This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective To evaluate the safety and efficacy of a self-developed micro-normothermic machine perfusion (NMP) system (micro-perfusion device) for preserving isolated porcine limbs. Methods Five healthy Landrace pigs were selected, and their left and right forelimbs were randomly divided into the NMP group and static cold storage (SCS) group. The NMP group was perfused with the self-developed micro-perfusion device and polymerized hemoglobin perfusate for 32 hours at normothermia, while the SCS group was preserved at 4 ℃. Hemodynamic parameters such as perfusion pressure and flow were monitored. The pH value, partial pressure of oxygen (PO₂), lactic acid (Lac), creatine kinase (CK) and lactate dehydrogenase (LDH) in the perfusate were measured. Hematoxylin-eosin staining was used to assess the muscle tissue structure, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling was employed to evaluate muscle cell apoptosis, and immunohistochemistry staining was applied to detect the expressions of tumor necrosis factor (TNF)-α and interleukin (IL)-6. A mixed-effects model was used to analyze the effects of time and treatment methods on tissue structure, cell apoptosis and inflammatory factors. Results The device could stably maintain a perfusion pressure of (69±15) mmHg and a flow rate of (117±42) mL/min. The pH value and electrolytes of the perfusate were generally stable, with PO₂ maintained at a high level. Lac was maintained at 5.38(3.81, 6.45) mmol/L, while CK and LDH increased over time. After 32 hours of perfusion in the NMP group, both the myocyte spacing and apoptosis rate were better than those in the SCS group. Mixed-effects model analysis showed that there were statistically significant differences in the effects of NMP treatment and SCS treatment on myocyte spacing and apoptosis rate per unit time (both P < 0.05). There were no statistically significant differences in TNF-α and IL-6 between the two groups, and mixed-effects model analysis showed no statistically significant differences in the effects of NMP treatment and SCS treatment on TNF-α and IL-6 per unit time (both P > 0.05). Conclusions The micro-perfusion device used in this study may achieve 32-hour normothermic preservation in a porcine limb amputation model, maintain basic metabolism and ionic homeostasis, reduce muscle structural damage and cell apoptosis without inducing additional inflammatory responses. This technology is expected to significantly extend the time window for replantation of amputated limbs in disaster rescue and long-distance transportation, providing an important technical basis for clinical translation and subsequent replantation research.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective To assess the current status of microbial and parasitic quality control for laboratory animals in Jiangxi Province by analyzing microbiological and parasitic test results from production facilities between 2020 and 2024, and to provide a basis for enhancing quality control measures. MethodsIn accordance with the current national standards for laboratory animals at the time of testing, the Jiangxi Provincial Laboratory Animal Quality Inspection Station (affiliated to Institute of Occupational Medicine of Jiangxi) conducted microbial and parasitic testing on 451 laboratory animals of 4 species from 6 laboratory animal production units in Jiangxi Province between 2020 and 2024, and analyzed the quality status of laboratory animals in the province. ResultsPasteurella pneumotropica was detected in one mouse sample in 2020, with a detection rate of 5.00%. Pseudomonas aeruginosa was detected in one mouse sample and mouse hepatitis virus antibody was detected in another mouse sample in 2023, with a detection rate of 2.78%, respectively. No microorganisms or parasites that should be excluded from SPF grade mice as specified in the national standards were detected in 2021, 2022, or 2024, with a qualification rate of 100.00%. Pasteurella pneumotropica was detected in