Multicenter analysis and a rapid screening model to predict early novel coronavirus pneumonia using a random forest algorithm.

ABSTRACT: Early determination of coronavirus disease 2019 (COVID-19) pneumonia from numerous suspected cases is critical for the early isolation and treatment of patients.The purpose of the study was to develop and validate a rapid screening model to predict early COVID-19 pneumonia from suspected cases using a random forest algorithm in China.A total of 914 initially suspected COVID-19 pneumonia in multiple centers were prospectively included. The computer-assisted embedding method was used to screen the variables. The random forest algorithm was adopted to build a rapid screening model based on the training set. The screening model was evaluated by the confusion matrix and receiver operating characteristic (ROC) analysis in the validation.The rapid screening model was set up based on 4 epidemiological features, 3 clinical manifestations, decreased white blood cell count and lymphocytes, and imaging changes on chest X-ray or computed tomography. The area under the ROC curve was 0.956, and the model had a sensitivity of 83.82% and a specificity of 89.57%. The confusion matrix revealed that the prospective screening model had an accuracy of 87.0% for predicting early COVID-19 pneumonia.Here, we developed and validated a rapid screening model that could predict early COVID-19 pneumonia with high sensitivity and specificity. The use of this model to screen for COVID-19 pneumonia have epidemiological and clinical significance.

A rapid screening model for early predicting novel coronavirus pneumonia in Zhejiang Province of China: a multicenter study.

Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries. Early finding of this pneumonia from huge numbers of suspects gives clinicians a big challenge. The aim of the study was to develop a rapid screening model for early predicting NCP in a Zhejiang population, as well as its utility in other areas. A total of 880 participants who were initially suspected of NCP from January 17 to February 19 were included. Potential predictors were selected via stepwise logistic regression analysis. The model was established based on epidemiological features, clinical manifestations, white blood cell count, and pulmonary imaging changes, with the area under receiver operating characteristic (AUROC) curve of 0.920. At a cut-off value of 1.0, the model could determine NCP with a sensitivity of 85% and a specificity of 82.3%. We further developed a simplified model by combining the geographical regions and rounding the coefficients, with the AUROC of 0.909, as well as a model without epidemiological factors with the AUROC of 0.859. The study demonstrated that the screening model was a helpful and cost-effective tool for early predicting NCP and had great clinical significance given the high activity of NCP.

Serum MicroRNA Levels as a Noninvasive Diagnostic Biomarker for the Early Diagnosis of Hepatitis B Virus-Related Liver Fibrosis.

BACKGROUND/AIMS: To investigate the role of selected serum microRNA (miRNA) levels as potential noninvasive biomarkers for differentiating S0-S2 (early fibrosis) from S3-S4 (late fibrosis) in patients with a chronic hepatitis B virus (HBV) infection. METHODS: One hundred twenty-three treatment-naive patients with a chronic HBV infection who underwent a liver biopsy were enrolled in this study. The levels of selected miRNAs were measured using a real-time quantitative polymerase chain reaction assay. A logistic regression analysis was performed to assess factors associated with fibrosis progression. Receiver operating characteristic (ROC) curve and discriminant analyses validated these the ability of these predicted variables to discriminate S0-S2 from S3-S4. RESULTS: Serum miR-29, miR-143, miR-223, miR-21, and miR-374 levels were significantly downregulated as fibrosis progressed from S0-S2 to S3-S4 (p<0.05), but not miR-16. The multivariate logistic regression analysis identified a panel of three miRNAs and platelets that were associated with a high diagnostic accuracy in discriminating S0-S2 from S3-S4, with an area under the curve of 0.936. CONCLUSIONS: The levels of the studied miRNAs, with the exception of miR-16, varied with fibrosis progression. A panel was identified that was capable of discriminating S0-S2 from S3-S4, indicating that serum miRNA levels could serve as a potential noninvasive biomarker of fibrosis progression.

Interleukin-23 mediates the pathogenesis of LPS/GalN-induced liver injury in mice.

