ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Asthma and cough variant asthma （CVA） are both chronic heterogeneous diseases characterized by airway microenvironment homeostasis disruption as their core pathological basis. In recent years， micro ribonucleic acid （miRNA）， as core post-transcriptional regulators， have been shown to finely modulate multiple critical signaling pathways， including Janus kinase/signal transducer and activator of transcription （JAK/STAT）， nuclear factor-κB （NF-κB）， transforming growth factor-β/Smad （TGF-β/Smad）， and phosphoinositide 3-kinase/protein kinase B （PI3K/Akt）， as well as various pathological processes such as airway epithelial barrier restoration， type 1 helper T cell（Th1）/Th2 immune balance， M1/M2 macrophage polarization， airway smooth muscle cell function， and airway hyperresponsiveness. miRNAs play a pivotal role in maintaining and disrupting airway microenvironment homeostasis. Based on recent Chinese and international literature， a logical framework centered on "airway microenvironment homeostasis disruption， miRNA regulation， and microenvironment restoration" was constructed. From the perspective of the airway microenvironment， the therapeutic roles of miRNA in asthma and CVA were systematically summarized， and the cascade regulatory mechanisms of miRNA throughout the entire disease course were elucidated. The hub miRNA was identified， and research progress on traditional Chinese medicine intervention strategies was explored. Furthermore， current clinical studies on RNA therapeutics and traditional Chinese medicine in achieving multi-target and multi-pathway integrated treatment by modulating miRNA were analyzed. The value of miRNA as biomarkers for diagnosis， phenotyping， and prognosis assessment， as well as the potential and application prospects of miRNA mimics and antagonists in precision therapy， were summarized， with the ultimate goal of advancing precision therapy for asthma and CVA.

ObjectiveTo construct a novel KPC mouse model of type 2 diabetes mellitus （T2DM） comorbid with spontaneous pancreatic cancer based on the gene editing-metabolic intervention dual-driven strategy， and to compare it with traditional models. MethodsA total of 14 male KPC mice were randomly divided into novel model group （T2DM-KPC group with 7 mice） and control group （KPC group with 7 mice）， and 14 male BALB/c-nu nude mice were randomly divided into traditional model group （T2DM-pancreatic cancer group with 7 mice） and control group （pancreatic cancer group with 7 mice）. The mice in the KPC group and the pancreatic cancer group were fed with normal diet， and those in the T2DM-KPC group and the T2DM-pancreatic cancer group were fed with a high-fat diet. After 4 weeks， the mice in the T2DM-KPC group and the T2DM-pancreatic cancer group were given intraperitoneal injection of streptozotocin. Subsequently， the mice in the KPC group and the T2DM-KPC group developed primary pancreatic tumor spontaneously over time， while those in the T2DM-pancreatic cancer group and the pancreatic cancer group were inoculated with tumor cells to form subcutaneous tumor xenograft at 2 weeks after stabilization of blood glucose. The 4 groups were observed in terms of tumor formation rate， tumor formation time， body weight， and the change in blood glucose； RNA sequencing was performed for tumors from the KPC group and the T2DM-KPC group， and then molecular subtyping was performed； HE staining， Masson staining， and immunohistochemical staining were used to assess the histopathological features and tumor microenvironment of pancreatic tumor from the T2DM-KPC group， which were compared with those of the T2DM-pancreatic cancer group. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups； the Fisher’s exact test was used for comparison of categorical data between multiple groups. ResultsThe T2DM-KPC group had a tumor formation rate of 85.71% and a tumor formation time of 104.40±2.87 days， while the T2DM-pancreatic cancer group had a tumor formation rate of 71.43% and a tumor formation time of 95.20±9.47 days， and there were no significant differences between the two groups in tumor formation rate， tumor formation time， body weight， and blood glucose （all P>0.05）. Molecular subtyping showed that the model in the KPC group highly resembled the pancreatic progenitor subtype of human pancreatic ductal adenocarcinoma （PDAC）， and the model in the T2DM-KPC group highly resembled the immunogenic subtype of PDAC. HE staining showed that tumor cells in the T2DM-KPC group were arranged into glandular tubular structures of varying shapes， exhibiting significant cellular atypia， and this model faithfully recapitulated the pathological features of primary pancreatic cancer and showed greater invasiveness than the KPC group. Immunohistochemical staining and Masson staining showed that compared with the T2DM-pancreatic cancer group， the T2DM-KPC group had significantly higher degrees of tumor proliferation （assessed by Ki-67 expression） and fibrosis （assessed by α-SMA and Masson） （all P<0.05）， suggesting that the mouse model in the T2DM-KPC group could better recapitulate the features of hyperproliferation and pronounced desmoplasia in human pancreatic cancer. ConclusionA novel KPC mouse model of T2DM comorbid with spontaneous pancreatic cancer is successfully constructed in this study. This model can accurately mimic the histopathological architecture and stromal microenvironment of T2DM comorbid with pancreatic cancer， realize the longitudinal simulation of the progression of pancreatic tissue from intraepithelial neoplasia to invasive carcinoma and metastasis in the presence of T2DM， and support the translational research on immunotherapy， thereby providing a novel experimental carrier for in vivo studies on spontaneous pancreatic cancer in T2DM.

