Robotics & Machine Learning Daily News2024,Issue(Feb.19) :56-56.

Air Force Hospital Reports Findings in Spinal Cord Injury (Machine learning and experiments revealed a novel pyroptosis-based classification linked to diagnosis and immune landscape in spinal cord injury)

Robotics & Machine Learning Daily News2024,Issue(Feb.19) :56-56.

Air Force Hospital Reports Findings in Spinal Cord Injury (Machine learning and experiments revealed a novel pyroptosis-based classification linked to diagnosis and immune landscape in spinal cord injury)

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Abstract

New research on Central Nervous System Diseases and Conditions - Spinal Cord Injury is the subject of a report. According to news reporting originating in Nanjing, People’s Republic of China, by NewsRx journalists, research stated, “Rising evidence indicates the development of pyroptosis in the initiation and pathogenesis of spinal cord injury (SCI). However, the associated effects of pyroptosis-related genes (PRGs) in SCI are unclear.” The news reporters obtained a quote from the research from Air Force Hospital, “We obtained the gene expression profiles of SCI and normal samples in the GEO. The R package limma screened for differentially expressed (DE) PRGs and performed functional enrichment analysis. Mechanical learning and PPI analysis helped filter essential PRGs to diagnose SCI. Peripheral blood was collected for validation from ten SCI patients and eight healthy individuals. The association of essential PRGs with immune infiltration was evaluated, and pyroptosis subtypes were recognized in SCI patients by unsupervised cluster analysis. Besides, a SCI model was built for in vivo validation of essential PRGs. We identified 25 DE-PRGs between SCI and normal controls. Functional enrichment analysis revealed the principal involvement of DE-PRGs in pyroptosis, inflammasome complex, interleukin-1 beta production, etc. Subsequently, three essential PRGs were identified and validated, showing excellent diagnostic efficacy and significant correlation with immune cell infiltration. Additionally, we developed diagnostic nomograms to predict the occurrence of SCI. Two pyroptosis subtypes exhibited distinct biological functions and immune landscapes among SCI patients. Finally, the expression of these essential PRGswas verified in vivo.”

Key words

Nanjing/People’s Republic of China/Asia/Central Nervous System/Central Nervous System Diseases and Conditions/Cyborgs/Diagnostics and Screening/Emerging Technologies/Genetics/Health and Medicine/Machine Learning/Pyroptosis/Spinal Cord/Spinal Cord Diseases and Conditions/Spinal Cord Injury

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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