Trial Analysis of Brain Activity Information for the Presymptomatic Disease Detection of Rheumatoid Arthritis.
Keisuke MaedaTakahiro OgawaTasuku KayamaTakuya SasakiKazuki TainakaMasaaki MurakamiMiki HaseyamaPublished in: Bioengineering (Basel, Switzerland) (2024)
This study presents a trial analysis that uses brain activity information obtained from mice to detect rheumatoid arthritis (RA) in its presymptomatic stages. Specifically, we confirmed that F759 mice, serving as a mouse model of RA that is dependent on the inflammatory cytokine IL-6, and healthy wild-type mice can be classified on the basis of brain activity information. We clarified which brain regions are useful for the presymptomatic detection of RA. We introduced a matrix completion-based approach to handle missing brain activity information to perform the aforementioned analysis. In addition, we implemented a canonical correlation-based method capable of analyzing the relationship between various types of brain activity information. This method allowed us to accurately classify F759 and wild-type mice, thereby identifying essential features, including crucial brain regions, for the presymptomatic detection of RA. Our experiment obtained brain activity information from 15 F759 and 10 wild-type mice and analyzed the acquired data. By employing four types of classifiers, our experimental results show that the thalamus and periaqueductal gray are effective for the classification task. Furthermore, we confirmed that classification performance was maximized when seven brain regions were used, excluding the electromyogram and nucleus accumbens.
Keyphrases
- wild type
- rheumatoid arthritis
- disease activity
- health information
- ankylosing spondylitis
- high fat diet induced
- mouse model
- clinical trial
- deep learning
- resting state
- interstitial lung disease
- study protocol
- type diabetes
- label free
- systemic lupus erythematosus
- phase ii
- functional connectivity
- phase iii
- loop mediated isothermal amplification
- oxidative stress
- multiple sclerosis
- systemic sclerosis
- brain injury
- artificial intelligence
- open label