Exosomes are widely distributed extracellular vesicles (EVs), which are currently a major research hotspot for researchers based on their wide range of sources, stable membrane structure, low immunogenicity, and containing a variety of biomolecules. A large number of literatures have shown that exosomes and exosome cargoes (especially microRNAs) play an important role in the activation of inflammation, development of tumor, differentiation of cells, regulation of immunity and so on. Studies have found that exosomes can stimulate the immune response of the body and participate in the occurrence and development of various diseases, including autoimmune diseases. Furthermore, the potential of exosomes as therapeutic tools in various diseases has also attracted much attention. Autoimmune thyroid disease (AITD) is one of the most common autoimmune diseases, mainly composed of Graves' disease (GD) and Hashimoto's thyroiditis (HT), which affects the health of many people and has a genetic predisposition, but its pathogenesis is still being explored. Starting from the relevant biological characteristics of exosomes, this review summarizes the current research status of exosomes and the association between exosomes and some diseases, with a focus on the situation of AITD and the potential role of exosomes (including substances in their vesicles) in AITD in combination with the current published literature, aiming to provide new directions for the pathogenesis, diagnosis or therapy of AITD.Supplemental data for this article is available online at
Background.Long noncoding RNAs (lncRNAs) have been shown to be involved in the regulation of numerous biological processes in embryonic development.We aimed to explore lncRNA expression profiles in ventricular septal defects (VSDs) and reveal their potential roles in heart development.Methods.Microarray analyses were performed to screen differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) in the amniotic fluid between the VSD group and the control group.Bioinformatics analyses were further used to identify the functional enrichment and signaling pathways of important mRNAs.Then, a coding-noncoding gene coexpression (CNC) network and competitive endogenous RNAs (ceRNA) network were drawn.Finally, qRT-PCR was performed to verify several hub lncRNAs and mRNAs in the network. Results.A total of 710 DE-lncRNAs and 397 DE-mRNAs were identified in the VSD group.GO and KEGG analyses revealed that the DE-mRNAs were enriched in cardiac development-related biological processes and pathways, including cell proliferation, cell apoptosis, and the Sonic Hedgehog signaling pathway.Four VSD related mRNAs was used to construct the CNC network, which included 149 pairs of coexpressing lncRNAs and mRNAs.In addition, a ceRNA network, including 15 lncRNAs, 194 miRNAs, and 4 mRNAs, was constructed to reveal the potential regulatory relationship between lncRNAs and proteincoding genes.Finally, seven RNAs in the ceRNA network were validated, including IDS, NR2F2, GPC3, LINC00598, GATA3-AS1, PWRN1, and LINC01551. Conclusion.Our study identified some lncRNAs and mRNAs may be potential biomarkers and therapeutic targets for foetuses with VSD, and described the lncRNA-associated ceRNA network in the progression of VSD.
Background.Long noncoding RNAs (lncRNAs) have been shown to be involved in the regulation of numerous biological processes in embryonic development.We aimed to explore lncRNA expression profiles in ventricular septal defects (VSDs) and reveal their potential roles in heart development.Methods.Microarray analyses were performed to screen differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) in the amniotic fluid between the VSD group and the control group.Bioinformatics analyses were further used to identify the functional enrichment and signaling pathways of important mRNAs.Then, a coding-noncoding gene coexpression (CNC) network and competitive endogenous RNAs (ceRNA) network were drawn.Finally, qRT-PCR was performed to verify several hub lncRNAs and mRNAs in the network. Results.A total of 710 DE-lncRNAs and 397 DE-mRNAs were identified in the VSD group.GO and KEGG analyses revealed that the DE-mRNAs were enriched in cardiac development-related biological processes and pathways, including cell proliferation, cell apoptosis, and the Sonic Hedgehog signaling pathway.Four VSD related mRNAs was used to construct the CNC network, which included 149 pairs of coexpressing lncRNAs and mRNAs.In addition, a ceRNA network, including 15 lncRNAs, 194 miRNAs, and 4 mRNAs, was constructed to reveal the potential regulatory relationship between lncRNAs and proteincoding genes.Finally, seven RNAs in the ceRNA network were validated, including IDS, NR2F2, GPC3, LINC00598, GATA3-AS1, PWRN1, and LINC01551. Conclusion.Our study identified some lncRNAs and mRNAs may be potential biomarkers and therapeutic targets for foetuses with VSD, and described the lncRNA-associated ceRNA network in the progression of VSD.
