dairy young bulls had greater quality than that from suckler cows. Crosses fattened by dairy farmers grew slower than those by specialised fatteners, but their beef was better in terms of cooking losses and tenderness.

The milk Fourier-transform infra-red spectrometry (FTIRS) can be used to predict the enteric methane emissions (EME) at population level. In this study, the variability in FTIRS predicted EME traits due to the breed of cow, farm, the production level of individual cows within herds, and their interactions were evaluated. A dataset obtained from milk recordings, which covered four breeds (Holstein, Brown Swiss, Simmental and Alpine Grey), 6,430 herds, 115,819 cows, and 1,759,706 test-day milk/spectra records was used. The herds were stratified into 5 production levels considering their average daily milk energy production; individual cows within herd were similarly stratified considering their individual production levels. The EME traits were predicted directly from milk FTIR spectra or indirectly from six informative milk FA predicted from milk spectra. The statistical model included, separately for each trait and method, breed, herd intensiveness level, cow production level, and their interactions, year, month, parity, and lactation stage. The direct and indirect methods yielded similar results in predicting CH4 yield per kg of DMI and CH4 intensity per kg of fat-protein corrected milk. The indirect method was reliable in predicting daily EME production per cow, the indirect one did not. EME was affected by the breed x herd production intensiveness interaction, and to a lesser degree, by the breed x cow production level interaction. A better understanding of the complex interactions influencing EME in dairy herds was achieved. This would be useful for the genetic improvement, the environmental certification of farms, and for setting prices in milk payment schemes.HIGHLIGHTS Causes of variation of the FTIR predicted EME were studied at population level using data from 6,430 herds and 1,759,706 milk spectra records Reliable daily EME estimates were achieved from 6 six informative fatty acids predicted from milk spectra EME was influenced by the interaction breed × level of herd intensiveness and, to a lesser extent, by the individual production level

This case report presents the first molecular identification of a gammacoronavirus in a free-ranging striped dolphin (Stenella coeruleoalba) that was found stranded along the Croatian coastline in 2022. The dolphin exhibited a concurrent infection with cetacean morbillivirus. The gammacoronavirus strain was amplified and sequenced from heart tissue imprinted on an FTA®card, revealing a notable genetic distance (approximately 8%) from previously characterized cetacean gammacoronaviruses. This finding highlights the importance of including gammacoronaviruses in routine diagnostics for stranded dolphins to gather epidemiological data on their prevalence and potential role in causing disease in cetaceans. This study sets the premises for a further understanding of the diversity and distribution of gammacoronaviruses in marine mammals and highlights the necessity for ongoing surveillance of emerging infectious diseases in wild populations.

During inflammation and tissue regeneration, the alarmin High Mobility Group Box 1 (HMGB1), in its reduced isoform, enhances the activity of the chemokine CXCL12, forming a heterocomplex that acts via the chemokine receptor CXCR4. Despite the established roles of both HMGB1 and CXCL12 in tumor progression and metastatic spread to distal sites, the role of the CXCL12/HMGB1 heterocomplex in cancer has never been investigated. By employing a newly established mass spectrometry protocol that allows an unambiguous distinction between reduced (red-HMGB1) and oxidized (ox-HMGB1) HMGB1 isoforms in cell lysates, we demonstrate that human epithelial cells derived from breast (MCF-7 and MDA-MB-231) and prostate (PC-3) cancer predominantly express red-HMGB1, while primary CD3+ T lymphocytes from peripheral blood express both HMGB1 isoforms. All these cancer cells release HMGB1 in the extracellular microenvironment together with varying concentrations of thioredoxin and thioredoxin reductase. The CXCL12/HMGB1 heterocomplex enhances, via CXCR4, the directional migration and invasiveness of cancer cells characterized by high metastatic potential that possess a fully active thioredoxin system, contributing to maintain red-HMGB1. On the contrary, cancer cells with low metastatic potential, lack thioredoxin reductase, promptly uptake CXCL12 and fail to respond to the heterocomplex. Our study demonstrates that the responsiveness of cancer cells to the CXCL12/HMGB1 heterocomplex, resulting in enhanced cell migration and invasiveness, depends on the maintenance of HMGB1 in its reduced isoform, and suggests disruption of the heterocomplex as a potential therapeutic target to inhibit invasion and metastatic spread in cancer therapies.

ABSTRACT: The causes of variation in the milk mineral profile of dairy cattle during the first phase of lactation were studied under the hypothesis that the milk mineral profile partially reflects the animals' metabolic status. Correlations between the minerals and the main milk constituents (i.e., protein, fat, and lactose percentages), and their associations with the cows' metabolic status indicators were explored. The metabolic status indicators (MET) that we used were blood energy-protein metabolites [nonesterified fatty acids, β-hydroxybutyrate (BHB), glucose, cholesterol, creatinine, and urea], and liver ultrasound measurements (predicted triacylglycerol liver content, portal vein area, portal vein diameter and liver depth). Milk and blood samples, and ultrasound measurements were taken from 295 Holstein cows belonging to 2 herds and in the first 120 d in milk (DIM). Milk mineral contents were determined by ICP-OES; these were considered the response variable and analyzed through a mixed model which included DIM, parity, milk yield, and MET as fixed effects, and the herd/date as a random effect. The MET traits were divided in tertiles. The results showed that milk protein was positively associated with body condition score (BCS) and glucose, and negatively associated with BHB blood content; milk fat was positively associated with BHB content; milk lactose was positively associated with BCS; and Ca, P, K and S were the minerals with the greatest number of associations with the cows' energy indicators, particularly BCS, predicted triacylglycerol liver content, glucose, BHB and urea. We conclude that the protein, fat, lactose, and mineral contents of milk partially reflect the metabolic adaptation of cows during lactation and within 120 DIM. Variations in the milk mineral profile were consistent with changes in the major milk constituents and the metabolic status of cows.

