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.

Objective:To explore the diagnostic value of total bilirubin to albumin ratio(B/A ratio)combined with alpha-fetoprotein(AFP)and abnormal prothrombin induced by vitamin K absence-Ⅱ(PIVKA-Ⅱ)for hepatocellular carcinoma(HCC).Methods:35 HCC patients(HCC group),35 cirrhosis patients(cirrhosis group),35 HCC patients post-transcatheter arterial chemoembolization(TACE)(TACE postoperative group),and 35 healthy volunteers(healthy control group)were selected in our hospital from October 2023 to October 2024.The serum B/A ratio,AFP,and PIVKA-Ⅱ levles were measured and compared across the groups.The correlations between serum B/A ratio,AFP,and PIVKA-Ⅱ in the HCC group were analyzed.The B/A ratio,AFP,PIVKA-Ⅱ were compared across different clinical and pathological features in HCC patients.The serum B/A ratio,AFP,and PIVKA-Ⅱ levels were compared pre and post operation in the HCC group.The diagnostic value of B/A ratio,AFP,PIVKA-Ⅱ alone and in combination for HCC were analyzed by receiver operating characteristic(ROC)curves.Results:The serum B/A ratio,AFP,and PIVKA-Ⅱ levels in HCC group and TACE postoperative group were significantly higher than those in the cirrhosis group and healthy control group,and the HCC group was higher than that in the TACE postoperative group(P＜0.05).Pearson correlation analysis results showed that,B/A ratio in the HCC group was positively correlated with AFP(r=0.352,P=0.001),B/A ratio was positively correlated with PIVKA-Ⅱ(r=0.327,P=0.003),and AFP was positively correlated with PIVKA-Ⅱ(r=0.285,P=0.008).Higher TNM stage,larger tumor diameter,presence of vascular invasion,and lower differentiation degree of HCC patients,who had higher B/A ratio,AFP,and PIVKA-Ⅱ levels(P＜0.05).Serum B/A ratio,AFP,and PIVKA-Ⅱ levels in the HCC group post operation were significantly lower than those in pre operation(P＜0.05).ROC curve analysis results showed that,when B/A ratio,AFP,and PIVKA-Ⅱ were detected separately,the area under the curve(AUC)was 0.785,0.756,and 0.802,respectively.The AUC for joint detection was 0.925.The AUC in combination was greater than that of individual detection of each indicator.Conclusion:The combination of B/A ratio,AFP,and PIVKA-Ⅱ testing significantly improves the diagnostic efficiency for HCC,which is worthy of clinical application.

Objective To develop a deep learning method for small sample multi-omics data using attention mechanism and Meta-learning for the establishment of autism diagnosis model.Methods MLAN(Meta-learning based attentive network)consisting of the omics feature pre-reduction module,the multi-omics data fusion and feature learning module,and the parameter optimization module was designed.Firstly,differential expression analysis was performed on high-dimensional multi-omics data to preliminarily screen out unimportant features.Secondly,a multi-channel attention mechanism was used to learn the importances of every set of omics data and to realize data fusion,and a two-layer fully connected network was constructed to further extract latent features and realize the diagnosis task.Finally,the Meta-learning algorithm Reptile was used to optimize the initial parameters of the above model to obtain the optimal parameters.A total of 58 children's saliva samples were collected,including 21 children diagnosed with autism,12 children with social disorders,and 25 healthy controls,and the protein and metabolomics data were detected by mass spectrometry.All data were randomly divided into training set and test set by 4∶1,and the training set was divided into training data and validation data in the same way for model training and validation.The test set was used for the final evaluation of the model effect.Five baseline models and three ablated models were constructed and evaluated along with MLAN based on metrics including multi-classification accuracy,F1-macro and F1-weighted scores.Results The constructed multi-classification autism diagnosis model MLAN achieved multi-classification accuracy,F1-macro and F1-weighted scores of 0.850±0.066,0.817±0.103 and 0.834±0.087.The values of all three indicators were better than those of baseline models and the ablated models.Conclusion The proposed MLAN can effectively deal with heterogeneous multi-omics data with small samples and achieve good results,which is expected to provide assistance for the clinical diagnosis of autism.

