No abstract

Background: Cephalometric analysis has long been, and still is one of the most important tools in evaluating craniomaxillofacial skeletal profile. To perform this, manual tracing of x-ray film and plotting landmarks have been required. This procedure is time-consuming and demands expertise. In these days, computerized cephalometric systems have been introduced; however, tracing and plotting still have to be done on the monitor display. Artificial intelligence is developing rapidly. Deep learning is one of the most evolving areas in artificial intelligence. The authors made an automated landmark predicting system, based on a deep learning neural network. Methods: On a personal desktop computer, a convolutional network was built for regression analysis of cephalometric landmarks’ coordinate values. Lateral cephalogram images were gathered through the internet and 219 images were obtained. Ten skeletal cephalometric landmarks were manually plotted and coordinate values of them were listed. The images were randomly divided into 153 training images and 66 testing images. Training images were expanded 51 folds. The network was trained with the expanded training images. With the testing images, landmarks were predicted by the network. Prediction errors from manually plotted points were evaluated. Results: Average and median prediction errors were 17.02 and 16.22 pixels. Angles and lengths in cephalometric analysis, predicted by the neural network, were not statistically different from those calculated from manually plotted points. Conclusion: Despite the variety of image quality, using cephalogram images on the internet is a feasible approach for landmark prediction.

IntroductionNanoparticles (NPs) are small entities that consist of a hydroxyapatite core, which can bind ions, proteins, and other organic molecules from the surrounding environment. These small conglomerations can influence environmental calcium levels and have the potential to modulate calcium homeostasis in vivo. Nanoparticles have been associated with various calcium-mediated disease processes, such as atherosclerosis and kidney stone formation. We hypothesized that nanoparticles could have an effect on other calcium-regulated processes, such as wound healing. In the present study, we synthesized pH-sensitive calcium-based nanoparticles and investigated their ability to enhance cutaneous wound repair.MethodsDifferent populations of nanoparticles were synthesized on collagen-coated plates under various growth conditions. Bilateral dorsal cutaneous wounds were made on 8-week-old female Balb/c mice. Nanoparticles were then either administered intravenously or applied topically to the wound bed. The rate of wound closure was quantified. Intravenously injected nanoparticles were tracked using a FLAG detection system. The effect of nanoparticles on fibroblast contraction and proliferation was assessed.ResultsA population of pH-sensitive calcium-based nanoparticles was identified. When intravenously administered, these nanoparticles acutely increased the rate of wound healing. Intravenously administered nanoparticles were localized to the wound site, as evidenced by FLAG staining. Nanoparticles increased fibroblast calcium uptake in vitro and caused contracture of a fibroblast populated collagen lattice in a dose-dependent manner. Nanoparticles also increased the rate of fibroblast proliferation.ConclusionIntravenously administered, calcium-based nanoparticles can acutely decrease open wound size via contracture. We hypothesize that their contraction effect is mediated by the release of ionized calcium into the wound bed, which occurs when the pH-sensitive nanoparticles disintegrate in the acidic wound microenvironment. This is the first study to demonstrate that calcium-based nanoparticles can have a therapeutic benefit, which has important implications for the treatment of wounds.

No abstract

The Microvascular Anastomotic System (3M coupler) uses a friction-fit union of implant rings composed of high-density polyethylene and stainless-steel pins. Several reports have described equal or greater patency rates, as well as more rapid performance, using the device, compared to conventional suturing techniques. Eighty-nine patients, who underwent head and neck surgery with free-tissue transfers, using the Microvascular Anastomotic System, were evaluated. A hundred and twenty-one venous anastomoses were done using the device. All but one was done in an end-to-end manner Arteries were anastomosed with a conventional suture technique. The flap survival rate was 100 percent. The authors conclude that the device is reliable and time-sparing for end-to-end venous anastomoses in head and neck reconstruction.