Comprehensive evaluation of software system reliability based on component-based generalized G-O models.

The component-based software system has a core that is based on architecture design. Predicting the reliability growth trends of a software system in the early stages of the development process is conducive to reducing waste and loss caused by blind development. Restricted by the lack of information and data in the design and integration phase, it is difficult to implement reliability prediction research at this stage. In this article, we focus on a software system in which the reliability of each component follows the G-O model. First, two system-level parameters, which are the total number of system faults and the detection rate of the system faults, are defined. Then, by studying the relationship between the total number of faults and the detection rate of faults between the components and the system, the defined system parameters are calculated from the known component parameters. On this basis, and by incorporating the system parameters, we construct a reliability growth model for the software system, called the component-based generalized G-O model (CB-GGOM). Besides, two approximate models of CB-GGOM are proposed to facilitate reliability evaluation of the software system in the early and stable stages of the integration test. An engineering explanation of the proposed models is also provided, and their effectiveness is verified through simulation and with an authentic example. Since the proposed models are formulated without any integration test data, they are beneficial for developers to optimize test strategies of the software system and implement defect prevention in advance.

LncRNA KCNQ10T1 shuttled by bone marrow mesenchymal stem cell-derived exosome inhibits sepsis via regulation of miR-154-3p/RNF19A axis.

This study aims to discuss the role of exosomes KCNQ10T1 derived from bone marrow mesenchymal stem cells (BMMSCs) in sepsis and to further investigate its potential molecular mechanisms. Exosomes extracted from BMMSCs are identified by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blot. Fluorescence labeling is applied to detect the internalization of exosomes in receptors. The proliferation ability, migration ability, and invasion ability of HUVECs are determined by CCK-8, EdU, wound healing, and Transwell. The levels of inflammatory cytokines in sepsis cells are quantitatively detected by ELISA. Kaplan-Meier survival curve is used to describe the overall survival. RT-qPCR is used to detect mRNA expression of related genes. Bioinformatics analysis is performed to search the downstream target of KCNQ1OT1 and miR-154-3p and the interaction is verified by luciferase reporter assay. Exosomes derived from BMMSCs alleviated the toxicity in sepsis cell models and animal models. In mice with septic cell models, exosomal KCNQ10T1 was down-regulated and associated with lower survival. Overexpression of KCNQ10T1 inhibited the proliferation and metastasis of LPS-induced HUVECs. Further research illustrated that miR-154-3p was the downstream target gene of KCNQ1OT1 and RNF19A was the downstream target gene of miR-154-3p. Importantly, functional research findings indicated that KCNQ1OT1 regulated sepsis progression by targeting miR-154-3p/RNF19A axis. Our study demonstrates that the exosomal KCNQ1OT1 suppresses sepsis via mediating miR-154-3p/RNF19A, which provides a latent target for sepsis treatment.

Controlled attenuation parameter by vibration-controlled transient elastography for steatosis assessment in members of the public undergoing regular health checkups with reference to magnetic resonance imaging-based proton density fat fraction.

AIM: Controlled attenuation parameter (CAP) measured by vibration-controlled transient elastography (FibroScan) allows repeatable and reliable assessment of liver steatosis for screening of patients at risk of non-alcoholic steatohepatitis development among asymptomatic individuals at a community level. However, this has never been compared with another quantitative method, such as magnetic resonance imaging-based proton density fat fraction, among the Chinese health checkup population. METHODS: A multicenter prospective study was conducted with Chinese individuals undergoing regular health checkups. Steatosis grading by magnetic resonance imaging-based proton density fat fraction was used as the reference to evaluate the diagnostic performance of CAP. RESULTS: A total of 173 individuals were included with mean age of 45 ± 11 years and body mass index of 25.8 ± 4.0 kg/m2 . A linear correlation was found between CAP and log10 -transformed magnetic resonance imaging-based proton density fat fraction results (Pearson's coefficient 0.772, P < 0.001). The areas under the receiver operating characteristic curve for distinguishing ≥S1 and ≥S2 steatosis were 0.88 (95% confidence interval 0.83-0.93) and 0.89 (95% confidence interval 0.83-0.95), respectively. When optimized for ≥90% sensitivity, the CAP cut-off for staging ≥S1 steatosis was 244 dB/m. CAP could classify patients with ≥S1 steatosis with similar performance as an ultrasound examination. CONCLUSIONS: As a non-invasive and quantitative method, CAP is highly adapted for population screening at a community level. With the integration of liver stiffness and CAP results in risk stratification scores for non-alcoholic steatohepatitis, vibration-controlled transient elastography can be useful in regular health checkups.