Eugenio Martignani

This review examines the relationship between climate-driven heat stress (HS) and bovine mastitis in the Po Valley, a key European dairy region characterized by intensive production systems and increasing climatic vulnerability. It aims to contextualize how rising temperature–humidity index (THI) levels influence animal health and productivity. This study synthesizes the current literature on biometeorological conditions, epidemiological trends, and physiological mechanisms linking HS to mastitis. Evidence indicates that prolonged exposure to elevated THI impairs thermoregulation, disrupts endocrine and metabolic balance, and weakens immune function, thereby increasing susceptibility to intramammary infections. Epidemiological data reveal a clear seasonal pattern, with mastitis incidence peaking during summer months and a growing predominance of environmental pathogens. Additionally, HS negatively affects milk yield and quality, amplifying economic losses in dairy systems. The findings highlight that mastitis in this context is not merely an infectious disease but a multifactorial condition shaped by environmental, physiological, and management factors. Overall, this review underscores the need for integrated mitigation strategies, including improved housing, nutrition, genetic selection, and precision monitoring, to enhance resilience. In the face of ongoing climate change, adapting dairy production systems will be essential to safeguard animal welfare, maintain productivity, and ensure the long-term sustainability of the Po Valley dairy sector.

Mastitis is the leading cause of economic losses in dairy farming, significantly impairing animal welfare and the quality and quantity of milk production. MicroRNAs are increasingly gaining attention, in both human and veterinary medicine, as biomarkers for various diseases. This study evaluated the diagnostic potential of four circulating microRNAs (miR-26-5p, miR-142-5p, miR-146a, and miR-223-3p) by examining changes in their expression in milk samples from dairy cows at different immune-cell subpopulations correlated to different stage of mastitis with a validated method. Additionally, this study has analyzed the possible source of these circulating microRNAs by the measurement of their secretion from activated immune cells (lymphocytes, monocytes, and neutrophils). miR-223-3p has been significantly expressed in an acute stage of mastitis (p < 0.01) but not in the chronic or susceptible stages. Conversely, mir-26-5p has been significantly reduced in acute, chronic, and susceptible groups of animals. In immune-cell cultures, miR-26 has been shown to be down-regulated in lipopolysaccharide (LPS)-stimulated neutrophils, while miR-223 has been shown to be up-regulated in phytohemagglutinin (PHA)-stimulated lymphocytes. The differential expression of miR-223-3p and miR-26-5p, combined with differential and total somatic cell count, could serve as a useful tool for identifying the evolutionary stage of mastitis-related inflammatory pathology.

Mastitis is the disease that causes the greatest economic losses in dairy farming, significantly im-pairing animal welfare and the quality and quantity of milk produced. MicroRNAs are increasingly gaining attention, both in human and veterinary medicine, as biomarkers for various diseases. This study evaluated the diagnostic potential of four circulating microRNAs (miR-26-5p, miR-142-5p, miR-146a, and miR-223-3p) by examining changes in their expression in milk samples from dairy cows at different immune cells subpopulations correlated to different stage of mastitis in validated method. Additionally, the project has analysed the possible source of these circulating microRNA by the measurement of their secretion from activated immune cells (lymphocytes, monocytes, and neutrophils). miR-223-3p has been significantly expressed in acute stage of mastitis (p<0.01) but not in chronic or susceptible stages. mir-26-5p has been significantly reduced in acute, chronic and susceptible groups of animals. In immune cell cultures miR-26 has been shown to downregulate in LPS-stimulated neutrophils while miR-223 has been shown to be upregulated in PHA-stimulated lymphocytes. The differential expression of miR-223-3p and miR-26-5p together with differential and classic somatic cell count could be utilized for identifying the evolutionary stage of masti-tis-related inflammatory pathology.

