ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

The risk prediction approach integrating disease and syndrome aligns more precisely with the clinical diagnosis and treatment needs of osteoporosis.Prior research has established a consensus on the model development methodology encompassing"Target outcome selection→ Key information collection→ Data mining and modeling →Model performance evaluation".Building on this foundation,a cohort of osteoporosis patients and syndrome cases with stable follow-up is established.Utilizing artificial intelligence algorithms,critical information in traditional Chinese medicine(TCM)symptoms and syndromes is objectively characterized and quantified alongside imaging data.Employing multi-omics sequencing technology,we seek to identify highly specific microscopic molecular information,analyze potential correlations among various dimensions of information,and develop a multidimensional risk prediction model for osteoporosis with distinctive TCM attributes.This model aims to identify biomarkers with both"disease"and"syndrome"characteristics,thereby advancing the precision diagnosis and treatment system for osteoporosis.

This study was aimed at exploring the mechanism underlying the effects of nitidine chloride against Talaromyces marnef-fei through network pharmacology analysis.We collected NC and TM action targets from various databases;constructed a protein-protein interaction(PPI)network by using common drug and disease targets;and performed KEGG pathway and GO enrichment analy-ses.In vitro cellular experiments were conducted to test the antibacterial ability of NC at various concentrations,qPCR was used to de-tect the mRNA expression of genes in the target pathway,and WB was used to examine the expression of proteins associated with tar-get signaling pathways in cells.We identified 153 target genes for NC and 2 095 target genes for TM,among which 23 targets over-lapped.By integrating the PPI network with KEGG enrichment analysis,we selected key target genes in the MAPK signaling pathway,such as FLT1,FLT3,CD38,and PRF1.The CFU results indicated that NC had favorable antibacterial capability.Moreover,qPCR demonstrated that NC downregulated the mRNA expression of FLT1,FLT3,and RPS6KA3,and upregulated the mRNA expression of MAP3K8.WB findings indicated that NC downregulated the expression of RSK2,VEGF,and FLT3 proteins,and upregulated the ex-pression of MAP3K8 protein.NC may exert its anti-TM effects by downregulating the expression of RSK2,VEGF,and FLT3 proteins,thereby inhibiting MAPK pathway activation.The potential targets and signaling pathways underlying NC's anti-TM action may pro-vide new insights to guide the clinical application of NC.

The risk prediction approach integrating disease and syndrome aligns more precisely with the clinical diagnosis and treatment needs of osteoporosis.Prior research has established a consensus on the model development methodology encompassing"Target outcome selection→ Key information collection→ Data mining and modeling →Model performance evaluation".Building on this foundation,a cohort of osteoporosis patients and syndrome cases with stable follow-up is established.Utilizing artificial intelligence algorithms,critical information in traditional Chinese medicine(TCM)symptoms and syndromes is objectively characterized and quantified alongside imaging data.Employing multi-omics sequencing technology,we seek to identify highly specific microscopic molecular information,analyze potential correlations among various dimensions of information,and develop a multidimensional risk prediction model for osteoporosis with distinctive TCM attributes.This model aims to identify biomarkers with both"disease"and"syndrome"characteristics,thereby advancing the precision diagnosis and treatment system for osteoporosis.

This study was aimed at exploring the mechanism underlying the effects of nitidine chloride against Talaromyces marnef-fei through network pharmacology analysis.We collected NC and TM action targets from various databases;constructed a protein-protein interaction(PPI)network by using common drug and disease targets;and performed KEGG pathway and GO enrichment analy-ses.In vitro cellular experiments were conducted to test the antibacterial ability of NC at various concentrations,qPCR was used to de-tect the mRNA expression of genes in the target pathway,and WB was used to examine the expression of proteins associated with tar-get signaling pathways in cells.We identified 153 target genes for NC and 2 095 target genes for TM,among which 23 targets over-lapped.By integrating the PPI network with KEGG enrichment analysis,we selected key target genes in the MAPK signaling pathway,such as FLT1,FLT3,CD38,and PRF1.The CFU results indicated that NC had favorable antibacterial capability.Moreover,qPCR demonstrated that NC downregulated the mRNA expression of FLT1,FLT3,and RPS6KA3,and upregulated the mRNA expression of MAP3K8.WB findings indicated that NC downregulated the expression of RSK2,VEGF,and FLT3 proteins,and upregulated the ex-pression of MAP3K8 protein.NC may exert its anti-TM effects by downregulating the expression of RSK2,VEGF,and FLT3 proteins,thereby inhibiting MAPK pathway activation.The potential targets and signaling pathways underlying NC's anti-TM action may pro-vide new insights to guide the clinical application of NC.

The dysregulation of cyclin-dependent kinase 12 (CDK12), which may result from genomic alterations or modulation by upstream effectors, is implicated in cancer oncogenesis and progression. CDK12 overexpression or activation is sufficient to induce tumor initiation, recurrence, and therapeutic resistance. However, CDK12 may also exert tumor-suppressive functions in a context-dependent manner. Therefore, caution is warranted when targeting CDK12 in future clinical trials. A comprehensive elucidation of the dual roles and underlying mechanisms of CDK12 in carcinogenesis is urgently needed to advance precision oncology. This review provides an overview of the current understanding of the dysregulation and biological roles of CDK12 in cancer. Subsequently, we systematically summarize the functions and mechanisms of the oncogenic and tumor-suppressive roles of CDK12 in different contexts. Finally, we discuss the potential of CDK12 as a novel therapeutic target and its implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

Objective: To investigate the causes and characteristics of immune hemolytic transfusion reactions (HTRs) triggered by anti-E antibodies, so as to provide a scientific reference for guaranteeing clinical blood transfusion safety. Methods: Five patients who experienced HTRs in our hospital from November 2023 to October 2024 were selected as the research subjects. ABO/RhD blood grouping, antibody screening, antibody identification, and the direct antiglobulin test (DAT) were conducted using the column agglutination method. The causes of HTRs in these patients were investigated using multiple techniques such as the two-step enzyme method, polyethylene glycol (PEG), acid elution technique, and capillary centrifugation method. Results: All five patients tested negative for antibody screening prior to transfusion. However, after transfusion of E+ phenotyped blood, patients 1, 2, 3, and 5 developed delayed haemolytic transfusion reaction (DHTR), while patient 4 experienced acute haemolytic transfusion reaction (AHTR). Anti-E antibodies were detected in all blood samples from the patients after the hemolytic transfusion reaction, including the enzyme-only anti-E antibody in two cases. Conclusion: Anti-E antibody can trigger both intravascular and extravascular hemolysis. It is recommended to conduct ABO/RhD and RhE antigen-matched transfusions and establish a regional blood transfusion database to reduce immune hemolytic transfusion reactions caused by anti-E antibody.