[Biological evaluation of the aggressiveness of copper slag dust]. / Biologiczna ocena agresywnosci pylu zuzla pomiedziowego.

By hemolytic, intraperitoneal and intratracheal tests, biological effects of the copper slag dust, which has recently been used in casts cleaning processes, have been investigated. It was found that the copper slag dust is not biologically inert. It exhibits slight fibrogenic properties resulting in fibrous changes after lung administration. The fibrosis resembles that of collagenosis. The fibrous reaction, in form of granulomas with developed procollagenic fibres, was found on intraperitoneal dust administration. Three and six months after intratracheal insufflation of 50 mg of the dust a significant increase in the content of hydroxyproline and lipids in lungs, as compared to controls, was found. Histopathological test revealed the connective tissue multiplication, of focal type, around dust clusters, forming granulomas consisting of macrophages and other mononuclear cells. In the hemolytic test the slag dust induced hemolysis of 7% ram erythrocytes. The test dust should be classified as weakly fibrogenic.

Diagnosis of Hashimoto's thyroiditis in ultrasound using tissue characterization and pixel classification.

Hashimoto's thyroiditis is the most common type of inflammation of the thyroid gland, and accurate diagnosis of Hashimoto's thyroiditis would be helpful to better manage the disease process and predict thyroid failure. Most of the published computer-based techniques that use ultrasound thyroid images for Hashimoto's thyroiditis diagnosis are limited by lack of procedure standardization because individual investigators use various initial ultrasound settings. This article presents a computer-aided diagnostic technique that uses grayscale features and classifiers to provide a more objective and reproducible classification of normal and Hashimoto's thyroiditis-affected cases. In this paradigm, we extracted grayscale features based on entropy, Gabor wavelet, moments, image texture, and higher order spectra from the 100 normal and 100 Hashimoto's thyroiditis-affected ultrasound thyroid images. Significant features were selected using t-test. The resulting feature vectors were used to build the following three classifiers using tenfold stratified cross validation technique: support vector machine, k-nearest neighbor, and radial basis probabilistic neural network. Our results show that a combination of 12 features coupled with support vector machine classifier with the polynomial kernel of order 1 and linear kernel gives the highest accuracy of 80%, sensitivity of 76%, specificity of 84%, and positive predictive value of 83.3% for the detection of Hashimoto's thyroiditis. The proposed computer-aided diagnostic system uses novel features that have not yet been explored for Hashimoto's thyroiditis diagnosis. Even though the accuracy is only 80%, the presented preliminary results are encouraging to warrant analysis of more such powerful features on larger databases.

Fasciitis eosinophilica.

Hypergamma-globulinemia and eosinophilia in the peripheral blood were found in a 4-year-old girl with scleroderma-like lesions within the upper and lower limbs. Histological examination excluded scleroderma. After 6 weeks of treatment with steroids, almost a complete retreat of scleroderma-like lesions was achieved.