Predictive factors for cerebrocardiac syndrome in patients with severe traumatic brain injury: a retrospective cohort study.

Background And Objective: Cerebrocardiac syndrome (CCS) is a severe complication of severe traumatic brain injury (sTBI) that carries high mortality and disability rates. Early identification of CCS poses a significant clinical challenge. The main objective of this study was to investigate potential risk factors associated with the development of secondary CCS in patients with sTBI.

USP5 promotes lipopolysaccharide-induced apoptosis and inflammatory response by stabilizing the TXNIP protein.

Background: The role of thioredoxin-interacting protein (TXNIP) in lipopolysaccharide-induced liver injury in mice has been reported, but the underlying mechanisms are poorly understood.

Methods: We overexpressed deubiquitinase in cells overexpressing TXNIP and then detected the level of TXNIP to screen out the deubiquitinase regulating TXNIP; the interaction between TXNIP and deubiquitinase was verified by coimmunoprecipitation. After knockdown of a deubiquitinase and overexpression of TXNIP in Huh7 and HepG2 cells, lipopolysaccharide was used to establish a cellular inflammatory model to explore the role of deubiquitinase and TXNIP in hepatocyte inflammation.

Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method.

Introduction: Sepsis has the characteristics of high incidence, high mortality of ICU patients. Early assessment of disease severity and risk stratification of death in patients with sepsis, and further targeted intervention are very important. The purpose of this study was to develop machine learning models based on sequential organ failure assessment (SOFA) components to early predict in-hospital mortality in ICU patients with sepsis and evaluate model performance.

An application based on bioinformatics and machine learning for risk prediction of sepsis at first clinical presentation using transcriptomic data.

Linking genotypic changes to phenotypic traits based on machine learning methods has various challenges. In this study, we developed a workflow based on bioinformatics and machine learning methods using transcriptomic data for sepsis obtained at the first clinical presentation for predicting the risk of sepsis. By combining bioinformatics with machine learning methods, we have attempted to overcome current challenges in predicting disease risk using transcriptomic data.

Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients.

Background: Currently, the rate of morbidity and mortality in acute respiratory distress syndrome (ARDS) remains high. One of the potential reasons for the poor and ineffective therapies is the lack of early and credible indicator of risk prediction that would help specific treatment of severely affected ARDS patients. Nevertheless, assessment of the clinical outcomes with transcriptomics of ARDS by alveolar macrophage has not been performed.

Gestational chronic intermittent hypoxia induces hypertension, proteinuria, and fetal growth restriction in mice.

Purpose: Pregnant women are predisposed to obstructive sleep apnea (OSA). Based on the fact that OSA is an independent risk factor for hypertension among the general population, we hypothesized that chronic intermittent hypoxia (CIH), as a feature of OSA, may lead to preeclampsia.

Methods: Pregnant and non-pregnant C57BL/6 J mice were exposed to two conditions of chronic intermittent hypoxia: CIH1 (21-5% O alternations), CIH2 (21-10% O alternations), and room air until day 19.

Low-dose urokinase thrombolytic therapy for patients with acute intermediate-high-risk pulmonary embolism: A retrospective cohort study.

Introduction: Patients at intermediate-high risk of developing a pulmonary embolism (PE) are very likely to experience adverse outcomes, such as cardiovascular instability and death. The role of thrombolytic therapy in intermediate-high-risk PE remains controversial.

Objectives: This study aimed to determine the efficacy and safety of low-dose urokinase (UK) thrombolytic therapy for intermediate-high-risk PE.

Surface Wettability Modification of Cyclic Olefin Polymer by Direct Femtosecond Laser Irradiation.

The effect of laser irradiation on surface wettability of cyclic olefin polymer (COP) was investigated. Under different laser parameters, a superhydrophilic or a superhydrophobic COP surface with a water contact angle (WCA) of almost 0° or 163°, respectively, could be achieved by direct femtosecond laser irradiation. The laser power deposition rate (PDR) was found to be a key factor on the wettability of the laser-treated COP surface.

Role of RhoA/Rho kinase signaling pathway in microgroove induced stem cell myogenic differentiation.

In our previous report, the authors have demonstrated that direct laser machined microchannels would trigger upregulation of myogenic markers in human mesenchymal stem cells (hMSCs) through promotion of cell elongation. However, the molecular basis signaling pathways behind this observation remains unclear. In this work, three types of microchannels generated by femtosecond laser were utilized to investigate possible mechanisms behind the induction of hMSCs myogenesis by microchannels.

Multifunctional wettability patterns prepared by laser processing on superhydrophobic TiO nanostructured surfaces.

A novel femtosecond laser patterning technique is reported to construct a three-dimensional (3D) wettability pattern on a superhydrophobic TiO nanotube array (TNA) surface in one-step. A 3D binary TNA pattern with extremely high contrast for microfluidic manipulators and biomedical scaffolds is used to guide droplet transportation and human mesenchymal stem cell site-selective growth, respectively.

Optical absorption enhancement in a Si nanohole structure with hexagonal unit cell for solar cell application.

Periodic hexagonal unit cell silicon nanohole (SiNH) structures with different structural dimensions have been fabricated using polystyrene spheres and investigated in terms of their microstructures and optical reflectance. Compared with a planar Si wafer, such structures exhibit much lower reflectance due to the enhanced scattering introduced by the SiNHs. Optical simulation using the finite element method has also been carried out in order to optimize the structural periodicity and hole diameter for maximum light absorption.

Design guideline of Si nanohole/PEDOT:PSS hybrid structure for solar cell application.

The finite element method is used to simulate light absorption in periodic hybrid Si nanohole (SiNH)/PEDOT:PSS arrays. The structural periodicity (P) and hole diameter (D) of the hybrid SiNH structure are varied to maximize light absorption. In terms of the solar cell performance under the AM1.

Optical absorption enhancement in nanopore textured-silicon thin film for photovoltaic application.

Silicon thin film with a nanopore textured surface is systematically studied via simulation for photovoltaic application, where the optical characteristics are closely correlated with the nanopore structural parameters. It is found that the solar energy absorption could be optimized when the nanopore array structure dimensions are set as follows: periodicity of 700 nm, depth of 2000 nm, and pore diameter versus periodicity ratio of 87.5%.