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Aim: Acute lung injury (ALI) is a common cause of morbidity in patients with severe sepsis. Exosomes (EXOs) have been reported to induce ALI after severe hemorrhagic shock; therefore, this study aimed to investigate the role of EXOs isolated from the blood of septic rats with ALI.

Materials and methods: Blood samples and lung tissues were collected from rats undergoing cecal ligation and puncture (CLP). EXOs were isolated by centrifugation from the blood of rats undergoing CLP and administered intravenously to normal rats, and 12 h after administration, lung tissues were harvested. Pathophysiological changes in the lung, the lung wet/dry weight ratio, and the lung microvascular permeability were assessed. Plasma inflammatory cytokines, namely tumor necrosis factor (TNF)-α, interleukin-6, and high-mobility group box chromosomal protein 1, were measured by enzyme-linked immunosorbent assay. In addition, lung microthrombosis was evaluated by immunohistochemistry. To investigate the effects of EXOs on tissue macrophages (Mϕs), the production of TNF-α by isolated tissue Mϕs was assessed in the presence or absence of EXOs in vitro .

Results: Interstitial pulmonary edema, inflammatory cell infiltration, microhemorrhage, and microthrombosis were observed in the lung after CLP. Similar pathophysiological changes were observed in normal rats administered EXOs, although the extent of these changes was less severe than that in rats undergoing CLP. After EXO administration, the lung wet/dry ratio, lung microvascular permeability, and plasma inflammatory cytokine levels increased. The production of TNF-α by tissue Mϕs increased during coculture with EXOs, blocked by anti-toll-like receptor 4 antibodies in the media. Furthermore, TNF-α production significantly decreased in EXO-stimulated cells treated with Triton X or proteinase K, suggesting that the surface protein and lipid fraction were most likely primary determinants.

Conclusion: EXOs isolated from the blood of septic rats trigger ALI by increasing inflammatory mediators.

Traumatic injury induces a complex host response, comprising endothelial damage, and simultaneous pro- and anti-inflammatory responses. These may contribute to complications seen in some patients days or weeks later. Although there is ever-increasing evidence showing that resuscitation with blood products improves survival, their impact on the host response remains unclear. A terminally anesthetized Large White pig model of traumatic hemorrhagic shock (THS) and prolonged care evaluated different resuscitation fluids (saline, fresh-frozen plasma, packed red blood cells and fresh-frozen plasma [1:1], or fresh whole blood [n = 9 per group]). Serial blood samples were collected for enzyme-linked immunosorbent assay, hematology, and flow cytometry, and postmortem tissue samples collected for RT-qPCR and immunohistochemistry. THS significantly increased circulating markers of endothelial activation (angiopoietin-2 and von Willibrand factor antigen; both P < 0.001) and glycocalyx shedding (hyaluronic acid; P < 0.001). THS also elicited a robust inflammatory response, with significant elevations in circulating interleukin-6 and high mobility group box 1 (both: P < 0.001), neutrophilia ( P < 0.001), lymphopenia ( P < 0.001), and increased inflammatory gene expression across a number of tissues. Compared with saline, resuscitation with blood products reduced hyaluronic acid ( P < 0.001) but not angiopoeitin-2 or von Willebrand factor antigen (both: P > 0.05). The effect of blood products on peripheral cytokine concentrations or immune cell populations was minimal, nor did they significantly alter tissue inflammatory gene expression, neutrophil, or lymphocyte number compared with saline-treated animals. These data suggest resuscitation with blood products can protect the endothelial glycocalyx, but they have little impact on the acute (<8 hours) host response(s) to THS and prolonged care compared to animals treated with saline.

Background: Severe burns continue to be associated with significant morbidity and mortality despite advances in resuscitation techniques. Concomitant injury, such as traumatic brain injury, adds complexity to resuscitation paradigms as high-volume fluid resuscitation together with high losses of plasma proteins may lead to poor outcomes with respect to traumatic brain injury and associated cerebral edema. Currently, "goal-directed" methods of resuscitation are utilized in which clinical end points guide fluid volume needs. Unfortunately, clinical changes often indicate that significant organ dysfunction has already occurred. In this targeted metabolomics study, we compare "aggressive" versus "restrictive" fluid resuscitation strategies to identify compounds indicative of injury progression.

