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
-
Objective: This study aimed to test whether the prognostic value of tryptophanyl-tRNA synthetase 1 (WARS1) for 28-day mortality in patients with sepsis was affected by monocytopenia. Methods: A prospective analysis of retrospectively collected samples from 74 sepsis patients was performed. WARS1, C-reactive protein (CRP), and procalcitonin were measured at admission and 24 and 72 h after admission. ⋯ The AUROCs of WARS1 at admission and 24 h for mortality were significantly higher in patients without monocytopenia (0.830, 0.818) than in patients with monocytopenia (0.232, 0.196; P < 0.001, both). When patients without monocytopenia were analyzed, the AUROCs of WARS1 for mortality were 0.830 and 0.818 at admission and 24 h, respectively, which were significantly higher than those of CRP (0.586, 0.653) and procalcitonin (0.456, 0.453) at the same time points ( P = 0.024 and 0.034, respectively). Conclusion: WARS1 is a useful biomarker for prognosis in sepsis patients without monocytopenia.
-
Background: Sepsis is a life-threatening systemic inflammatory disease that can cause many diseases, including acute kidney injury (AKI). Increasing evidence showed that a variety of circular RNAs were considered to be involved in the development of the disease. In this study, we aimed to elucidate the role and potential mechanism of circUSP42 in sepsis-induced AKI. ⋯ In addition, circUSP42 induced DUSP1 expression via sponging miR-182-5p to ameliorate LPS-induced HK2 cell damage. Conclusion : Our results showed that circUSP42 overexpression might attenuate LPS-induced HK2 cell injury by regulating miR-182-5p/DUSP1 axis. This might provide therapeutic strategy for the treatment of sepsis.
-
Background: Intermediate-risk pulmonary embolism (PE) patients in the intensive care unit (ICU) are at a higher risk of hemodynamic deterioration than those in the general ward. This study aimed to construct a machine learning (ML) model to accurately identify the tendency for hemodynamic deterioration in the ICU patients with intermediate-risk PE. Method: A total of 704 intermediate-risk PE patients from the MIMIC-IV database were retrospectively collected. ⋯ Simplified XGBoost model demonstrated the best predictive performance with an area under the curve of 0.866 (95% confidence interval, 0.800-0.925), and after recalibrated by isotonic regression, the area under the curve improved to 0.885 (95% confidence interval, 0.822-0.935). Based on the simplified XGBoost model, a web app was developed to identify the tendency for hemodynamic deterioration in ICU patients with intermediate-risk PE. Conclusion: A simplified XGBoost model can accurately predict the occurrence of hemodynamic deterioration for intermediate-risk PE patients in the ICU, assisting clinical workers in providing more personalized management for PE patients in the ICU.
-
The analysis of the single-cell transcriptome has emerged as a powerful tool to gain insights on the basic mechanisms of health and disease. It is widely used to reveal the cellular diversity and complexity of tissues at cellular resolution by RNA sequencing of the whole transcriptome from a single cell. Equally, it is applied to discover an unknown, rare population of cells in the tissue. ⋯ And with the development of numerous packages in R and Python, new directions in the computational analysis of single-cell transcriptomes can be taken to characterize healthy versus diseased tissues to obtain novel pathological insights. Downstream analysis such as differential gene expression analysis, gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, cell-cell interaction analysis, and trajectory analysis has become standard practice in the workflow of single-cell transcriptome analysis to further examine the biology of different cell types. Here, we provide a broad overview of single-cell transcriptome analysis in health and disease conditions currently applied in various studies.
-
Patients 65 years and older account for an increasing proportion of traumatic brain injury (TBI) patients. Aged TBI patients experience increased morbidity and mortality compared with young TBI patients. We previously demonstrated a marked accumulation of CD8 + T-cells within the brains of aged TBI mice compared with young TBI mice. ⋯ Contrastingly, no difference was detected in young mice after aCD49d Ab treatment. Collectively, aCD49 Ab treatment reduced T-cells in the injured brain, improved survival, and attenuated neurocognitive and gait deficits. Hence, aCD49d Ab may be a promising therapeutic intervention in aged TBI subjects-a population often excluded in TBI clinical trials.