ABSTRACT: The aim of this study was to investigate the associations between subclinical intramammary infection (IMI) from different pathogens combined with inflammation status and a set of blood biochemical traits including energy-related metabolites, indicators of liver function or hepatic damage, oxidative stress, inflammation, innate immunity, and mineral status in 349 lactating Holstein cows. Data were analyzed with a linear model including the following fixed class effects: days in milk, parity, herd, somatic cell count (SCC), bacteriological status (positive and negative), and the SCC × bacteriological status interaction. Several metabolites had significant associations with subclinical IMI or SCC. Increased SCC was associated with a linear decrease in cholesterol concentrations which ranged from −2% for the class ≥50,000 and

Avian metapneumovirus (aMPV) has been identified as an important cause of respiratory and reproductive disease, leading to significant productive losses worldwide. Different subtypes have been found to circulate in different regions, with aMPV-A and B posing a significant burden especially in the Old World, and aMPV-C in North America, albeit with limited exceptions of marginal economic relevance. Recently, both aMPV-A and aMPV-B have been reported in the U.S.; however, the route of introduction has not been investigated. In the present study, the potential importation pathways have been studied through phylogenetic and phylodynamic analyses based on a broad collection of partial attachment (G) protein sequences collected worldwide. aMPV-B circulating in the U.S. seems the descendant of Eastern Asian strains, which, in turn, are related to European ones. A likely introduction pathway mediated by wild bird migration through the Beringian crucible, where the East Asian and Pacific American flight paths intersect, appears likely and was previously reported for avian influenza. aMPV-A, on the other hand, showed a Mexican origin, involving strains related to Asian ones. Given the low likelihood of trade or illegal importation, the role of wild birds appears probable also in this case, since the region is covered by different flight paths directed in a North–South direction through America. Since the information on the role of wild birds in aMPV epidemiology is still scarce and scattered, considering the significant practical implications for the poultry industry demonstrated by recent U.S. outbreaks, further surveys on wild birds are encouraged.

Abstract Background Subclinical intramammary infection (IMI) represents a significant problem in maintaining dairy cows’ health. Disease severity and extent depend on the interaction between the causative agent, environment, and host. To investigate the molecular mechanisms behind the host immune response, we used RNA-Seq for the milk somatic cells (SC) transcriptome profiling in healthy cows (n = 9), and cows naturally affected by subclinical IMI from Prototheca spp. (n = 11) and Streptococcus agalactiae (S. agalactiae; n = 11). Data Integration Analysis for Biomarker discovery using Latent Components (DIABLO) was used to integrate transcriptomic data and host phenotypic traits related to milk composition, SC composition, and udder health to identify hub variables for subclinical IMI detection. Results A total of 1,682 and 2,427 differentially expressed genes (DEGs) were identified when comparing Prototheca spp. and S. agalactiae to healthy animals, respectively. Pathogen-specific pathway analyses evidenced that Prototheca’s infection upregulated antigen processing and lymphocyte proliferation pathways while S. agalactiae induced a reduction of energy-related pathways like the tricarboxylic acid cycle, and carbohydrate and lipid metabolism. The integrative analysis of commonly shared DEGs between the two pathogens (n = 681) referred to the core-mastitis response genes, and phenotypic data evidenced a strong covariation between those genes and the flow cytometry immune cells (r 2 = 0.72), followed by the udder health (r 2 = 0.64) and milk quality parameters (r 2 = 0.64). Variables with r ≥ 0.90 were used to build a network in which the top 20 hub variables were identified with the Cytoscape cytohubba plug-in. The genes in common between DIABLO and cytohubba (n = 10) were submitted to a ROC analysis which showed they had excellent predictive performances in terms of discriminating healthy and mastitis-affected animals (sensitivity > 0.89, specificity > 0.81, accuracy > 0.87, and precision > 0.69). Among these genes, CIITA could play a key role in regulating the animals’ response to subclinical IMI. Conclusions Despite some differences in the enriched pathways, the two mastitis-causing pathogens seemed to induce a shared host immune-transcriptomic response. The hub variables identified with the integrative approach might be included in screening and diagnostic tools for subclinical IMI detection.

Objectives Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease affecting mainly the axial skeleton. Peripheral involvement (arthritis, enthesitis and dactylitis) and extra-musculoskeletal manifestations, including uveitis, psoriasis and bowel inflammation, occur in a relevant proportion of patients. AS is responsible for chronic and severe back pain caused by local inflammation that can lead to osteoproliferation and ultimately spinal fusion. The association of AS with the human leucocyte antigen-B27 gene, together with elevated levels of chemokines, CCL17 and CCL22, in the sera of patients with AS, led us to study the role of CCR4+ T cells in the disease pathogenesis.Methods CD8+CCR4+ T cells isolated from the blood of patients with AS (n=76) or healthy donors were analysed by multiparameter flow cytometry, and gene expression was evaluated by RNA sequencing. Patients with AS were stratified according to the therapeutic regimen and current disease score.Results CD8+CCR4+ T cells display a distinct effector phenotype and upregulate the inflammatory chemokine receptors CCR1, CCR5, CX3CR1 and L-selectin CD62L, indicating an altered migration ability. CD8+CCR4+ T cells expressing CX3CR1 present an enhanced cytotoxic profile, expressing both perforin and granzyme B. RNA-sequencing pathway analysis revealed that CD8+CCR4+ T cells from patients with active disease significantly upregulate genes promoting osteogenesis, a core process in AS pathogenesis.Conclusions Our results shed light on a new molecular mechanism by which T cells may selectively migrate to inflammatory loci, promote new bone formation and contribute to the pathological ossification process observed in AS.