For livestock, transport can involve several potential stressors including human handling, stocking density, air temperature, noise, vibration, and loading/unloading procedures. The animal’s perception of and its ability to adapt to those stimuli are not fully understood, which makes it difficult to carry out welfare assessments. This study aimed to detect stressful moments in lambs during transport through changes in physiological and molecular markers. Data obtained from bio-loggers that record physiological variables and an evaluation of molecular biomarkers such as cortisol and circulating microRNAs (c-miRNAs) identified the most stressful moments of transport, which can be a valuable tool for evaluating and improving transport conditions for livestock. Rasa Aragonesa lambs were implanted with bio-loggers that record subcutaneous body temperature (BT) and heart rate (HR). Plasma and saliva were sampled for molecular analyses; specifically, saliva for cortisol concentrations, plasma for creatine kinase (CK), and lactate dehydrogenase (LDH), and plasma and saliva for c-miRNAs expression profiles. Immediately after the lambs were unloaded, the bio-loggers registered a significant (P < 0.05) spike-in HR and a drop in BT, and salivary cortisol concentrations increased significantly (P < 0.05), which indicated unloading as one of the main stressful points for the lambs. Out of the 17 miRNAs tested, 4 showed a significant difference in expression (P < 0.05). MiR-23a and -27a were both expressed in plasma and saliva, while miR-17 and -24 were most expressed in saliva after unloading. Finally, the expression of plasmatic miR-23a, -24, and 27a were significantly (P < 0.05) positively correlated with the LDH whose concentrations together with those of CK are significantly increased (P < 0.01) after unloading. The study identified the timing of a lamb’s adaptation response during and after transport, which reflected the dynamic nature of ovine plasma and salivary miRNAs during transport-induced stress, giving them the potential to be biomarkers that can be useful in animal welfare assessments.

The agricultural sector is amidst an industrial revolution driven by the integration of sensing, communication, and artificial intelligence (AI). Within this context, the internet of things (IoT) takes center stage, particularly in facilitating remote livestock monitoring. Challenges persist, particularly in effective field communication, adequate coverage, and long-range data transmission. This study focuses on employing LoRa communication for livestock monitoring in mountainous pastures in the north-western Alps in Italy. The empirical assessment tackles the complexity of predicting LoRa path loss attributed to diverse land-cover types, highlighting the subtle difficulty of gateway deployment to ensure reliable coverage in real-world scenarios. Moreover, the high expense of densely deploying end devices makes it difficult to fully analyze LoRa link behavior, hindering a complete understanding of networking coverage in mountainous environments. This study aims to elucidate the stability of LoRa link performance in spatial dimensions and ascertain the extent of reliable communication coverage achievable by gateways in mountainous environments. Additionally, an innovative deep learning approach was proposed to accurately estimate path loss across challenging terrains. Remote sensing contributes to land-cover recognition, while Bidirectional Long Short-Term Memory (Bi-LSTM) enhances the path loss model’s precision. Through rigorous implementation and comprehensive evaluation using collected experimental data, this deep learning approach significantly curtails estimation errors, outperforming established models. Our results demonstrate that our prediction model outperforms established models with a reduction in estimation error to less than 5 dB, marking a 2X improvement over state-of-the-art models. Overall, this study signifies a substantial advancement in IoT-driven livestock monitoring, presenting robust communication and precise path loss prediction in rugged landscapes.

The agricultural sector is amidst an industrial revolution driven by the integration of sensing, communication, and artificial intelligence (AI). Within this context, the internet of things (IoT) takes center stage, particularly in facilitating remote livestock monitoring. Challenges persist, particularly in effective field communication, adequate coverage, and long-range data transmission. This study focuses on employing LoRa communication for livestock monitoring in mountainous pastures in the north-western Alps in Italy. The empirical assessment tackles the complexity of predicting LoRa path loss attributed to diverse land-cover types, highlighting the subtle difficulty of gateway deployment to ensure reliable coverage in real-world scenarios. Moreover, the high expense of densely deploying end devices makes it difficult to fully analyze LoRa link behavior, hindering a complete understanding of networking coverage in mountainous environments. This study aims to elucidate the stability of Lora link performance in spatial dimensions and ascertain theextent of reliable communication coverage achievable by gateways in mountainous environments. Additionally an innovative deep learning approach was proposed to accurately estimate path loss across challenging terrains. Remote sensing contributes to land-cover recognition, while Bidirectional Long Short-Term Memory (Bi-LSTM) enhances the path loss model’s precision. Through rigorous implementation and comprehensive evaluation using collected experimental data, this deep learning approach significantly curtails estimation errors, outperforming established models. Our results demonstrate that our prediction model outperforms established models with a reduction in estimation error to less than 5dB, marking a 2X improvement over state-of-the-art models. Overall, this study signifies a substantial advancement in IoT-driven livestock monitoring, presenting robust communication and precise path loss prediction in rugged landscapes.

