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Abstract: Background: Eugenol has been found to inhibit a variety of disease processes, including abdominal aortic aneurysm (AAA) formation. However, the specific role and the underlying molecular mechanism of Eugenol in AAA progression need to be further revealed. Methods: Vascular smooth muscle cells (VSMCs) were pretreated with Eugenol, followed by treated with Angiotensin II (Ang-II). VSMCs were transfected with HMGB2 siRNA or overexpression vector and treated with Ang-II to confirm the effect of HMGB2 on AAA progression. Cell proliferation and death were determined using cell counting kit 8 assay, 5-ethynyl-2'-deoxyuridine assay, and flow cytometry. Inflammatory factors were examined by ELISA. Fe 2+ , glutathione, and malondialdehyde levels were tested to evaluate cell ferroptosis. The protein levels of ferroptosis-related markers, high mobility group box 2 (HMGB2), and STAT3 were measured using western blot. Human AAA tissues and normal abdominal aortic tissues were collected to detect HMGB2 mRNA expression by quantitative real-time PCR. The interaction between HMGB2 and STAT3 was confirmed by chromatin immunoprecipitation assay and dual-luciferase reporter assay. Results: Eugenol enhanced VSMCs proliferation, while restrained Ang-II-induced death, inflammation, and ferroptosis. HMGB2 was upregulated in AAA tissues and Ang-II-induced VSMCs, and Eugenol significantly decreased HMGB2 expression. HMGB2 knockdown reduced Ang-II-induced VSMCs death, inflammation, and ferroptosis, Besides, HMGB2 overexpression abolished the effect of Eugenol on Ang-II-induced VSMCs injury. Transcription factor STAT3 bound to HMGB2 promoter region to increase its expression. In addition, Eugenol decreased STAT3 expression to regulate HMGB2. Conclusion: Eugenol could slow down the development of AAA, which might be achieved by regulating STAT3/HMGB2 axis.

Abstract: Background: Acute lung injury (ALI) is a severe complication of sepsis, characterized by inflammation, edema, and injury to alveolar cells, leading to high mortality rates. Septic ALI is a complex disease involving multiple factors and signaling pathways. STEAP family member 1 (STEAP1) has been reported to be upregulated in a sepsis-induced ALI model. However, the role of STEAP1 in the regulation of septic ALI is not yet fully understood. Methods: The study stimulated human pulmonary microvascular endothelial cells (HPMECs) using lipopolysaccharides (LPS) to establish an in vitro ALI model. The study used quantitative real-time polymerase chain reaction to measure mRNA expression, and western blotting assay or immunohistochemistry assay to analyze protein expression. Cell Counting Kit-8 assay was performed to assess cell viability. Flow cytometry was conducted to analyze cell apoptosis. Tube formation assay was used to analyze the tube formation rate of human umbilical vein endothelial cells. Enzyme-linked immunosorbent assays were used to measure the levels of interleukin 1beta and tumor necrosis factor alpha. The levels of Fe 2+ and reactive oxygen species were determined using colorimetric and fluorometric assays, respectively. The glutathione level was also determined using a colorimetric assay. m6A RNA immunoprecipitation assay, dual-luciferase reporter assay, and RNA immunoprecipitation assay were performed to identify the association of STEAP1 with methyltransferase 14, N6-adenosine-methyltransferase noncatalytic subunit (METTL14) and insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2). The transcript half-life of STEAP1 was analyzed by actinomycin D assay. Finally, a rat model of polymicrobial sepsis was established to analyze the effects of STEAP1 knockdown on lung injury in vivo . Results: We found that the mRNA expression levels of STEAP1 and METTL14 were upregulated in the blood of ALI patients induced by sepsis compared to healthy volunteers. LPS treatment increased the protein levels of STEAP1 and METTL14 in HPMECs. STEAP1 depletion attenuated LPS-induced promoting effects on HPMECs' apoptosis, inflammatory response, and ferroptosis, as well as LPS-induced inhibitory effect on tube formation. We also found that METTL14 and IGF2BP2 stabilized STEAP1 mRNA expression through the m6A methylation modification process. Moreover, METTL14 silencing attenuated LPS-induced effects by decreasing STEAP1 expression in HPMECs, and STEAP1 silencing ameliorated cecal ligation and puncture-induced lung injury of mice. Conclusion: METTL14/IGF2BP2-mediated m6A modification of STEAP1 aggravated ALI induced by sepsis. These findings suggest potential therapeutic targets for the treatment of this disease.