four rat samples in 2020, with a detection rate of 20.00%. Pseudomonas aeruginosa was detected in two rat samples in 2021, with a detection rate of 10.00%, and Tyzzer's disease agent antibody was detected in four rat samples in 2024, with a detection rate of 10.00%. No microorganisms or parasites that should be excluded from SPF grade rats as specified in the national standards were detected in 2022 or 2023, with a qualification rate of 100.00%. For rabbits and guinea pigs, no microorganisms or parasites required to be tested for conventional grade rabbits and guinea pigs as specified in the national standards were detected from 2020 to 2024, with the qualification rate of both species reaching 100.00%. ConclusionBased on the microbial and parasitic testing results, the quality of rabbits and guinea pigs in Jiangxi Province is satisfactory. However, some issues persist with rats and mice. It is recommended to enhance the quality of experimental animals in Jiangxi Province by increasing the frequency of random inspections by quality testing units or by improving the self-inspection capabilities of production and user facilities.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

AIM:To investigate the current status of astigmatism and its associated factors among children and adolescents from kindergarten through senior high school in Yangpu District, Shanghai, and to provide scientific evidence for the prevention and control of refractive errors.METHODS:A cluster sampling method was employed. From September to November 2024, students from 14 randomly selected schools in Yangpu District, Shanghai, were enrolled as study subjects. Autorefraction and ocular biometry were performed under non-cycloplegic conditions, and questionnaire surveys were administered. Comparisons of astigmatism degree, detection rate, and axis were made across age groups, educational stages, and sexes. Multiple linear and logistic regression analyses were conducted to identify factors associated with astigmatism.RESULTS:A total of 7 233 students aged 4-18 y were enrolled including 3 731 males, 3 502 females, with the mean age 10.13±4.18 y, astigmatism -0.76±0.82 D, and the detection rate(≤-1.00 D)was 29.23%. Both the degree and detection rate of astigmatism were correlated with age and educational stage, peaking in senior high school, with the most pronounced changes observed during primary school. Besides age, astigmatic refractive power was influenced by spherical equivalent(β=0.105, P<0.001), mean keratometry(β=-0.118, P<0.001), sex(with boys as the reference, girls: β=0.054, P<0.001), frequent sustained near work for 30-40 min(with “almost never” as the reference, β=-0.030, P=0.038), preterm birth(β=-0.023, P=0.044), maternal myopia(β=-0.028, P=0.020), and homework completion time on rest days(β=-0.035, P=0.041). The detection rate of astigmatism was associated with maternal myopia(OR=1.130, P=0.039), male sex(OR=0.773, P<0.001), shorter sleep duration on school days(OR=0.909, P=0.028), shorter sleep duration on rest days(OR=0.937, P=0.046), preterm birth(OR=1.382, P=0.012), frequent excessive head lowering(OR=1.216, P=0.045), homework completion time on rest days(OR=1.043, P=0.046), higher spherical equivalent(OR=0.891, P<0.001), and higher mean keratometry(OR=1.188, P<0.001).CONCLUSION:The degree and detection rate of astigmatism among children and adolescents from kindergarten to senior high school in Yangpu District, Shanghai are correlated with educational stage, and primary school may represent a critical period for astigmatism prevention and control. Male sex, maternal myopia, preterm birth, high-intensity near work, and insufficient sleep and other factors may be associated with the onset and progression of astigmatism. It is recommended that education and health departments strengthen visual health screening during primary school, while promoting behavioral interventions such as scientific eye-use habits and adequate sleep across different educational stages to delay the onset and progression of astigmatism.