Farm procedures have an impact on animal welfare by activating the hypothalamic-pituitary-adrenal axis that induces a wide array of physiological responses. This adaptive system guarantees that the animal copes with environmental variations and it induces metabolic and molecular changes that can be quantified. MicroRNAs (miRNAs) play a key role in the regulation of homeostasis and emerging evidence has identified circulating miRNAs as promising biomarkers of stress-related disorders in animals. Based on a clustering analysis of salivary cortisol trends and levels, 20 ewes were classified into two different clusters. The introduction of a ram in the flock was identified as a common farm practice and reference time point to collect saliva samples. Sixteen miRNAs related to the adaptation response were selected. Among them, miR-16b, miR-21, miR-24, miR-26a, miR-27a, miR-99a, and miR-223 were amplified in saliva samples. Cluster 1 was characterized by a lower expression of miR-16b and miR-21 compared with Cluster 2 (p < 0.05). This study identified for the first time several miRNAs expressed in sheep saliva, pointing out significant differences in the expression patterns between the cortisol clusters. In addition, the trend analyses of these miRNAs resulted in clusters (p = 0.017), suggesting the possible cooperation of miR-16b and -21 in the integrated stress responses, as already demonstrated in other species as well. Other research to define the role of these miRNAs is needed, but the evaluation of the salivary miRNAs could support the selection of ewes for different profiles of response to sources of stressors common in the farm scenario.

Background Mesenchymal stem cells (MSCs) have been used therapeutically in equine medicine. MSCs release extracellular vesicles (EVs), which affect cell processes by inhibiting cell apoptosis and regulating inflammation. To date, little is known about equine EVs and their regenerative properties. Objectives To characterise equine MSC-derived extracellular vesicles (EVs) and evaluate their effect on equine chondrocytes treated with pro-inflammatory cytokines in vitro. Study design In vitro experiments with randomised complete block design. Methods Mesenchymal stem cells from bone marrow, adipose tissue, and synovial fluid were cultured in vitro. The MSC culture medium was centrifuged and filtered. Isolated particles were analysed for size and concentration (total number of particles per mL). Transmission electron microscopy analysis was performed to evaluate the morphology and CD9 expression of the particles. Chondrocytes from healthy equines were treated with the inflammatory cytokines interleukin (IL)-1β and tumour necrosis factor-alpha. MSC-derived EVs from bone marrow and synovial fluid cells were added as co-treatments in vitro. Gene expression analysis by real-time PCR was performed to evaluate the effects of EVs. Results The particles isolated from MSCs derived from different tissues did not differ significantly in size and concentration. The particles had a round-like shape and positively expressed CD9. EVs from bone marrow cells displayed reduced expression of metalloproteinase-13. Main limitations Sample size and characterisation of the content of EVs Conclusions EVs isolated from equine bone marrow MSCs reduced metalloproteinase 13 gene expression; this gene encodes an enzyme related to cartilage degradation in inflamed chondrocytes in vitro. EVs derived from MSCs can reduce inflammation and could potentially be used as an adjuvant treatment to improve tissue and cartilage repair in the articular pathologies.

Myxomatous mitral valve degeneration (MMVD) is the most common acquired cardiac disease in canine species, and valvular interstitial cells (VICs) are considered the main responsible for the development of this pathology. The scientific interest is focused on isolating and characterizing these cells. The aims of the present study were to verify a novel VICs mechanical isolation method and to characterize isolated cells using immunocytochemistry and immunofluorescence, with parallel histological and immunohistochemistry assays on bovine and canine healthy and MMVD mitral valves. Antibodies against vimentin (VIM), smooth muscle actin (SMA), von Willebrand (vW) factor, Transforming Growth Factor (TGF) β1, and Transient Receptor Potential Vanilloid 1 (TRPV1) were used. The isolation method was considered reliable and able to isolate only VICs. The different assays demonstrated a different expression of SMA in healthy and MMVD mitral valves, and TRPV1 was isolated for the first time from bovine and canine VICs and the correspondent mitral valve leaflets. The novelties of the present study are the new isolation method, that may allow correlations between laboratory and clinical conditions, and the identification of TRPV1, which will lead to further investigations to understand its function and possible role in the etiology of MMVD and to the design of new therapeutic strategies.