Exploring the intricacies of Pasteurella multocida dynamics in high-altitude livestock and its consequences for bovine health: A personal exploration of the yak paradox.

Pasturella multocida (P. multocida), a gram-negative bacterium, has long been a focus of interest in animal health because of its capacity to cause different infections, including hemorrhagic septicemia. Yaks, primarily found in high-altitude environments, are among the several livestock animals affected by these bacteria. Yaks are essential to the socioeconomic life of the people who depend on them since they are adapted to the cold and hypoxic conditions of highland environments. Nevertheless, these terrains exhibit a greater incidence of P. multocida despite the severe environmental complications. This predominance has been linked to the possible attenuation of the yak's immunological responses in such circumstances and the evolution of some bacterial strains to favor survival in the respiratory passages of the animals. Moreover, these particular strains threaten other cattle populations that interact with yaks, which might result in unanticipated outbreaks in areas previously thought to be low risk. Considering these findings, designing and executing preventative and control strategies suited explicitly for these distinct biological environments is imperative. Through such strategies, yaks' health will be guaranteed, and a larger bovine population will be safeguarded against unanticipated epidemics. The current review provides thorough insights that were previously dispersed among several investigations. Its distinct method of connecting the ecology of yaks with the dynamics of infection offers substantial background information for further studies and livestock management plans.

Fecal microbiota of diarrheic calves: Before, during, and after recovering from disease.

BACKGROUND: It is unknown if gastrointestinal dysbiosis in diarrheic calves causes disease or is a consequence of the disease. OBJECTIVES: Describe the fecal microbiota of calves before, during, and after recovering from diarrhea. ANIMALS: Fifteen female Holstein calves of 0 to 21 days old from a single farm. Seven calves remained healthy throughout the study, and 8 developed diarrhea on Day 14. METHODS: Longitudinal cohort study. Microbiota composition was characterized by amplifying the V4 region of the 16S rRNA gene. RESULTS: Diversity (Shannon index) increased with age in healthy and diarrheic calves from Day 3 to 21, but diarrheic calves had a lower diversity on the day diarrhea was first observed (Day 14). By Day 21, diversity increased in calves that recovered from diarrhea and was not significantly different from that of their healthy counterparts (P > .05). Weighted UniFrac distance showed significant differences in the fecal microbiota between diarrheic and healthy calves at Day 14 of age (PERMANOVA, P < .05), but not before or after diarrhea (PERMANOVA, P > .05). Lactobacillus, Clostridium Sensu Stricto 1, and Collinsella were differentially abundant on Day 10 in calves that developed diarrhea on Day 14 (P < .05). CONCLUSION AND CLINICAL IMPORTANCE: The fecal microbiota of healthy and diarrheic calves evolved similarly during the first 10 days of age but differed significantly on the day of onset of diarrhea. Enriching Lactobacillus, Clostridium Sensu Stricto 1, and Collinsella before diarrhea onset could have been contributed to the development of diarrhea.

Meta-analysis of prevalence of paratuberculosis in cattle using published estimates under serum and milk ELISA.

Johne's disease (JD), caused by Mycobacterium avium subspecies paratuberculosis (MAP), poses significant challenges to the global livestock industry, particularly affecting bovine populations. To better understand the prevalence of paratuberculosis and its diagnostic nuances, a comprehensive meta-analysis was conducted. This analysis encompassed 21 studies involving 632,767 cows for milk enzyme-linked immunosorbent assay (ELISA) and 51 studies involving 256,409 cows for serum ELISA. The pooled prevalence estimate for paratuberculosis on a cow-basis was found to be 16% (95% CI: 14%; 18%) for milk ELISA and 8% (95% CI: 7%; 8%) for serum ELISA. Notably, higher confidence intervals (CI) were observed in milk ELISA, the Europe and Asia groups, suggesting variability in prevalence estimates within these regions. Conversely, lower CIs were noted in the USA and Canada groups, indicating greater consistency in prevalence estimates within these countries. However, serum ELISA exhibited high CI values across all regions, underscoring potential variability in diagnostic performance. These findings provide valuable insights for veterinarians, researchers, policymakers, and livestock producers in optimizing paratuberculosis detection and control strategies to mitigate its impact on bovine health and agricultural productivity.

Early Detection of Lumpy Skin Disease in Cattle Using Deep Learning-A Comparative Analysis of Pretrained Models.

