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ObjectiveMucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) modulates the inflammatory immune response and organ dysfunction, which are closely implicated in sepsis pathogenesis and progression. This study aimed to explore the role of MALT1 in sepsis-induced organ injury, immune cell dysregulation, and inflammatory storms.MethodsSeptic mice were constructed by intraperitoneal injection of lipopolysaccharide, followed by overexpression or knockdown of MALT1 by tail vein injection of the corresponding lentivirus. Mouse naïve CD4+ T cells and bone marrow-derived macrophages were treated with MALT1 overexpression/knockdown lentivirus plus lipopolysaccharide.ResultsIn the lungs, livers, and kidneys of septic mice, MALT1 overexpression exaggerated their injuries, as shown by hematoxylin and eosin staining (all p p p p p p p p Ex vivo experiments revealed that MALT1 overexpression promoted the polarization of M1 macrophages and naïve CD4+ T cells toward Th2 and Th17 cells (all p p in vivo and ex vivo (p ConclusionMucosa-associated lymphoid tissue lymphoma translocation protein 1 amplifies multiple organ injury, inflammation, oxidative stress, and imbalance of macrophages and CD4+ T cells by activating the NF-κB pathway in sepsis.

Purpose: Computed tomography (CT) characteristics associated with critical outcomes of patients with coronavirus disease 2019 (COVID-19) have been reported. However, CT risk factors for mortality have not been directly reported. We aim to determine the CT-based quantitative predictors for COVID-19 mortality.Methods: In this retrospective study, laboratory-confirmed COVID-19 patients at Wuhan Central Hospital between December 9, 2019, and March 19, 2020, were included. A novel prognostic biomarker, V-HU score, depicting the volume (V) of total pneumonia infection and the average Hounsfield unit (HU) of consolidation areas was automatically quantified from CT by an artificial intelligence (AI) system. Cox proportional hazards models were used to investigate risk factors for mortality.Results: The study included 238 patients (women 136/238, 57%; median age, 65 years, IQR 51–74 years), 126 of whom were survivors. The V-HU score was an independent predictor (hazard ratio [HR] 2.78, 95% confidence interval [CI] 1.50–5.17; p = 0.001) after adjusting for several COVID-19 prognostic indicators significant in univariable analysis. The prognostic performance of the model containing clinical and outpatient laboratory factors was improved by integrating the V-HU score (c-index: 0.695 vs. 0.728; p < 0.001). Older patients (age ≥ 65 years; HR 3.56, 95% CI 1.64–7.71; p < 0.001) and younger patients (age < 65 years; HR 4.60, 95% CI 1.92–10.99; p < 0.001) could be further risk-stratified by the V-HU score.Conclusions: A combination of an increased volume of total pneumonia infection and high HU value of consolidation areas showed a strong correlation to COVID-19 mortality, as determined by AI quantified CT.