Treatment of masticatory disorders and development of ALS diagnostic biomarkers by fusion of AI and neurophysiological data

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K17088
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 57060:Surgical dentistry-related
• Research Institution: Osaka University
• Principal Investigator: Seki Soju 大阪大学, 大学院歯学研究科, 助教 (60755081)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: ALS / 筋萎縮性側索硬化症 / 三叉神経中脳路核 / 一次感覚神経 / 咀嚼障害 / 電気生理学

Outline of Final Research Achievements

In amyotrophic lateral sclerosis (ALS), we examined (1) how mastication disorder manifests itself, and (2) mastication behavior using artificial intelligence (AI). In addition, we investigated how the primary sensory neurons that control mastication are affected by the disease by electrophysiological studies. In (1), we used a video camera to capture the mastication behavior of ALS model mice and automatically detected the mastication cycle using AI, and found that the mastication cycle was significantly prolonged in ALS model mice from around 12 weeks of age compared to wild-type mice. In (2), we are currently conducting electrophysiological investigations of the primary sensory nerves that control mastication, and found abnormal firing activity and modulation of basic membrane properties in ALS model mice at maturity.

Free Research Field

ALS

Academic Significance and Societal Importance of the Research Achievements

本研究で開発した人工知能 (Artificial Intelligence; AI)　による咀嚼障害鑑別モデルを用いて、ALSモデルマウスで咀嚼障害を検出することができた。同時に三叉神経系ニューロンの発火異常を神経生理学的手法により確認、ALS咀嚼障害の原因を解明し、今後脳内生理活性物質によるALS治療法の考案につながる可能性がある。さらに、ALS患者の咀嚼運動を観察し、咀嚼障害鑑別AIを発展させ、現在早期発見が困難なALS診断バイオマーカーの開発を行うことを目的としている。