Computational discovery of PGD, MAPK14, and KRAS as diagnostic biomarkers for neonatal sepsis through integrated machine learning, immune infiltration analysis, and molecular docking - Summary - MDSpire

Computational discovery of PGD, MAPK14, and KRAS as diagnostic biomarkers for neonatal sepsis through integrated machine learning, immune infiltration analysis, and molecular docking

  • By

  • Li Luo

  • Jing Chen

  • Weiwei Du

  • Jianchuan Hu

  • May 29, 2026

  • 0 min

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Objective:

To identify and validate diagnostic biomarkers for neonatal sepsis associated with ferroptosis and cuproptosis pathways using integrated bioinformatics and machine learning approaches.

Key Findings:
  • Three biomarkers—PGD, MAPK14, and KRAS—were identified with strong diagnostic performance (AUC > 0.79 in external validation).
  • Increased neutrophils and Tregs, and decreased CD8+ T cells were observed in sepsis.
  • Dasatinib and gefitinib were identified as high−affinity binders to MAPK14 and KRAS.
Interpretation:

Limitations:
Conclusion:

Original Source(s)

Computational discovery of PGD, MAPK14, and KRAS as diagnostic biomarkers for neonatal sepsis through integrated machine learning, immune infiltration analysis, and molecular docking

  • by Li Luo, Jing Chen, Weiwei Du, Jianchuan Hu

  • May 29, 2026

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