OBJECTIVE:Disorders in iron metabolism increase the risk of type 2 diabetes mellitus.Hepcidin play an important role in maintaining iron homeostasis in the body,but its level increases with increased inflammation.Changes in hepcidin and iron homeostasis and the extent of their association with inflammation in people with and without type 2 diabetes mellitus are unknown.Meta-analysis was used to evaluate the effect of inflammation on serum hepcidin and iron metabolism related parameters in patients with type 2 diabetes mellitus.METHODS:CNKI,PubMed,Web of Science and EBSCOhost databases were searched by computer to collect observational studies related to inflammatory index and hepcidin in patients with type 2 diabetes mellitus.The search time was from September 1,2000 to September 30,2024.Three researchers independently screened the literature,extracted data and evaluated the quality of the included literature.Meta-analysis was performed by Review Manager 5.3,Stata 17.0 and GraphPad Prism 8.0.2 software.RESULTS:A total of 15 articles(17 studies)involving 3 159 participants,including 1 357 patients with type 2 diabetes mellitus,were included.Meta-analysis results showed that compared with the control group,patients with type 2 diabetes mellitus had higher levels of serum hepcidin[standardized mean difference(SMD)=0.35,95％confidence interval(CI)(0.05,0.65),P＜0.05],serum ferritin(SMD=0.49,95％CI(0.21,0.78),P＜0.01)and serum transferrin(SMD=0.19,95％CI(0.00,0.37),P＜0.05).Subgroup analysis results indicated that inflammation had a significant effect on serum hepcidin(SMD=0.76,95％CI(0.17,1.34),P＜0.05)and serum ferritin(SMD=0.77,95％CI(0.06,1.47),P＜0.05)in patients with type 2 diabetes mellitus.CONCLUSION:Hepcidin concentration is positively correlated with type 2 diabetes mellitus.Inflammation is one of the risk factors of type 2 diabetes mellitus.Early prevention of inflammation has certain significance in preventing iron metabolism disorder in patients with type 2 diabetes mellitus.

Abstract To systematically investigate the childhood obesogenic environment from environmental and institutional perspectives, the study reviews the historical evolution of the commercial determinants of health (CDoH) theory. Focusing on three dimensions—products, marketing, and the social environment, it characterizes the contemporary childhood obesogenic environment, summarizes and compares relevant international regulatory policies, and proposes future research priorities and practical policy directions. The study aims to provide a system based theoretical foundation and actionable policy pathways for childhood obesity prevention and control in China.

Objective: To analyze the epidemiological characteristics of varicella among nursery children in Shenzhen from 2015 to 2024, and to evaluate the impact of optimizing varicella vaccine (VarV) immunization strategies on varicella incidence. Methods: Varicella incidence data for nursery children in Shenzhen from 2015 to 2024 were obtained from the China Disease Prevention and Control Information System. The study period was divided into three phases:one dose self pay VarV (January 2015 to October 2017), two dose self pay VarV (November 2017 to October 2019), and two dose free VarV (November 2019 to December 2024). Interrupted time series (ITS) analysis was conducted to assess changes in the level and trend of varicella incidence associated with each phase of policy implementation. Results: A total of 27 517 varicella cases was reported among nursery children from 2015 to 2024, with an average annual incidence of 514.01/100 000. During the same period, 136 clustered outbreaks were reported in nursery institutions, involving a cumulative total of 1 091 cases. ITS analysis showed that during the self pay 1 dose stage, the varicella incidence among nursery children showed an upward trend, with an average monthly increase of 2.58/100 000 (95% CI =2.21/ 100 000 -2.95/100 000, P <0.01). After the implementation of the self pay 2 dose strategy, the incidence decreased, with a change in incidence of -26.12/100 000 (95% CI =-37.30/100 000 to -14.94/100 000) and a change in slope of -2.65/100 000 (95% CI = -3.38/100 000 to -1.93/100 000)(all P <0.01). After the implementation of the free 2 dose strategy, the incidence decreased further, with a change in incidence of -40.03/100 000 (95% CI =-50.39/100 000 to -29.66/100 000, P <0.01) and a change in slope of -0.56/100 000 (95% CI =-1.20/100 000-0.08/100 000, P =0.09). Conclusion The gradual optimization of the VarV vaccination strategy in Shenzhen from self pay 1 dose to free 2 dose has significantly reduced the varicella incidence among nursery children, demonstrating good short term control and long term intervention effectiveness.

