The effects of electromagnetic field on distraction osteogenesis and new bony tissue were investigated. Twenty-five New Zealand rabbits were divided into an experimental (12 rabbits) and a control (13 rabbits) group. An osteotomy was performed on the right tibia in the diaphyseal region in both groups. The experimental group was exposed to a magnetic field of 50 Hz 1.0 mT for 3 hours a day for 13 weeks. The control group was kept in a similar environment but with no electromagnetic field. The distraction was continued until an increase of 10 mm was achieved. At weeks 4, 8, and 13, radiography, scintigraphy, and a biopsy were performed in both groups, and the results were statistically analyzed. The X-ray results were similar in both groups at all times. On the other hand while the scintigraphic and histopathological results were similar at weeks 4 and 13 in both groups, the osteoblastic activity was significantly greater in the experimental group at week 8 (p < 0.01). In conclusion an electromagnetic field increases the osteoblastic activity and osteogenesis, but has little effect during the remodeling phase.
Animals ; *Electromagnetic Fields ; Osteoblasts/physiology/radiation effects ; Osteogenesis/radiation effects ; *Osteogenesis, Distraction ; Osteotomy ; Rabbits

We performed biomechanical comparison of a xenograft bone plate-screw (XBPS) system for achieving cadaveric lumbar transpedicular stabilization (TS) in dogs. Twenty dogs' cadaveric L2-4 lumbar specimens were harvested and their muscles were removed, but the discs and ligaments were left intact. These specimens were separated to four groups: the L2-4 intact group as control (group I, n = 5), the L3 laminectomy and bilateral facetectomy group (LBF) (group II, n = 5), the LBF plus TS with metal plate-screw group (group III, n = 5) and the LBF plus TS with XBPS group (group IV, n = 5). Five kinds of biomechanical tests were applied to the specimens: flexion, extension, left-right bending and rotation. The averages of the 16 stiffness values were calculated and then these were statistically analyzed. The statistical results show that the XBPS system contributes spinal stability and this system can be a good choice for achieving TS.
Animals ; Biomechanics ; Bone Plates/*veterinary ; Bone Screws/*veterinary ; Cadaver ; Dogs ; Lumbar Vertebrae/physiology/*surgery ; Range of Motion, Articular/physiology ; Spinal Fusion/instrumentation/*methods ; Transplantation, Heterologous/instrumentation/*methods

Gastric hemangiomas are rare benign vascular tumors that can cause severe gastrointestinal system bleeding. We presented the case of a neonate with fresh bleeding and melena from the orogastric tube and detected gastric hemangioma in esophagogastroduodenoscopic examination. Propranolol is widely used in treatment of cutaneous hemangiomas and non-gastric gastrointestinal system hemangiomas. However, the surgical approach is preferred for treating gastric hemangiomas, and there are few reports of gastric hemangiomas associated with non-surgical treatment. Gastric hemorrhage decreased with antacid and somatostatin treatment. Propranolol treatment was initiated before the surgery decision. After three weeks of treatment, we observed regression in the hemangioma with endoscopic evaluation. During the course of treatment, the patient's gastrointestinal system bleeding did not recur, and there were no side effects associated with propranolol.
Hemangioma* ; Hemorrhage ; Humans ; Infant, Newborn* ; Melena ; Propranolol* ; Somatostatin ; Stomach

Purpose: The aim of this study was to assess the performance of a deep learning system for permanent tooth germ detection on pediatric panoramic radiographs. Materials and Methods: In total, 4518 anonymized panoramic radiographs of children between 5 and 13 years of age were collected. YOLOv4, a convolutional neural network (CNN)-based object detection model, was used to automatically detect permanent tooth germs. Panoramic images of children processed in LabelImg were trained and tested in the YOLOv4 algorithm. True-positive, false-positive, and false-negative rates were calculated. A confusion matrix was used to evaluate the performance of the model. Results: The YOLOv4 model, which detected permanent tooth germs on pediatric panoramic radiographs, provided an average precision value of 94.16% and an F1 value of 0.90, indicating a high level of significance. The average YOLOv4 inference time was 90 ms. Conclusion The detection of permanent tooth germs on pediatric panoramic X-rays using a deep learning-based approach may facilitate the early diagnosis of tooth deficiency or supernumerary teeth and help dental practitioners find more accurate treatment options while saving time and effort.