Background Aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) are the two most widely studied noninvasive markers of liver fibrosis. We aimed to assess the diagnostic accuracy of APRI and FIB-4 for liver fibrosis in patients with autoimmune hepatitis (AIH) using liver biopsy as the reference standard. Methods PubMed, EMBASE, Cochrane Library and Web of Science databases were searched for studies (published as of May 1st, 2021) that assessed the diagnostic performance of APRI and FIB-4 for liver fibrosis in AIH. The summary area under receiver operating characteristics curve (AUROC), sensitivity, specificity, diagnostic odds ratios were used to assess the diagnostic accuracy of APRI and FIB-4 for detecting liver fibrosis. Results Fourteen studies (including 1015 patients) were selected with 13 studies each evaluating the use of APRI and FIB-4 for detecting different stages of fibrosis in AIH. For prediction of significant fibrosis, advanced fibrosis, and cirrhosis, the summary AUROC value was 0.66 [95% confidence interval (CI): 0.61–0.70], 0.71 (95% CI: 0.67–0.75), and 0.75 (95% CI: 0.71–0.79) for APRI, and the summary AUROC value was 0.75 (95% CI: 0.71–0.79), 0.73 (95% CI: 0.69–0.77) and 0.79 (95% CI: 0.75–0.82) for FIB-4, respectively. The summary sensitivity and specificity for diagnosis of significant fibrosis, advanced fibrosis, and cirrhosis were 90% and 36%, 78% and 55%, and 77% and 61% for APRI, and 70% and 70%, 65% and 70%, and 78% and 65% for FIB-4, respectively. Conclusions APRI and FIB-4 showed suboptimal diagnostic performance for identifying liver fibrosis in AIH with mediocre sensitivity and specificity.
To develop a novel non-invasive model for predicting clinically significant portal hypertension (CSPH) in patients with liver cirrhosis, and investigate whether carvedilol therapy could reduce the risk of hepatic decompensation in patients with high-risk CSPH stratified by the novel non-invasive model.
Methods
A total of 1,304 patients with liver cirrhosis were enrolled in the study. Non-invasive risk factors of CSPH were identified by a systemic review and meta-analysis of studies containing patients with hepatic venous pressure gradient (HVPG)-proved CSPH.
Results
A total of six studies from the meta-analysis were involved in this study (n=819), and liver stiffness measurement (LSM) and platelet count (PLT) were eventually identified as independent risk factors of CSPH. A novel CSPH risk model was established as follows: 0.095310×LSM (kPa)-0.01005×PLT (×10^9/L)-0.11, and the cutoff values of >0 (high-risk) and <-0.68 (low-risk) were used to rule in and out CSPH, respectively. In the HVPG cohort (n=151), the areas under the receiver operating characteristic curve (IDDF2023-ABS-0098-Figure 1. Performance of different models for diagnosis of clinically significant portal hypertension) of the novel model, ANTICIPATE model, and Baveno VII criteria for stratifying CSPH were 0.91(0.86-0.95), 0.80(0.73-0.87), and 0.83(0.77-0.89). In the follow-up cohort (n=1,102), the cumulative incidences (1.7% vs 2.5% vs 15.8%) of decompensation events were significantly different by using the novel model cutoff values of >0, 0 to -0.68 (medium-risk), and <-0.68 (IDDF2023-ABS-0098 Figure 2. The cumulative incidence of liver decompensation in follow-up cohort, p<0.001). Remarkably, in the carvedilol-treating cohort, the patients with high-risk CSPH stratified by the novel model and treated with carvedilol (treating cohort, n=51) had significantly lower rates of decompensation events than those of non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=102 after PSM, (IDDF2023-ABS-0098 Figure 3. Decompensation according to treatment group (A) Cumulative incidence of decompensation before propensity score matching PSM (B) Cumulative incidence of decompensation after PSM), all p<0.05).
Conclusions
A novel non-invasive model has favorable CSPH and subsequent decompensation stratification in patients with liver cirrhosis. Treatment with carvedilol among high-risk CSPH patients stratified by the novel model significantly reduces the risk of hepatic decompensation.
Objective: To develop a novel non-invasive model for CSPH, and investigate whether carvedilol could reduce the risk of decompensation in patients with high-risk CSPH stratified by the novel model. Methods: International multicenter observational study with a median follow-up time of 38 months. Three cohorts were included in study from 6 countries. In this study, a total of 1,304 patients were fulfilled diagnosis of liver cirrhosis. Patients were treated with carvedilol in longitudinal carvedilol-treating cohort. The primary outcome was the development of the first hepatic decompensation . Results: Six studies from the meta-analysis were involved (n=819), and LSM and platelet count (PLT) were identified as independent risk factors of CSPH, with pooled risk ratios of 1.10 (95% confidence interval [CI] 1.06-1.15) and 0.99 (95% CI 0.98-0.99). A novel model was established. In HVPG cohort (n=151), the areas under the receiver operating characteristic curve (AUC) of the novel model, ANTICIPATE model, and Baveno VII criteria for CSPH were 0.91 (95% CI 0.86-0.95), 0.80 (95% CI 0.73-0.87), and 0.83 (95% CI 0.77-0.89). The novel model narrows down the grey zone to 22.5%, significantly lower than 50.3%, using Baveno VII criteria (p<0.001). In follow-up cohort (n=1,102), the cumulative incidences (1.7% vs 2.5% vs 15.8%) of decompensation events were significantly different by using the novel model cutoff values of >0, 0 to -0.68 (medium-risk), and <-0.68 (p<0.001). In the carvedilol-treating cohort, the patients with high-risk CSPH stratified by the novel model (treating cohort, n=51) had significantly lower rates of decompensation than those of NSBBs untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=102 after PSM, all p<0.05). Conclusion: A novel model provides stratification for CSPH and decompensation in patients with liver cirrhosis. Treatment with carvedilol significantly reduces the risk of decompensation among high-risk CSPH patients stratified by the novel model.
