Studies on cytotoxicity of nickel ions using C3H10T1/2 fibroblast cells

Cytotoxicity of Ni ions were examined using C3H mouse derived 10T1/2 fibroblast cells. It became evident that Ni ions had dose-dependent cytotoxicity. The cell number incubated in DME medium containing 0.04 mM/L Ni ion for 6 days was reduced to half that in control DME medium without Ni. The cell totally disappeared in DME medium containing 2 mM/L Ni ion. The dissolution of Ni ions from Ni-containing metallic restorations must be lower than these concentration levels so that oral tissues might not be damaged. No neoplastic transformation was found on all cells examined.     

The cellular basis of impaired T lymphocyte functions in the elderly

Immunologic changes associated with aging were studied by various immunologic tests in 24 aged persons (age range, 76-83) and 25 young persons (age range, 20-40). The responses to phytohemagglutinin (PHA) and concanavalin A (Con A) were depressed in the aged subjects compared to the young ones (p less than 0.05), whereas the responses to pokeweed mitogen (PWM) were similar. The activity of adhereent and non-adherent cells was assessed in various combinations. The adherent cells of aged persons were indistinguishable from those of young persons in their ability to response to Con A. Lymphocytes from the aged synthesized larger in vitro amounts of immunoglobulin than did lymphocytes from the young, when stimulated with PWM. Con A-stimulated T lymphocytes derived from aged subjects showed a variable loss of suppressor activity. The mixed lymphocyte culture reaction with mitomycin-treated allogeneic and autologous cells was also impaired in aged subjects. Such an impaired response in the aged is related to higher incidences of malignant lesions and auto-antibodies.     

Detecting Distal Radial Fractures from Wrist Radiographs Using a Deep Convolutional Neural Network with an Accuracy Comparable to Hand Orthopedic Surgeons

In recent years, fracture image diagnosis using a convolutional neural network (CNN) has been reported. The purpose of the present study was to evaluate the ability of CNN to diagnose distal radius fractures (DRFs) using frontal and lateral wrist radiographs. We included 503 cases of DRF diagnosed by plain radiographs and 289 cases without fracture. We implemented the CNN model using Keras and Tensorflow. Frontal and lateral views of wrist radiographs were manually cropped and trained separately. Fine-tuning was performed using EfficientNets. The diagnostic ability of CNN was evaluated using 150 images with and without fractures from anteroposterior and lateral radiographs. The CNN model diagnosed DRF based on three views: frontal view, lateral view, and both frontal and lateral view. We determined the sensitivity, specificity, and accuracy of the CNN model, plotted a receiver operating characteristic (ROC) curve, and calculated the area under the ROC curve (AUC). We further compared performances between the CNN and three hand orthopedic surgeons. EfficientNet-B2 in the frontal view and EfficientNet-B4 in the lateral view showed highest accuracy on the validation dataset, and these models were used for combined views. The accuracy, sensitivity, and specificity of the CNN based on both anteroposterior and lateral radiographs were 99.3, 98.7, and 100, respectively. The accuracy of the CNN was equal to or better than that of three orthopedic surgeons. The AUC of the CNN on the combined views was 0.993. The CNN model exhibited high accuracy in the diagnosis of distal radius fracture with a plain radiograph.