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 systematically evaluate the efficacy, patient-reported outcomes (PROs) and safety of hyaluronic acid (HA) fillers and collagen stimulators (PCL/PLLA) for various facial aesthetic indications.Methods:This study focused on facial fillers approved and widely used in China, including HA fillers such as Juvéderm?, Restylane?, Belotero?, Fillmed?, and PCL/PLLA such as Ellansé?, L?viselle?, and CureWhite?. A systematic literature search was conducted across both English and Chinese databases, including PubMed, Cochrane Library, Embase, CNKI, and Wanfang Data, covering the period from database inception to August 24, 2023, to identify randomized controlled trials (RCTs). The characteristics and outcomes of the included RCTs were summarized and analyzed, including efficacy indicators by injection site, patient satisfaction, and safety profiles. Network meta-analysis (NMA) was performed using R software to compare efficacy outcomes, including the 6-month improvement response rate for nasolabial folds (NLF) and the global aesthetic improvement scale (GAIS).Results:A total of 38 articles were included. Among them, Juvéderm? was most frequently used as the treatment group (17 out of 38 articles), while Restylane? was the most common comparator (17 out of 38 articles), particularly in studies involving NLF injections (15 out of 16 articles). For collagen stimulators, only 2 studies on Ellansé? were included, both focusing solely on NLF treatment. Quality assessment showed that 34 studies were of medium to high quality, with Juvéderm? accounting for the majority of high-quality studies (11 articles). Based on injection sites, NLF was the most studied area (16 articles), followed by the midface (8 articles), and the remaining 14 articles covered other regions including lips, nose, chin, and infraorbital area. In the NLF region, the 6-month improvement response rate assessed by blinded investigators showed that Juvéderm? showed better outcomes than Restylane? ( RR=1.07, 95% CI: 0.89-1.32), while Belotero? was slightly inferior to Restylane? ( RR=0.97, 95% CI: 0.65-1.44), although the differences were not statistically significant. Subject-reported outcomes showed consistent trends with investigator assessments. For 6-month GAIS improvement, Juvéderm? and Restylane? showed comparable result within the HA filler category ( RR=1.01, 95% CI: 0.71-1.43). The collagen stimulator Ellansé? demonstrated numerically higher values than HA fillers ( RR=1.32, 95% CI: 0.86-2.08). However, none of these differences reached statistical significance. In midface treatments, Juvéderm? had more long-term evidence, with follow-up periods extending up to 24 months. Four studies reported numerically greater volume enhancement with Juvéderm? compared to Restylane?. For other facial areas, Juvéderm? had the most comprehensive clinical evidence, covering the widest range of injection sites. No relevant RCTs were available for collagen stimulators in these regions. Regarding patient satisfaction, 19 studies reported patient-reported outcomes, with Juvéderm? contributing 16 of them, and showing higher satisfaction in 6 head-to-head comparisons with Restylane?. In contrast, collagen stimulators currently lack such evidence. Safety result indicated that HA fillers were generally safe and well tolerated, while safety data for collagen stimulators remain limited due to insufficient high-quality evidence. Conclusion:Among the HA fillers, Juvéderm? has a large quantity and highest quality of clinical studies, and NMA result shows its superior efficacy in NLF. In comparison, the current evidence is still not sufficient to draw a clear conclusion for the PCL/PLLA due to a lack of adequate high-quality clinical evidence regarding its clinical efficacy, PROs, and safety.

