Bioinformatics Research

KEY FINDING: Neuropathic pain peaked on day 7 after chronic constriction injury in mice, concurrent with myelin lesions in both the spinal cord and sciatic nerve.

KEY FINDING: The improved MLSMOTE multi-label learning framework effectively addresses the class imbalance problem in EMR data.

KEY FINDING: Vscan Air and SonoEye Chison achieved the best overall ratings, differing significantly from the other devices (p < 0.01).

KEY FINDING: Three hub genes (DCN, FSTL1, and COL12A1) were identified as significantly altered in sarcopenic SCI patients both before and after rehabilitation training.

KEY FINDING: AI-based devices, including those with EMG-based robotic hands, have demonstrated significant improvements in upper limb motor function with a reduction of spasticity in stroke patients, reporting long-lasting results.

KEY FINDING: Psychological factors accounted for 36.3% of the total predictive weight for functional outcomes in SCI patients.

KEY FINDING: According to NRS-2002, 28.3% of patients were at high risk for malnutrition. MST identified 30.8% of patients at high risk, while MUST classified 30.6% of patients at medium and high risk.

KEY FINDING: AI improves diagnostic accuracy by identifying subtle lesions or fiber tract disruptions often missed by human radiologists and integrates multimodal data for comprehensive diagnosis.

KEY FINDING: Prior exercise significantly increased the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) in rats with CCI, indicating a reduction in pain sensitivity.

KEY FINDING: Resistance exercise, especially isotonic exercise, improves muscle strength, walking ability, and balance in individuals with incomplete SCI.