Search

Background: To identify the distinct trajectories of the Sequential Organ Failure Assessment (SOFA) scores at 72 h for patients with sepsis in the Medical Information Mart for Intensive Care (MIMIC)-IV database and determine their effects on mortality and adverse clinical outcomes. Methods: A retrospective cohort study was carried out involving patients with sepsis from the MIMIC-IV database. Group-based trajectory modeling (GBTM) was used to identify the distinct trajectory groups for the SOFA scores in patients with sepsis in the intensive care unit (ICU). The Cox proportional hazards regression model was used to investigate the relationship between the longitudinal change trajectory of the SOFA score and mortality and adverse clinical outcomes. Results: A total of 16,743 patients with sepsis were included in the cohort. The median survival age was 66 years (interquartile range: 54–76 years). The 7-day and 28-day in-hospital mortality were 6.0% and 17.6%, respectively. Five different trajectories of SOFA scores according to the model fitting standard were determined: group 1 (32.8%), group 2 (30.0%), group 3 (17.6%), group 4 (14.0%) and group 5 (5.7%). Univariate and multivariate Cox regression analyses showed that, for different clinical outcomes, trajectory group 1 was used as the reference, while trajectory groups 2–5 were all risk factors associated with the outcome (P < 0.001). Subgroup analysis revealed an interaction between the two covariates of age and mechanical ventilation and the different trajectory groups of patients’ SOFA scores (P < 0.05). Conclusion: This approach may help identify various groups of patients with sepsis, who may be at different levels of risk for adverse health outcomes, and provide subgroups with clinical importance.

Summary: Sepsis-associated acute kidney injury (S-AKI) is very common and early prediction is beneficial. This study aiming to develop an accurate ensemble model to predict the risk of S-AKI based on easily available clinical information. Patients with sepsis from the United States (US) database Medical Information Mart for Intensive Care-IV were used as a modeling cohort to predict the occurrence of AKI by combining Support Vector Machine, Random Forest, Neural Network, and Extreme Gradient Boost as four first-level learners via stacking algorithm. The external validation databases were the eICU Collaborative Research Database from US and Critical Care Database comprising infection patients at Zigong Fourth People’s Hospital from China, whose AUROC values for the ensemble model 48–12 h before the onset of AKI were 0.774–0.788 and 0.756–0.813, respectively. In this study, an ensemble model for early prediction of S-AKI onset was developed and it demonstrated good performance in multicenter external datasets.

The increasing utilization of wood-based products raises new demands for improved durability, for example an enhanced liquid repellence. Superhydrophobic or superamphiphobic surfaces have been widely fabricated. Less attention has been paid to such modifications on wood and the changes of its hygroscopic or solvoscopic properties. In this work, wood veneers were surface modified by hydrophobized silicone nanofilaments. Results revealed that the surface-modified wood showed a superamphiphobic behavior, i.e. it repelled water, ethylene glycol and hexadecane with contact angles greater than 150° and roll-off angles of less than 10°. Most importantly, a plastron effect was observed when the surface-modified wood was submerged in water, ethylene glycol or hexadecane, which reduced the liquid sorption rate and extent to various degrees. By comparing the measured permeabilities and the estimated diffusive mass flux and supported by Hansen solubility parameters and the degrees of swelling, it is concluded that diffusion is the major cause for the liquid uptake in the surface-modified wood. Moreover, the interaction between the liquid and the modified layer (the solubility of the liquid in the modified layer) also needs to be considered, especially in hexadecane.

E3 ubiquitin ligase Cbl-b has emerged as a gatekeeper that controls the activation threshold of the T cell antigen receptor and maintains the balance between tolerance and autoimmunity. Here, we report that the loss of Cbl-b facilitates T helper 2 (Th2) and Th9 cell differentiation in vitro. In a mouse model of asthma, the absence of Cbl-b results in severe airway inflammation and stronger Th2 and Th9 responses. Mechanistically, Cbl-b selectively associates with Stat6 upon IL-4 ligation and targets Stat6 for ubiquitination and degradation. These processes are heightened in the presence of T cell receptor (TCR)/CD28 costimulation. Furthermore, we identify K108 and K398 as Stat6 ubiquitination sites. Intriguingly, introducing Stat6 deficiency into Cblb−/− mice abrogates hyper-Th2 responses but only partially attenuates Th9 responses. Therefore, our data reveal a function for Cbl-b in the regulation of Th2 and Th9 cell differentiation.

E3 ubiquitin ligase Cbl-b plays a crucial role in T cell activation and tolerance induction. However, the molecular mechanism by which Cbl-b inhibits T cell activation remains unclear. Here, we report that Cbl-b does not inhibit PI3K but rather suppresses TCR/CD28-induced inactivation of Pten. The elevated Akt activity in Cbl-b−/− T cells is therefore due to heightened Pten inactivation. Suppression of Pten inactivation in T cells by Cbl-b is achieved by impeding the association of Pten with Nedd4, which targets Pten K13 for K63-linked polyubiquitination. Consistent with this finding, introducing Nedd4 deficiency into Cbl-b−/− mice abrogates hyper-T cell responses caused by the loss of Cbl-b. Hence, our data demonstrate that Cbl-b inhibits T cell activation by suppressing Pten inactivation independently of its ubiquitin ligase activity.