ABSTRACT
Multilocus enzyme electrophoresis was used to determine genetic relationships amongst 32 intestinal spirochaetes (Serpulina spp.) isolated from rats (17), rheas (7), chickens, (4), ducks (2), a swan (1) and a flamingo (1). The strains were divided into 20 electrophoretic types (ETs), with a mean genetic diversity per locus of 0.62. The results were compared with those previously published for porcine intestinal spirochaetes. One strain from a healthy rat, and three rhea strains which were recovered from cases of necrotizing typhlitis, were grouped in the same ETs as certain porcine strains of Serpulina hyodysenteriae. The rhea strains could be differentiated from these by pulsed-field gel electrophoresis. Fifteen of the rat strains were genetically and phenotypically closely related. In contrast the avian strains were genetically more heterogeneous, with pathogenic isolates located in three different genetic groups.
Subject(s)
Brachyspira/genetics , Enzymes/genetics , Intestines/microbiology , Alleles , Animals , Bacteriological Techniques , Birds , Brachyspira/isolation & purification , Chickens , DNA, Bacterial/analysis , Ducks , Electrophoresis, Gel, Pulsed-Field , Phylogeny , Polymorphism, Restriction Fragment Length , Rats , SwineABSTRACT
We have implemented a diagnostic system designed to advise on the likely causes of sanitary problems with public water sources. The approach to the problem makes extensive use of rule based expert systems and multi media information (maps, data, text, expert knowledge). The rules were based on actual water survey data, with a weighting scheme designed to highlight causes of health risks approximately in reverse order of importance (where such order may be presumed to exist). Out put is a vailable in one of several languages.
ABSTRACT
Data from over 2000 stations and knowledge from experts on atmospheric transport, soil geochemistry, lake chemistry, wetland processes and acidification modelling were assembled in an expert system. The data were grouped by aggregates of tertiary watersheds based on water chemistry knowledge. A set of expert rules was used to determine which of six existing models was most appropriate for a given set of data. Comparison of computed and observed alkalinity indicated median relative errors from 11.3-17.9%, with regression slopes ranging from 0.91-1.18 and regression coefficients between 0.82 and 0.99. The expert model performance was further confirmed with paleolimnological data and other independent sets of data. The sensitivity of the predicted alkalinity was illustrated by changing some of the rules. Given that the rules were acceptable by experts and produced reasonable agreement with observations, the knowledge-based system seemed a viable approach to the impact assessment of acidic deposition.