Lumpy Skin Disease (LSD) poses a significant threat to agricultural economies, particularly in livestock-dependent countries like India, due to its high transmission rate leading to severe morbidity and mortality among cattle. This underscores the urgent need for early and accurate detection to effectively manage and mitigate outbreaks. Leveraging advancements in computer vision and artificial intelligence, our research develops an automated system for LSD detection in cattle using deep learning techniques. We utilized two publicly available datasets comprising images of healthy cattle and those with LSD, including additional images of cattle affected by other diseases to enhance specificity and ensure the model detects LSD specifically rather than general illness signs. Our methodology involved preprocessing the images, applying data augmentation, and balancing the datasets to improve model generalizability. We evaluated over ten pretrained deep learning models-Xception, VGG16, VGG19, ResNet152V2, InceptionV3, MobileNetV2, DenseNet201, NASNetMobile, NASNetLarge, and EfficientNetV2S-using transfer learning. The models were rigorously trained and tested under diverse conditions, with performance assessed using metrics such as accuracy, sensitivity, specificity, precision, F1-score, and AUC-ROC. Notably, VGG16 and MobileNetV2 emerged as the most effective, achieving accuracies of 96.07% and 96.39%, sensitivities of 93.75% and 98.57%, and specificities of 97.14% and 94.59%, respectively. Our study critically highlights the strengths and limitations of each model, demonstrating that while high accuracy is achievable, sensitivity and specificity are crucial for clinical applicability. By meticulously detailing the performance characteristics and including images of cattle with other diseases, we ensured the robustness and reliability of the models. This comprehensive comparative analysis enriches our understanding of deep learning applications in veterinary diagnostics and makes a substantial contribution to the field of automated disease recognition in livestock farming. Our findings suggest that adopting such AI-driven diagnostic tools can enhance the early detection and control of LSD, ultimately benefiting animal health and the agricultural economy.

Flow of information for bovine health surveillance: Two socio-economic models demonstrating the impact of the organisational profiles of local actors.

Passive surveillance is based on spontaneous reporting to veterinary authorities of disease suspicions by farmers and other stakeholders in animal production. Stakeholders are considered "actors" in sociology of organisations research. In veterinary public health, passive surveillance is considered to be the most effective method to detect disease outbreaks and to generate epidemiological information for decision-making on surveillance and control strategies. Nevertheless, under-reporting of cases is an inherent problem, reducing the ability of the system to rapidly detect infected animals. Previous studies have shown, for example, that passive surveillance for bovine brucellosis in France, through compulsory reporting of all bovine abortions, has limited sensitivity, with variability in reporting rates despite similar cattle farming profiles. Based on this observation and on sociological literature in health surveillance, we hypothesised that oversight organisational factors in different areas influence health actor contributions to passive surveillance. Therefore, to improve the efficiency of surveillance systems, we need to understand the organisational levers (supporting factors) and organisational drags (hindering factors) on the production and dissemination of health information. We conducted semi-structured interviews with the surveillance actors in two administrative geographic divisions in France (Departments A and B) with similar cattle farming profiles but contrasting abortion reporting rates (low and high, respectively). We assumed that these rates were related to health actor organisation in each administrative division. We mapped actor relationships and looked for behavioural recurrences and differences between the two departments. This analysis led to two socio-economic models explaining the configurations observed: pro-curative in Department A, and pro-preventive in Department B. These models showed a link between the level of competition endured by veterinarians on the sale of veterinary medicinal products and the overall contribution of the actors to health surveillance. The pro-preventive model had a higher contribution to surveillance than the pro-curative model. Importantly, the nature of the information produced in this configuration of actors corresponded to the needs of surveillance, providing collective and early information that circulated more readily between actors. We highlighted three characteristics that help to identify the configuration of a system of actors: 1) the pressure of competition exerted on veterinarian activities; 2) the dominant business model and form of organisation of veterinary clinics; and 3) the frequency of interactions between the main surveillance actors outside of crises. The first two characteristics affect the local contribution to data reporting for surveillance, and the third affects network responsiveness in a health crisis.

Analytical approaches for detection of breath VOC biomarkers of cattle diseases -A review.

