This bibliometric study maps English-language Web of Science Core Collection evidence on Tongxie Yaofang (TXYF) for ulcerative colitis and distinguishes clinical, mechanistic, and translational research streams. The analysis identifies a rapidly expanding, China-led field, with network pharmacology, animal models, microbiota, and inflammatory signaling research outpacing standardized clinical endpoint studies.
Research Article
Knowledge Mapping of Clinical Evidence and Mechanistic Research on Tongxie Yaofang for Ulcerative Colitis: A Bibliometric Analysis
In This Article
Summary
Abstract
To systematically map the knowledge landscape of clinical evidence and mechanistic research on Tongxie Yaofang (TXYF) for ulcerative colitis (UC), we conducted a bibliometric and knowledge-graph analysis of English-language articles and reviews retrieved from the Web of Science Core Collection through 31 December 2025. After screening, 133 records were analyzed for publication trends, collaboration networks, journal distribution, co-citation clusters, keyword co-occurrence, and clinical-versus-mechanistic thematic structure. Operational criteria were used to classify records as clinical evidence, mechanistic research, or translational/bridge studies. The field expanded markedly after 2020, with Chinese institutions dominating, but international and cross-team collaboration remained limited. Mechanistic research showed strong activity around nuclear factor kappa B (NF-κB)/NOD-like receptor protein 3 (NLRP3), mitogen-activated protein kinase (MAPK)/AKT (protein kinase B), gut microbiota, short-chain fatty-acid metabolism, intestinal barrier repair, macrophage polarization, and computational pharmacology. Clinical evidence in the English-language WoSCC corpus was comparatively sparse and often relied on broad symptom or disease-activity outcomes rather than standardized patient-reported, endoscopic, histologic, and biomarker endpoints. These findings indicate a translational disconnect between mechanistic discovery and clinical evaluation, and they support the development of mechanism-informed, multicenter clinical studies with predefined biological readouts.
Introduction
Ulcerative colitis (UC) is a chronic inflammatory disease of the colon shaped by environmental, genetic, microbial, epithelial-barrier, and immune factors1. Current management has moved beyond symptom relief toward treat-to-target strategies that emphasize mucosal healing, durable remission, and prevention of complications. Although 5-aminosalicylic acid, corticosteroids, immunomodulators, biologics, small-molecule inhibitors, and interleukin-targeted therapies have improved outcomes for many patients, primary non-response, secondary loss of response, infection risk, cost, and treatment burden remain clinically important challenges2,3,4. These unmet needs have sustained interest in multi-component adjunctive approaches that may regulate inflammation, barrier injury, microbiota disturbance, and immune imbalance through coordinated mechanisms.
Tongxie Yaofang (TXYF), a classical traditional Chinese medicine (TCM) formula associated with the principle of restraining wood and supporting earth, is commonly discussed for diarrhea and abdominal pain related to liver-stagnation and spleen-deficiency patterns5. In contemporary clinical practice, it has become a frequently prescribed treatment for ulcerative colitis and related inflammatory bowel diseases. Recent scientific research on Tongxieyao Formula has progressed from clinical empirical validation to in-depth molecular mechanism analysis6,7. Modern pharmacological studies reveal that this formula does not act as a single anti-inflammatory agent but exerts effects through multiple pathways8. In terms of inflammation regulation, research demonstrates its significant ability to inhibit overactivation of relevant signaling pathways and inflammatory microsomes. Regarding intestinal mucosal barrier repair, the formula upregulates tight junction protein expression and reduces intestinal permeability9. Additionally, the restoration of gut microbiota balance and modulation of the neuroendocrine-immune network of the gut-brain axis are emerging as novel focal points for elucidating the therapeutic mechanisms of Tongxieyao Formula. Latest basic experiments indicate that the formula improves immune dysregulation by regulating tryptophan metabolism and receptor activity, providing robust evidence supporting the scientific rationale for its therapeutic efficacy in ulcerative colitis10.
