Hematological Normality, Serum Biochemistry, and Acute Phase Proteins in Healthy Beef Calves in the Brazilian Savannah

The Brazilian savannah region, characterized by high average temperatures, well-defined rainy and dry seasons, soil with low productive potential, and high pressure for parasitic diseases, is home to the highest percentage of the beef herd, which is the world's largest commercial beef producer. Therefore, breeds that present rusticity combined with productivity are the focus of research in cattle breeding in the region. Considering their geographic particularities and their effects on the animals' blood parameters, the objective was to study the behavior of hematological variables, serum biochemistry, and acute phase proteins in beef calves at weaning age. Jugular blood samples were collected in a single day from 30 weaning calves (about eight months old and 200 kg of body weight) from the following breeds: Nellore, Senepol, Nellore × Aberdeen Angus cross, Nellore × Senepol cross, and Nellore × Aberdeen Angus × Senepol cross. Hematological data were obtained using an automatic cell counter, serum biochemical measurements were obtained using commercial kits, and the electrophoretogram was obtained using the SDS-page technique. In general, the results were consistent with data already published in similar situations regarding health status, age, and level of metabolic activity. However, differences observed between groups can be explained by differences observed in other concurrent variables like temperament. The pure zebu breed was more reactive than pure taurine. While crossbreds showed intermediate values, and parasitic infestation, the pure taurine breed with higher parasite infestation, while the zebu breed had lower values, which produced effects in some laboratory tests, and generated differences between breeds. In conclusion, the reference intervals available for healthy animals can be routinely used without interference from the geographic region for animals produced without nutritional failures as long as changes are recorded in pathological, infectious, metabolic, or nutritional deficiency situations. However, it is suggested that a study covering a larger number of herds may demonstrate a greater geographic effect on the studied variables.

Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases

Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock.

Sexual Dimorphic Innate Immune Response to a Viral-Bacterial Respiratory Disease Challenge in Beef Calves

The potential for sexually dimorphic innate immune responses to respiratory disease was evaluated, where eight steers and seven heifers (280 ± 4 kg) were subjected to a viral−bacterial respiratory disease challenge utilizing bovine herpesvirus-1 (BoHV-1; intranasal; 1 × 108 PFU/nostril) and Mannheimia haemolytica (MH; intratracheal; 1.3 × 107 CFU/head) administered 72 h later. Body temperature was lesser in heifers than steers (p < 0.01). There was a sex × time interaction (p = 0.05) for white blood cells where heifers had reduced concentrations compared with steers at −72 and 0 h but greater concentrations from 36 to 60 h post-MH. Concentrations of neutrophils were lesser in heifers compared to steers from 0 to 4 h, and from 8 to 12 h (p = 0.03). Lymphocytes were greater in heifers compared to steers at 12 h and from 36 to 60 h post-MH (p < 0.01). The neutrophil−lymphocyte ratio was lesser in heifers compared to steers from 2 to 24 h and at 48 h post-MH (p < 0.01). Monocytes were greater in heifers compared to steers from 24 to 60 h post-MH (p < 0.01), while eosinophils were greater in heifers compared to steers at 48 and 60 h (p < 0.01). Serum IL-4 was lesser in heifers compared to steers at 0 h and from 2 to 72 h post-MH challenge (p = 0.02). Non-esterified fatty acid concentrations were lesser (p < 0.01) in heifers compared to steers from 2 to 4 h post-MH challenge. Urea nitrogen concentrations were greater (p < 0.01) in heifers than steers at 36 h post-MH challenge. Data from this study reveal distinct differences in the acute phase response following a respiratory disease challenge where steers produced an early response, while the response in heifers appeared to be delayed.