Diagnosis of diseases in cattle at early stages is of significance both economically and clinically. Non-invasive diagnostic samples such as breath are preferred since they cause minimum inconvenience or pain to the animals. In this review, different sampling devices, sample preparation techniques, instrumentation, and statistical analysis approaches that have been designed and tested are described and compared in terms of their applicability in the diagnosis of common cattle diseases. The sample preparation techniques used include solid-phase microextraction (SPME), sorbent extraction, and needle trap device (NTD). The collected volatile organic compounds (VOCs) are determined using gas chromatography-mass spectrometry (GC-MS) and the electronic nose (e-nose) technology. The majority of studies are focused on the diagnosis of ketosis and bovine respiratory disease (BRD). The common diseases and potential biomarkers are summarized and discussed. Due to the differences in the number of subjects and the type of animals used in different studies, the results are not consistent. Acetone, although detected in almost all studies and subjects, has elevated concentrations in cattle suffering from ketosis. The results of currently available studies were not indicative of specific biomarkers for BRD, and further investigation is required. The current studies have shortcomings in regards to defining useful VOC profiles, the impact on animal welfare, and the practical application at the producer level. While the presented approaches are promising, more controlled, standardized clinical studies need to be conducted before breath analysis can be routinely performed on cattle.

Stakeholder perceptions of non-regulatory bovine health issues in Ireland: past and future perspectives.

BACKGROUND: In recent years, there have been multiple (political, environmental, cultural) drivers of change in Irish agriculture, including the establishment of Animal Health Ireland (AHI) in 2009, to provide leadership of non-regulatory livestock health issues (diseases and conditions of livestock that are endemic in Ireland but which are not currently subject to international legislation). In this study, we describe the opinion of stakeholders (farmers, veterinary practitioners and agricultural industry professional service providers), elicited by means of a survey, on their perceptions of changes in selected non-regulatory bovine health issues over the last 10 years and priority issues relevant to non-regulatory bovine health to be tackled over the next 10 years. RESULTS: A total of 673 individuals participated in the online questionnaire. For the majority of the non-regulatory bovine health issues, most participants felt there had been improvements over the last 10 years. However, professional service providers were generally more conservative in their response to improvements on-farm compared to farmers. Several issues, particularly BVD and udder health/milk quality, were viewed more positively by all relevant respondents. There was reasonable agreement between responses from different respondent types and sectors regarding the top three priorities relevant to non-regulatory bovine animal health for the next 10 years in Ireland, which included antimicrobial resistance (highlighting measures to reduce both on-farm usage and resistance), anthelmintic resistance, greenhouse emissions and calf welfare. CONCLUSIONS: The results are encouraging, demonstrating a perception of improvement in a number of non-regulatory bovine health issues in Ireland over the last ten years. With respect to the next 10 years, stakeholders prioritised antimicrobial and anthelmintic resistance, greenhouse gas emissions and calf welfare, which aligns closely with broader societal concerns. This information is useful to AHI, particularly with respect to future priorities. However, these concerns are broad in scope and will require further considerations, including collaborations, between AHI and partnering organisations. Given that there were differences between farmers and professional service providers in responses, it is useful to consider how the aims and the benefits of future AHI programmes are framed and communicated to all stakeholders.

A Participatory Investigation of Bovine Health and Production Issues in Pakistan.

Systems to record the frequency of animal health events in Pakistan are limited. A participatory approach was used to address gaps in farmers' knowledge and understanding of bovine health and production issues in five agroecological zones (AEZs) of Pakistan. Participatory tools, including simple ranking, pairwise ranking, constraint impact scoring, and constraint profiling were used in group discussions with farmers and animal health professionals (AHPs) in six districts of two provinces, Punjab and Sindh. The results of the ranking activities showed that foot-and-mouth disease (FMD), clinical mastitis, ticks, hemorrhagic septicemia, reproductive disorders, blackleg, and endoparasites were the most important bovine health and production constraints for small-scale dairy farmers. Constraint impact scoring showed that the participants perceived that: (1) milk production was severely affected by FMD and mastitis; (2) blackleg and parasitism led to poor growth rates and reduced meat production; (3) reproductive disorders and mastitis caused major economic losses (due to the high cost of treatment); and (4) blackleg and hemorrhagic septicemia were the leading causes of mortality in cattle and buffaloes. Although there was strong agreement in responses and constraint impact scores between farmers and AHPs, farmers were more concerned about health issues that cause high mortalities, whereas AHPs emphasized the importance of disorders with a high economic impact. Despite socioeconomic differences among AEZs, farmers' knowledge about bovine health and production constraints was similar. The findings from this study revealed that farmers had limited understanding of the risk factors and routes of transmission of various infectious diseases of bovines, which emphasizes the need to develop and implement tailored extension programs in Pakistan to control contagious diseases of animals and to improve the profitability of small-scale dairy farmers.