Methods: A porcine model of combined brain injury and severe burns was utilized. Injured animals were randomized to receive either "aggressive" fluid resuscitation using the Parkland formula or "restrictive" resuscitation with the modified Brooke formula. Resuscitation was continued for 8 hours. Plasma and urine samples were collected for targeted analysis of oxylipins and steroids by ultra-performance liquid chromatography-tandem mass spectrometry.

Results: Sixty-nine serum and urinary oxylipins were identified. Significant elevations of 15 urinary oxylipins were noted in animals that received the restrictive resuscitation strategy. No significant differences in plasma oxylipins were found. Twenty-eight serum steroids and 29 urinary steroids were isolated. The concentrations of three serum steroids were significantly higher in the "restricted" resuscitation group. No differences in urinary steroids were identified.

Conclusions: In this study, targeted metabolomics was used to identify plasma and urinary oxylipins and steroids in both the restrictive and aggressive resuscitation groups. Notably, significant elevations in 15 urinary oxylipins and three serum steroids were identified only in animals that were randomized to "restricted" resuscitation. These findings demonstrate detectable differences in lipid metabolites within 8 hours of severe injury, which may correlate with differences in inflammation and facilitate goal-directed resuscitation.

Background: Infants with congenital heart disease (CHD) frequently undergo surgery during their first year of life. Infants undergoing CHD surgery experience systemic inflammation and hemodilution that can deplete circulating immunoglobulins (Ig).

Methods: In this prospective single-center observational cohort study without healthy controls, we quantified IgG, IgA, and IgM at four perioperative time points (T0 = preoperative; T1 = 24 h; T2 = 72 h; T3 = day 7) in 300 infants (<12 months), including 280 with cardiopulmonary bypass (CPB) and 20 without CPB. Postoperative infections were defined using Centers for Disease Control and Prevention/National Healthcare Safety Network cardiothoracic criteria. Multivariable logistic and linear models assessed associations between Ig depletion, CPB characteristics, and clinical outcomes.

Results: Mean IgG fell 23% at T1 (910 ± 160→700 ± 140 mg/dL, P < 0.001) and partially recovered by T3. Longer CPB was independently related to larger IgG decline ( β = 2.5% per 10 min, P < 0.001; R ² = 0.14). Infection occurred in 17% of infants and was associated with lower IgG at T1 (650 ± 135 vs. 725 ± 140 mg/dL, P < 0.001) and prolonged intensive care unit stay (median: 7 vs. 5 days, P < 0.01). Baseline IgG < 900 mg/dL (adjusted odds ratio [aOR]: 2.1), CPB > 120 min (aOR: 2.5), gestation < 37 weeks (aOR: 1.9), and surgical complexity (Risk Adjustment for Congenital Heart Surgery category ≥3; aOR: 1.8) independently predicted infection.

Conclusions: Substantial early postoperative IgG depletion correlates with infection risk and intensive care unit utilization after infant CHD surgery. Routine perioperative Ig monitoring may help stratify risk and identify candidates for Ig-based interventions.

Background: Diabetic ketoacidosis (DKA) frequently results in acute kidney injury (AKI), elevating mortality and healthcare costs. However, comprehensive national studies on AKI risk factors in DKA patients are scarce.

Methods: A retrospective analysis was conducted on 464,057 hospitalizations for DKA throughout the United States from 2010 to 2019, using the Nationwide Inpatient Sample database. Instances of AKI were identified through International Classification of Diseases (9th and 10th revisions) diagnostic codes, and multivariable logistic regression was applied to assess risk factors, including demographic characteristics, preexisting comorbidities, complications, and institutional variables.

Results: In the analyzed cohort, 175,233 patients (37.8%) developed AKI, with its prevalence increasing from 28.2% in 2010 to 46.3% by 2019. The multivariate analysis indicated several independent risk factors: age ≥45 years; Black race; comorbidities ≥1; bed size of hospital (medium, large); urban and teaching hospitals; region of hospital (Midwest/North Central, South, West); preexisting comorbidities (congestive heart failure, coagulopathy, fluid and electrolyte disorders, other neurological disorders, pulmonary circulation disorders, chronic kidney disease excluding end-stage renal disease, weight loss, pancreatitis). Protective factors included being female, Hispanic/Native American, having Medicaid, private insurance/self-pay, and undergoing elective admission. The development of AKI was associated with worsened outcomes, including increased complications, a greater need for invasive therapies (dialysis, ventilator support), prolonged hospital stays (median 4 vs. 3 days; P  < 0.001), higher median treatment costs ($31,386 vs. $20,157; P  < 0.001), and increased mortality rates (4.1% vs. 0.9%, P  < 0.001).