Abstract: Liver ischemia reperfusion (IR) injury significantly impacts clinical outcomes by increasing the risk of hepatic dysfunction after liver surgery. Fatty livers are more susceptible to IR stress. Recent studies have demonstrated that S100A9 plays a crucial role in both IR injury and the progression of liver steatosis. Nevertheless, the precise mechanisms underlying these effects remain unclear. In our study, transcriptome analysis of fatty livers subjected to IR insult in mice identified S100A9 as an important mediator. Employing loss-of-function approaches, we investigated the immune regulatory function of S100A9 and its downstream signaling in fatty liver IR injury. As expected, S100A9 emerged as one of the most significantly upregulated genes during the reperfusion stage in fatty livers. Genetic knockdown of S100A9 markedly ameliorated liver pathological damage, evidenced by reduced macrophage/neutrophil infiltration as well as the decreased expression of proinflammatory factors. Transcriptome/functional studies revealed that S100A9 triggered liver inflammatory response via regulating toll-like receptor 2 (TLR2)/activating transcription factor 4 (ATF4) signaling. Additionally, TLR2 expression was notably increased in macrophages from ischemic fatty livers. In vitro , recombinant S100A9-stimulated macrophages exhibited the elevated production of proinflammatory factors and TLR2/ATF4 pathway activation. Intriguingly, S100A9 facilitated ATF4 nuclear translocation and enhanced NEK7/NLRP3 inflammasome activation in macrophages. In conclusion, our study identified S100A9 as a key regulator responsible for macrophage NLRP3 inflammasome activation and subsequent inflammatory injury in fatty liver IR process. Targeting TLR2/ATF4 signaling may offer a novel therapeutic strategy for mitigating S100A9-mediated liver injury.

Abstract: Background : Extracorporeal membrane oxygenation (ECMO) is an effective technique for providing short-term mechanical support to the heart, lungs, or both. During ECMO treatment, the inflammatory response, particularly involving cytokines, plays a crucial role in pathophysiology. However, the potential effects of cytokines on patients receiving ECMO are not comprehensively understood. Methods : We acquired three ECMO support datasets, namely two bulk and one single-cell RNA sequencing (RNA-seq), from the Gene Expression Omnibus (GEO) combined with hospital cohorts to investigate the expression pattern and potential biological processes of cytokine-related genes (CRGs) in patients under ECMO. Subsequently, machine learning approaches, including support vector machine (SVM), random forest (RF), modified Lasso penalized regression, extreme gradient boosting (XGBoost), and artificial neural network (ANN), were applied to identify hub CRGs, thus developing a prediction model called CRG classifier. The predictive and prognostic performance of the model was comprehensively evaluated in GEO and hospital cohorts. Finally, we mechanistically analyzed the relationship between hub cytokines, immune cells, and pivotal molecular pathways. Results : Analyzing bulk and single-cell RNA-seq data revealed that most CRGs were significantly differentially expressed; the enrichment scores of cytokine and cytokine-cytokine receptor (CCR) interaction were significantly higher during ECMO. Based on multiple machine learning algorithms, nine key CRGs (CCL2, CCL4, IFNG, IL1R2, IL20RB, IL31RA, IL4, IL7, and IL7R) were used to develop the CRG classifier. The CRG classifier exhibited excellent prognostic values (AUC > 0.85), serving as an independent risk factor. It performed better in predicting mortality and yielded a larger net benefit than other clinical features in GEO and hospital cohorts. Additionally, IL1R2, CCL4, and IL7R were predominantly expressed in monocytes, NK cells, and T cells, respectively. Their expression was significantly positively correlated with the relative abundance of corresponding immune cells. Gene set variation analysis (GSVA) revealed that para-inflammation, complement and coagulation cascades, and IL6/JAK/STAT3 signaling were significantly enriched in the subgroup that died after receiving ECMO. Spearman correlation analyses and Mantel tests revealed that the expression of hub cytokines (IL1R2, CCL4, and IL7R) and pivotal molecular pathways scores (complement and coagulation cascades, IL6/JAK/STAT3 signaling, and para-inflammation) were closely related. Conclusion : A predictive model (CRG classifier) comprising nine CRGs based on multiple machine learning algorithms was constructed, potentially assisting clinicians in guiding individualized ECMO treatment. Additionally, elucidating the underlying mechanistic pathways of cytokines during ECMO will provide new insights into its treatment.