BACKGROUND: Interleukin-23 (IL-23) is required for T helper 17 (Th17) cell responses and IL-17 production in hepatitis B virus infection. A previous study showed that the IL-23/IL-17 axis aggravates immune injury in patients with chronic hepatitis B virus infection. However, the role of IL-23 in acute liver injury remains unclear. OBJECTIVE: The purpose of this study was to determine the role of the inflammatory cytokine IL-23 in lipopolysaccharide/d-galactosamine (LPS/GalN)-induced acute liver injury in mice. METHODS: Serum IL-23 from patients with chronic hepatitis B virus (CHB), acute-on-chronic liver failure (ACLF) and healthy individuals who served as healthy controls (HCs) was measured by ELISA. An IL-23p19 neutralizing antibody or an IL-23p40 neutralizing antibody was administered intravenously at the time of challenge with LPS (10µg/kg) and GalN (400mg/kg) in C57BL/6 mice. Hepatic pathology and the expression of Th17-related cytokines, including IL-17 and TNF-α; neutrophil chemoattractants, including Cxcl1, Cxcl2, Cxcl9, and Cxcl10; and the stabilization factor Csf3 were assessed in liver tissue. RESULTS: Serum IL-23 was significantly upregulated in ACLF patients compared with CHB patients and HCs (P<0.05 for both). Serum IL-23 was significantly upregulated in the non-survival group compared with the survival group of ACLF patients, which was consistent with LPS/GalN-induced acute hepatic injury in mice (P<0.05 for both). Moreover, after treatment, serum IL-23 was downregulated in the survival group of ACLF patients (P<0.001). Compared with LPS/GalN mice, mice treated with either an IL-23p19 neutralizing antibody or an IL-23p40 neutralizing antibody showed less severe liver tissue histopathology and significant reductions in the expression of Th17-related inflammatory cytokine, including IL-17 and TNF-α; neutrophil chemoattractants, including Cxcl1, Cxcl2, Cxcl9, and Cxcl10; and stabilization factors Csf3 within the liver tissue compared with LPS/GalN mice (P<0.05 for all). CONCLUSION: High serum IL-23 was associated with mortality in ACLF patients and LPS/GalN-induced acute liver injury in mice. IL-23 neutralizing antibodies attenuated liver injury by reducing the expression of Th17-related inflammatory cytokines, neutrophil chemoattractants and stabilization factors within the liver tissue, which indicated that IL-23 likely functions upstream of Th17-related cytokine and chemokine expression to recruit inflammatory cells into the liver.

Role of interleukin-23 in monocyte-derived dendritic cells of HBV-related acute-on-chronic liver failure and its correlation with the severity of liver damage.

BACKGROUND: The role of interleukin-23 (IL-23) in monocyte-derived dendritic cells (MoDCs) from hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) patients remains unclear. The aim of this study was to observe the correlation between the activation of the IL-23 signaling pathway and the prognosis of HBV-ACLF patients. MATERIALS AND METHODS: The baseline levels of serum IL-6, IL-12, IL-17, IL-23, tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ) from immune tolerant (IT), chronic hepatitis B (CHB), HBV-ACLF patients and healthy individuals who served as healthy controls (HCs) were analyzed using the Luminex system, whereas serum IL-23 from HBV-ACLF patients was measured by ELISA before and after treatment. Purified monocytes were isolated from peripheral blood and were induced into MoDCs, IL-23, IL-23R, NF-κB and TRAF6 expression in MoDCs from 4 groups was analyzed using real-time PCR, and IL-23R and intracellular IL-23 were evaluated by flow cytometry. RESULTS: Serum IL-6, IL-12, IL-17, IL-23 and TNF-α levels were upregulated in HBV-ACLF patients compared with IT patients, CHB patients and HCs (P<0.05 for all). Serum IL-23 was closely correlated with elevated serum IL-17 in HBV-ACLF patients (r=0.5935, P<0.0001). Moreover, IL-23 and IL-23R levels were significantly upregulated in MoDCs from patients with CHB or HBV-ACLF compared with HCs, and further upregulation of IL-23 and IL-23R was observed in HBV-ACLF patients compared to CHB patients (P<0.05 for all). IL-23 expression was markedly enhanced and was correlated with elevated NF-κB and TRAF6 in MoDCs from HBV-ACLF patients (P<0.05 for both). Linear correlation analysis demonstrated significant correlations between the expression of IL-23 and disease severity markers (MELD scoring system, international normalized ratio, prothrombin time and total bilirubin, r=0.6874, r=0.6475, r=0.6249, r=0.3771, respectively, P<0.05 for all) for individual HBV-ACLF patients, and IL-23 levels were significantly upregulated in non-survival HBV-ACLF patients compared with survival HBV-ACLF patients (P<0.05). CONCLUSION: IL-23 in serum and MoDCs is significantly elevated in HBV-ACLF patients, TRAF6/NF-κB may play a role in IL-23 production by MoDCs in HBV-ACLF patients and high pre-treatment IL-23 levels in MoDCs are associated with mortality in HBV-ACLF patients.