Despite increasing publication activity, the evidence landscape remains fragmented. Current studies predominantly adopt single-perspective approaches: either focusing on clinical efficacy indicators through small-sample randomized controlled trials or conducting purely basic experiments investigating specific signaling pathway interventions11,12. There exists a significant disconnect between clinical evidence and mechanistic studies, with insufficient integration of their interactive relationships. Additionally, systematic analysis has yet to be conducted regarding core research team distribution, cross-institutional collaboration intensity, the foundational role of seminal literature, and temporal evolution patterns of research themes. For instance, while keywords such as network pharmacology, gut microbiota, and signaling pathways show high frequency in keyword clustering, quantitative big data analysis remains lacking to elucidate how these research hotspots evolved from traditional symptom evaluation methods and determine their future developmental trajectories13. In UC-related research, TXYF has been investigated through reviews, network pharmacology, molecular docking, disease models, microbiota analyses, transcriptomics, macrophage-polarization experiments, and fecal microbiota transplantation validation2,14,15,16,17,18,19,20. Current evidence suggests that TXYF research has shifted from empirical symptom-oriented interpretation toward hypotheses involving nuclear factor kappa B (NF-κB)/NOD-like receptor protein 3 (NLRP3), mitogen-activated protein kinase (MAPK)/AKT (protein kinase B), IL-10RA/NF-kB signaling, epithelial-barrier protection, microbial remodeling, and mitophagy. Clinical studies and protocols tend to emphasize symptom relief, disease activity, recurrence, safety, and TCM syndrome differentiation, whereas mechanistic studies frequently examine computational target prediction, inflammatory signaling, animal or cellular validation, microbiota modulation, and epithelial-barrier repair2,14,15,16,17,18,19,20. These streams are not yet well integrated: mechanistic findings are seldom prospectively embedded into clinical trial endpoints, and clinical studies rarely include standardized biomarker panels capable of testing the biological pathways proposed by preclinical work.
This study therefore, aimed to map the English-language WoSCC research landscape on TXYF for UC, identify key contributors and knowledge structures, and compare the maturity and translational connectivity of clinical evidence and mechanistic research. The goal was not to claim exhaustive coverage of all Chinese and international TXYF studies, but to characterize the internationally indexed English-language corpus and to identify where future work should strengthen reproducibility, collaboration, endpoint standardization, and mechanism-to-clinic study design.
Protocol
Study design
This study used a bibliometric and knowledge-graph design focused on clinical evidence and mechanistic research on TXYF for UC. The workflow is shown in Figure 1 and includes six linked stages: database retrieval, duplicate removal, title/abstract screening, full-text eligibility assessment, structured data extraction, and visualization/synthesis. The final analytical sample consisted of 133 English-language articles and reviews. Table 1 summarizes the search strategy and eligibility criteria, and the Table of Materials lists the bibliographic platform, exported data type, software tools, and reproducibility notes.
The design integrates bibliographic metadata, author and institutional information, countries/regions, source journals, cited references, keywords, abstracts, and manually coded thematic attributes. This approach allows the manuscript to describe publication growth and collaboration patterns while also examining whether clinical evidence and mechanistic research are developing as connected translational streams or as parallel, weakly linked bodies of work.
Data source and search strategy
The data source was the Web of Science Core Collection (WoSCC), selected because it provides standardized citation records, author keywords, institutional affiliations, country/region fields, cited references, and export formats compatible with VOSviewer and CiteSpace. The search covered records available through 31 December 2025. Both retrieval and data export were performed at a single time point to reduce instability caused by database updates.
The exact topic-search query executed in WoSCC was:
TS=(("Tongxie Yaofang" OR "Tong Xie Yao Fang" OR "Tongxie-Yaofang" OR "Tongxie formula" OR "TXYF") AND ("ulcerative colitis" OR "UC"))
Search results were limited to English-language articles and reviews. Conference abstracts, editorials, letters, corrections, book reviews, and records without sufficient bibliographic information were excluded. These restrictions were applied to maintain metadata consistency for network construction; however, the English-only WoSCC design is acknowledged in the Discussion as an important retrieval limitation rather than evidence that Chinese-language clinical work is absent.
For reproducibility, all eligible WoSCC records were exported as full records with cited references. Restrictive descriptors such as clinical, mechanism, network pharmacology, signaling pathway, microbiota, or trial were not added to the initial query. After retrieval, records were manually screened and coded by title, abstract, and, when necessary, full text. Geographic fields were standardized before visualization: affiliation records from Taiwan, Hong Kong, and Macao were treated as China regional records for country-level counting and were not interpreted as separate sovereign countries.
