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Daily Sepsis Research Analysis

3 papers

Three studies advance sepsis science across mechanism and diagnostics: dimethyl fumarate (DMF) mitigates sepsis-induced lung injury by blocking STING-driven ferroptosis and preserving GPX4; a gut microbiota-derived Proline–Leucine dipeptide exacerbates lung inflammation via C/EBP-β/NOD2/NF-κB; and plasma extracellular vesicle 5-hydroxymethylcytosine signatures show high accuracy for diagnosing septic cardiomyopathy.

Summary

Three studies advance sepsis science across mechanism and diagnostics: dimethyl fumarate (DMF) mitigates sepsis-induced lung injury by blocking STING-driven ferroptosis and preserving GPX4; a gut microbiota-derived Proline–Leucine dipeptide exacerbates lung inflammation via C/EBP-β/NOD2/NF-κB; and plasma extracellular vesicle 5-hydroxymethylcytosine signatures show high accuracy for diagnosing septic cardiomyopathy.

Research Themes

  • Ferroptosis and innate immune signaling in sepsis
  • Gut–lung axis and microbiome-derived metabolites
  • Epigenetic extracellular vesicle biomarkers for organ dysfunction

Selected Articles

1. Dimethyl fumarate improves sepsis-induced acute lung injury by inhibiting STING-mediated ferroptosis.

73Level VCase-controlJournal of bioenergetics and biomembranes · 2025PMID: 40616736

In CLP-induced sepsis models, DMF reduced ferroptosis, inflammation, and oxidative injury in lungs, and improved histology. Mechanistically, DMF blocked STING activation and prevented STING-mediated autophagic degradation of GPX4, thereby limiting ROS and ferroptotic death.

Impact: This study links STING signaling to ferroptosis via GPX4 autophagic degradation and identifies DMF as a dual-function inhibitor, highlighting a tractable therapeutic axis for sepsis-induced lung injury.

Clinical Implications: While preclinical, the data support repurposing DMF—already approved for multiple sclerosis—as a candidate to mitigate sepsis-related ALI/ARDS by targeting the STING–ferroptosis axis.

Key Findings

  • CLP increased pulmonary ferroptosis, inflammation, and oxidative stress; DMF markedly attenuated these and improved histological injury.
  • DMF suppressed LPS-induced ferroptosis in MLE-12 alveolar epithelial cells.
  • DMF inhibited STING activation and prevented STING-mediated autophagic degradation of GPX4, reducing ROS and ferroptotic death.

Methodological Strengths

  • Integrated in vivo CLP sepsis model with complementary in vitro validation.
  • Mechanistic dissection linking STING signaling to GPX4 autophagic degradation and ferroptosis.

Limitations

  • Preclinical animal and cell models without human clinical validation.
  • Optimal dosing, timing, and safety of DMF in sepsis remain untested.

Future Directions: Validate the STING–ferroptosis–GPX4 axis and DMF efficacy in large-animal models and early-phase clinical trials; develop biomarkers to identify ferroptosis-high sepsis patients.

2. Gut microbiota-derived Proline-Leucine dipeptide aggravated sepsis-induced acute lung injury via activating Nod2/NF-κB signaling pathway.

70Level VCase-controlMolecular immunology · 2025PMID: 40614662

Multi-omics profiling in sepsis revealed elevated Pro–Leu, alongside dysbiosis, which correlated with worsened lung injury. Pro–Leu and LPS synergistically amplified TNF-α, IL-6, and IL-1β via C/EBP-β/NOD2/NF-κB in lung tissues and MH-S cells.

Impact: Identifies a specific microbiota-derived dipeptide as a modifiable mediator of the gut–lung axis in sepsis, providing a concrete pathway (NOD2/NF-κB) for therapeutic targeting.

Clinical Implications: Although preclinical, measuring Pro–Leu or modulating its production/signaling (e.g., via microbiome interventions or NOD2/NF-κB blockade) could mitigate sepsis-associated lung injury.

Key Findings

  • Sepsis reduced gut microbiota diversity and increased Bacteroidetes and Escherichia–Shigella, with concomitant elevation of the Pro–Leu dipeptide.
  • Pro–Leu levels correlated with microbial community shifts and exacerbated sepsis-induced lung injury in mice.
  • Pro–Leu and LPS upregulated C/EBP-β, NOD2, and p-NF-κB, enhancing TNF-α, IL-6, and IL-1β production in lung tissues and MH-S cells.

Methodological Strengths

  • Combined 16S rDNA sequencing with untargeted metabolomics to link dysbiosis to specific metabolites.
  • Validated mechanistic pathway across animal models and macrophage-like lung cells with signaling readouts.

Limitations

  • Findings are limited to animal and cell models; human validation of Pro–Leu levels and effects is lacking.
  • Complexity of microbiome–host interactions may limit generalizability and causality inference in humans.

Future Directions: Quantify Pro–Leu in human sepsis cohorts and test it as a biomarker and interventional target; evaluate microbiome or NOD2/NF-κB–directed therapies in translational studies.

3. 5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.

62Level IIICase-controlScientific reports · 2025PMID: 40615404

Plasma extracellular vesicle 5hmC-Seal profiling distinguished septic cardiomyopathy from sepsis without cardiomyopathy and non-sepsis controls with high accuracy, supported by external dataset validation.

Impact: Introduces an epigenetic liquid biopsy approach for septic cardiomyopathy with strong diagnostic performance, addressing a critical gap in early identification.

Clinical Implications: If validated prospectively, EV 5hmC signatures could complement echocardiography and cardiac biomarkers to enable earlier diagnosis and risk stratification of septic cardiomyopathy.

Key Findings

  • 5hmC-Seal profiling of plasma EV DNA in 13 SCM, 18 sepsis without cardiomyopathy, and 8 non-sepsis controls enabled machine learning model development.
  • The diagnostic model achieved accuracy 0.962 with 92.3% sensitivity and 88.89% specificity.
  • External validation using GEO datasets reported accuracy up to 1.000 and differential diagnostic AUCs of 0.959 and 0.944.

Methodological Strengths

  • Application of 5hmC-Seal to extracellular vesicle DNA enabling high-resolution epigenetic profiling.
  • Use of machine learning with external dataset validation to assess diagnostic performance.

Limitations

  • Small sample size increases risk of overfitting and limits generalizability.
  • Validation relied on public datasets that may differ in sample type or context from EV 5hmC profiles; prospective multicenter validation is needed.

Future Directions: Prospective, multicenter studies to validate EV 5hmC classifiers, assay standardization, and head-to-head comparisons with echocardiography and cardiac biomarkers.