Dual oxidase 1: A predictive tool for the prognosis of hepatocellular carcinoma patients.

Dual oxidase 1 (DUOX1), which is the main source of reactive oxygen species (ROS) production in the airway, can be silenced in human lung cancer and hepatocellular carcinomas. However, the prognostic value of DUOX1 expression in hepatocellular carcinoma patients is still unclear. We investigated the prognostic value of DUOX1 expression in liver cancer patients. DUOX1 mRNA expression was determined in tumor tissues and non-tumor tissues by real­time PCR. For evaluation of the prognostic value of DUOX1 expression, Kaplan-Meier method and Cox's proportional hazards model (univariate analysis and multivariate analysis) were employed. A simple risk score was devised by using significant variables obtained from the Cox's regression analysis to further predict the HCC patient prognosis. We observed a reduced DUOX1 mRNA level in the cancer tissues in comparison to the non­cancer tissues. More importantly, Kaplan-Meier analysis showed that patients with high DUOX1 expression had longer disease-free survival and overall survival compared with those with low expression of DUOX1. Cox's regression analysis indicated that DUOX1 expression, age, and intrahepatic metastasis may be significant prognostic factors for disease-free survival and overall survival. Finally, we found that patients with total scores of >2 and >1 were more likely to relapse and succumb to the disease than patients whose total scores were ≤2 and ≤1. In conclusion, DUOX1 expression in liver tumors is a potential prognostic tool for patients. The risk scoring system is useful for predicting the survival of liver cancer patients after tumor resection.

The combination of three molecular markers can be a valuable predictive tool for the prognosis of hepatocellular carcinoma patients.

Based on molecular profiling, several prognostic markers for HCC are also used in clinic, but only a few genes have been identified as useful. We collected 72 post-operative liver cancer tissue samples. Genes expression were tested by RT-PCR. Multilayer perceptron and discriminant analysis were built, and their ability to predict the prognosis of HCC patients were tested. Receiver operating characteristic (ROC) analysis was performed and multivariate analysis with Cox's Proportional Hazard Model was used for confirming the markers'predictive efficiency for HCC patients'survival. A simple risk scoring system devised for further predicting the prognosis of liver tumor patients. Multilayer perceptron and discriminant analysis showed a very strong predictive value in evaluating liver cancer patients'prognosis. Cox multivariate regression analysis demonstrated that DUOX1, GLS2, FBP1 and age were independent risk factors for the prognosis of HCC patients after surgery. Finally, the risk scoring system revealed that patients whose total score >1 and >3 are more likely to relapse and die than patients whose total score ≤1 and ≤3. The three genes model proposed proved to be highly predictive of the HCC patients' prognosis. Implementation of risk scoring system in clinical practice can help in evaluating survival of HCC patients after operation.