Objective To develop a deep learning method for small sample multi-omics data using attention mechanism and Meta-learning for the establishment of autism diagnosis model.Methods MLAN(Meta-learning based attentive network)consisting of the omics feature pre-reduction module,the multi-omics data fusion and feature learning module,and the parameter optimization module was designed.Firstly,differential expression analysis was performed on high-dimensional multi-omics data to preliminarily screen out unimportant features.Secondly,a multi-channel attention mechanism was used to learn the importances of every set of omics data and to realize data fusion,and a two-layer fully connected network was constructed to further extract latent features and realize the diagnosis task.Finally,the Meta-learning algorithm Reptile was used to optimize the initial parameters of the above model to obtain the optimal parameters.A total of 58 children's saliva samples were collected,including 21 children diagnosed with autism,12 children with social disorders,and 25 healthy controls,and the protein and metabolomics data were detected by mass spectrometry.All data were randomly divided into training set and test set by 4∶1,and the training set was divided into training data and validation data in the same way for model training and validation.The test set was used for the final evaluation of the model effect.Five baseline models and three ablated models were constructed and evaluated along with MLAN based on metrics including multi-classification accuracy,F1-macro and F1-weighted scores.Results The constructed multi-classification autism diagnosis model MLAN achieved multi-classification accuracy,F1-macro and F1-weighted scores of 0.850±0.066,0.817±0.103 and 0.834±0.087.The values of all three indicators were better than those of baseline models and the ablated models.Conclusion The proposed MLAN can effectively deal with heterogeneous multi-omics data with small samples and achieve good results,which is expected to provide assistance for the clinical diagnosis of autism.

Objective:To explore the diagnostic value of total bilirubin to albumin ratio(B/A ratio)combined with alpha-fetoprotein(AFP)and abnormal prothrombin induced by vitamin K absence-Ⅱ(PIVKA-Ⅱ)for hepatocellular carcinoma(HCC).Methods:35 HCC patients(HCC group),35 cirrhosis patients(cirrhosis group),35 HCC patients post-transcatheter arterial chemoembolization(TACE)(TACE postoperative group),and 35 healthy volunteers(healthy control group)were selected in our hospital from October 2023 to October 2024.The serum B/A ratio,AFP,and PIVKA-Ⅱ levles were measured and compared across the groups.The correlations between serum B/A ratio,AFP,and PIVKA-Ⅱ in the HCC group were analyzed.The B/A ratio,AFP,PIVKA-Ⅱ were compared across different clinical and pathological features in HCC patients.The serum B/A ratio,AFP,and PIVKA-Ⅱ levels were compared pre and post operation in the HCC group.The diagnostic value of B/A ratio,AFP,PIVKA-Ⅱ alone and in combination for HCC were analyzed by receiver operating characteristic(ROC)curves.Results:The serum B/A ratio,AFP,and PIVKA-Ⅱ levels in HCC group and TACE postoperative group were significantly higher than those in the cirrhosis group and healthy control group,and the HCC group was higher than that in the TACE postoperative group(P＜0.05).Pearson correlation analysis results showed that,B/A ratio in the HCC group was positively correlated with AFP(r=0.352,P=0.001),B/A ratio was positively correlated with PIVKA-Ⅱ(r=0.327,P=0.003),and AFP was positively correlated with PIVKA-Ⅱ(r=0.285,P=0.008).Higher TNM stage,larger tumor diameter,presence of vascular invasion,and lower differentiation degree of HCC patients,who had higher B/A ratio,AFP,and PIVKA-Ⅱ levels(P＜0.05).Serum B/A ratio,AFP,and PIVKA-Ⅱ levels in the HCC group post operation were significantly lower than those in pre operation(P＜0.05).ROC curve analysis results showed that,when B/A ratio,AFP,and PIVKA-Ⅱ were detected separately,the area under the curve(AUC)was 0.785,0.756,and 0.802,respectively.The AUC for joint detection was 0.925.The AUC in combination was greater than that of individual detection of each indicator.Conclusion:The combination of B/A ratio,AFP,and PIVKA-Ⅱ testing significantly improves the diagnostic efficiency for HCC,which is worthy of clinical application.

AIM To establish a UPLC-ESI-MS/MS method for analyzing the toxic material basis of 95％ethanol cold soaked ultrasonic extract(EC),95％ethanol heated reflux extract(EH)and water decoction extract(WD)from Dryopteris crassirhizoma Nakai.METHODS The analysis was performed on a 25 ℃ thermostatic agilent ZORBAX RRHD StableBond C18 column(2.1 mm×150 mm,1.8 μm),with the mobile phase comprising of methanol-0.2％formic acid flowing at 0.30 mL/min,and heated electrospray ion source was adopted in positive and negative ion scanning.Compounds were identified by Compound Discover 3.3 software combined with the database and related literature,and the main differential components were screened by Heatmap cluster analysis and partial least squares discriminant analysis.RESULTS 72 compounds were identified(22 phloroglucinols,19 flavonoids,8 phenylpropanoids,6 terpenoids and 17 other components).The main toxic differential components were phloroglucinols such as flavaspidic acid AB,didemethylpseudoaspidin AA and filixic acid PBP,flavonoids such as(-)-epicatechin,(-)-epigallocatechin,cianidanol,and other compounds such as indole-3-carboxaldehyde.CONCLUSION This method can rapidly,effectively and comprehensively characterize the main chemical composition of D.crassirhizoma,and provide a reference for the study of its pharmacological mechanism.