Objective To explore the relationship between insulin resistance and idiopathic central precocious puberty(ICPP)in girls and the diagnostic value of insulin resistance.Methods Clinical data of 245 girls aged 4 to 7.5 years with low luteinizing hormone(LH)levels(0.2-0.83 IU/L),normal body weight(body mass index standard deviation score between-2 and+2),and early breast development who visited the Department of Pediatric Endocrinology,Henan Provincial Maternal and Child Health Hospital from January 2022 to March 2025 were retrospectively analyzed.According to the Expert Consensus on the Diagnosis and Treatment of Central Precocious Puberty(2022),patients were assigned to an ICPP group(n=123)or a control group(n=122).Correlations between the homeostasis model assessment of insulin resistance(HOMA-IR)and selected indices were assessed.Multivariable logistic regression was used to evaluate the association between HOMA-IR and ICPP,and the diagnostic performance of various indices for ICPP was evaluated.Results HOMA-IR was higher in the ICPP group than in the control group(P<0.001)and was positively correlated with LH peak(rs=0.467,P<0.05)and the LH peak/FSH peak ratio(rs=0.444,P<0.05).The multivariable logistic regression model including age,BMI,and basal LH showed that HOMA-IR was closely associated with ICPP(OR=2.756,95%CI:1.940-3.913).Receiver operating characteristic curve analysis showed that the areas under the curve for basal LH,HOMA-IR,and their combination in diagnosing ICPP were 0.735,0.735,and 0.805,respectively(P<0.05),and the combined model had a greater area under the curve than either basal LH or HOMA-IR alone(both P<0.05).Conclusions HOMA-IR is closely associated with ICPP in girls with low LH and normal body weight,and combining HOMA-IR with basal LH improves early identification and diagnostic efficiency in this population.

Aim To investigate the therapeutic effect of newly formulated Tadalafil tablets on liver fibrosis in mice induced by carbon tetrachloride(CCl4)and its impact on the activation of hepatic stellate cells(HSCs).Methods Liver fibrosis model was estab-lished by intraperitoneally injecting 20％CCl4 corn oil solution twice a week for eight weeks.After four weeks of modeling,the treatment group was administered ei-ther the newly formulated Tadalafil tablets(1.0 mg·kg-1)or the Cialis(2.5 mg·kg-1)via gavage for the remaining four weeks.We assessed the effects of Tadalafil on collagen deposition,tissue structural dam-age,and HSCs activation markers in the fibrotic liver of mice using serum biochemical analysis,histopathologi-cal staining,and Western blotting following the treat-ment period.LX-2 cells were cultured and treated with tadalafil after TGF β1 stimulation,and the effects of tadalafil on LX-2 cell activation were assessed via Western blot.Results Compared to the normal mice,the model group mice exhibited a significantly higher liver-specific index,increased liver function indicators,and notable hepatocyte necrosis.Additionally,liver lobules were damaged,accompanied by severe infiltra-tion of inflammatory cells.Both smooth muscle actin(α-SMA)and fibronectin(Fn)were elevated,serving as markers of HSCs activation.As a result of treatment with the newly formulated Tadalafil tablets,liver tissue damage was significantly reduced,transaminase levels decreased,necrosis and inflammatory cell infiltration were reduced,and collagen fiber deposition was allevia-ted,and α-SMA and Fn expression was reduced.It was worth noting that low-dose newly formulated Tadalafil tablets were found to be as effective as high-dose Cia-lis.In a cellular model,Tadalafil significantly inhibited the activation of LX-2 cells and reduced the expression of proteins related to cell activation.Conclusions The newly formulated Tadalafil tablets can significantly inhibit HSCs activation,reduce extracellular matrix(ECM)deposition,improve liver fibrosis and liver function damage caused by CCl4.This new formulation offers a significant advantage over Cialis in terms of ef-fectiveness,with a lower effective dose.

Coronavirus,a major pathogen infecting humans,mammals,and birds,causes primarily respiratory diseases af-ter infecting humans.Seven coronaviruses have been found to infect humans and subsequently cause varying degrees of respira-tory symptoms.From 2019 to 2023,millions of people died from severe acute respiratory syndrome coronavirus 2 infections,and the virus continues to mutate.Therefore,drug screening research must urgently be expanded to develop more effective,broad-spectrum anti-coronavirus drugs.In-depth research has indicated that the coronavirus 3C-like protease and RNA polymer-ase are necessary for viral reproduction and are highly conserved among strains,and consequently are anti-virus targets of great interest.This article summarizes the enzymes encoded by coronaviruses and drug screening methods,to provide a reference for coronavirus prevention and control.

AIM To investigate the differences between boiled powder and decoction of Ermiao Powder.METHODS GC-MS was used to identify volatile constituents,after which the content determination of linalool,4-terpineol,α-terpineol,β-eucalyptol and taxifolin in distillate was performed,evaporation rate curve was drawn.The rat model for collagen-induced arthritis was established,then HE and SO/FG staining were conducted,and body weight,footpad swelling degree,arthritis score,immune organ(spleen,thymus)indices,serum inflammatory factors(IL-10,IL-6),ankle joint structure(foot claw swelling,micro-CT)and locomotor ability were detected.RESULTS Total 43 and 26 volatile constituents were identified in boiled powder and decoction,respectively.With the extension of boiling time,the average evaporation rates of 5 volatile constituents in the boiled powder distillate demonstrated the trends of first increase and then decrease,which reached a maximum at 15-20 min;those in the decoction distillate displayed the trends of decrease,which were not detected after 15 min except for β-eucalyptol.Compared with the decoction,the boiled powder exhibited stronger effects on improving foot swelling and arthritis score,alleviating pathological changes in joint tissues,inhibiting inflammatory factors and restoring motor ability.CONCLUSION More volatile constituents are observable in the boiled powder of Ermiao Powder than those in its decoction,along with stronger anti-rheumatoid arthritis activity.The optimal decocting endpoint is determined to be within 15 min in boiling water.