A systematic review of the utility of biomarkers as aids in the early diagnosis and outcome prediction of bovine respiratory disease complex in feedlot cattle

Bovine respiratory disease complex (BRDC) is a common, serious problem in feedlot cattle worldwide. Early diagnosis and outcome prediction are critical for making decisions to prevent economic loss and to limit antimicrobial use. Diagnosing BRDC is commonly based on visual signs and behavioral changes; both assessments are considered to have low diagnostic accuracy. Biomarkers are important for supporting the diagnosis of BRDC, determining the necessity and potential outcomes of treatment, and assisting in research in which differentiating diseased animals is required. There are few reviews summarizing the biomarkers available and utilized. We systematically evaluated the detection and prognostic potential of biomarkers from the literature published between January 1990 and December 2020. We performed a descriptive analysis of 5 biomarker categories: acute-phase proteins, stress-related hormones, other blood biomarkers, omics biomarkers, and non-blood biomarkers. The retrieved articles consisted of studies or trials that assessed the detection value and treatment and/or outcome prediction efficacy of biomarkers for BRDC in feedlot cattle; 23 manuscripts for review and analysis satisfied the selection criteria. Based on our review, we cannot recommend a specific biomarker as the sole method for the early detection or outcome prediction for BRDC, given that the application and efficacy of biomarkers varies in different situations. Our systematic review may serve as a reference for clinical and research investigations of early detection and outcome prediction of BRDC.

Predictive Models for Weekly Cattle Mortality after Arrival at a Feeding Location Using Records, Weather, and Transport Data at Time of Purchase

Feedlot mortality negatively affects animal welfare and profitability. To the best of our knowledge, there are no publications on predictive models for weekly all-cause mortality in feedlot cattle. In this study, random forest models to predict weekly mortality for cattle purchase groups (n = 14,217 purchase groups; 860,545 animals) from arrival at the feeding location (Day 1) to Day 42 and cumulative mortality from Day 43 until slaughter were built using records, weather, and transport data available at the time of purchase. Models were evaluated by calculating the root mean squared error (RMSE) and accuracy (as defined as the percent of purchase groups that had predictions within 0.25% and 0.50% of actual mortality). The models had high accuracy (>90%), but the RMSE estimates were high (range = 1.0% to 4.1%). The best predictors were maximum temperature and purchase weight, although this varied by week. The models performed well among purchase groups with low weekly mortality but performed poorly in high mortality purchase groups. Although high mortality purchase groups were not accurately predicted utilizing the models in this study, the models may potentially have utility as a screening tool for very low mortality purchase groups after arrival. Future studies should consider building iterative models that utilize the strongest predictors identified in this study.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Differential haptoglobin responsiveness to a Mannheimia haemolytica challenge altered immunologic, physiologic, and behavior responses in beef steers

Indicator traits associated with disease resiliency would be useful to improve the health and welfare of feedlot cattle. A post hoc analysis of data collected previously (Kayser et al., 2019a) was conducted to investigate differences in immunologic, physiologic, and behavioral responses of steers (N = 36, initial BW = 386 ± 24 kg) that had differential haptoglobin (HPT) responses to an experimentally induced challenge with Mannheimia haemolytica (MH). Rumen temperature, DMI, and feeding behavior data were collected continuously, and serial blood samples were collected following the MH challenge. Retrospectively, it was determined that 9 of the 18 MH-challenged steers mounted a minimal HPT response, despite having similar leukocyte and temperature responses to other MH-challenged steers with a greater HPT response. Our objective was to examine differences in behavioral and physiological responses between MH-challenged HPT responsive (RES; n = 9), MH-challenged HPT nonresponsive (NON; n = 9), and phosphate-buffered saline-inoculated controls (CON; n = 18). Additionally, 1H NMR analysis was conducted to determine whether the HPT-responsive phenotype affected serum metabolite profiles. The RES steers had lesser (P < 0.05) cortisol concentrations than NON and CON steers. The magnitude of the increases in neutrophil concentrations and rumen temperature, and the reduction in DMI following the MH challenge were greatest (P < 0.05) in RES steers. Univariate analysis of serum metabolites indicated differences between RES, NON, and CON steers following the MH challenge; however, multivariate analysis revealed no difference between HPT-responsive phenotypes. Prior to the MH challenge, RES steers had longer (P < 0.05) head down and bunk visit durations, slower eating rates (P < 0.01) and greater (P < 0.05) daily variances in bunk visit frequency and head down duration compared with NON steers, suggesting that feeding behavior patterns were associated with the HPT-responsive phenotype. During the 28-d postchallenge period, RES steers had decreased (P < 0.05) final BW, tended (P = 0.06) to have lesser DMI, and had greater (P < 0.05) daily variances in head down and bunk visit durations compared with NON steers, which may have been attributed to their greater acute-phase protein response to the MH challenge. These results indicate that the HPT-responsive phenotype affected feeding behavior patterns and may be associated with disease resiliency in beef cattle.

