Non-invasive strategies in monitoring of animal health - diagnostic and immunological data of pigs using novel biological matrices
Abstract
[ENG:]The dataset contains research results on the use of novel biological matrices obtained from pigs for the diagnosis of infectious diseases and the assessment of their immune status. The data were collected within a research project conducted in commercial pig herds maintained in a closed farrow-to-finish system.The deposited data are provided in CSV, and ZIP formats. ZIP archives contain organized sets of raw data files, grouped by biological matrix (serum, colostrum, processing fluid), production group, and type of analyzed parameters. Each record includes basic descriptive metadata for the sample, including the measured parameter, production group, and type of biological material. The data contained in ZIP archives with Tables A are associated with the publication: Augustyniak A, Czyżewska-Dors E, Pomorska-Mól M. Concentrations of selected immunological parameters in the serum and processing fluid of suckling piglets and the serum and colostrum of their mothers. BMC Vet Res. 2024 May 3;20(1):170. The data contained in ZIP archives with Tables B are associated with the publication: Augustyniak A, Czyżewska-Dors E, Pomorska-Mól M. Field study on the utility of fluid obtained from testicles as a sample for detecting antibodies to selected swine pathogens. Sci Rep. 2025;15(1):22402. The dataset includes results from commercial diagnostic assays used to measure immunological parameters (immunoglobulins, cytokines, acute phase proteins) and to detect infections with selected porcine pathogens. Data were processed using spreadsheet software (Microsoft Excel) and laboratory software Magellan v.7.2 (Tecan). The dataset documentation provides explanations of abbreviations, parameter names, and measurement units.
Fields of Study & Subjects
Animal health and immunology
Animal Virus Infections Studies
Veterinary medicine and infectious diseases
Publication details
- Journal / source
- RepOD
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Dataset