Prognostic value of neutrophil-to-lymphocyte ratio in end-stage liver disease: A meta-analysis.

BACKGROUND: The neutrophil-to-lymphocyte ratio (NLR) is commonly utilized as a prognostic indicator in end-stage liver disease (ESLD), encompassing conditions like liver failure and decompensated cirrhosis. Nevertheless, some studies have contested the prognostic value of NLR in ESLD. AIM: To investigate the ability of NLR to predict ESLD. METHODS: Databases, such as Embase, PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Weipu, and Wanfang, were comprehensively searched to identify studies published before October 2022 assessing the prognostic ability of NLR to predict mortality in patients with ESLD. Effect sizes were calculated using comprehensive meta-analysis software and SATAT 15.1. RESULTS: A total of thirty studies involving patients with end-stage liver disease (ESLD) were included in the evaluation. Among the pooled results of eight studies, it was observed that the Neutrophil-to-Lymphocyte Ratio (NLR) was significantly higher in non-survivors compared to survivors (random-effects model: standardized mean difference = 1.02, 95% confidence interval = 0.67-1.37). Additionally, twenty-seven studies examined the associations between NLR and mortality in ESLD patients, reporting either hazard ratios (HR) or odds ratios (OR). The combined findings indicated a link between NLR and ESLD mortality (random-effects model; univariate HR = 1.07, 95%CI = 1.05-1.09; multivariate HR = 1.07, 95%CI = 1.07-1.09; univariate OR = 1.29, 95%CI = 1.18-1.39; multivariate OR = 1.29, 95%CI = 1.09-1.49). Furthermore, subgroup and meta-regression analyses revealed regional variations in the impact of NLR on ESLD mortality, with Asian studies demonstrating a more pronounced effect. CONCLUSION: Increased NLR in patients with ESLD is associated with a higher risk of mortality, particularly in Asian patients. NLR is a useful prognostic biomarker in patients with ESLD.

The occurrence of immune-related adverse events is an independent risk factor both for serum HBsAg increase and HBV reactivation in HBsAg-positive cancer patients receiving PD-1 inhibitor combinational therapy.

Background: Previous studies have suggested the potential of PD-1/PD-L1 inhibitors in the treatment of chronic HBV infection. However, since phase III clinical trials have not yet been announced, additional clinical insights may be obtained by observing changes in serum hepatitis B surface antigen (HBsAg) and HBV-DNA levels in cancer patients undergoing PD-1 inhibitor therapy. Objective: To explore the effects of PD-1 inhibitor combinational therapy on serum HBsAg and HBV-DNA levels, investigate the incidence of HBsAg loss, HBV reactivation (HBVr), and immune-related adverse events (irAEs), and identify the risk factors associated with significant HBsAg fluctuations and HBVr. Methods: A retrospective study including 1195 HBsAg-positive cancer patients who received PD-1 inhibitors between July 2019 and June 2023 was conducted, and 180 patients were enrolled in this study. Serum HBsAg levels before and after PD-1 inhibitor administration were compared across different subgroups. The Pearson χ2 or Fisher exact test was performed to investigate the relationships between categorical variables. Univariable and multivariable analysis were performed to identify the risk factors associated with significant HBsAg fluctuations and HBVr. Results: With the concurrent use of antiviral agents, serum HBsAg levels decreased (Z=-3.966, P < 0.0001) in 129 patients and increased (t=-2.047, P=0.043) in 51 patients. Additionally, 7 patients (3.89%) achieved serum HBsAg loss. Virus replication was suppressed in most of the enrolled patients. When divided patients into different subgroups, significant HBsAg decreases after PD-1 inhibitor administration were discovered in lower baseline HBsAg group (Z=-2.277, P=0.023), HBeAg-seronegative group (Z=-2.200, P=0.028), non-irAEs occurrence group (Z=-2.007, P=0.045) and liver cancer group (Z=-1.987, P=0.047). Of note, 11 patients and 36 patients experienced HBVr (6.11%) and irAEs (20%), respectively, which could lead to discontinuation or delayed use of PD-1 inhibitors. After multivariable analysis, HBeAg-seropositive (OR, 7.236 [95% CI, 1.757-29.793], P=0.01) and the occurrence of irAEs (OR, 4.077 [95% CI, 1.252-13.273], P=0.02) were identified as the independent risk factors for significant HBsAg increase, the occurrence of irAEs (OR, 5.560 [95% CI, 1.252-13.273], P=0.01) was identified as the only independent risk factor for HBVr. Conclusion: PD-1 inhibitors combined with nucleos(t)ide analogues (NAs) may exert therapeutic potential for chronic HBV infection in cancer patients. However, attention also should be paid to the risk of significant elevation in HBsAg levels, HBVr, and irAEs associated with PD-1 inhibitor combinational therapy.

Type 1 diabetes, its complications, and non-ischemic cardiomyopathy: a mendelian randomization study of European ancestry.

BACKGROUND: Type 1 diabetes (T1D) is a significant risk factor for a range of cardiovascular diseases. Nonetheless, the causal relationship between T1D and non-ischemic cardiomyopathy (NICM) remains to be elucidated. Furthermore, the mechanisms responsible for the progression from T1D to NICM have not been definitively characterized. OBJECTIVE: The aim of this study was to conduct a Mendelian randomization (MR) study to investigate the causal effects of T1D and its complications on the development of NICM. Additionally, this study aimed to conduct a mediation analysis to identify potential mediators within this correlation. METHODS: Genetic variants were used as instrumental variables for T1D. The summary data for T1D were obtained from two genome-wide association study datasets. The summary data for T1D with complications and NICM were obtained from the Finnish database. Two-sample MR, multivariable MR and mediation MR were conducted in this study. RESULTS: The study revealed a causal association between T1D, T1D with complications, and NICM (with odds ratios of 1.02, 95% CI 1.01-1.04, p = 1.17e-04 and 1.03, 95% CI 1.01-1.05, p = 3.15e-3). Even after adjusting for confounding factors such as body mass index and hypertension, T1D remained statistically significant (with odds ratio of 1.02, 95% CI 1.01-1.04, p = 1.35e-4). Mediation analysis indicated that monokine induced by gamma interferon may play a mediating role in the pathogenesis of T1D-NICM (mediation effect indicated by odds ratio of 1.005, 95% CI 1.001-1.01, p = 4.9e-2). CONCLUSION: The study demonstrates a causal relationship between T1D, its complications, and NICM. Additionally, monokine induced by gamma interferon may act as a potential mediator in the pathogenesis of T1D-NICM.

Single-cell Technologies Provide Novel Insights into Liver Physiology and Pathology.

The liver is the largest glandular organ in the body and has a unique distribution of cells and biomolecules. However, the treatment outcome of end-stage liver disease is extremely poor. Single-cell sequencing is a new advanced and powerful technique for identifying rare cell populations and biomolecules by analyzing the characteristics of gene expression between individual cells. These cells and biomolecules might be used as potential targets for immunotherapy of liver diseases and contribute to the development of precise individualized treatment. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) or other single-cell histological techniques have solved the problem of cell population heterogeneity and characterize molecular changes associated with liver diseases with higher accuracy and resolution. In this review, we comprehensively summarized single-cell approaches including transcriptomic, spatial transcriptomic, immunomic, proteomic, epigenomic, and multiomic technologies, and described their application in liver physiology and pathology. We also discussed advanced techniques and recent studies in the field of single-cell; our review might provide new insights into the pathophysiological mechanisms of the liver to achieve precise and individualized treatment of liver diseases.

E2F1-mediated Up-regulation of NCAPG Promotes Hepatocellular Carcinoma Development by Inhibiting Pyroptosis.

Background and Aims: As a subunit of the condensin complex, NCAPG has an important role in maintaining chromosome condensation, but its biological function and regulatory mechanism in hepatocellular carcinoma (HCC) remains undefined. Methods: The prognostic ability of NCAPG in HCC patients was examined by univariate and multivariate Cox regression analysis. ROC curves were plotted to compare the predictive ability of NCAPG and AFP. Double luciferase reporter system, and ChIP were used to investigate transcriptional potential of E2F1 to NCAPG. Pyroptosis was observed by scanning electron microscopy. Protein expression of NCAPG, E2F1, and major proteins constituting NLRP3 inflammasome was determined by western blotting and ELISA. An in vivo tumor formation assay was conducted to verify the in vitro results. Results: Up-regulated NCAPG was identified in HCC tissues compared with adjacent tissue and high NCAPG was positively correlated with poor prognosis. Serum NCAPG mRNA level was a prognostic factor in HCC patients and also a diagnostic factor with higher predictive ability compared with AFP [AUROC 0.766 (95% CI: 0.650-0.881) vs. 0.649 (95% CI 0.506-0.793)]. HBx transfection resulted in concomitant up-regulation of E2F1 and NCAPG. E2F1 significantly increased the activity of luciferase reporter fused with NCAPG reporter, and the interaction of E2F1 and NCAPG gene was confirmed by ChIP. Silencing of E2F1 resulted in significant down-regulation of NCAPG. Knockdown of NCAPG promote pyroptosis mediated by NLRP3 inflammasome activation in multiple HCC cell lines and also suppressed tumorigenesis in vitro. Conclusions: We identified a novel role of NCAPG in the regulation of NLRP3 inflammasome-mediated pyroptosis, which was regulated by its upstream transactivator, E2F1. The role of E2F1-NCAPG-NLRP3 regulation of pyroptosis network may be a potential target in HCC treatment.

Subcellular localization and relevant mechanisms of human cancer-related micropeptides.

Rapid advances in high-quality sequencing and bioinformatics have invalidated the argument that noncoding RNAs (ncRNAs) are junk transcripts that do not encode proteins. Increasing evidence suggests that small open reading frames (sORFs) in ncRNAs can encode micropeptides and polypeptides within 100 amino acids in length. Several micropeptides have been characterized and proven to have various functions in human physiology and pathology, particularly in cancer. The present review mainly highlights the latest studies on ncRNA-encoded micropeptides in different cancers and categorizes them based on their subcellular localization, thereby providing a theoretical basis for micropeptide applications in the early diagnosis and prognosis of cancer and as therapeutic targets. However, considering the inherent characteristics of micropeptides and the limitations of the assay technology methods, more detailed information is warranted.

Comparison of the 2005 Montreal Criteria and the 2019 Cirrhotic Cardiomyopathy Consortium Criteria for the Diagnosis of Cirrhotic Cardiomyopathy.

The comparison between the diagnostic criteria for cirrhotic cardiomyopathy (CCM) first proposed in 2005 (2005 Montreal criteria), and those redefined in the 2019 Cirrhotic Cardiomyopathy Consortium (2019 CCC criteria) has generated significant controversy. Importantly, the predictive value of these criteria in cirrhotic patients (CPs) remains unclear to this date. Thus, the present study aims to compare the 2 sets of criteria and investigate their predictive value in CPs. Between April 2021 and April 2023, a total of 104 CPs with an average age of 46.4 ± 8.9 years, who had no history of other cardiac diseases or malignancies were enrolled in this prospective single-center observational cohort study, conducted at the Third Affiliated Hospital of Sun Yat-Sen University. Various echocardiographic indicators were measured and assessed for their prognostic value and association with clinical outcomes. The prevalence of CCM was found to be comparable when evaluated using both the 2019 CCC and 2005 Montreal criteria (54.8% vs 44.2%, p = 0.161). However, the diagnosis of systolic dysfunction was significantly different between the 2 criteria (52.9% vs 1.0%, p <0.001). Among patients with systolic dysfunction, 27.9% had reduced left ventricular global longitudinal strain, while 25% had increased left ventricular global longitudinal strain. Moreover, fewer patients were diagnosed with diastolic dysfunction (DD) using the 2019 CCC criteria (4.8% vs 44.2%, p <0.001). Multivariate Cox analysis revealed that CPs who had encephalopathy, a high model for end-stage liver disease score, and DD diagnosed using the 2019 CCC criteria exhibited a poorer prognosis. In conclusion, although the prevalence of CCM according to both criteria is similar, the consistency is poor, indicating that they are not the same group of patients. Importantly, CPs with DD diagnosed according to the 2019 CCC criteria might be associated with increased adverse events.

Pan-cancer analysis reveals that G6PD is a prognostic biomarker and therapeutic target for a variety of cancers.

Background: Despite accumulating evidence revealing that Glucose-6-phosphate dehydrogenase (G6PD) is highly expressed in many tumor tissues and plays a remarkable role in cancer tumorigenesis and progression, there is still a lack of G6PD pan-cancer analysis. This study was designed to analyze the expression status and prognostic significance of G6PD in pan-cancer. Methods: G6PD expression data were obtained from multiple data resources including the Genotype-Tissue Expression, the Cancer Genome Atlas, and the Tumor Immunity Estimation Resource. These data were used to assess the G6PD expression, prognostic value, and clinical characteristics. The ESTIMATE algorithms were used to analyze the association between G6PD expression and immune-infiltrating cells and the tumor microenvironment. The functional enrichment analysis was also performed across pan-cancer. In addition, the GDSC1 database containing 403 drugs was utilized to explore the relationship between drug sensitivity and G6PD expression levels. Furthermore, we also performed clinical validation and in vitro experiments to further validate the role of G6PD in hepatocellular carcinoma (HCC) cells and its correlation with prognosis. The R software was used for statistical analysis and data visualization. Results: G6PD expression was upregulated in most cancers compared to their normal counterparts. The study also revealed that G6PD expression was a prognostic indicator and high levels of G6PD expression were correlated with worse clinical prognosis including overall survival, disease-specific survival, and progression-free interval in multiple cancers. Furthermore, the G6PD level was also related to cancer immunity infiltration in most of the cancers, especially in KIRC, LGG, and LIHC. In addition to this, G6PD expression was positively related to pathological stages of KIRP, BRCA, KIRC, and LIHC. Functional analysis and protein-protein interactions network results revealed that G6PD was involved in metabolism-related activities, immune responses, proliferation, and apoptosis. Drug sensitivity analysis showed that IC50 values of most identified anti-cancer drugs were positively correlated with the G6PD expression. Notably, in vitro functional validation showed that G6PD knockdown attenuated the phenotypes of proliferation in HCC. Conclusion: G6PD may serve as a potential prognostic biomarker for cancers and may be a potential therapeutic target gene for tumor therapy.

An Optimal Prognostic Model Based on Multiparameter Ultrasound for Acute-on-Chronic Liver Failure.

OBJECTIVE: Acute-on-chronic liver failure (ACLF) is associated with a considerably high mortality, and accurate prognosis prediction is critical to navigate intervention decisions and improve clinical outcomes. The objective of this study was to establish a better prognostic model for ACLF based on multiparameter ultrasound in combination with clinical features. METHODS: A total of 149 patients with ACLF were prospectively enrolled and underwent conventional ultrasound, 2-D shear wave elastography (SWE), attenuation imaging, color Doppler sonography, superb microvascular imaging and contrast-enhanced ultrasound (CEUS). Univariate and multivariate analyses were performed to identify independent ultrasound signatures for the prognosis of ACLF, which, when integrated with clinical characteristics, were used to establish a prognostic model. RESULTS: Hepatic perfusion features of CEUS differed significantly between the poor and good prognosis groups, among which the time interval (TI) between peak portal vein (PV) velocity and liver parenchyma (LP) enhancement, TI(PV, LP), was independently associated with the prognosis of ACLF. A prediction model comprising TI(PV, LP) and the international normalized ratio was established, and the area under the curve (AUC) was 0.851, which is greater than those of the Model for End-stage Liver Disease (0.785), fall time of LP model (0.754), 2-D SWE nomogram (0.708) and TI(PV, LP) (0.352). Furthermore, the performance of the model was verified in an independent validation cohort (AUC = 0.920). CONCLUSION: The newly developed model performs better than existing tested models; thus, it has potential as a better non-invasive model for predicting the prognosis of patients with ACLF. A future multicenter, large-sample study is required to validate the performance of this model.

Stable and durable antibody responses in SARS-recovered donors vaccinated with inactivated SARS-CoV-2 vaccine.

Whether the immune imprinting caused by severe acute respiratory syndrome coronavirus (SARS-CoV) affects the efficiency of SARS-CoV-2 vaccination has attracted global concern. Little is known about the dynamic changes of antibody response in SARS convalescents inoculated with three doses of inactivated SARS-CoV-2 vaccine although lack of cross-neutralizing antibody response to SARS-CoV-2 in SARS survivors has been reported. We longitudinally examined the neutralizing antibodies (nAbs) against SARS-CoV and SARS-CoV-2 as well as spikes binding IgA, IgG, IgM, IgG1, and IgG3 antibodies in 9 SARS-recovered donors and 21 SARS-naïve donors. Stably higher nAbs and spike antigens-specific IgA, IgG antibodies against SARS-CoV-2 were observed in SARS-recovered donors compared with SARS-naïve donors during the period with two doses of BBIBP-CorV vaccination. However, the third-dose BBIBP-CorV stimulated a sharply and shortly higher increase of nAbs in SARS-naïve donors than in SARS-recovered donors. It is worth noting that, regardless of prior SARS infection, the Omicron subvariants were found to subvert immune responses. Moreover, certain subvariants such as BA.2, BA.2.75, or BA.5 exhibited a high degree of immune evasion in SARS survivors. Interestingly, BBIBP-CorV recalled higher nAbs against SARS-CoV compared with SARS-CoV-2 in SARS-recovered donors. In SARS survivors, a single dose of inactivated SARS-CoV-2 vaccine provoked immune imprinting for the SARS antigen, providing protection against wild-type SARS-CoV-2, and the earlier variants of concern (VOCs) including Alpha, Beta, Gamma, and Delta but not against Omicron subvariants. As such, it is important to evaluate the type and dosage of SARS-CoV-2 vaccine for SARS survivors.

A Prognostic Nomogram with High Accuracy Based on 2D-SWE in Patients with Acute-on-chronic Liver Failure.

Background and Aims: Acute-on-chronic liver failure (ACLF) is associated with very high mortality. Accurate prediction of prognosis is critical in navigating optimal treatment decisions to improve patient survival. This study was aimed to develop a new nomogram integrating two-dimensional shear wave elastography (2D-SWE) values with other independent prognostic factors to improve the precision of predicting ACLF patient outcomes. Methods: A total of 449 consecutive patients with ACLF were recruited and randomly allocated to a training cohort (n=315) or a test cohort (n=134). 2D-SWE values, conventional ultrasound features, laboratory tests, and other clinical characteristics were included in univariate and multivariate analysis. Factors with prognostic value were then used to construct a novel prognostic nomogram. Receiver operating curves (ROCs) were generated to evaluate and compare the performance of the novel and published models including the Model for End-Stage Liver Disease (MELD), MELD combined with sodium (MELD-Na), and Jin's model. The model was validated in a prospective cohort (n=102). Results: A ACLF prognostic nomogram was developed with independent prognostic factors, including 2D-SWE, age, total bilirubin (TB), neutrophils (Neu), and the international normalized ratio (INR). The area under the ROC curve (AUC) was 0.849 for the new model in the training cohort and 0.861 in the prospective validation cohort, which were significantly greater than those for MELD (0.758), MELD-Na (0.750), and Jin's model (0.777, all p <0.05). Calibration curve analysis revealed good agreement between the predicted and observed probabilities. The new nomogram had superior overall net benefit and clinical utility. Conclusions: We established and validated a 2D-SWE-based noninvasive nomogram to predict the prognosis of ACLF patients that was more accurate than other prognostic models.

NTCP Deficiency Affects the Levels of Circulating Bile Acids and Induces Osteoporosis.

Background: The p.Ser267Phe mutation in the SLC10A1 gene can cause NTCP deficiency. However, the full clinical presentation of p.Ser267Phe homozygous individuals and its long-term consequences remain unclear. Hence, in the present study, we characterized the phenotypic characteristics of NTCP deficiency and evaluated its long-term prognosis. Methods: Ten NTCP p.Ser267Phe homozygous individuals were recruited and a comprehensive medical evaluation with a 5-year follow-up observation was performed. The phenotypic characteristics of NTCP deficiency were also demonstrated using an NTCP-global knockout mouse model. Results: During the 5-year follow-up observation of 10 NTCP p.Ser267Phe homozygous adults, we found that the most common phenotypic features of NTCP deficiency in adults were hypercholanemia, vitamin D deficiency, bone loss, and gallbladder abnormalities. The profile of bile acids (BAs) in the serum was significantly altered in these individuals and marked by both elevated proportion and concentration of primary and conjugated BAs. Moreover, the NTCP deficiency led to increased levels of serum BAs, decreased levels of vitamin D, and aggravated the osteoporotic phenotype induced by estrogen withdrawal in mice. Conclusions: Both mice and humans with NTCP deficiency presented hypercholanemia and were more prone to vitamin D deficiency and aggravated osteoporotic phenotype. Therefore, we recommend monitoring the levels of BAs and vitamin D, bone density, and abdominal ultrasounds in individuals with NTCP deficiency.

Plasma-Derived Exosomal SncRNA as a Promising Diagnostic Biomarker for Early Detection of HBV-Related Acute-on-Chronic Liver Failure.

Objectives: The small noncoding RNAs (sncRNAs) including microRNAs and the noncanonical sncRNAs [i.e., tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNAs)] are a vital class of gene regulators in response to a variety of diseases. We focus on an sncRNA signature enriched in hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) to develop a plasma exosome-based noninvasive biomarker for human ACLF. Methods: In this work, sncRNAs related to HBV-ACLF were identified by small RNA sequencing (RNA-seq) in plasma exosomes collected from 3 normal subjects, 4 chronic hepatitis B (CHB) patients with flare, and 6 HBV-ACLF patients in the discovery cohort. Thereafter, the differentially expressed sncRNAs were further verified in a validation cohort (n = 313) using the newly developed molecular signature incorporating different mi/ts/rsRNAs (named as MTR-RNAs) through qRT-PCR assays. Subsequently, using the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) model analysis, we developed an MTR-RNA classifier for early detection of ACLF. Results: The identified sncRNAs (hsa-miR-23b-3p, hsa-miR-223-3p, hsa-miR-339-5p, tsRNA-20, tsRNA-46, and rsRNA-249) were specifically differentially expressed in plasma exosomes of HBV-ACLF. The MTR-RNA signature (AUC = 0.787) containing the above sncRNAs distinguished HBV-ACLF cases among normal subjects with 71.67% specificity and 74.29% sensitivity, CHB patients with flare (AUC = 0.694, 85.71% sensitivity/59.5% specificity), and patients with CHB/cirrhosis (AUC = 0.785, 57.14% sensitivity/94.59% specificity). Notably, it revealed 100% specificity/94.80% sensitivity in detecting patients or normal people. Conclusions: Our as-constructed plasma-derived exosomal sncRNA signature can serve as a reliable biomarker for ACLF detection and also be adopted to be the pre-triage biomarker for selecting cases that can gain benefits from adjuvant treatment.

Expression and Regulatory Network Analysis of Function of Small Nucleolar RNA Host Gene 4 in Hepatocellular Carcinoma.

Background and Aims: Long non-coding RNA small nucleolar RNA host genes (SNHGs) play a critical role in the occurrence and development of tumors. In this study, we aimed to investigate the role of SNHG4 in hepatocellular carcinoma (HCC) and its underlining mechanism. Methods: Datasets were acquired from The Cancer Genome Atlas (TCGA) database. lncLocator 2.0 was used to identify the distribution of SNHG4 in HCC cells. Gene expression, Kaplan-Meier survival, microRNA and transcription factor target analyses were performed with the University of Alabama Cancer (UALCAN) Database, Kaplan-Meier Plotter, LinkedOmics, WebGestalt and gene set enrichment analysis, respectively. Gene Ontology and pathway enrichment analyses and assessment of RNA binding proteins were performed by R software, circlncRNAnet and Encyclopedia of RNA Interactomes (ENCORI). In addition, CirclncRNAnet and ENCORI were used to find the correlation between SNHG4 and important proteins, while the prognostic value was assessed with the Human Protein Atlas database and Kaplan-Meier Plotter. Results: Expression of SNHG4 in HCC is higher in HCC tissue than in normal healthy liver tissues and is mainly distributed in the nucleus. SNHG4 positively correlated with poor prognosis (p<0.01 for overall survival and recurrence-free survival). Functional enrichment analysis revealed SNHG4 involvement with regulation of ribosomal RNA synthesis and the RNA processing and surveillance pathway. SNHG4 is closely associated with miR-154 and miR-206, transcription factor target E2F family and the signaling pathway for MAPK/ERK and mTOR. U2 auxiliary factor 2 (U2AF2) showed strong correlation with SNHG4, while low-expression of U2AF2 showed good prognosis. Conclusions: Based on our findings, we infer SNHG4 may play a role in the formation of HCC via regulation of tumor-related pathways.

The Immune Landscape of Hepatitis B Virus-Related Acute Liver Failure by Integration Analysis.

Hepatitis B virus-related acute liver failure (HBV-ALF) is a common type of liver failure, associated with high short-term mortality and morbidity rates. However, the immune landscape of HBV-ALF and its correlation with cell death are currently unknown. Based on 3 Gene Expression Omnibus data sets, infiltrated immune cells were quantified by single-sample gene set enrichment analysis method. The expression levels of immune genes and the abundance of immune cells in liver failure were compared with those in normal liver. The enrichment scores of cell death gene sets from Kyoto Encyclopedia of Genes and Genomes (KEGG) were calculated by gene set variation analysis method, and a protein-protein interaction (PPI) network was constructed using Cytoscape. Besides 21 differentially expressed immune genes, we identified 11 types of differentially infiltrated immune cells in HBV-ALF compared with normal liver. Enriched pathways of these immune genes mainly consisted of chemokine receptors, chemokine binding, interleukin-10 signaling, and TNFs bind their physiological receptors by Reactome pathway analysis. In addition, the enrichment scores of apoptosis and necroptosis pathway instead of autophagy and ferroptosis were increased in liver failure compared with normal liver. PPI network and gene cluster analysis of immune genes and apoptosis and necroptosis genes suggested that hub genes were mainly related to immune response and apoptosis. In summary, our study offers a conceptual framework to understand the immune landscape of HBV-ALF, which might help to improve prognosis.

A coarse-refine segmentation network for COVID-19 CT images.

The rapid spread of the novel coronavirus disease 2019 (COVID-19) causes a significant impact on public health. It is critical to diagnose COVID-19 patients so that they can receive reasonable treatments quickly. The doctors can obtain a precise estimate of the infection's progression and decide more effective treatment options by segmenting the CT images of COVID-19 patients. However, it is challenging to segment infected regions in CT slices because the infected regions are multi-scale, and the boundary is not clear due to the low contrast between the infected area and the normal area. In this paper, a coarse-refine segmentation network is proposed to address these challenges. The coarse-refine architecture and hybrid loss is used to guide the model to predict the delicate structures with clear boundaries to address the problem of unclear boundaries. The atrous spatial pyramid pooling module in the network is added to improve the performance in detecting infected regions with different scales. Experimental results show that the model in the segmentation of COVID-19 CT images outperforms other familiar medical segmentation models, enabling the doctor to get a more accurate estimate on the progression of the infection and thus can provide more reasonable treatment options.

Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Patients With Severe Acute Exacerbation.

Background: Patients with chronic hepatitis B (CHB) with severe acute exacerbation (SAE) are at a progression stage of acute-on-chronic liver failure (ACLF) but uniform models for predicting ACLF occurrence are lacking. We aimed to present a risk prediction model to early identify the patients at a high risk of ACLF and predict the survival of the patient. Methods: We selected the best variable combination using a novel recursive feature elimination algorithm to develop and validate a classification regression model and also an online application on a cloud server from the training cohort with a total of 342 patients with CHB with SAE and two external cohorts with a sample size of 96 and 65 patients, respectively. Findings: An excellent prediction model called the PATA model including four predictors, prothrombin time (PT), age, total bilirubin (Tbil), and alanine aminotransferase (ALT) could achieve an area under the receiver operating characteristic curve (AUC) of 0.959 (95% CI 0.941-0.977) in the development set, and AUC of 0.932 (95% CI 0.876-0.987) and 0.905 (95% CI 0.826-0.984) in the two external validation cohorts, respectively. The calibration curve for risk prediction probability of ACLF showed optimal agreement between prediction by PATA model and actual observation. After predictive stratification into different risk groups, the C-index of predictive 90-days mortality was 0.720 (0.675-0.765) for the PATA model, 0.549 (0.506-0.592) for the end-stage liver disease score model, and 0.648 (0.581-0.715) for Child-Turcotte-Pugh scoring system. Interpretation: The highlypredictive risk model and easy-to-use online application can accurately predict the risk of ACLF with a poor prognosis. They may facilitate risk communication and guidetherapeutic options.

Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression.

Background: Biliary atresia (BA) is a severe cholangiopathy of early infancy that destroys cholangiocytes, obstructs ductular pathways and if left untreated, culminates to liver cirrhosis. Mechanisms underlying the etiological heterogeneity remain elusive and few studies have attempted phenotyping BA. We applied machine learning to identify distinct subtypes of BA which correlate with the underlying pathogenesis. Methods: The BA microarray dataset GSE46995 was downloaded from the Gene Expression Omnibus (GEO) database. Unsupervised hierarchical cluster analysis was performed to identify BA subtypes. Then, functional enrichment analysis was applied and hub genes identified to explore molecular mechanisms associated with each subtype. An independent dataset GSE15235 was used for validation process. Results: Based on unsupervised cluster analysis, BA patients can be classified into three distinct subtypes: Autoimmune, Viral and Embryonic subtypes. Functional analysis of Subtype 1 correlated with Fc Gamma Receptor (FCGR) activation and hub gene FCGR2A, suggesting an autoimmune response targeting bile ducts. Subtype 2 was associated with immune receptor activity, cytokine receptor, signaling by interleukins, viral protein interaction, suggesting BA is associated with viral infection. Subtype 3 was associated with signaling and regulation of expression of Robo receptors and hub gene ITGB2, corresponding to embryonic BA. Moreover, Reactome pathway analysis showed Neutrophil degranulation pathway enrichment in all subtypes, suggesting it may result from an early insult that leads to biliary stasis. Conclusions: The classification of BA into different subtypes improves our current understanding of the underlying pathogenesis of BA and provides new insights for future studies.

Atrial fibrillation increases inpatient and 4-year all-cause mortality in critically ill patients with liver cirrhosis.

BACKGROUND: The association between atrial fibrillation (AF) and cirrhosis is unclear. Therefore, the aim of the present study was to determine the association between AF and short-term and 4-year mortality in critically ill patients with cirrhosis using a large database. METHODS: The Medical Information Mart for Intensive Care III (MIMIC III) database was used to identify patients with cirrhosis hospitalized in an intensive care unit from 2001 to 2012. Demographic and clinical data were extracted from the database. Clinical data and demographic information were collected for each patient in our study. Kaplan-Meier analysis and multivariate Cox regression models were performed to examine the relation between atrial fibrillation and in-hospital and 4-year all-cause mortality. RESULTS: A total of 1,481 patients (mean age: 58 years, 68% male) with liver cirrhosis were included in the analysis, and the prevalence of AF was 14.18%. The inpatient all-cause mortality rate was 26.6%, and patients who died in hospital had a significantly higher rate of AF (21.57% vs. 11.50%, P<0.001). Multivariate Cox regression analysis indicated that AF was significantly associated with inpatient all-cause mortality [hazard ratio (HR): 1.52, 95% confidence interval (CI): 1.19-1.95, P<0.001], and 4-year all-cause mortality (HR: 1.55, 95% CI: 1.12-2.13, P=0.008). Kaplan-Meier survival analysis showed that patients with AF had a significantly higher inpatient and 4-year all-cause mortality. CONCLUSIONS: Critically ill patients with liver cirrhosis have a high rate of AF, and the presence of AF is an independent risk factor for inpatient and 4-year all-cause mortality.

U-Shaped Relationship of Low-Density Lipoprotein Cholesterol With Risk of Severe COVID-19 From a Multicenter Pooled Analysis.

Low-density lipoprotein cholesterol (LDL-C) is a well-known risk factor for coronary heart disease but protects against infection and sepsis. We aimed to disclose the exact association between LDL-C and severe 2019 novel coronavirus disease (COVID-19). Baseline data were retrospectively collected for 601 non-severe COVID-19 patients from two centers in Guangzhou and one center in Shenzhen, and patients on admission were medically observed for at least 15 days to determine the final outcome, including the non-severe group (n = 460) and the severe group (severe and critical cases) (n = 141). Among 601 cases, 76 (12.65%) received lipid-lowering therapy; the proportion of patients taking lipid-lowering drugs in the severe group was higher than that in the non-severe group (22.7 vs. 9.6%). We found a U-shaped association between LDL-C level and risk of severe COVID-19 using restricted cubic splines. Using univariate logistic regression analysis, odds ratios for severe COVID-19 for patients with LDL-C ≤1.6 mmol/L (61.9 mg/dL) and above 3.4 mmol/L (131.4 mg/dL) were 2.29 (95% confidence interval 1.12-4.68; p = 0.023) and 2.02 (1.04-3.94; p = 0.039), respectively, compared to those with LDL-C of 2.81-3.40 mmol/L (108.6-131.4 mg/dL); following multifactorial adjustment, odds ratios were 2.61 (1.07-6.37; p = 0.035) and 2.36 (1.09-5.14; p = 0.030). Similar results were yielded using 0.3 and 0.5 mmol/L categories of LDL-C and sensitivity analyses. Both low and high LDL-C levels were significantly associated with higher risk of severe COVID-19. Although our findings do not necessarily imply causality, they suggest that clinicians should pay more attention to lipid-lowering therapy in COVID-19 patients to improve clinical prognosis.