Influence of econazole and 5-fluorocytosine on the ultrastructure of Aspergillus fumigatus and the cytochemical localization of calcium ions as measured by laser microprobe mass analysis

The ultrastructural changes and the localization of Ca++ ions have been investigated in Aspergillus fumigatus after exposure in vitro to econazole (50 micrograms ml-1) and to 5-fluorocytosine (100 micrograms ml-1) for 24 h. The changes obtained with econazole concerned the cell periphery, necrotization of mitochondria and hyperactivity of the central vacuole. After cytochemical Ca++ localization a marked increase in precipitate was observed on mitochondria, vacuoles and collapsed membranes, compared to the control. Laser microprobe mass analysis confirmed that the measured amount of Ca++ ions corresponded to the degree of precipitate formation in the different cellular compartments. After exposure to 5-fluorocytosine, abnormal behaviour of the nuclei and internal lipidification of the mitochondria and of the cytoplasm were seen. No discernible Ca++ activity was present on the cellular structures by cytochemical localization. Assay by laser microprobe mass analysis, however, showed a slight increase in Ca++ which points to a structural bonding of the Ca++.     

Computer-assisted differential diagnosis of malignant mesothelioma based on syntactic structure analysis.

BACKGROUND: Malignant mesothelioma, a mesoderm-derived tumor, is related to asbestos exposure and remains a diagnostic challenge because none of the genetic or immunohistochemical markers have yet been proven to be specific. To assist in the identification of mesothelioma and to differentiate it from other common lesions at the same location, we have tested the performance of syntactic structure analysis (SSA) in an automated classification procedure. MATERIALS AND METHODS: Light-microscopic images of tissue sections of malignant mesothelioma, hyperplastic mesothelium, and adenocarcinoma were analyzed using parameters selected from the Voronoi diagram, Gabriel's graph, and the minimum spanning tree which were classified with a K-nearest-neighbor algorithm. RESULTS: Results showed that mesotheliomas were diagnosed correctly in 74% of the cases; 76% of the adenocarcinomas were correctly graded, and 88% of the mesotheliomas were correctly typed. The performance of the parameters was dependent on the obtained classification (i.e., tumor-tumor versus tumor-benign). CONCLUSIONS: Our results suggest that SSA is valuable in the differential classification of mesothelioma and that it supplements a visually appraised diagnosis. The recognition scores may be increased by a combination of SSA with, for example, cellular or nuclear parameters, measured at higher magnifications to form a solid base for fully automated expert systems.