Transforming the Adaptation Physiology of Farm Animals through Sensors

Simple Summary

Strategy for the protection and welfare of farm animals, and the sustainable animal production is dependent on the thorough understanding of the adaptation physiology. Real-time, continuous, and precise measurement of the multi-dimensions and complex intricacies of adaptive capacity of farm animals namely the mental, behavioral, and physiological states are possible only through the sensor-based approaches. This paper critically reviews the latest sensor technologies as assessment tools for the adaptation physiology of farm animals and explores their advantages over traditional measurement methods. Digital innovation, diagnostics, genetic testing, biosensors, and wearable animal devices are important tools that enable the development of decision support farming platforms and provides the path for predicting diseases in livestock. Sensor fusion data from a multitude of biochemical, emotional, and physiological functions of the farm animals not only helps to identify the most productive animal but also allows farmers to predict which individual animal may have greater resilience to common diseases. Insights into the cost of adoption of sensor technologies on farms including computing capacity, human resources in training, and the sensor hardware are being discussed.

Abstract

Despite recent scientific advancements, there is a gap in the use of technology to measure signals, behaviors, and processes of adaptation physiology of farm animals. Sensors present exciting opportunities for sustained, real-time, non-intrusive measurement of farm animal behavioral, mental, and physiological parameters with the integration of nanotechnology and instrumentation. This paper critically reviews the sensing technology and sensor data-based models used to explore biological systems such as animal behavior, energy metabolism, epidemiology, immunity, health, and animal reproduction. The use of sensor technology to assess physiological parameters can provide tremendous benefits and tools to overcome and minimize production losses while making positive contributions to animal welfare. Of course, sensor technology is not free from challenges; these devices are at times highly sensitive and prone to damage from dirt, dust, sunlight, color, fur, feathers, and environmental forces. Rural farmers unfamiliar with the technologies must be convinced and taught to use sensor-based technologies in farming and livestock management. While there is no doubt that demand will grow for non-invasive sensor-based technologies that require minimum contact with animals and can provide remote access to data, their true success lies in the acceptance of these technologies by the livestock industry.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Bovine Respiratory Disease: Looking Back and Looking Forward, What Do We See?

Changes in cattle feeding in the twentieth century led to the "Golden Age of Cattle Feeding" on the US High Plains; this was accompanied by recognition that bovine respiratory disease (BRD) is the leading cause of feedlot morbidity and mortality. Decades of research have illuminated the multiple viruses and bacteria that contribute to BRD, which led to vaccines and antimicrobials to prevent, treat, and control BRD. Despite these discoveries, feedlot BRD morbidities do not appear to have changed substantially over this time. New technologies are being developed that have the potential to improve accuracy of BRD detection.

Use of faecal volatile organic compound analysis for ante-mortem discrimination between CWD-positive, -negative exposed, and -known negative white-tailed deer (Odocoileus virginianus)

Chronic wasting disease (CWD) is a naturally occurring infectious, fatal, transmissible spongiform encephalopathy of cervids. Currently, disease confirmation relies on post-mortem detection of infectious prions in the medial retropharyngeal lymph nodes or obex in the brain via immunohistochemistry (IHC). Detection of CWD in living animals using this method is impractical, and IHC and other experimental assays are not reliable in detecting low concentrations of prion present in biofluids or faeces. Here, we evaluate the capability of faecal volatile organic compound analysis to discriminate between CWD-positive and -exposed white-tailed deer located at two positive cervid farms, and two groups of CWD-negative deer from two separate disease-free farms.

Recent advancement in biosensors technology for animal and livestock health management

The term biosensors encompasses devices that have the potential to quantify physiological, immunological and behavioural responses of livestock and multiple animal species. Novel biosensing methodologies offer highly specialised monitoring devices for the specific measurement of individual and multiple parameters covering an animal's physiology as well as monitoring of an animal's environment. These devices are not only highly specific and sensitive for the parameters being analysed, but they are also reliable and easy to use, and can accelerate the monitoring process. Novel biosensors in livestock management provide significant benefits and applications in disease detection and isolation, health monitoring and detection of reproductive cycles, as well as monitoring physiological wellbeing of the animal via analysis of the animal's environment. With the development of integrated systems and the Internet of Things, the continuously monitoring devices are expected to become affordable. The data generated from integrated livestock monitoring is anticipated to assist farmers and the agricultural industry to improve animal productivity in the future. The data is expected to reduce the impact of the livestock industry on the environment, while at the same time driving the new wave towards the improvements of viable farming techniques. This review focusses on the emerging technological advancements in monitoring of livestock health for detailed, precise information on productivity, as well as physiology and well-being. Biosensors will contribute to the 4th revolution in agriculture by incorporating innovative technologies into cost-effective diagnostic methods that can mitigate the potentially catastrophic effects of infectious outbreaks in farmed animals.