Aim To investigate the effect of dihydro-myricetin(DMY)on Ang Ⅱ-induced cardiac hypertro-phy in mice and the underlying mechanisms.Methods Fifty mice were randomly divided into control group,Ang Ⅱ group,Ang Ⅱ+catopril 12.0 mg·kg-1·d-1 group,AngⅡ+DMY 100 mg·kg-1·d-1 group,and Ang Ⅱ+DMY 200 mg·kg-1·d-1 group,with 10 mice in each group.The control mice were given saline by gavage,the drug intervention group was given DMY,and the positive drug group was given captopril;the mice in all groups except the control group were in-jected subcutaneously with Ang Ⅱ 1.0mg·kg-1·d-1.After four weeks,heart weight/body weight(HW/BW)and left ventricular weight/body weight(LVW/BW)ratios were calculated.The mRNA ex-pression of the fetal genes atrial natriuretic factor(ANF),brain natriuretic peptide(BNP),β-myosin heavy chain(β-MHC),adenosine triphosphate 5β-subunit(ATP 5β)and uncoupling protein 2(UCP2)were monitored,and the morphological changes of car-diac tissue were observed.Secondly,the creatine ki-nase isoenzyme(CK-MB),lactate dehydrogenase(LDH),free fatty acids(FFA)and lactic acid in ser-um were investigated.Lastly,the expression of AMP-activated proteinkinase(AMPK),peroxisome prolifer-ator-activated receptor alpha(PPAR-α)and T-cell nu-clear factor cytoplasmic 4(NFATc4)protein expres-sion were also detected.The Ang Ⅱ-induced H9C2 cardiomyocyte hypertrophy model was established and treated with the AMPK inhibitor compound C.The mRNA of ANF,BNP,β-MHC and the protein expres-sion of AMPK/PPAR-α were analyzed.Results DMY intervention significantly reduced HW/BW and LVW/BW in mice,fetal genes ANF,BNP,β-MHC and UCP2 mRNA expression decreased,whereas ATP 5 β mRNA increased,and the degree of hypertrophy of cardiomyocytes was alleviated.In addition,the serum levels of CK-MB,LDH,FFA and lactic acid were re-duced in DMY treated groups.Finally,DMY upregu-lated the protein expression of P-AMPK,AMPK and PPAR-α,and downregulated protein expression of NFATc4.In the Ang Ⅱ-induced cardiomyocyte hyper-trophy model,DMY pretreatment reduced the mRNA expression of fetal genes(ANF,BNP,β-MHC).However,when AMPK was inhibited by compound C,the expression of these fetal genes rebounded,accom-panied by decreased protein levels of AMPK and PPAR-α.Conclusions DMY can improve Ang Ⅱ-in-duced myocardial hypertrophy in mice by ameliorating disorders of glycolipid metabolism and increasing ener-gy supply to cardiomyocytes,and its mechanism is re-lated to the activation of the AMPK/PPAR-α pathway and the inhibition of NFATc4 expression.

AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

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.

Abnormal expression of CMTM4 protein is closely related to tumour occurrence,development and prognosis.Although the important role of CMTM4 in tumours has been gradually manifested,its spe-cific mechanism of action in cervical cancer remains unclear.The aim of this study was to investigate the relationship between CMTM4 expression and clinicopathological features in cervical cancer and study its mechanism.Immunohistochemistry and Western blot were used to detect the expression level of CMTM4 in cancer tissues and paracancerous tissues,and it was found that CMTM4 was significantly under-ex-pressed in cervical cancer tissues(P＜0.001).The chi-square test analysed the relationship between high and low CMTM4 expression and the clinical and pathological characteristics of cervical cancer pa-tients and results found that CMTM4 expression was correlated with the number of births,HPV infection status,pathological type,FIGO stage and lymph node metastasis.Data from Western blot and RT-qPCR found that CMTM4 protein and mRNA levels in HaCaT cells were significantly higher than that of C-33A cells,HeLa cells,U14 cells,and HT-3 cells.Among them,the most significant change in CMTM4 ex-pression was observed in C-33A cells,so the C-33A cell line was selected for subsequent overexpression experiments.CCK-8 analysis found that the proliferation ability of C-33A cervical cancer cells in the pcDNA-CMTM4 group was significantly lower than that in the pcDNA-NC group(P＜0.001).Flow cy-tometry and Western blot results indicated that CMTM4 overexpression promoted apoptosis(P＜0.001),significantly increased Bax(P＜0.001)and cleaved caspase 3(P＜0.05)protein levels,and significant-ly decreased Bcl-2 protein level(P＜0.01).Western blot results further found that CMTM4 overexpres-sion significantly reduced the protein levels of p-PI3K(P＜0.001)and p-AKT(P＜0.01),but did not affect the protein levels of PI3K and AKT(P＞0.05).The above findings indicated that CMTM4 gene expression was down-regulated in cervical cancer,and CMTM4 overexpression inhibited cervical cancer cell proliferation and induced apoptosis by inhibiting the PI3K/AKT pathway.Therefore,CMTM4 may be used as a biological marker for screening cervical cancer.