The University of Iowa College of Medicine histology teaching laboratory incorporates extensive Web- and computer-based teaching modalities, including the Virtual Microscope (VM), as emerging learning aids in histology and pathology laboratory instruction. We report here our experience in offering a multiple resource-based approach to laboratory instruction while retaining the opportunity and requirement of examining actual microscopic slide preparations with the microscope. Acceptance of this approach has been high among our students and faculty, and performance levels established over years of teaching histology by traditional means have been maintained.
Structure-activity relationship (SAR) models are recognized as powerful tools to predict the toxicologic potential of new or untested chemicals and also provide insight into possible mechanisms of toxicity. Models have been based on physicochemical attributes and structural features of chemicals. We describe herein the development of a new SAR modeling algorithm called cat-SAR that is capable of analyzing and predicting chemical activity from divergent biological response data. The cat-SAR program develops chemical fragment-based SAR models from categorical biological response data (e.g. toxicologically active and inactive compounds). The database selected for model development was a published set of chemicals documented to cause respiratory hypersensitivity in humans. Two models were generated that differed only in that one model included explicate hydrogen containing fragments. The predictive abilities of the models were tested using leave-one-out cross-validation tests. One model had a sensitivity of 0.94 and specificity of 0.87 yielding an overall correct prediction of 91%. The second model had a sensitivity of 0.89, specificity of 0.95 and overall correct prediction of 92%. The demonstrated predictive capabilities of the cat-SAR approach, together with its modeling flexibility and design transparency, suggest the potential for its widespread applicability to toxicity prediction and for deriving mechanistic insight into toxicologic effects.
The University of Iowa College of Medicine histology teaching laboratory incorporates extensive Web- and computer-based teaching modalities, including the Virtual Microscope (VM), as emerging learning aids in histology and pathology laboratory instruction. We report here our experience in offering a multiple resource-based approach to laboratory instruction while retaining the opportunity and requirement of examining actual microscopic slide preparations with the microscope. Acceptance of this approach has been high among our students and faculty, and performance levels established over years of teaching histology by traditional means have been maintained.
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