Eligibility criteria and literature screening
To ensure high relevance between the included literature and the research topic, and to enhance the accuracy and interpretability of subsequent knowledge graph analysis results, this study established clear inclusion and exclusion criteria prior to formal analysis and conducted staged screening of retrieved literature using standardized procedures. The overall screening process comprised four steps: document deduplication, initial screening of titles and abstracts, full-text re-screening, and final inclusion determination (see Figure 1 for detailed workflow). Following systematic retrieval and progressive screening, a total of 133 articles were ultimately included in the bibliometric analysis of this study.
Regarding inclusion criteria, this study primarily selected literature meeting the following requirements: First, the research topic must explicitly involve Tongxie Yaofang and ulcerative colitis, meaning both Tongxie Yaofang and ulcerative colitis serve as core research subjects rather than being merely mentioned in background or discussion sections. Second, the literature type must be strictly limited to formally published articles or reviews to ensure completeness of bibliographic information and citation data. Third, the language of the literature must be restricted to English to enhance data source consistency and meet the fundamental requirements of international bibliometric analysis. Fourth, the literature records should contain relatively complete metadata information, including title, author, source journal, abstract, keywords, and citation details, enabling subsequent collaborative network analysis, keyword co-occurrence analysis, and co-citation analysis.
The exclusion criteria primarily include the following categories: First, duplicate literature records; Second, studies not directly related to the themes of Tongxie Yaofang (Pain-Relieving Formula) or ulcerative colitis, such as those solely discussing other traditional Chinese medicine formulations or focusing on general inflammatory bowel diseases without explicit reference to Tongxie Yaofang; Third, conference abstracts, editorials, reader letters, errata, book reviews, and other informal academic documents lacking complete research structures; Fourth, records with incomplete bibliographic information or unavailable valid abstracts and basic citation details; Fifth, literature where Tongxie Yaofang is not the primary research subject despite search term matches, or ulcerative colitis is not the main disease focus. Through these criteria, the study aims to minimize interference from non-target literature and low-information-content materials on research outcomes.
The literature screening process was conducted using a hierarchical progressive approach. First, all original records imported from databases were transferred to literature management software and spreadsheets, where title, author, year, and journal information were verified, and duplicate records were removed. Subsequently, the initial screening phase for titles and abstracts was initiated, with each record's title and abstract independently reviewed against predefined inclusion/exclusion criteria to preliminarily exclude documents that clearly did not meet the thematic requirements. Following this, retained documents underwent full-text re-examination to assess whether their research subjects, content, and core themes genuinely centered on "Pain Relief Formula for Treating Ulcerative Colitis," while also verifying compliance with literature type classification and metadata completeness requirements.
Operational definitions were applied before coding. Clinical evidence studies were defined as records whose primary aim was to evaluate patient-level efficacy, safety, recurrence, symptom change, disease activity, quality of life, TCM syndrome outcomes, inflammatory markers, endoscopic outcomes, histologic outcomes, or other clinical endpoints. Mechanistic studies were defined as records whose primary aim was to explain TXYF action through network pharmacology, molecular docking, molecular dynamics, target prediction, animal models, cellular validation, microbiota analysis, multi-omics, inflammatory signaling, immune regulation, epithelial-barrier repair, oxidative stress, apoptosis, mitophagy, or related pathways. Translational or bridge studies were defined as records that connected clinical evaluation with mechanistic measurement, evidence synthesis, biomarker mapping, or experimental validation in a way that could inform clinical trial design.
Data extraction and thematic classification
After completing literature screening and ultimately selecting 133 target publications, this study conducted structured extraction and organization of relevant bibliographic information to establish the data foundation for subsequent knowledge graph analysis. The data extraction primarily encompassed three components: basic literature information, citation details, and thematic attribute data. Basic literature information included title, author, publication year, source journal, country/region, institution, document type, and abstract. Citation data comprised citation frequency, references, keywords, and author keywords. Thematic attribute information was utilized for research content stratification and comparative analysis, covering research subjects, methodologies, models, and core thematic directions.