Glycogen synthase 1 (GYS1) is the rate-limiting enzyme responsible for glycogen synthesis in skeletal muscle, heart, brain, and other extrahepatic tissues, playing a central role in systemic energy homeostasis. The human GYS1 gene maps to chromosome 19q13.33, comprises 16 exons, and encodes a 737-amino-acid polypeptide that is highly conserved across mammals. GYS1 activity is subject to multilayered and precisely coordinated regulation. At the transcriptional level, the GYS1 promoter contains a hypoxia response element (HRE) that mediates HIF-1α-dependent induction under low-oxygen conditions, as well as a muscle-specific enhancer harboring MEF2 and MyoD binding sites that confers tissue-restricted expression. At the post-translational level, a hierarchical phosphorylation cascade serves as the primary activity switch: glycogen synthase kinase 3β (GSK3β) sequentially phosphorylates four C-terminal serine residues following casein kinase II priming, while protein kinase A (PKA) and AMP-activated protein kinase (AMPK) provide parallel inhibitory inputs at both N- and C-terminal sites. Dephosphorylation and reactivation are mediated by protein phosphatase 1 (PP1) through tissue-specific glycogen-targeting regulatory subunits such as PPP1R3A and PPP1R3B, which anchor PP1 to glycogen particles and direct its activity toward GYS1. The allosteric activator glucose-6-phosphate (G6P) binds at the dimer interface, simultaneously enhancing catalytic efficiency and promoting dephosphorylation susceptibility, thereby establishing a feed-forward activation loop that couples substrate availability to glycogen synthesis. Beyond phosphorylation, GYS1 is regulated by ubiquitination (mediated by the E3 ligase PJA1), acetylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification, and SUMOylation, which collectively modulate protein stability, subcellular localization, and protein-protein interactions. Epigenetic mechanisms, including CpG island methylation and histone acetylation dynamics, govern chromatin accessibility at the GYS1 locus, while muscle-specific microRNAs such as miR-1 and miR-206 fine-tune GYS1 expression at the post-transcriptional level. Dysregulation of GYS1 has been identified as a central pathogenic driver in a spectrum of human diseases. In inherited glycogen storage disorders—including Lafora disease, adult polyglucosan body disease (APBD), and Pompe disease—loss of upstream regulatory control leads to GYS1 hyperactivation and the accumulation of structurally abnormal or excessive glycogen, resulting in progressive neurodegeneration, myopathy, and multiorgan dysfunction. In type 2 diabetes mellitus (T2DM), impaired insulin signaling through the PI3K-AKT-GSK3β axis maintains GYS1 in a hyperphosphorylated inactive state in skeletal muscle, compromising postprandial glucose disposal and exacerbating hyperglycemia. In oncology, GYS1 exhibits context-dependent roles across multiple cancer types. In hepatocellular carcinoma, FMO2⁺ cancer-associated fibroblasts stabilize GYS1 by competitively inhibiting PJA1-mediated ubiquitination, and stabilized GYS1 subsequently activates NF‑κB/CCL19 signaling to promote tertiary lymphoid structure formation and enhance anti-PD-1 immunotherapy responsiveness. In clear cell renal cell carcinoma, GYS1 promotes tumor progression through non-canonical NF‑κB pathway activation via the scaffold protein RPS27A. In triple-negative breast cancer, GYS1 has been identified as a trigger of disulfidptosis and an activator of NF-κB signaling through non-enzymatic facilitation of IκBα degradation. In colorectal cancer, mitochondrial fission deficiency drives AMPK-dependent GYS1 upregulation and glycogen accumulation as a compensatory survival mechanism, while in cervical cancer, GYS1-maintained glycogen reserves fuel the pentose phosphate pathway to generate NADPH for ROS clearance, thereby conferring cisplatin resistance in cancer stem cells. Therapeutic strategies targeting GYS1 have gained substantial momentum across these disease contexts. For glycogen storage disorders, antisense oligonucleotides, small interfering RNAs (e.g., ABX1100), and small-molecule inhibitors (e.g., MZ-101) have demonstrated preclinical and early clinical efficacy in reducing pathological glycogen accumulation. For T2DM, pharmacological activation of GYS1 through GSK3β inhibition or enhancement of PP1-mediated dephosphorylation is being explored to restore insulin-stimulated glycogen synthesis. In cancer, GYS1-directed interventions—including targeted silencing to sensitize tumors to chemotherapy and immune microenvironment modulation to enhance immunotherapy—represent emerging precision oncology approaches. This review provides a comprehensive and integrated account of GYS1 gene structure, tissue-specific distribution, regulatory networks, and pathogenic roles in metabolic disorders and malignancies, with the aim of establishing a theoretical framework for the development of GYS1-targeted precision therapies.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

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.