Search PubMed⌕ Search

Biomedical subjects

A M Mortimer

Publications and source records attributed to A M Mortimer.

25 records · Page 2Linked to original sources
PubMed1990

The positive:negative dichotomy in schizophrenia.

Two studies are reported. In the first, of 62 schizophrenic patients, no correlation between negative symptom scores (rated blindly) and any measure of positive symptoms was found. This independence was confirmed by factor and cluster analyses, which left the question of a third 'disorganisation' class of schizophrenic symptoms open. In the second study, of 80 patients, formal thought disorder separated unequivocally into 'positive formal thought disorder' and 'alogia' syndromes on the basis of correlations with positive and negative symptoms. Catatonic motor disorder also showed evidence of a corresponding positive: negative division, although this only emerged when severity or chronicity of illness was controlled for. Cognitive impairment showed a broad range of affiliations and its particular correlation with negative symptoms was perhaps artefactual.

Adult↗
PubMed1989

New probability matrices for identification of Streptomyces.

The character state data obtained for clusters defined in a previous phenetic classification were used to construct two probabilistic matrices for Streptomyces species. These superseded an original published identification matrix by exclusion of other genera and the inclusion of more Streptomyces species. Separate matrices were constructed for major and minor clusters. The minimum number of diagnostic characters for each matrix was selected by computer programs for determination of character separation indices (CHARSEP) and a selection of group diagnostic properties (DIACHAR). The resulting matrices consisted of 26 phena x 50 characters (major clusters) and 28 phena x 39 characters (minor clusters). Cluster overlap (OVERMAT program) was small in both matrices. Identification scores were used to evaluate both matrices. The theoretically best scores for the most typical example of each cluster (MOSTTYP program) were all satisfactory. Input of test data for randomly selected cluster representatives resulted in correct identification with high scores. The major cluster matrix was shown to be practically sound by its application to 35 unknown soil isolates, 77% of which were clearly identified. The minor cluster matrix provides tentative probabilistic identifications as the small number of strains in each cluster reduces its ability to withstand test variation. A diagnostic table for single-membered clusters, constructed using the CHARSEP and DIACHAR programs, was also produced.

Computers↗
PubMed1989

Detecting aberrant strains in bacterial groups as an aid to constructing databases for computer identification.

Computer assisted identification systems require that databases on the test results of the species are of high quality. One reason for poor quality is the inadvertent inclusion of strains that do not belong to a taxon; this can readily occur in groups where ancillary criteria (e.g. serology) are not available. A possible strategy is to exclude strains that are very atypical in their properties, i.e. that are very outlying, provided an objective criterion can be used. A computer program, OUTLIER, for the detection of outlying strains in bacterial clusters was evaluated. A brief description of the theory and operation of the program is given. The program uses as an objective criterion the degree to which the strain data fits a chi-square. This allows easy identification of aberrant strains that should be excluded in constructing a database. The program utilizes 1.0 data and calculations are based upon a choice of one of four identification coefficients. The relative merits of these four coefficients were examined for eight sets of bacterial data. Two of the coefficients, -log10 Willcox likelihood and Taxonomic distance squared appear to show little significant differences and we recommend these for routine work, with the first being the more useful. The Pattern distance squared was useful in indicating where atypical strains may be metabolically less active or slow-growing members of a cluster rather than true outliers. The Variance-weighted Taxonomic distance squared behaved anomalously and we do not recommend it.

Bacteria↗
PubMed1983

A probability matrix for identification of some Streptomycetes.

The character state data obtained for clusters defined at the 77.5% SSM similarity level in the phenetic numerical classification described by Williams et al. (1983) were used to construct a probabilistic identification matrix. The 23 phena included were the major clusters (19 Streptomyces, 2 Streptoverticillium and 'Nocardia' mediterranea) and one minor cluster (Streptomyces fradiae). The characters most diagnostic for these clusters were selected using Sneath's CHARSEP and DIACHAR programs. The resulting matrix consisted of 41 characters x 23 phena. Identification scores, determined by Sneath's MATIDEN program were used to evaluate the matrix. Theoretical assessment was achieved by determination of the cluster overlap (OVERMAT), the identification scores for the Hypothetical Medium Organism of each cluster (MOSTTYP), and the scores for randomly selected cluster representatives using the classification data of Williams et al. (1983). The matrix was evaluated practically by the independent re-determination of the characters for the same cluster representatives, which also provided a measure of test error. Finally it was used to identify unknown isolates from a range of habitats. The results showed that the matrix was theoretically sound. Test error was within acceptable limits and did not distort identifications. Of the unknown isolates, 80% were clearly identified with a cluster. It is suggested that the matrix could form the basis for a more objective identification and grouping of the large number of Streptomyces species which have been described.

Drug Resistance, Microbial↗