Thematic attributes were extracted in addition to standard bibliometric fields. For each record, the authors coded the dominant study type, principal model or method, main clinical or mechanistic focus, and whether the study directly linked mechanism-level findings to clinical endpoints. Ambiguous records were classified according to the primary objective stated in the title, abstract, and methods rather than by brief speculative discussion statements.
Clinical endpoint coding was refined into patient-reported outcomes (PROs) and objective endpoints. PROs included diarrhea, abdominal pain, stool frequency, global symptom improvement, quality of life, and TCM syndrome scores. Objective endpoints included disease activity indices, inflammatory markers, endoscopic or mucosal-healing measures, histology, recurrence, safety events, microbiota profiles, epithelial-barrier indicators, cytokines, immune-cell phenotypes, and pathway biomarkers.
Studies combining network pharmacology prediction with animal, cellular, microbiota, or molecular validation were coded as mechanistic studies if mechanism elucidation was the primary aim. Studies focused on efficacy observation but mentioning possible mechanisms only in the Discussion were coded as clinical evidence studies. Protocols or evidence-synthesis records that explicitly attempted to integrate clinical-effect evaluation with mechanism exploration were coded as translational/bridge studies.
Bibliometric analysis and visualization
Bibliometric analysis was conducted with spreadsheet software, VOSviewer, and CiteSpace; the Table of Materials reports the version/identifier fields and flags items requiring author confirmation from the original analysis logs. Spreadsheet software was used for duplicate checks, descriptive statistics, annual publication counts, research-type classification, and preparation of source tables. VOSviewer was used to build co-authorship, institutional, country/region, journal, and keyword co-occurrence networks. CiteSpace was used for co-citation analysis, cluster detection, timeline interpretation, and burst-keyword detection.
Co-citation analysis was used to identify knowledge-base modules repeatedly cited by TXYF-UC studies. Clusters were manually interpreted by reading representative titles, abstracts, and cited-reference contexts, with attention to UC inflammatory mechanisms, TCM compound intervention evidence, gut microbiota and mucosal barrier studies, and computational pharmacology methods.
Keyword preprocessing included synonym consolidation, spelling standardization, case normalization, removal of non-informative terms, and harmonization of equivalent biological concepts. Keyword co-occurrence and temporal analyses were then used to identify major research hotspots and emerging frontiers, including inflammatory signaling, TCM clinical evidence, microbiota-metabolism interactions, computational pharmacology, and barrier-immunity regulation.
Clinical-versus-mechanistic mapping combined the thematic classification with keyword clusters and coded endpoint domains. The comparison examined six domains: symptom control, inflammatory response, intestinal barrier repair, gut microbiota, immune regulation, and disease progression.
Results
Literature screening and overall publication characteristics
Based on established search strategies and screening criteria, this study ultimately included 133 English-language articles related to the use of Tongxieyao Formula in the treatment of ulcerative colitis, forming the foundational sample for subsequent knowledge graph analysis. Overall, this field has evolved from early sporadic explorations into a research direction with considerable scale and continuity, exhibiting distinct phased characteristics in publication trends, research types, and methodological approaches.
First, Figure 2 illustrates the annual publication trends and cumulative growth trajectory of this field from 2003 to 2025. The results show that early-stage publications were relatively low, indicating the field was primarily in its initial and accumulation phase. After 2010, the number of related publications gradually increased, suggesting the emergence of a stable research focus in this area. Following 2020, annual publication volumes continued to rise with a significantly steeper cumulative curve, indicating accelerated development in recent years. Hierarchical column structures further reveal that clinical evidence studies consistently form the primary foundation, while mechanism studies expand during mid-to-late stages. Although translational or bridging studies have appeared, their overall proportion remains limited. Figure 2B further analyzes research type composition: the outer ring shows clinical evidence studies as the dominant category, followed by mechanism studies, with translational research accounting for the smallest proportion, reflecting current reliance on clinical observations and fundamental mechanism exploration. The inner ring demonstrates that mechanism studies primarily utilize animal models and network pharmacology, with multi-omics approaches and alternative pathways gradually gaining prominence, indicating a shift from single-pathway validation to multi-technology integration. Figure 2C reveals temporal evolution characteristics across different research methodologies. It can be observed that randomized controlled trials (RCTs)/reviews persist throughout all stages, indicating that clinical orientation remains a critical pillar in this field. Concurrently, mechanistic research approaches such as network pharmacology, animal models, and multi-omics/microbiota studies have significantly increased during the mid-to-late stages, particularly in recent years. This trend suggests a gradual shift in research focus from traditional efficacy observation to systematic mechanism elucidation and molecular-level validation.