Conclusion: AKI is prevalent in DKA, linked to higher mortality and costs, necessitating early risk assessment and intervention.

Sepsis is a life-threatening syndrome characterized by acute organ dysfunction caused by a dysregulated host response to infection, often complicated by multi-organ injury. Myocardial injury occurs in approximately 40% of patients with sepsis, and failure to promptly recognize and manage this condition may result in missed treatment windows, disease exacerbation, and increased mortality. Sepsis-induced myocardial injury is reversible, and early diagnosis coupled with timely intervention can significantly reduce mortality. However, due to the unclear underlying pathophysiology and the absence of a definitive gold standard for diagnosis, conventional biomarkers of myocardial injury offer limited diagnostic utility. Emerging biomarkers such as high-mobility group box 1 protein, microRNAs, and growth differentiation factor 15 are currently being explored to understand their potential role in early detection and prognostic assessment. In this review, recent research advances in both traditional and novel biomarkers associated with sepsis-induced cardiomyopathy have been summarized, providing insights into their clinical applications and future research directions.

Endotoxemia is a feature of sepsis pathogenesis and has also been found to mediate the pathophysiology of multiple inflammatory conditions. In this work, we use a lipopolysaccharide (LPS) induced endotoxemia model in zebrafish to identify novel mediators of LPS toxicity. We performed transcriptomic studies on LPS-treated larvae, followed by in silico analysis, which revealed associations between the signatures of LPS-treated embryos and those of drugs involving diverse pathways. In parallel, we performed an in vivo screen using >1,500 FDA-approved compounds and identified multiple novel small molecules that reduced inflammation and prevented LPS toxicity. We focused on the direct thrombin inhibitor dabigatran, which was identified through both the in vivo and in silico analyses. We found that dabigatran co-administration significantly reduced the expression of inflammatory cytokines and completely protected zebrafish from endotoxemic death due to LPS. Surprisingly, we found that this protection occurs in prothrombin mutant fish, proving that protection from endotoxemia occurs independently of the anticoagulant function of dabigatran. We additionally found that dabigatran administration significantly decreased nitric oxide production and apoptosis compared to LPS treatment alone, suggesting possible mechanisms by which protection from endotoxemia is achieved. In summary, we identify several novel small molecules that prevent LPS-induced endotoxemia and show that one such small molecule, dabigatran, exerts a thrombin-independent effect on nitric oxide production and apoptosis. This and the other identified small molecules warrant further exploration in inflammatory conditions including sepsis.

Background: Accumulating evidence supports the use of the prothrombin time-international normalized ratio-to-albumin ratio (PTAR) as a prognostic biomarker in various diseases. This study evaluated whether PTAR, an easily measurable index, predicts short- and long-term all-cause mortality in cancer patients with sepsis (cancer sepsis).

Methods: This retrospective cohort study used data from 1,584 adult cancer-sepsis patients in the ICU from the MIMIC-IV database (v3.1) and 82 patients from a Chinese tertiary oncology hospital. Mortality at 28 and 365 days was analyzed using multivariable Cox models, restricted cubic splines, Kaplan-Meier curves, and subgroup analyses. Discriminatory performance was assessed with the area under the receiver operating characteristic curve (AUC), comparing PTAR with the Sequential Organ Failure Assessment (SOFA) score, international normalized ratio (INR), and serum albumin (ALB). AUC differences were tested using DeLong's test.

Results: In the MIMIC-IV cohort, patients in the highest PTAR quartile (Q4) had significantly higher risks of 28-day (adjusted HR = 2.038) and 365-day mortality (adjusted HR = 1.615). PTAR showed superior discrimination compared to the SOFA score and INR at both time points. In the Chinese cohort, PTAR also predicted 28-day mortality (adjusted HR = 4.682), with better AUC (0.721) than SOFA (0.564).

