No abstract

Rheumatoid arthritis is an autoimmune condition that predominantly affects the synovial joints, causing joint destruction, pain, and disability. Historically, the standard for measuring the long-term efficacy of disease-modifying antirheumatic drugs has been the assessment of plain radiographs with scoring techniques that quantify joint damage. However, with significant improvements in therapy, current radiographic scoring systems may no longer be fit for purpose for the milder spectrum of disease seen today. We argue that artificial intelligence is an apt solution to further improve upon radiographic scoring, as it can readily learn to recognize subtle patterns in imaging data to not only improve efficiency, but can also increase the sensitivity to variation in mild disease. Current work in the area demonstrates the feasibility of automating scoring but is yet to take full advantage of the strengths of artificial intelligence. By fully leveraging the power of artificial intelligence, faster and more sensitive scoring could enable the ongoing development of effective treatments for patients with rheumatoid arthritis.

Electric-field stimulation of neuronal activity can be used to improve the speed of regeneration for severed and damaged nerves. Most techniques, however, require invasive electronic circuitry which can be uncomfortable for the patient and can damage surrounding tissue. A recently suggested technique by Sliow et al instead uses a graft-antenna - a metal ring wrapped around the damaged nerve - powered by an external magnetic stimulation device. This technique requires no electrodes and internal circuitry; all power is provided wirelessly. This paper examines the microscopic mechanisms which allow the magnetic stimulation device to cause neural activation via the graft-antenna. A computational model of the system was created and used to find that under magnetic stimulation, diverging electric fields appear at the metal ring’s edges. If the magnetic stimulation is sufficient, the gradients of these fields can trigger neural activation in the nerve. In agreement with in vivo measurements on rat sciatic nerves, direct contact between the antenna and the nerve ensures neural activation given sufficient magnetic stimulation. Simulations also showed that the presence of a thin gap between the graft-antenna and the nerve does not preclude neural activation but does reduce its efficacy.

Background/Aim: Pancreatic cancer is the second most common gastrointestinal cancer in the world, yet the fiveyear survival outcome rate of less than 5% urges for improvement in medical interventions of pancreatic cancer. Currently, high dose radiation therapy (RT) is used as an adjuvant treatment; however, the high level of RT required to treat advanced neoplasms leads to high incidence rates of side effects. In recent years, the utilization of cytokines as radiosensitizing agents has been studied, in order to reduce the amount of radiation required. However, few studies have examined IL-28 regarding its potential as a radiosensitizer. This study is the first to utilize IL-28 as a radiosensitizing agent in pancreatic cancer. Materials and Methods: MiaPaCa-2, a widely used pancreatic cancer cell line was used in this study. Clonogenic survival and cell proliferation assays were used to evaluate growth and proliferation of MiaPaCa-2 cells. Caspase-3 activity assay was used to evaluate apoptosis of MiaPaCa-2 cells and RT-PCR was used to study the possible molecular mechanisms. Results: Our results showed that IL-28/RT enhanced RT-induced inhibition of cell proliferation and promoted apoptosis of MiaPaCa-2 cells. Furthermore, compared