To analyze serum bile acid profiles in pregnant women with normal pregnancy, intrahepatic cholestasis of pregnancy (ICP) and asymptomatic hypercholanemia of pregnancy (AHP), and to evaluate the application value of serum bile acid profiles in the diagnosis of ICP and AHP.
A large percentage of patients undergoing esophagogastroduodenoscopy (EGD) screening do not have esophageal varices (EV) or have only small EV. We evaluated a large, international, multicenter cohort to develop a novel score, termed FIB-4plus, by combining the fibrosis-4 (FIB-4) score, liver stiffness measurement (LSM), and spleen stiffness measurement (SSM) to identify high-risk EV (HRV) in compensated cirrhosis. This international cohort study involved patients with compensated cirrhosis from 17 Chinese hospitals and one Croatian institution (NCT04546360). Two-dimensional shear wave elastography-derived LSM and SSM values, and components of the FIB-4 score (i.e., age, aspartate aminotransferase, alanine aminotransferase, and platelet count [PLT]) were combined using machine learning algorithms (logistic regression [LR] and extreme gradient boosting [XGBoost]) to develop the LR-FIB-4plus and XGBoost-FIB-4plus models, respectively. Shapley Additive exPlanations method was used to interpret the model predictions. We analyzed data from 502 patients with compensated cirrhosis who underwent EGD screening. The XGBoost-FIB-4plus score demonstrated superior predictive performance for HRV, with an area under the receiver operating characteristic curve (AUROC) of 0.927 (95% CI: 0.897-0.957) in the training cohort (n=268), and 0.919 (95% CI: 0.843-0.995) and 0.902 (95% CI: 0.820-0.984) in the first (n=118) and second (n=82) external validation cohorts, respectively. Additionally, the XGBoost-FIB-4plus score exhibited high AUROC values for predicting EV across all cohorts. The FIB-4plus score outperformed the individual parameters (LSM, SSM, PLT, and FIB-4). The FIB-4plus score effectively predicted EV and HRV in patients with compensated cirrhosis, providing clinicians with a valuable tool for optimizing patient management and outcomes.
Background Long noncoding RNAs (lncRNAs) have been shown to be involved in the regulation of numerous biological processes in embryonic development. We aimed to explore lncRNA expression profiles in ventricular septal defects (VSDs) and reveal their potential roles in heart development. Methods Microarray analyses were performed to screen differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) in the amniotic fluid between the VSD group and the control group. Bioinformatics analyses were further used to identify the functional enrichment and signaling pathways of important mRNAs. Then, a coding–noncoding gene coexpression (CNC) network and competitive endogenous RNAs (ceRNA) network were drawn. Finally, qRT ‒ PCR was performed to verify several hub lncRNAs and mRNAs in the network. Results A total of 710 DE-lncRNAs and 397 DE-mRNAs were identified in the VSD group. GO and KEGG analyses revealed that the DE-mRNAs were enriched in cardiac development-related biological processes and pathways, including cell proliferation, cell apoptosis, and the Sonic Hedgehog signaling pathway. Four VSD related mRNAs was used to construct the CNC network, which included 149 pairs of coexpressing lncRNAs and mRNAs. In addition, a ceRNA network, including 15 lncRNAs, 194 miRNAs, and four mRNAs, was constructed to reveal the potential regulatory relationship between lncRNAs and protein-coding genes. Finally, seven RNAs in the ceRNA network were validated, including IDS, NR2F2, GPC3, LINC00598, GATA3-AS1, PWRN1, and LINC01551. Conclusion Our study identified some lncRNAs and mRNAs may be potential biomarkers and therapeutic targets for foetuses with VSD, and described the lncRNA-associated ceRNA network in the progression of VSD.
Two-dimensional shear wave elastography (2D-SWE) has recently been proposed to detect clinically significant portal hypertension (CSPH), we aimed to perform a meta-analysis based on the published data to assess the diagnostic accuracy of 2D-SWE for detecting CSPH.Literature databases were searched up until 1 August 2021. The summary area under receiver operating characteristics curve (AUROC), the summary diagnostic odds ratio (DOR), and the summary sensitivity and specificity were used to examine the accuracy of 2D-SWE for evaluating CSPH. Heterogeneity was explored using meta-regression.Finally 9 studies with 956 patients were included in this study for evaluation and meta-analysis. 2D-SWE showed good diagnostic performance for detecting CSPH with a summary sensitivity of 83% (95% confidence interval [CI]: 76%-88%) and summary specificity of 78% (95% CI: 65%-87%); the summary AUROC was 0.88 (95% CI: 0.84-0.90). Summary positive likelihood ratio (LR), negative LR, and DOR of 2D-SWE for detecting CSPH were 3.7 (95% CI: 2.4-5.9), 0.22 (95% CI: 0.16-0.30), and 17 (95% CI: 10-29), respectively.2D-SWE showed good performance in diagnosing CSPH and can be considered as an important and noninvasive adjunctive approach in the management of patients with CSPH.
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