Conclusions: PTAR at ICU admission independently predicts 28-day mortality in cancer patients with sepsis in both the MIMIC-IV and Chinese cohorts, outperforming SOFA and INR. The 365-day mortality was validated only in the MIMIC-IV cohort, where PTAR demonstrated stronger predictive performance compared to INR and SOFA. Therefore, PTAR can serve as a complementary biomarker to be used in conjunction with existing clinical scoring systems and laboratory indicators, providing additional risk assessment information for cancer-sepsis.

Persistent Inflammation, Immunosuppression, and Catabolism Syndrome (PICS) can occur following sepsis when there is an overwhelming systemic inflammatory response that leads to multiple organ dysfunction, significant morbidity, and chronic critical illness. Despite the increasing recognition of this clinical problem, there are no interventions that can reverse this response. This study aims to characterize the immune responses in a murine PICS model using cecal ligation and puncture (CLP) and assess the efficacy of various immunomodulatory agents, including G-CSF, GM-CSF, and anti-PD-L1 antibody, in reversing the immune dysfunction when given after day four, once the typical acute response to sepsis starts to subside. Our results showed that anti-PD-L1 therapy showed greater efficacy than G-CSF and GM-CSF in reversing immunosuppression post-CLP, as evidenced by improved immune cell numbers, immune function, MHC-II and CD11b expression on innate immune cells, and INFγ production from T cells. However, while improving certain immune parameters, anti-PD-L1 treatment did not allow for effective bacterial clearance when the mice were inoculated with Pseudomonas aeruginosa eight days after CLP. Interestingly, despite this decreased bacterial clearance, anti-PD-L1 therapy did not affect survival for CLP mice (100% survival) compared with untreated CLP mice (60% survival). These findings suggest that anti-PD-L1 therapy may improve some of the immune dysfunction seen after CLP and allow for improved survival towards secondary bacterial infections.

Background: Accurate prediction of 28-day mortality in intensive care unit (ICU) patients represents a critical challenge in modern critical care medicine, with profound implications for clinical decision-making, resource optimization, and patient-centered care. Traditional severity scoring systems and conventional machine learning approaches have consistently demonstrated limitations in discriminative performance, calibration accuracy, and generalizability across heterogeneous patient populations.

Methods: This retrospective cohort study employed comprehensive data from 654 consecutively admitted adult ICU patients at a tertiary academic medical center between August 2022 and August 2024.We developed and rigorously validated four distinct prediction methodologies: Logistic Regression (LR), Random Forest (RF), Gradient Boosting (GB), and an innovative Multi-Model Fusion (MMF) framework incorporating probability averaging from constituent models. Our evaluation framework encompassed exhaustive discrimination metrics (AUC-ROC, sensitivity, specificity, F1-score), sophisticated calibration assessment (Brier score, calibration curves, Hosmer-Lemeshow test), detailed subgroup analyses across clinically relevantpatient strata, and multi-dimensional feature importance evaluation.

Results: The Multi-Model Fusion paradigm demonstrated statistically superior performance with an AUC-ROC of 0.862 (95% CI: 0.821-0.903), significantly outperforming all individual models (LR: ΔAUC=0.121, p<0.001; RF: ΔAUC=0.034, p=0.018; GB: ΔAUC=0.027, p=0.032). The fusion model achieved an optimal equilibrium between sensitivity (84.6%) and specificity (81.0%) while maintaining exceptional calibration characteristics (Brier score: 0.140; Hosmer-Lemeshow test: χ²=6.28, p=0.616). Remarkable performance consistency was observed across all patient subgroups (AUC-ROC range: 0.815-0.875), encompassing diverse age strata, disease severity spectra, and intervention requirements. SOFA score, APACHE II score, and Glasgow Coma Scale emerged as consistently robust predictors across all feature importance methodologies. Clinically meaningful risk stratification delineated three distinct mortalitycategories: low-risk (<0.3 probability, 5.6% observed mortality), moderate-risk (0.3-0.7, 31.7%), and high-risk (>0.7, 83.3%).

Conclusion: The Multi-Model Fusion framework establishes a clinically actionable and methodologically sophisticated paradigm for 28-day mortality prediction in ICU patients, effectively addressing fundamental limitations of conventional approaches through enhanced discriminative performance, exemplary calibration accuracy, and consistent generalizability across diverse patient populations. These compelling findings strongly advocate for its integration intoICU clinical decision support ecosystems to advance prognostic precision and guide personalized therapeutic strategies.