Integration of multi-omics and machine learning reveals sodium overload related molecular subtypes and biomarkers in sepsis
Researchers have identified a five-biomarker signature related to sodium overload in sepsis patients using machine learning and multi-omics data. The study highlights the gene TXN as a potential therapeutic target for mitigating immune dysfunction and cell death in sepsis.
Why it matters
This research offers a potential breakthrough in diagnostic and treatment strategies for sepsis, a life-threatening medical condition.
Scientific Reports ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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