Abstract: Background: Fluid overload (FO) in critically ill children correlates with higher morbidity and mortality rates. Continuous renal replacement therapy (CRRT) is commonly employed to manage FO. In adults, both FO and CRRT adversely affect myocardial function. It remains unclear if children experience similar cardiovascular effects. Methods: Observational single-center study on children (<18 years) receiving CRRT at Texas Children's Hospital from 11/2019 to 3/2021. Excluded were those with end-stage renal disease, pacemakers, extracorporeal membrane oxygenation, ventricular assist devices, apheresis, or without an arterial line. Electrocardiometry (ICON Osypka Medical GmbH, Berlin, Germany) which is noninvasive and utilizes bioimpedance, was applied to obtain hemodynamic data over the first 48 h of CRRT. Our aim was to identify how FO >15% affects hemodynamics in children receiving CRRT. Results: Seventeen children, median age 43 months (interquartile range [IQR] 12-124), were included. The median FO at CRRT initiation was 14.4% (2.4%-25.6%), with 9 (53%) patients having FO >15%. Differences were noted in systemic vascular resistance index (1,277 [IQR 1088-1,666] vs. 1,030 [IQR 868-1,181] dynes/s/cm 5 /m 2 , P < 0.01), and cardiac index (3.90 [IQR 3.23-4.75] vs. 5.68 [IQR 4.65-6.32] L/min/m 2 , P < 0.01), with no differences in heart rate or mean arterial pressure between children with and without FO. Conclusion: FO affects the hemodynamic profile of children on CRRT, with those having FO >15% showing higher systemic vascular resistance index and lower cardiac index, despite heart rate and mean arterial pressure remaining unchanged. Our study illustrates the feasibility and utility of electrocardiometry in these patients, suggesting future research employ this technology to further explore the hemodynamic effects of dialysis in children.

Abstract: Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to ICUs of Mayo Clinic Hospitals over eight-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status. Of 19,177 patients, 42% were female with a median age of 65 (IQR, 55-76) years, APACHE III score of 70 (IQR, 56-87), hospital length of stay (LOS) of 7 (IQR, 4-12) days, and ICU LOS of 2 (IQR, 1-4) days. Four distinct trajectories were identified: fast recovery (27% with a mortality rate of 3.5% and median hospital LOS of 3 (IQR, 2-15) days), slow recovery (62% with a mortality rate of 3.6% and hospital LOS of 8 (IQR, 6-13) days), fast decline (4% with a mortality rate of 99.7% and hospital LOS of 1 (IQR, 0-1) day), and delayed decline (7% with a mortality rate of 97.9% and hospital LOS of 5 (IQR, 3-8) days). Distinct trajectories remained robust and were distinguished by Charlston comorbidity index, Apache III scores, day 1 and day 3 SOFA (p < 0.001 ANOVA). These findings provide a foundation for developing prediction models and digital twin decision support tools, improving both shared decision-making and resource planning.

Abstract: Introduction: Coagulopathy following traumatic injury impairs stable blood clot formation and exacerbates mortality from hemorrhage. Understanding how these alterations impact blood clot stability is critical to improving resuscitation. Furthermore, the incorporation of machine learning algorithms to assess clinical markers, coagulation assays and biochemical assays allows us to define the contributions of these factors to mortality. In this study, we aimed to quantify changes in clot formation and mechanics after traumatic injury and their correlation to mortality.Materials and Methods: Plasma was isolated from injured patients upon arrival to the emergency department prior to blood product administration, or procedural intervention. Coagulation kinetics and mechanics of healthy donors and patient plasma were compared with rheological, turbidity and thrombin generation assays. ELISA's were performed to determine tissue plasminogen activator (tPA) and D-dimer concentration. Recursive elimination with random forest models were used to assess the predictive strength of clinical and laboratory factors.Results: Sixty-three patients were included in the study. Median injury severity score (ISS) was 17, median age was 38 years, and mortality was 30%. Trauma patients exhibited reduced clot stiffness, increased fibrinolysis, and reduced thrombin generation compared to healthy donors. Deceased patients exhibited the greatest deviation from healthy levels. Fibrinogen, clot stiffness, D-dimer and tPA all demonstrated significant correlation to ISS. Machine-learning algorithms identified the importance of coagulation kinetics and clot structure on patient outcomes.Conclusions: Rheological markers of coagulopathy and biochemical factors are associated with injury severity and are highly predictive of mortality after trauma, providing evidence for integrated predictive models and therapeutic strategies.

