High Mobility Group Box 1 (HMGB1): Potential Target in Sepsis-Associated Encephalopathy

MSC-derived exosomal miR-140-3p improves cognitive dysfunction in sepsis-associated encephalopathy by HMGB1 and S-lactoylglutathione metabolism

MiRNAs in mesenchymal stem cells (MSCs)-derived exosome (MSCs-exo) play an important role in the treatment of sepsis. We explored the mechanism through which MSCs-exo influences cognitive impairment in sepsis-associated encephalopathy (SAE). Here, we show that miR-140-3p targeted Hmgb1. MSCs-exo plus miR-140-3p mimic (Exo) and antibiotic imipenem/cilastatin (ABX) improve survival, weight, and cognitive impairment in cecal ligation and puncture (CLP) mice. Exo and ABX inhibit high mobility group box 1 (HMGB1), IBA-1, interleukin (IL)-1β, IL-6, iNOS, TNF-α, p65/p-p65, NLRP3, Caspase 1, and GSDMD-N levels. In addition, Exo upregulates S-lactoylglutathione levels in the hippocampus of CLP mice. Our data further demonstrates that Exo and S-lactoylglutathione increase GSH levels in LPS-induced HMC3 cells and decrease LD and GLO2 levels, inhibiting inflammatory responses and pyroptosis. These findings suggest that MSCs-exo-mediated delivery of miR-140-3p ameliorates cognitive impairment in mice with SAE by HMGB1 and S-lactoylglutathione metabolism, providing potential therapeutic targets for the clinical treatment of SAE.

Improved prediction of sepsis-associated encephalopathy in intensive care unit sepsis patients with an innovative nomogram tool

Background

Sepsis-associated encephalopathy (SAE) occurs as a result of systemic inflammation caused by sepsis. It has been observed that the majority of sepsis patients experience SAE while being treated in the intensive care unit (ICU), and a significant number of survivors continue suffering from cognitive impairment even after recovering from the illness. The objective of this study was to create a predictive nomogram that could be used to identify SAE risk factors in patients with ICU sepsis.

Methods

We conducted a retrospective cohort study using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. We defined SAE as a Glasgow Coma Scale (GCS) score of 15 or less, or delirium. The patients were randomly divided into training and validation cohorts. We used least absolute shrinkage and selection operator (LASSO) regression modeling to optimize feature selection. Independent risk factors were determined through a multivariable logistic regression analysis, and a prediction model was built. The performance of the nomogram was evaluated using various metrics including the area under the receiver operating characteristic curve (AUC), calibration plots, Hosmer-Lemeshow test, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

Among the 4,476 sepsis patients screened, 2,781 (62.1%) developed SAE. In-hospital mortality was higher in the SAE group compared to the non-SAE group (9.5% vs. 3.7%, p < 0.001). Several variables were analyzed, including the patient's age, gender, BMI on admission, mean arterial pressure, body temperature, platelet count, sodium level, and use of midazolam. These variables were used to create and validate a nomogram. The nomogram's performance, assessed by AUC, NRI, IDI, and DCA, was found to be superior to the conventional SOFA score combined with delirium. Calibration plots and the Hosmer-Lemeshow test confirmed the accuracy of the nomogram. The enhanced NRI and IDI values demonstrated that our scoring system outperformed traditional diagnostic approaches. Additionally, the DCA curve indicated the practicality of the nomogram in clinical settings.

Conclusion

This study successfully identified autonomous risk factors associated with the emergence of SAE in sepsis patients and utilized them to formulate a predictive model. The outcomes of this investigation have the potential to serve as a valuable clinical resource for the timely detection of SAE in patients.

The Role of Iron Metabolism in Sepsis-associated Encephalopathy: a Potential Target

Sepsis-associated encephalopathy (SAE) is an acute cerebral dysfunction secondary to infection, and the severity can range from mild delirium to deep coma. Disorders of iron metabolism have been proven to play an important role in a variety of neurodegenerative diseases by inducing cell damage through iron accumulation in glial cells and neurons. Recent studies have found that iron accumulation is also a potential mechanism of SAE. Systemic inflammation can induce changes in the expression of transporters and receptors on cells, especially high expression of divalent metal transporter1 (DMT1) and low expression of ferroportin (Fpn) 1, which leads to iron accumulation in cells. Excessive free Fe2+ can participate in the Fenton reaction to produce reactive oxygen species (ROS) to directly damage cells or induce ferroptosis. As a result, it may be of great help to improve SAE by treatment of targeting disorders of iron metabolism. Therefore, it is important to review the current research progress on the mechanism of SAE based on iron metabolism disorders. In addition, we also briefly describe the current status of SAE and iron metabolism disorders and emphasize the therapeutic prospect of targeting iron accumulation as a treatment for SAE, especially iron chelator. Moreover, drug delivery and side effects can be improved with the development of nanotechnology. This work suggests that treating SAE based on disorders of iron metabolism will be a thriving field.