Animal health and welfare are fundamental premises from both a social and scientific perspective. This principle applies to any animal species, whether pets, livestock, wildlife, or laboratory animals. Appropriate management of these populations is crucial to prevent health issues that could compromise their quality of life. Early diagnosis of diseases plays a key role in their effective management and progression. Pathological conditions not only directly impact animal welfare but may also interfere with various physiological functions, such as reproduction, leading to infertility, which is an especially critical concern for endangered species. In addition, the impairment of the immune system makes animals more susceptible to various diseases, with zoonotic diseases being especially relevant. Therefore, preventing and early detecting diseases are essential, as they pose a direct threat to public health and undermine biodiversity conservation efforts. To address these challenges, it is imperative to develop and implement new, rapid, and accurate methods for identifying biomarkers for the early diagnosis of pathological states affecting animal health and welfare.
This Research Topic highlights the need for more accurate and rapid methods to identify health issues in animals early. The development and validation of new diagnostic methods for the early identification of health loss from different matrices (blood, saliva, urine, feces, hair, or tissues) will be crucial in managing animal health and welfare. Early diagnosis will be key to preventing a decline in animal health, or at least reducing the degree of discomfort, by applying management protocols and high welfare standards that directly influence the maintenance of a stable state of health. The identification of new biomarkers, the development and validation of new biochemical techniques, the development and validation of new diagnostic imaging techniques, or the application of artificial intelligence are positioned as major challenges in current predictive biomedicine. All these topics are very relevant for predicting, improving, and guaranteeing the maintenance of animal health.
To gather further insights within the scope of veterinary diagnostics and disease prediction, we welcome articles addressing, but not limited to, the following themes:
• Application of artificial intelligence as a predictive method in the early detection of diseases in animals • New approaches to chromatography in disease diagnosis • The application of immunoassays in the preliminary assessment of health status • Use of -omics techniques in the early identification of biomarkers of health loss. • Development of new methods/assays and analytical validations in the identification of indicator parameters of alteration of health status. • Hormonal monitoring and its relationship with pathologies • Implementation and development of new non-invasive techniques for early disease detection • Predictive studies of disease based on early biomarkers of loss of welfare and its implication in animal health • Studies on the influence of diseases on reproductive efficiency and implications for biodiversity. • Studies on the impact of animal welfare on the appearance of emerging zoonoses • Prevention, prevalence and diagnosis studies of emerging diseases
Original research articles, short communications, review articles, and case reports will be accepted.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Clinical Trial
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
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Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.