Introduction: Trauma and hemorrhagic shock (T/HS) are associated with multiple organ injury. Antithrombin (AT) has anti-inflammatory and organ protective activity through its interaction with endothelial heparan sulfate containing a 3-O-sulfate modification. Our objective was to examine the effects of T/HS on 3-O-sulfated (3-OS) heparan sulfate expression and determine whether AT-heparan sulfate interactions are necessary for its anti-inflammatory properties.

Methods: Male Sprague Dawley rats underwent laparotomy, gut distension and fixed-pressure hemorrhagic shock (HS) and resuscitation. Liquid chromatography-coupled mass spectrometry analyses were performed to measure pulmonary and plasma heparan sulfate di/tetrasaccharides. Pulmonary mRNA levels were assessed by nCounter panel. Rats were treated with vehicle or surfen (1 mg/kg), a small molecule heparan sulfate antagonist, to block the interaction between AT and endothelial cells prior to T/HS and resuscitated with fresh frozen plasma (FFP), lactated Ringer's (LR), or AT-supplemented LR. Lung injury was assessed histologically for injury and fibrin deposition and immunostained for myeloperoxidase (MPO). Plasma was assessed for circulating inflammatory biomarkers.

Results: T/HS significantly reduced pulmonary expression of 6-O and 3-O sulfated heparan sulfate, which was associated with reduced pulmonary 6-O- and 3-O-sulfotransferase mRNA levels. Surfen increased fibrin deposition and inflammatory cell infiltration into pulmonary tissue in T/HS rats resuscitated with FFP but had no effect in LR resuscitated rats. Although T/HS and LR resuscitation worsened histologic lung injury compared to sham, regardless of surfen treatment, lung injury was notably improved in FFP resuscitated rodents pre-treated with vehicle but not surfen. Surfen abrogated the anti-inflammatory effects of FFP, indicated by notable increases in circulating levels of multiple pro-inflammatory mediators compared to rats pre-treated with vehicle. Finally, we observed significant increases in pulmonary fibrin and MPO staining in rats pre-treated with surfen followed by resuscitation with LR supplemented with AT compared to vehicle, which was associated with notable increases in lung injury scores.

Conclusions: T/HS causes pronounced reductions in pulmonary expression of 3-OS heparan sulfate, which is essential to AT's anti-thrombotic and anti-inflammatory activity. Blocking the interaction between AT and the endothelium attenuates the anti-thromboinflammatory and organ protective properties of FFP, suggesting that AT-endothelial anticoagulant function and anti-inflammatory signaling is important for organ protection during T/HS.

Introduction: The understanding of the interaction of closed-loop control of ventilation and oxygenation, specifically fraction of inspired oxygen (FiO2) and positive end-expiratory pressure (PEEP), and fluid resuscitation after burn injury and acute lung injury from smoke inhalation is limited. We compared the effectiveness of FiO2, PEEP, and ventilation adjusted automatically using adaptive support ventilation (ASV) and decision support fluid resuscitation based on urine output in a clinically relevant conscious ovine model of lung injury secondary to combined smoke inhalation and major burn injury.

Methods: Sheep were subjected to burn and smoke inhalation injury under deep anesthesia and analgesia. After injury, sheep were randomly allocated to two groups. 1) Closed-loop group: automated mechanical ventilation (ASV), oxygen FiO2 and PEEP (n = 9); and 2) Control group: mechanically ventilated with standard ASV mode (n = 8). FiO2, PEEP, and the percentage of the minute volume (%MV) were automatically adjusted in group 1, whereas PEEP was held at 5 cmH2O, and FiO2 and %MV were manually adjusted in group 2. Decision support fluid resuscitation was guided based on urine output. Cardiopulmonary hemodynamics were monitored for 48 h.

Results: There were no differences in body weight and the severity of smoke injury between the two groups. The Closed-loop group resulted in significantly higher PEEP, %MV, static lung compliance, and survival rate; the driving pressure was significantly lower compared to the Control group. In the Closed-loop group, the net fluid balance at 48 h was significantly greater than in the Control group.

Conclusion: Closed-loop ventilation and oxygenation with decision support fluid resuscitation improve lung mechanics and survival in sheep with combined burn and smoke inhalation. There were no negative interactions observed between automated PEEP control and fluid management.