Table 22,14,15,16,17,18,19,20is a representative evidence table rather than a complete list of all 133 bibliometric records. The included entries were selected because they directly focused on TXYF and UC and illustrated major evidence roles in the field: foundational review, computational mechanism prediction, experimental validation, microbiota/multi-omics validation, disease-progression extension, and clinical-mechanistic bridging. The completely cleaned bibliographic dataset and screening record are supplied as supplementary source data (Supplementary File 1).
| First author | Year | Journal / Source | Study type | Main approach or model | Main focus / core finding | Reference number | |||||||
| Chen | 2021 | Evidence-Based Complementary and Alternative Medicine | Narrative review | Literature review | Summarized the chemical constituents, pharmacologic basis, and potential anti-UC mechanisms of TXYF | 14 | |||||||
| Zou | 2022 | Evidence-Based Complementary and Alternative Medicine | Mechanistic prediction study | Network pharmacology + molecular docking | Explored multi-component and multi-target mechanisms of TXYF against UC | 15 | |||||||
| Zhang | 2022 | Phytomedicine | Experimental mechanistic study | DSS-induced colitis model | Reported that TXYF regulated macrophage polarization and ameliorated colitis via the NF-κB/NLRP3 pathway | 16 | |||||||
| Liu | 2024 | Aging (Albany NY) | Mechanistic prediction study | Network pharmacology | Suggested that TXYF acts against UC through multi-target regulation centered on the MAPK/AKT pathway | 2 | |||||||
| Tang | 2024 | Medicine | Mechanistic prediction study | Network pharmacology + molecular docking + molecular dynamics | Indicated multi-target, multi-function therapeutic potential of TXYF for UC | 17 | |||||||
| Xu | 2024 | Journal of Ethnopharmacology | Experimental mechanistic study | AOM/DSS colitis-associated colorectal cancer model | Showed that TXYF induced mitophagy and inhibited colitis-associated colorectal cancer through the PINK1/Parkin pathway | 18 | |||||||
| Shang | 2025 | Phytomedicine | Experimental mechanistic study | DSS-induced colitis + 16S rRNA + transcriptomics + co-culture + FMT | Demonstrated that TXYF improved mucosal integrity, reshaped gut microbiota, and regulated IL-10RA/NF-κB-mediated macrophage polarization | 19 | |||||||
| INPLASY protocol | 2024 | INPLASY | Protocol | Meta-analysis + network pharmacology | Proposed integrating clinical-effect synthesis with mechanistic exploration for TXYF in UC | 20 | |||||||
Table 2: Representative core studies on Tongxie Yaofang for ulcerative colitis. This table lists selected, directly relevant TXYF-UC studies that illustrate major evidence roles, including foundational review, computational prediction, experimental validation, microbiota/multi-omics validation, disease progression extension, and clinical-mechanistic bridging; it is not the complete 133-record dataset.
Global research landscape and collaboration patterns
From a global research perspective, studies on Tongxie Yaofang for the treatment of ulcerative colitis have formed a relatively clear geographical concentration and collaborative network structure. However, the overall landscape still exhibits characteristics of "core country dominance, significant institutional clustering, and limited cross-regional in-depth collaboration."
Figure 3A illustrates the global distribution of publications and collaboration relationships after country/region normalization. China had the largest node size and the highest publication output in the WoSCC English-language corpus. Records from Taiwan, Hong Kong, and Macao were handled as China regional affiliation records for country-level statistics and should not be interpreted as independent country nodes (Figure 3B). The United States, South Korea, and several European countries formed smaller secondary nodes. Bubble size indicates publication output, whereas color indicates citation intensity; together, these features suggest differences in both productivity and citation impact across the mapped affiliation landscape.
At the institutional level, Figure 3C illustrates collaborative clustering characteristics across regional institutions. The institutional network exhibits distinct regional clustering patterns, with Guangdong, Beijing, Shanghai, and other provinces forming institution clusters represented by different colors. Notably, nodes from Guangzhou and Beijing institutions stand out prominently, indicating these regions' significant activity in research on Tongxieyao Formula for treating ulcerative colitis. Traditional Chinese Medicine (TCM) universities and their affiliated research platforms constitute the primary collaborative framework, highlighting the strong dependence of this research direction on TCM higher education and research institutions. Figure 3D further reveals the core-periphery structure of institutional collaboration networks. Guangzhou University of Chinese Medicine and Beijing University of Chinese Medicine occupy central positions with the largest node sizes and densest connections, serving not only as high-output institutions but also as key bridges for cross-regional cooperation. Institutions such as Shanghai University of Traditional Chinese Medicine form secondary hubs, collectively supporting the institutional network in this field.
Regarding author collaboration patterns, Figure 3E reveals distinct clustering characteristics in the field's author network. Multiple color-coded author subgroups form stable collaborative clusters around core researchers, indicating relatively tight internal team collaboration. However, connections between clusters remain limited, with numerous isolated or weakly connected author nodes distributed peripherally, suggesting insufficient cross-team, cross-institutional, and cross-regional collaboration. This phenomenon indicates that while several mature research teams have emerged in the field, overall collaboration remains localized rather than forming advanced, wide-area collaborative networks. Table 3 summarizes the distribution of directly relevant core records by document type, journal/source, and dominant method.
Journal distribution and knowledge base
Analysis of journal distribution and knowledge base reveals that research on Tongxieyao Formula for treating ulcerative colitis has established a relatively clear publication carrier structure and knowledge source spectrum. However, the overall landscape still exhibits characteristics of "dominance by traditional Chinese medicine and natural medicine journals, enhanced multidisciplinary integration, and continuous strengthening of mechanism-oriented knowledge foundations." The distribution of relevant journals, journal association structures, and knowledge base clustering is illustrated in Figure 4, while core knowledge literature and their thematic contributions are summarized in Table 42,14,15,16,18,19,20.
| Reference (first author, year) | Journal / Source | Research role in the field | Main thematic contribution | Reference number | |||||
| Chen, 2021 | Evidence-Based Complementary and Alternative Medicine | Foundational review | Framed TXYF as a classical prescription with potential anti-UC value and organized its constituent- and pathway-level evidence | 14 | |||||
| Zou, 2022 | Evidence-Based Complementary and Alternative Medicine | Early mechanism-prediction paper | Strengthened the multi-component, multi-target interpretation of TXYF in UC | 15 | |||||
| Zhang, 2022 | Phytomedicine | First-wave experimental validation | Linked TXYF to macrophage polarization and NF-κB/NLRP3-mediated inflammatory control in DSS colitis | 16 | |||||
| Liu, 2024 | Aging (Albany NY) | Updated pathway-focused mechanism study | Highlighted MAPK/AKT as a central signaling axis in TXYF-mediated anti-UC effects | 2 | |||||
| Xu, 2024 | Journal of Ethnopharmacology | Extension into carcinogenesis-related disease progression | Expanded TXYF research from inflammatory control to prevention of colitis-associated colorectal cancer via mitophagy | 18 | |||||
| Shang, 2025 | Phytomedicine | Advanced translational mechanistic study | Integrated microbiota profiling, transcriptomics, macrophage polarization, epithelial crosstalk, and FMT-based causality validation | 19 | |||||
| INPLASY protocol, 2024 | INPLASY | Clinical-mechanistic bridge | Signaled movement toward combining evidence synthesis with mechanism mining for TXYF in UC | 20 | |||||
Table 4: Core knowledge-base references and thematic contributions. This table summarizes representative co-cited or field-defining records and explains their roles in interpreting inflammatory mechanisms, providing evidence for TXYF interventions, advancing computational pharmacology, advancing microbiota/barrier research, and developing translational bridges.
Figure 4A summarizes the major source journals. The horizontal bar length represents publication count, the numeric value shown at the end of each bar represents total citations, and the colored square indicates the journal quartile category used in the figure. This clarification resolves the apparent inconsistency between the publication-count axis and the larger numeric labels. Overall, the field is concentrated in TCM, ethnopharmacology, complementary medicine, pharmacology, and integrative medicine journals.
