Restorabite™: Phase II trial of jaw stretching exercises using a novel device for patients with trismus following head and neck cancer.

Patients treated for oral cancer, may experience restricted mouth opening (trismus). Barriers such as cost have limited the utilization of traditional jaw stretching devices, and consequently, patients experience problems with swallowing, oral care, communication, and cancer surveillance. The safety and efficacy of Restorabite™, a new device designed to overcome these barriers, is evaluated prospectively over 12 months. This phase II investigator-led trial included patients with chronic trismus underwent 10-weeks of trismus therapy using Restorabite™. Safety, adherence, changes in mouth opening, and patient-reported outcomes are presented. 114/120 participants with trismus completed the intervention, and 104 had their progress monitored for 12 months. Thirteen participants withdrew due to tumour recurrence. At the completion of the intervention, mouth opening improved by 10.4 mm (p < .001). This increased to 13.7 mm at 12 months (p < .001). Patient reported outcome all significantly improved and 47 participants were no longer classified as having trismus. There were no serious treatment related adverse events. In patients with trismus following head and neck cancer treatment, a 10-week programme of jaw stretching exercises using Restorbite™ safely improves mouth opening and associated quality of life outcomes with high adherence and the benefits are maintained for 12-months.

Amplification, Resistance, and Kinetics of the Jaw Stretching Device (ARK-JSD): analysis of the force variation and implications for trismus therapy.

PURPOSE: Jaw-stretching devices, including the Amplification, Resistance, and Kinetics of the Jaw (ARK-JSD), are an effective option for treating trismus after head and neck cancer (HNC) treatment. The force, however, that is applied to the patient's jaw is unknown. METHODS: Ten ARK-JSD devices were constructed for each of the levels of resistance (total of 30 samples). Each sample was tested using a Universal Testing Machine (UTM). RESULTS: The easy, medium, and hard ARK-JSD had a mean maximum force of 12.3, 21.0, and 32.7 Newtons (N) at a mean interincisal distance (IID) of 8.0 mm, 13.0 mm, and 16.0 mm, respectively. The force varied by 6.9 N for the easy and 24.1 N for the hard ARK-JSD. Fatigue analysis demonstrated up to 5.5 N loss of force over 10 weeks. CONCLUSION: The ARK-JSD is a low-cost trismus device that can force between 12.3 and 32.7 N. The variation in resistance may impact efficacy. Understanding this variation will assist clinicians and patients using the ARK-JSD for trismus therapy.

Improved Poisson-Boltzmann Methods for High-Performance Computing.

Implicit solvent models based on the Poisson-Boltzmann equation (PBE) have been widely used to study electrostatic interactions in biophysical processes. These models often treat the solvent and solute regions as high and low dielectric continua, leading to a large jump in dielectrics across the molecular surface which is difficult to handle. Higher order interface schemes are often needed to seek higher accuracy for PBE applications. However, these methods are usually very liberal in the use of grid points nearby the molecular surface, making them difficult to use on high-performance computing platforms. Alternatively, the harmonic average (HA) method has been used to approximate dielectric interface conditions near the molecular surface with surprisingly good convergence and is well suited for high-performance computing. By adopting a 7-point stencil, the HA method is advantageous in generating simple 7-banded coefficient matrices, which greatly facilitate linear system solution with dense data parallelism, on high-performance computing platforms such as a graphics processing unit (GPU). However, the HA method is limited due to its lower accuracy. Therefore, it would be of great interest for high-performance applications to develop more accurate methods while retaining the simplicity and effectiveness of the 7-point stencil discretization scheme. In this study, we have developed two new algorithms based on the spirit of the HA method by introducing more physical interface relations and imposing the discretized Poisson's equation to the second order, respectively. Our testing shows that, for typical biomolecules, the new methods significantly improve the numerical accuracy to that comparable to the second-order solvers and with ∼65% overall efficiency gain on widely available high-performance GPU platforms.