RESUMEN
In order to evaluate the sIgA-ELISA method reported previously for differentiating Mycoplasma hyopneumoniae (M. hyopneumoniae) infected from vaccinated pigs, dynamics of anti-M. hyopneumoniae secretory IgA (sIgA) antibody secretion in nasal mucus and IgG antibodies in serum from 10 pigs experimentally infected with M. hyopneumoniae or vaccinated with an inactivated vaccine were examined using sIgA-ELISA and a commercial M. hyopneumoniae antibody detection kit (IgG-ELISA), respectively. In addition, nasal swabs and serum samples from 2368 pigs of different ages originating from 10 pig farms with different M. hyopneumoniae infection and vaccination status were examined using the two ELISA. In the experimental model, anti-M. hyopneumoniae IgG antibodies were detected in both, the challenge group and the vaccine group. Anti-M. hyopneumoniae sIgA antibodies were detected in the challenge group from 7 days post challenge onwards, but not in the vaccine group. According to the data obtained from pig farms maintaining administration of inactivated vaccine, the prevalence of anti-M. hyopneumoniae sIgA antibody positive pigs was significantly lower than that of IgG antibody positive pigs. In non-vaccinating herds, the prevalence of sIgA antibodies was correlated with the severity of clinical symptoms typical for porcine enzootic pneumonia. In all suckling pigs, no matter vaccinated or not, the prevalence of anti-M. hyopneumoniae sIgA antibody positives was significantly lower than that of IgG antibody positives. These results prove that the sIgA-ELISA is a valuable method enabling the surveillance of M. hyopneumoniae infections in pig herds without interference due to maternally derived antibodies or antibodies induced by administration of inactivated vaccines.
Asunto(s)
Ensayo de Inmunoadsorción Enzimática/veterinaria , Inmunoglobulina A Secretora/sangre , Mycoplasma hyopneumoniae/clasificación , Neumonía Porcina por Mycoplasma/prevención & control , Enfermedades de los Porcinos/prevención & control , Animales , Femenino , Masculino , Mycoplasma hyopneumoniae/inmunología , Mycoplasma hyopneumoniae/aislamiento & purificación , Neumonía Porcina por Mycoplasma/diagnóstico , Neumonía Porcina por Mycoplasma/microbiología , Porcinos , Enfermedades de los Porcinos/microbiología , Vacunación/veterinaria , Vacunas de Productos Inactivados/inmunologíaRESUMEN
Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST.