Zhijun Su

Whether tenofovir disoproxil fumarate (TDF) or entecavir (ETV) combined with pegylated interferon offers superior functional cure potential in chronic hepa

China’s 2025 clinical guideline designates age ≥ 65 years, pregnancy, and chronic comorbidity as patient categories requiring prior

We compared the efficacy of four treatment strategies for chronic hepatitis B (CHB): tenofovir disoproxil fumarate (TDF), tenofovir alafenamide (TAF), tenofovir amibufenamide (TMF), and TDF-to-TAF switch strategies strategy. We conducted a network meta-analysis to provide evidence-based clinical guidance. We systematically retrieved PubMed, Web of Science, Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI) databases up to April 2025 for randomized controlled trials (RCTs) and cohort studies. We assessed literature quality using the Cochrane Risk of Bias (ROB) tool and Newcastle-Ottawa Scale (NOS). Stata 17 was employed for network meta-analysis, focusing on virological response rate, hepatitis B surface antigen (HBsAg) clearance rate, hepatitis B e antigen (HBeAg) clearance rate, and alanine aminotransferase (ALT) normalization rate. Virological response did not differ between TMF monotherapy and TDF-to-TAF switch (OR = -0.03; 95% CI -0.42 to 0.36). HBsAg clearance was similar between TAF and TMF (95% CI: -1.17-1.14). For the rate of HBeAg loss, both TAF and TMF exhibited favorable therapeutic effects. For ALT normalization rate, TMF monotherapy was the most effective, with an average effect size of 0.11 (95% CI: -0.14-0.37), while TDF monotherapy was generally inferior to the other three treatment strategies. Our findings may help guide the selection of individualized CHB treatment strategies. However, given the limited evidence and potential bias, these results are preliminary and must be interpreted with caution. For regimens such as TMF that lack robust data, well-established alternatives should be preferred. Long-term, multi-endpoint studies are required to confirm both efficacy and safety before routine clinical adoption.

Objective To analyze clinical features and identify prognostic factors in HIV/AIDS patients with cryptococcal meningitis (CM), and to develop a predictive model for short-term mortality. Methods A multicenter retrospective study was conducted on 197 HIV/AIDS patients diagnosed with CM from 2013 to 2023. Clinical data were collected, and multivariate logistic regression was used to construct a prognostic model. Results The median age was 48 years (IQR: 33–57.5), with 75.6% males. Common symptoms included headache (68.5%), fever (52.8%), and nausea/vomiting (49.2%). Independent risk factors for mortality were consciousness disturbance (OR = 7.785, P = 0.013) and elevated intracranial pressure (OR = 1.011, P = 0.023), while CD8⁺T lymphocytes (OR = 0.997, P = 0.022) and platelet count (OR = 0.990, P = 0.014) were protective. The prognostic model (AUC = 0.860, 95% CI: 0.776–0.943) demonstrated sensitivity of 71.4% and specificity of 89.3%. Conclusion Consciousness disturbance, intracranial pressure, CD8⁺ T cells, and platelets independently predict mortality in HIV/AIDS-associated CM. Early intervention targeting these factors may improve outcomes.

Introduction The objective of the study was to determine the clinical features and prognostic risk factors of acquired immunodeficiency syndrome (AIDS) combined with Talaromyces marneffei (TM) infection. Methods We retrospectively analyzed the clinical data of 133 hospitalized patients diagnosed with AIDS and TM co-infection. Patients were divided into an improvement group and a deterioration group on the basis of their discharge outcomes. To further investigate the severity of adverse outcomes, subgroup analysis was performed on the deterioration group. Due to the issue of complete separation in the data, Firth’s logistic regression model was employed to identify independent prognostic factors. Finally, the predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve. Results Among 133 patients with AIDS and TM co-infection, the main manifestations were fever (93.23%) and severe immunodeficiency with median CD4⁺ T cell count of 8.50 cells/μL, with blood culture showing the highest positive rate (93.85%). Firth’s logistic regression analysis revealed that timely antifungal therapy (OR 0.004, 95% CI P < 0.001) and higher baseline albumin (ALB) levels (OR 0.858, 95% CI 0.732–0.973, P = 0.016) were independent protective factors for improving patient prognosis. The area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.930 (95% CI 0.878–0.982). Conclusions Timely antifungal therapy and good nutritional status are key determinants of prognosis in patients with AIDS and TM co-infection. Early diagnosis, prompt initiation of effective treatment, and active nutritional support are of great significance for improving patient survival outcomes.

Background: Colorectal cancer (CRC) is a prevalent and lethal malignancy, with the role of gut microbiota in its development still unclear. This study examines differences in gut microbiota between CRC patients and healthy controls and explores their association with host gene expression to identify potential diagnostic and therapeutic targets.Methods: Fecal samples from 10 CRC patients and 13 healthy controls were subjected to 16S rRNA sequencing. Transcriptome sequencing of tumor tissues, normal mucosa, and colorectal polyps from same 10 CRC patients was performed to identify differentially expressed genes (DEGs). Pearson correlation analysis was employed to associate operational taxonomic units (OTUs) with host gene expression.Results: β-diversity analysis showed significant differences in microbiota between CRC patients and controls (P < 0.01). LEfSe identified 38 distinct bacterial taxa, with genera such as Bacteroides, Peptostreptococcus, and Parabacteroides being enriched in CRC patients. Transcriptome analysis uncovered 1,026 DEGs. Notably, TIMP1 and BCAT1 were positively correlated (r > 0.76, P < 0.01) with pathogenic bacteria like Fusobacterium nucleatum and Peptostreptococcus stomatis. Tumor-related genes TRPM4, MYBL2, and CDKN2A were significantly upregulated and correlated with specific bacterial taxa.Conclusion: This study underscores the significant alterations in gut microbiota associated with CRC and reveals novel correlations between specific microbes and host gene expression, offering potential diagnostic markers and therapeutic targets for CRC.

Immunotherapy targeting immune checkpoints such as programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) has emerged as a novel treatment option for various cancers, including colon cancer. However, immune evasion mechanisms can limit the efficacy of cancer immunotherapy. Understanding the regulatory mechanisms of PD-1/PD-L1 expression is therefore critical to enhancing immunotherapeutic outcomes. A previous study demonstrated that the adenosine A1 receptor (Adora1) regulates PD-L1 expression and tumor immune evasion in human melanoma; however, its role in colon cancer and associated immune escape remains poorly defined. To investigate this, we downregulated Adora1 expression in CT26 colon cancer cells using lentiviral transduction of Adora1-targeting shRNA. We assessed Adora1 and PD-L1 expression levels and evaluated cell proliferation in CT26 cells. In vivo, we inoculated CT26 cells into mice and monitored tumor growth, immune cell phenotypes, and T cell exhaustion within the tumors. Additionally, we evaluated T cell exhaustion in vitro by co-culturing T cells with CT26 cells. While Adora1 knockdown did not impact CT26 cell viability or proliferation in vitro, it significantly suppressed tumor growth in vivo (P<0.0001). Furthermore, Adora1 downregulation reduced T cell exhaustion (all P=0.0025) by decreasing PD-L1 expression in CT26 cells. Knockdown of Adora1 did not alter Atf3 expression but led to reduced Irf1 expression (P=0.0268), which contributed to the downregulation of PD-L1. Overall, these findings suggest that Adora1 downregulation inhibits immune escape in colon cancer by suppressing PD-L1 expression.

Background: As an uncommon serological pattern, the effect of hepatitis B e antigen/anti-hepatitis B e (HBeAg/anti-HBe) coexistence on peginterferon-α (Peg-IFN-α) therapy in patients with chronic hepatitis B (CHB) remains unknown. Moreover, Peg-IFN-α is clinically limited due to several side effects. It is of significant value to early identify the favored population for Peg-IFN-α therapy in CHB patients. Objectives: This study aimed to analyze the impact of HBeAg/anti-HBe coexistence on the effectiveness of Peg-IFN-α and to construct a nomogram for predicting the occurrence of HBeAg seroconversion in treatment-naïve CHB patients with Peg-IFN-α therapy. Design: Retrospective, case–control study of treatment-naïve CHB patients with Peg-IFN-α at a tertiary care center. Methods: Data from HBeAg-positive treatment-naïve CHB patients were retrospectively analyzed. Clinical characteristics of the HBeAg/anti-HBe coexistence group were compared with those of the anti-HBe-negative group. In addition, univariate and multivariate logistic regression analyses were performed to identify independent risk factors for HBeAg seroconversion. The nomogram for the prediction of HBeAg seroconversion was constructed and evaluated. Results: A total of 140 HBeAg-positive CHB patients were enrolled. Patients with HBeAg/anti-HBe coexistence accounted for 11.4% of HBeAg-positive patients, and their hepatitis B surface antigen (HBsAg) and HBeAg levels were significantly lower than those of anti-HBe negative patients, but the HBeAg seroconversion rate was higher after Peg-IFN-α treatment. As revealed by multivariate logistic analysis, HBeAg/anti-HBe coexistence, baseline HBsAg, baseline HBeAg, and alanine aminotransferase ratio at baseline were independent correlates of HBeAg seroconversion. The nomogram model constructed based on these four independent correlates demonstrated good discrimination (area under the curve = 0.866), calibration, and clinical adaptability. Conclusion: HBeAg/anti-HBe coexistence is associated with a higher HBeAg seroconversion rate, and the nomogram model constructed based on HBeAg/anti-HBe coexistence performs well in predicting HBeAg seroconversion in treatment-naïve CHB patients treated with Peg-IFN-α therapy.