Use of fecal volatile organic compound analysis to discriminate between non-vaccinated and BCG-Vaccinated cattle prior to and after Mycobacterium bovis challenge

Bovine tuberculosis is a zoonotic disease of global public health concern. Development of diagnostic tools to improve test accuracy and efficiency in domestic livestock and enable surveillance of wildlife reservoirs would improve disease management and eradication efforts. Use of volatile organic compound analysis in breath and fecal samples is being developed and optimized as a means to detect disease in humans and animals. In this study we demonstrate that VOCs present in fecal samples can be used to discriminate between non-vaccinated and BCG-vaccinated cattle prior to and after Mycobacterium bovis challenge.

Biomarkers for differentiation of causes of respiratory distress in dogs and cats: Part 2--Lower airway, thromboembolic, and inflammatory diseases

OBJECTIVES

To review the current veterinary and relevant human literature regarding biomarkers of respiratory diseases leading to dyspnea and to summarize the availability, feasibility, and practicality of using respiratory biomarkers in the veterinary setting.

DATA SOURCES

Veterinary and human medical literature: original research articles, scientific reviews, consensus statements, and recent textbooks.

HUMAN DATA SYNTHESIS

Numerous biomarkers have been evaluated in people for discriminating respiratory disease processes with varying degrees of success.

VETERINARY DATA SYNTHESIS

Although biomarkers should not dictate clinical decisions in lieu of gold standard diagnostics, their use may be useful in directing care in the stabilization process. Serum immunoglobulins have shown promise as an indicator of asthma in cats. A group of biomarkers has also been evaluated in exhaled breath. Of these, hydrogen peroxide has shown the most potential as a marker of inflammation in asthma and potentially aspiration pneumonia, but methods for measurement are not standardized. D-dimers may be useful in screening for thromboembolic disease in dogs. There are a variety of markers of inflammation and oxidative stress, which are being evaluated for their ability to assess the severity and type of underlying disease process. Of these, amino terminal pro-C-type natriuretic peptide may be the most useful in determining if antibiotic therapy is warranted. Although critically evaluated for their use in respiratory disorders, many of the biomarkers which have been evaluated have been found to be affected by more than one type of respiratory or systemic disease.

CONCLUSION

At this time, there are point-of-care biomarkers that have been shown to reliably differentiate between causes of dyspnea in dogs and cats. Future clinical research is warranted to understand of how various diseases affect the biomarkers and more bedside tests for their utilization.

Application of Functional Genomics for Bovine Respiratory Disease Diagnostics

Bovine respiratory disease (BRD) is the most common economically important disease affecting cattle. For developing accurate diagnostics that can predict disease susceptibility/resistance and stratification, it is necessary to identify the molecular mechanisms that underlie BRD. To study the complex interactions among the bovine host and the multitude of viral and bacterial pathogens, as well as the environmental factors associated with BRD etiology, genome-scale high-throughput functional genomics methods such as microarrays, RNA-seq, and proteomics are helpful. In this review, we summarize the progress made in our understanding of BRD using functional genomics approaches. We also discuss some of the available bioinformatics resources for analyzing high-throughput data, in the context of biological pathways and molecular interactions. Although resources for studying host response to infection are avail-able, the corresponding information is lacking for majority of BRD pathogens, impeding progress in identifying diagnostic signatures for BRD using functional genomics approaches.

Use of Antimicrobial Metaphylaxis for the Control of Bovine Respiratory Disease in High-Risk Cattle

Despite research and increased availability of antimicrobials, the prevalence and challenges associated with BRD in stocker and feedlot operations remain. Preconditioned calves can better handle the transition from the origin ranch to the feedlot, yet there is incentive for buyers to purchase high-risk cattle at a reduced cost, and this is influenced by the proven efficacy and availability of antimicrobial metaphylaxis. The poor sensitivity of current BRD field diagnostic methods, typical pathogenesis of BRD, and labor issues are additional reasons to use metaphylaxis. Nevertheless, practitioners should consider comprehensive and novel approaches to judiciously guide decisions on metaphylactic use of antimicrobials.