Animal model research on spleen and stomach diseases in traditional Chinese medicine （TCM） is of great significance for elucidating the nature of diseases and syndromes and for revealing the mechanisms of action of Chinese herbal medicinals. At present， studies on classical TCM syndrome models of spleen and stomach diseases mainly focus on spleen deficiency syndrome， liver constraint syndrome， and damp-heat syndrome. Model construction is mostly based on the etiological and pathophysiological characteristics of syndrome， and model evaluation primarily involves macroscopic manifestations and physicochemical indicators. This paper summarizes the current research status of animal models integrating disease and syndrome for seven common spleen and stomach diseases， including chronic gastritis and gastric precancerous lesions， gastroesophageal reflux disease， functional dyspepsia， inflammatory bowel disease， irritable bowel syndrome， functional constipation， and functional diarrhea. The modeling methods and characteristics of disease-syndrome combined animal models for each disease are analyzed. It is proposed that future research on disease-syndrome integration in spleen and stomach diseases should move toward syste-matic， precise， and integrative development， and that interdisciplinary and cross-disciplinary research approaches should be adopted to enhance the predictive value and application efficiency of disease-syndrome combined animal models.

ObjectiveTo evaluate the comprehensive intervention effects of Huangqin Qingre Chubi Capsule （黄芩清热除痹胶囊， HQC） on self-perception of patients （SPP） and immune inflammation in patients with rheumatoid arthritis （RA）， and to explore its potential mechanisms. MethodsClinical data of 452 RA patients were retrospectively collected. Patients were divided into a control group （274 cases）， treated with conventional western medicine， and an observation group （178 cases）， treated with HQC for at least 2 weeks in addition to conventional western medicine. The treatment duration was 2 weeks for both groups. Propensity score matching （PSM） was performed at a ratio of 1∶1 to match patients between groups. SPP including the Chinese version of the short form-36 health survey （SF-36）， self-rating anxiety scale （SAS）， self-rating depression scale （SDS）， visual analog scale （VAS）， and Chinese patient-reported index for rheumatoid arthritis （CPRI-RA）， as well as immune inflammatory indicators， including erythrocyte sedimentation rate （ESR）， high-sensitivity C-reactive protein （hs-CRP）， rheumatoid factor （RF）， anti-cyclic citrullinated peptide antibody （anti-CCP）， interleukin-6 （IL-6）， immunoglobulin A （IgA）， immunoglobulin G （IgG）， immunoglobulin M （IgM）， complement C3， and complement C4， were collected before and after treatment. Spearman correlation analysis was used to assess the relationships between SPP and immune inflammatory indicators. Logistic regression， association rule analysis， and mediation analysis were performed to evaluate the effects and potential pathways of HQC on SPP and immune inflammatory indicators. Network pharmacology was applied to identify the active components and core targets of HQC in the treatment of RA， followed by molecular docking verification. In cell experiments， cells were divided into normal group， model group， 20% medicated serum group， and 80 nmol/L control group. Human synovial fibroblasts （FLS） were cultured with complete medium in the normal group， while human rheumatoid arthritis fibroblast-like synoviocytes （RA-FLS） were cultured in the model group. In the 20% medicated serum group， RA-FLS were cultured with medium containing 20% HQC-medicated serum， and in the 80 nmol/L control group， RA-FLS were cultured with complete medium containing 80 nmol/L methotrexate suspension. After 48 h of culture， cell viability was detected by cell counting kit-8 （CCK-8） assay. Levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， and interleukin-10 （IL-10） in the cell supernatant were measured by enzyme-linked immunosorbent assay （ELISA）. Protein levels of matrix metalloproteinase 9 （MMP9）， transcription factor AP-1 subunit （JUN）， vascular endothelial growth factor A （VEGFA）， and C-X-C motif chemokine ligand 8 （CXCL8） were detected by Western Blot， and cell migration ability was evaluated using Transwell assay. ResultsAfter PSM， 178 cases were included in each group. After treatment， SF-36 scores increased， while scores of SAS， SDS， VAS and CPRI-RA， levels of ESR， hs-CRP， IL-6， complement C3， and complement C4 levels decreased in both groups； IgG and IgM levels were also reduced in the observation group （P＜0.05）. Physical functioning （correlation coefficient -0.19， P＜0.05） and social functioning （correlation coefficient -0.18， P＜0.05） of SF-36 were negatively correlated with hs-CRP， while VAS score was positively correlated with hs-CRP （correlation coefficient 0.19， P＜0.05）. HQC showed high associations with improvements in multiple indicators of SPP and immune inflammatory， and acted as a protective factor for the improvement of several SPP； hs-CRP and ESR played partial mediating roles in the improvement of SPP induced by HQC （P＜0.05）. Network pharmacology analysis identified baicalein， quercetin， α1-sitosterol， β-sitosterol， stigmasterol， baicalin， and crocetin as the core active components， and JUN， IL-6， VEGFA， MMP9， IL-1β， and CXCL8 as the core targets. Molecular docking results showed strong binding affinities of quercetin with VEGFA， JUN， MMP9， IL-6， and IL-1β， of baicalin with VEGFA and MMP9， and of wogonin with CXCL8. Cell experiments demonstrated that HQC and methotrexate inhibited RA-FLS viability and migration， reduced levels of IL-1β， IL-6， and IL-8， decreased protein levels of MMP9， JUN， VEGFA， and CXCL8， and increased IL-10 levels （P＜0.05）. ConclusionHQC can improve SPP in RA by regulating immune inflammatory responses. Its mechanism may be related to multi-pathway and multi-target inhibition of synovial cell inflammation and migration.

