# Trial Analysis of Brain Activity Information for the Presymptomatic Disease Detection of Rheumatoid Arthritis

**Authors:** Keisuke Maeda, Takahiro Ogawa, Tasuku Kayama, Takuya Sasaki, Kazuki Tainaka, Masaaki Murakami, Miki Haseyama

PMC · DOI: 10.3390/bioengineering11060523 · Bioengineering · 2024-05-21

## TL;DR

This study explores using brain activity to detect rheumatoid arthritis in mice before symptoms appear, identifying key brain regions for early detection.

## Contribution

The study introduces a novel method combining matrix completion and canonical correlation analysis for presymptomatic RA detection using brain activity.

## Key findings

- The thalamus and periaqueductal gray are effective for classifying RA-prone mice.
- Classification performance is maximized using seven specific brain regions.
- A matrix completion-based approach successfully handles missing brain activity data.

## Abstract

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.

## Linked entities

- **Diseases:** rheumatoid arthritis (MONDO:0008383)
- **Species:** Mus musculus (taxon 10090)

## Full-text entities

- **Genes:** Il6 (interleukin 6) [NCBI Gene 16193] {aka Il-6}
- **Diseases:** RA (MESH:D001172), inflammatory (MESH:D007249)
- **Species:** Mus musculus (house mouse, species) [taxon 10090]

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11200460/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/PMC11200460/full.md

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Source: https://tomesphere.com/paper/PMC11200460