Shock : molecular, cellular, and systemic pathobiological aspects and therapeutic approaches : the official journal the Shock Society, the European Shock Society, the Brazilian Shock Society, the International Federation of Shock Societies
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The variant single nucleotide polymorphism rs8104571 has been associated with poor outcomes following traumatic brain injury (TBI) and is most prevalent in those of African ancestry. This single nucleotide polymorphism (SNP) resides within a gene coding for the TRPM4 protein, which complexes with SUR1 protein to create a transmembrane ion channel and is believed to contribute to cellular swelling and cell death in neurological tissue. Our study evaluates the relationship between circulating TRPM4 and SUR1, rs8104571 genotype, and clinical outcome in TBI patients. ⋯ Plasma TRPM4 abundance increased with acute kidney injury severity ( P = 0.02). The association between increased plasma TRPM4 and variant rs810457 supports an underlying mechanism involving increased neuroinflammation with a subsequent increase in the leakage of TRPM4 from the central nervous system into circulation. Alternative sources of plasma TRPM4 including the kidney cannot be excluded and may play a significant role in the pathophysiology of trauma as well.
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Background: Acute infections and sepsis are a leading cause of death. These patients are primarily encountered at the emergency department (ED), where early assessment for sepsis is necessary to improve outcome. In sepsis, the inflammatory response causes several characteristic pathophysiological changes, including a dysregulated and generalized activation of the endothelium. ⋯ Results : For sepsis, E-selectin and ICAM-1 both showed an area under the receiver operating characteristic (AUROC) of 0.62, lower than procalcitonin with 0.77 (both P < 0.01) and lactate with 0.73 ( P = 0.030 and 0.046, respectively), but similar to CRP with 0.60 ( P = 0.758 and 0.876, respectively). For 28-day in-hospital mortality among patients with infection, ICAM-1 performed best with an AUROC of 0.75. Conclusions : Despite promising results in small studies and specific cohorts, particularly in intensive care units, this large-scale evaluation of four endothelial biomarkers highlights their limited diagnostic utility in a broader inclusion setup design at the earliest possible time point of evaluation.
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Background : The interrelation between the plasma proteome and plasma metabolome with sepsis presents a multifaceted dynamic that necessitates further research to elucidate the underlying causal mechanisms. Methods : Our investigation used public genome-wide association study data to explore the relationships among the plasma proteome, metabolome, and sepsis, considering different sepsis subgroup. Initially, two-sample Mendelian randomization established causal connections between the plasma proteome and metabolome with sepsis. ⋯ Further scrutiny revealed that this plasma metabolite notably augments the abundance of ICAM5 protein ( P value = 3.52E-04, OR = 1.11, 95% CI = 1.04-1.17), devoid of any detected heterogeneity, pleiotropy, or reverse causality. Mediated Mendelian randomization revealed ICAM5 mediated 11.9% of 1,2,3-benzenetriol sulfate (2)'s total effect on sepsis progression. Conclusion : This study details the causal link between the plasma proteome and metabolome with sepsis, highlighting the roles of ICAM5 and 1,2,3-benzenetriol sulfate (2) in sepsis progression, both independently and through crosstalk.
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Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The adoption of the Phoenix sepsis criteria eliminated the Systemic Inflammatory Response Syndrome criteria from the definition of pediatric sepsis. The objective of this study is to derive and validate machine learning models predicting in-hospital mortality for children with suspected or confirmed infection or who met the Phoenix sepsis criteria for sepsis and septic shock. ⋯ For children with Phoenix sepsis and Phoenix septic shock, the multivariable logistic regression, light gradient boosting machine, random forest, eXtreme Gradient Boosting, support vector machine, multilayer perceptron, and decision tree models predicting in-hospital mortality had AUPRCs of 0.48-0.65 (95% CI range: 0.42-0.66), 0.50-0.70 (95% CI range: 0.44-0.70), 0.52-0.70 (95% CI range: 0.47-0.71), 0.50-0.70 (95% CI range: 0.44-0.70), 0.49-0.67 (95% CI range: 0.43-0.68), 0.49-0.66 (95% CI range: 0.45-0.67), and 0.30-0.38 (95% CI range: 0.28-0.40) and AUROCs of 0.82-0.88 (95% CI range: 0.82-0.90), 0.84-0.88 (95% CI range: 0.84-0.90), 0.81-0.88 (95% CI range: 0.81-0.90), 0.84-0.88 (95% CI range: 0.83-0.90), 0.82-0.87 (95% CI range: 0.82-0.90), 0.80-0.86 (95% CI range: 0.79-0.89), and 0.76-0.82 (95% CI range: 0.75-0.85), respectively. Conclusion: Among children with Phoenix sepsis admitted to a PICU, the random forest model had the best AUPRC for in-hospital mortality compared to the light gradient boosting machine, eXtreme Gradient Boosting, logistic regression, multilayer perceptron, support vector machine, and decision tree models or a Phoenix Sepsis Score ≥ 2. These findings suggest that machine learning methods to predict in-hospital mortality in children with suspected infection predict mortality in a PICU setting with more accuracy than application of the Phoenix sepsis criteria.
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Background: Acute lung injury (ALI) is a severe condition characterized by a high mortality rate, driven by an uncontrolled inflammatory response. Emerging evidence has underscored the crucial role of the ubiquitin system in ALI. However, because of their vast number, the specific functions of individual ubiquitination regulators remain unclear. ⋯ Results: Through screening the expression of 40 ubiquitin-specific proteases (USPs), which are responsible for removing ubiquitination, we identified several USPs that exhibited differential expression in LPS-treated HLOs compared to untreated HLOs. Notably, USP31 emerged as the most significantly upregulated USP, and the knockdown of USP31 markedly attenuated the inflammatory response of HLOs to LPS treatment. Conclusions: USP31 may play a facilitating role in the inflammatory response during ALI.