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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Hematopoietic stem/progenitor cells (HSPC) have both unique and common responses following hemorrhage, injury, and sepsis. HSPCs from different lineages have a distinctive response to these "stress" signals. ⋯ In this review, we summarize the pathophysiology of emergency myelopoiesis and the role of myeloid-derived suppressor cells, impaired erythropoiesis, as well as the mobilization of HSPCs from the bone marrow. Finally, we discuss potential therapeutic options to optimize HSPC function after severe trauma or infection.
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Review
Calpain Activation and Organ Failure in Sepsis: Molecular Insights and Therapeutic Perspectives.
Sepsis is a severe systemic response to infection; its ensuing organ failure commonly portends an unfavorable prognosis. Despite the fact that sepsis has been studied for decades, the molecular mechanisms underlying sepsis-induced organ dysfunction remain elusive and more complex than previously thought, and effective therapies are extremely limited. Calpain is a type of calcium-dependent cysteine protease that includes dozens of isoforms. ⋯ Further, there is an accumulating body of evidence supporting the beneficial effect of calpain inhibition or regulation on multiple organ failure in sepsis. Better understanding of the underlying molecular mechanisms is helpful in the development of calpain/calpastatin-targeted therapeutic strategies to protect against sepsis-induced organ injury. The aim of this review is to summarize the recent literature and evidence surrounding the role of the calpain/calpastatin system in the process of organ dysfunction caused by sepsis-including regulation of cell death, modulation of inflammatory response, and disruption of critical proteins-to provide guidance for future research and therapy development.
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Comparative Study Observational Study
Resonance Raman Spectroscopy Derived Tissue Hemoglobin Oxygen Saturation in Critically Ill and Injured Patients.
In this study, we examined the ability of resonance Raman spectroscopy to measure tissue hemoglobin oxygenation (R-StO2) noninvasively in critically ill patients and compared its performance with conventional central venous hemoglobin oxygen saturation (ScvO2). ⋯ R-StO2 has the potential to predict ScvO2 with high precision and might serve as a faster, safer, and noninvasive surrogate to these measures.
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Physical trauma is one of the leading causes of mortality worldwide. Early post-traumatic upregulation of the pro-inflammatory immune response to traumatic injury is paralleled by an anti-inflammatory reaction. A prevalence of each has been associated with the development of secondary complications, including nosocomial infections, acute lung injury, acute respiratory distress syndrome, sepsis, and death after trauma. ⋯ Altered antigen presentation on neutrophils has been shown to possess biomarker features predicting both outcome and vulnerability to infectious complications in severely injured patients. Dysregulated activation of neutrophils following trauma affects their functions including phagocytizing capacity, production of reactive oxygen species, formation of neutrophil extracellular traps, which all together have been associated with the development of secondary complications. Thus, we highlight neutrophils and their functions as potential future targets for optimizing post-traumatic treatment strategies, which potentially may improve patient outcomes.
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Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes. Our primary objective was to develop artificial intelligence capable of predicting sepsis earlier using a minimal set of streaming physiological data in real time. ⋯ This study demonstrates that salient physiomarkers derived from continuous bedside monitoring are temporally and differentially expressed in septic patients. Using this information, minimalistic artificial intelligence models can be developed to predict sepsis earlier in critically ill patients.