The clinical syndrome of BRD: what it is and what it is not

The clinical syndrome of bovine respiratory disease (BRD) continues to be a major challenge in bovine production systems. We are challenged by our ability to predict morbidity in groups of cattle, our ability to accurately diagnose and provide a prognosis for individual cases, and our ability to evaluate the results of preventive and therapeutic interventions in the field when production system data are the sole basis for analysis. However, we are fortunate to have perhaps the highest quantity and quality of negative-controlled, prospective, randomized, and masked clinical trial data for any disease in veterinary medicine. It is nevertheless important to recognize that case definitions in these studies may not be consistent or necessarily externally relevant, and that production data in these studies are often missing.

A pilot study exploring the use of breath analysis to differentiate healthy cattle from cattle experimentally infected with Mycobacterium bovis

Bovine tuberculosis, caused by Mycobacterium bovis, is a zoonotic disease of international public health importance. Ante-mortem surveillance is essential for control; however, current surveillance tests are hampered by limitations affecting ease of use or quality of results. There is an emerging interest in human and veterinary medicine in diagnosing disease via identification of volatile organic compounds produced by pathogens and host-pathogen interactions. The objective of this pilot study was to explore application of existing human breath collection and analysis methodologies to cattle as a means to identify M. bovis infection through detection of unique volatile organic compounds or changes in the volatile organic compound profiles present in breath. Breath samples from 23 male Holstein calves (7 non-infected and 16 M. bovis-infected) were collected onto commercially available sorbent cartridges using a mask system at 90 days post-inoculation with M. bovis. Samples were analyzed using gas chromatography-mass spectrometry, and chromatographic data were analyzed using standard analytical chemical and metabolomic analyses, principle components analysis, and a linear discriminant algorithm. The findings provide proof of concept that breath-derived volatile organic compound analysis can be used to differentiate between healthy and M. bovis-infected cattle.

The non-invasive and automated detection of bovine respiratory disease onset in receiver calves using infrared thermography

Bovine respiratory disease complex (BRD) causes considerable economic loss and biosecurity cost to the beef industry globally and also results in significant degradation to the welfare of affected animals. The successful treatment of this disease depends on the early, timely and cost effective identification of affected animals. The objective of the present study was to investigate the use of an automated, RFID driven, noninvasive infrared thermography technology to determine BRD in cattle. Sixty-five calves averaging 220 kg were exposed to standard industry practices of transport and auction. The animals were monitored for BRD using conventional biometric signs for clinical scores, core temperatures, haematology, serum cortisol and infrared thermal values over 3 weeks. The data collected demonstrated that true positive animals for BRD based on a gold standard including core temperature, clinical score, white blood cell number and neutrophil/lymphocyte ratio displayed higher peak infrared thermal values of 35.7±0.35 °C compared to true negative animals 34.9±0.22 °C (P<0.01). The study also demonstrated that such biometric data can be non-invasively and automatically collected based on a system developed around the animal's water station. It is concluded that the deployment of such systems in the cattle industry would aid animal managers and practitioners in the identification and management of BRD in cattle populations.

The application of exhaled breath gas and exhaled breath condensate analysis in the investigation of the lower respiratory tract in veterinary medicine: A review

The analysis of biomarkers in exhaled breath (EB) and exhaled breath condensate (EBC) may allow non-invasive and repeatable assessment of respiratory health and disease in mammals. Compared to human medicine, however, research data from EB and EBC analysis in veterinary medicine are limited and more patient variables influencing concentrations of EB/EBC analytes may be present. In addition, variations in methodologies between studies may influence results. A comparison of the approaches used in veterinary research by different groups may aid in the identification of potentially reliable and repeatable biomarkers suitable for further investigation. To date, changes in acid-base status and increased concentrations of inflammatory mediators have been the main findings in studies of pulmonary disease states in animals. Whilst these biomarkers are unlikely to represent specific and sensitive diagnostic parameters, they do have potential application in monitoring disease progression and treatment response.