Bioinformatics Research

KEY FINDING: The study population had a high migraine burden, with most participants diagnosed with chronic migraine and using multiple acute and preventive medications.

KEY FINDING: Acute injury outcome predictors, including blood and cerebrospinal fluid biomarkers, neuroimaging signal changes, and autonomic system abnormalities, often do not predict chronic SCI syndrome phenotypes.

KEY FINDING: A total of 1,271 metabolites were identified in the bladder muscle of rats after traumatic spinal cord injury.

KEY FINDING: Peak peripherin levels were significantly higher in GBS patients compared to other groups, indicating its potential as a specific biomarker for acute PNS axonal damage.

KEY FINDING: Preoperative JOA score, presence of a psychiatric disorder, and ASIA grade were identified as significant factors associated with the last JOS score.

KEY FINDING: Distal lumbar tissue cells were severely impacted, leading to degenerative microenvironments characterized by disease-associated microglia and oligodendrocytes activation alongside increased inhibitory interneurons proportion following SCI.

KEY FINDING: Machine learning (ML) demonstrates enhanced precision in forecasting AIS (ASIA Impairment Scale) result scores, which are used to classify the severity of spinal cord injuries.

KEY FINDING: The AI model achieved a sensitivity of 0.78, precision of 0.68, and F1-score of 0.72 per slice in detecting osteolytic bone metastases.

KEY FINDING: SCI regulates canonical pathways associated with protein synthesis, neuroplasticity, wound healing, and neurotransmitter degradation.

KEY FINDING: Identified the spatial distribution of neural progenitor cells characterized by combinatorial TFs along the dorsoventral axis.