Age-related macular degeneration (AMD) represents a predominant cause of blindness among older adults, with limited therapeutic options currently available. Oxidative stress, inflammation, and retinal pigment epithelium injury are recognized as key contributors to the pathogenesis of AMD. Regulated cell death plays a pivotal role in mediating cellular responses to stress, maintaining tissue homeostasis, and contributing to disease progression. Recent research has elucidated several regulated cell death pathways-such as apoptosis, ferroptosis, pyroptosis, necroptosis, and autophagy-that may contribute to the progression of AMD owing to cell death in the retinal pigment epithelium. These discoveries open new avenues for therapeutic interventions in patients with AMD. In this review, we provide a comprehensive summary and analysis of the latest advancements regarding the relationship between regulated cell death and AMD. Moreover, we examined the therapeutic potential of targeting regulated cell death pathways for the treatment and prevention of AMD, highlighting their roles as promising targets for future therapeutic strategies.

Peganum harmala L. (P. harmala) is a significant economic and medicinal plant. The seeds of P. harmala have been extensively utilized in traditional Chinese medicine, Uighur medicine, and Mongolian medicine, as documented in the Drug Standard of the Ministry of Health of China. Twelve novel tryptamine-derived alkaloids (1-12) and eight known compounds (13-20) were isolated from P. harmala seeds. Compounds 1 and 2 represent the first reported instances of tryptamine-derived heteromers, comprising tryptamine and aniline fragments with previously undocumented C-3-N-1' linkage and C-3-C-4' connection, respectively. Compounds 3-5 were identified as indole-quinazoline heteromers, exhibiting a novel C-3 and NH-1' linkage between indole and quinazoline-derived fragments. Compound 6 demonstrates the dimerization pattern of C-C linked tryptamine-quinazoline dimer. Compound 8 represents a tryptamine-derived heterodimer with a distinctive carbon skeleton, featuring an unusual spiro-tricyclic ring (7) and conventional bicyclic tryptamine. Compounds 9-11 constitute novel 6/5/5/5 spiro-tetracyclic tryptamine-derived alkaloids presenting a unique ring system of tryptamine-spiro-pyrrolizine. Compounds 1-3 and 6-11 were identified as racemates. Compounds 2, 7, 9, 10, and 12 were confirmed via X-ray crystallographic analysis. All isolated compounds (1-20) exhibited varying degrees of antiviral efficacy against respiratory syncytial virus (RSV). Notably, the anti-RSV activity of compound 12 (IC₅₀ 5.01 ± 0.14 μmol·L^-1) surpassed that of the positive control (ribavirin, IC₅₀ 6.23 ± 0.95 μmol·L^-1), as validated through plaque reduction and immunofluorescence assays. The identification of anti-RSV compounds from P. harmala seeds may enhance the development and application of this plant in antiviral therapeutic products.
Antiviral Agents/isolation & purification* ; Tryptamines/isolation & purification* ; Peganum/chemistry* ; Seeds/chemistry* ; Alkaloids/isolation & purification* ; Molecular Structure ; Humans ; Respiratory Syncytial Viruses/drug effects* ; Plant Extracts/pharmacology* ; Drugs, Chinese Herbal/pharmacology*

A pyrene-phenol-based fluorescent probe PyP which showed typical intramolecular charge transfer(ICT)and monomer-excimer activities was synthesized by using pyrene carboxaldehyde hydrazone and 4-tert-butyl-2,6-diformylphenol as the raw materials.The effects of solvents on PyP were studied,and the results showed that the color of protic polar solvents(Ethanol,N,N-dimethylformamide,methanol and H2O)were successfully identified.Based on the solvent polarity-regulated PyP monomer-excimer switching,the rapid and highly sensitive ratiometric probe,"Turn-off"and"Turn-on"multimodal probes were established for detection of trace water content in organic solvents(Dimethyl sulfoxide,N,N-dimethylformamide,ethanol and methanol),with detection limits(3σ/k)of 0.0021％,0.046％,0.062％and 0.024％.The method was successfully used to detect water content in dimethyl sulfoxide,N,N-dimethy lformamide,ethanol and methanol commercial organic solvents,with recoveries ranging from 97.2％to 108.0％.The developed method showed good accuracy and stability,and had good application prospect.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.