The mitochondrial division inhibitor Mdivi-1 protected organ function and extended the treatment window in rats with uncontrolled haemorrhagic shock.

Aim: To elucidate whether the application of the mitochondrial division inhibitor Mdivi-1 can protect organ function and prolong the treatment window for traumatic hemorrhagic shock.

Methods: Before definitive haemostasis treatment, Mdivi-1 (0.25 mg/kg, 0.

The New Nano-Resuscitation Solution (TPP-MR) Attenuated Myocardial Injury in Hemorrhagic Shock Rats by Inhibiting Ferroptosis.

Background: Hemorrhagic shock was a leading cause of death worldwide, with myocardial injury being a primary affected organ. As commonly used solutions in fluid resuscitation, acetated Ringer's (AR) and Lactate Ringer's solution (LR) were far from perfect for their adverse reactions such as lactic acidosis and electrolyte imbalances. In previous studies, TPP@PAMAM-MR (TPP-MR), a novel nanocrystal resuscitation fluid has been found to protect against myocardial injury in septic rats.

Cuproptosis-Related Genes as Prognostic Biomarkers for Sepsis: Insights into Immune Function and Personalized Immunotherapy.

Background: This study aimed to discover diagnostic and prognostic biomarkers for sepsis immunotherapy through analyzing the novel cellular death process, cuproptosis.

Methods: We used transcriptome data from sepsis patients to identify key cuproptosis-related genes (CuRGs). We created a predictive model and used the CIBERSORT algorithm to observe the link between these genes and the septic immune microenvironment.

Corrigendum: Integrative single-cell RNA sequencing and metabolomics decipher the imbalanced lipid-metabolism in maladaptive immune responses during sepsis.

[This corrects the article DOI: 10.3389/fimmu.2023.

Construction and validation of a mitochondria-associated genes prognostic signature and immune microenvironment characteristic of sepsis.

Background: Sepsis is a common critical condition seen in clinical settings, with mitochondrial dysfunction playing an important role in the progression of sepsis. However, a mitochondrial prognosis model related to sepsis has not been established yet, and the relationship between the sepsis immune microenvironment and mitochondria remains unclear.

Methods: Sepsis prognostic mitochondria-associated genes (MiAGs) were screened by univariate Cox, multivariate Cox, and LASSO analysis from the GEO dataset.

Metabolomics and machine learning approaches for diagnostic and prognostic biomarkers screening in sepsis.

Background: Sepsis is a life-threatening disease with a poor prognosis, and metabolic disorders play a crucial role in its development. This study aims to identify key metabolites that may be associated with the accurate diagnosis and prognosis of sepsis.

Methods: Septic patients and healthy individuals were enrolled to investigate metabolic changes using non-targeted liquid chromatography-high-resolution mass spectrometry metabolomics.

VDAC2 malonylation participates in sepsis-induced myocardial dysfunction via mitochondrial-related ferroptosis.

Sepsis-induced myocardial dysfunction (SIMD) is a prevalent and severe form of organ dysfunction with elusive underlying mechanisms and limited treatment options. In this study, the cecal ligation and puncture and lipopolysaccharide (LPS) were used to reproduce sepsis model and vivo. The level of voltage-dependent anion channel 2 (VDAC2) malonylation and myocardial malonyl-CoA were detected by mass spectrometry and LC-MS-based metabolomics.

Identification of featured necroptosis-related genes and imbalanced immune infiltration in sepsis machine learning.

The precise diagnostic and prognostic biological markers were needed in immunotherapy for sepsis. Considering the role of necroptosis and immune cell infiltration in sepsis, differentially expressed necroptosis-related genes (DE-NRGs) were identified, and the relationship between DE-NRGs and the immune microenvironment in sepsis was analyzed. Machine learning algorithms were applied for screening hub genes related to necroptosis in the training cohort.

The Landscape of Featured Metabolism-Related Genes and Imbalanced Immune Cell Subsets in Sepsis.

Sepsis is a heterogeneous disease state triggered by an uncontrolled inflammatory host response with high mortality and morbidity in severely ill patients. Unfortunately, the treatment effectiveness varies among sepsis patients and the underlying mechanisms have yet to be elucidated. The present aim is to explore featured metabolism-related genes that may become the biomarkers in patients with sepsis.