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Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.
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Macrophages acquire distinct phenotypes during tissue stress and inflammatory responses. Macrophages are roughly categorized into two different subsets named inflammatory M1 and anti-inflammatory M2 macrophages. We herein identified a unique pathogenic macrophage subpopulation driven by IL-23 with a distinct gene expression profile including defined types of cytokines. The freshly isolated resting mouse peritoneal macrophages were stimulated with different cytokines in vitro, the expression of cytokines and chemokines were detected by microarray, real-time PCR, ELISA and multiple colors flow cytometry. Adoptive transfer of macrophages and imiquimod-induced psoriasis mice were used. In contrast to M1- and M2-polarized macrophages, IL-23-treated macrophages produce large amounts of IL-17A, IL-22 and IFN-γ. Biochemical and molecular studies showed that IL-23 induces IL-17A expression in macrophages through the signal transducer and activator of transcription 3 (STAT3)-retinoid related orphan receptor-γ T (RORγT) pathway. T-bet mediates the IFN-γ production in IL-23-treated macrophages. Importantly, IL-23-treated macrophages significantly promote the dermatitis pathogenesis in a psoriasis-like mouse model. IL-23-treated resting macrophages express a distinctive gene expression prolife compared with M1 and M2 macrophages. The identification of IL-23-induced macrophage polarization may help us to understand the contribution of macrophage subpopulation in Th17-cytokines-related pathogenesis.