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.

OBJECTIVE To compare the efficacy and safety of vedolizumab （VDZ） versus infliximab （IFX） in biologic-naive（Bio-naive） patients with moderate-to-severe active ulcerative colitis （UC）， and to analyze the factors influencing efficacy. METHODS Clinical data were retrospectively collected from Bio-naive patients with moderate-to-severe active UC who received treatment in the Department of Gastroenterology at Shanxi Provincial People’s Hospital from June 2023 to June 2024. Based on the type of biologic agent administered， the patients were divided into the IFX group （41 cases） and the VDZ group （30 cases）. Patients in the two groups received IFX （5 mg/kg） or VDZ （300 mg） for induction and maintenance of remission therapy. The two groups were compared regarding modified Mayo score， serological indicators （hemoglobin， albumin， platelet count， erythrocyte sedimentation rate， C-reactive protein）， combined medication， efficacy-related indexes （clinical response rate/remission rate， and endoscopic response rate/remission rate）， and the occurrence of adverse drug reactions （ADR）. Based on Logistic regression model， univariate and multivariate analyses were conducted to identify potential factors influencing clinical remission at week 14 and endoscopic remission at week 38. RESULTS There were no statistically significant differences in clinical response rate/remission rate， or endoscopic response rate/remission rate between the two groups at weeks 14 and 38 （ P ＞0.05）. However， at week 14 of treatment， the proportion of patients using concomitant corticosteroids in VDZ group was 26.67%， significantly higher than the 7.50% in IFX group （ P ＜0.05）. There was no statistical significance in the overall incidence of ADR between the two groups （ P ＞0.05）； all ADRs in the IFX group were grade 3 and led to treatment discontinuation （6 cases）， whereas ADR in the VDZ group was grade 2 and did not interrupt therapy （1 case）. Univariate and multivariate regression analyses revealed that disease type （relapsing） was significantly associated with clinical remission at week 14 of treatment， and a history of smoking was significantly associated with endoscopic remission at week 38 of treatment （the odds ratios were 0.08 for both， with 95% confidence intervals of 0.01-0.77 and 0.01-0.91 respectively， P ＜0.05）. CONCLUSIONS For Bio-naive patients with moderate-to-severe active UC， VDZ and IFX demonstrate comparable efficacy in inducing and maintaining clinical remission and promoting mucosal healing， as well as overall safety. Although IFX can achieve faster control of inflammation in the early stage of the disease， it causes more severe ADR. Disease type （relapsing） and smoking history are identified as independent negative predictors for short-term clinical remission and long-term endoscopic remission， respectively.