Figure 4B reveals the disciplinary association structure between source journals from two perspectives. The left network diagram demonstrates that Phytomedicine and Journal of Ethnopharmacology exhibit larger node sizes and stronger connection intensities, indicating not only their high publication frequency but also their role as key knowledge dissemination hubs in this field. Frontiers in Pharmacology, Evidence-Based Complementary and Alternative Medicine, and several Chinese Medicine-related journals form secondary connections around core nodes, suggesting distinct multidisciplinary characteristics in this research direction, particularly linking Traditional Chinese Medicine, natural product pharmacology, integrative complementary medicine, and certain comprehensive medicine fields. The right string diagram further illustrates strong knowledge flow and citation coupling relationships among major journals, with the most pronounced interconnections observed between Phytomedicine, Journal of Ethnopharmacology, and Evidence-Based Complementary and Alternative Medicine. This reflects that academic exchanges and knowledge accumulation in this field primarily rely on these journal platforms.
Figure 4C further reveals the clustering structure of knowledge bases in this field. The figure demonstrates that current knowledge bases primarily focus on four interconnected yet distinct modules with their own focal points. The first module, UC inflammatory mechanisms, centers around the NF-κB/NLRP3 axis, connecting research nodes in immunology, mucosal biology, and inflammation-related studies, indicating that inflammatory responses and associated signaling pathways in ulcerative colitis constitute the most fundamental pathological knowledge source in this domain. The second module, TCM compound intervention evidence, takes TXYF and the network pharmacology framework as key nodes, reflecting that evidence supporting Paoxieyao Formula and traditional Chinese medicine compound interventions has formed a relatively independent research support system. The third module, gut microbiota and mucosal barrier, includes critical nodes such as FMT validation and tight-junction-related studies, suggesting that gut microbiota and mucosal barrier repair have become significant knowledge growth points in mechanistic research in recent years. The fourth is the network pharmacology methodology, where nodes such as computational prediction, molecular docking, and macrophage polarization are interconnected, indicating that the current methodological foundation in this field is expanding from traditional experimental validation to computational prediction and multi-level mechanism integration.
Table 4 further summarizes key references in this field and their thematic contributions to the knowledge base. The results indicate that core references primarily serve three functions: first, providing fundamental theoretical support for the inflammatory mechanisms, immune responses, and barrier damage in ulcerative colitis (UC); second, offering direct evidence for the therapeutic efficacy and action mechanisms of Tongxieyao Formula and other traditional Chinese medicine compound formulations in treating UC; and third, establishing methodological frameworks for network pharmacology, molecular docking, and multi-omics integrated analysis.
Research hotspots and temporal evolution
To further elucidate the core thematic structure and evolutionary trajectory of the study on Tongxieyao Formula in treating ulcerative colitis, this study constructed a hotspot identification framework based on keyword co-occurrence, temporal heat distribution, and emergence analysis, with results shown in Figure 5.
First, as shown in Figure 5A, the keyword co-occurrence network presents five distinct thematic clusters, forming a highly interconnected knowledge structure centered around the two core nodes of Tongxie Yaofang and ulcerative colitis. The first cluster is the inflammatory signaling cluster, with NF-κB as the core node, interconnected with keywords such as NLRP3, AKT, apoptosis, and macrophage polarization, indicating that inflammatory responses and their downstream signal transduction pathways constitute one of the most critical research axes in this field. The second cluster is the TCM clinical evidence cluster, primarily comprising terms related to RCTs, clinical efficacy, disease activity index, symptom scores, and TCM syndrome concepts such as "liver stagnation" and "spleen deficiency," demonstrating that this field retains strong characteristics of clinical efficacy evaluation and syndrome differentiation-based treatment. The third category is clustering of gut microbiota and metabolism, represented by gut microbiota, short-chain fatty acids (SCFA), 16S rRNA, tryptophan metabolism, and fecal microbiota transplantation, reflecting that microbial homeostasis and metabolic reprogramming have become one of the most active mechanistic hotspots in recent years. The fourth category is clustering of network pharmacology methods, including keywords such as network pharmacology, molecular docking, molecular dynamics, target prediction, and TCMSP, indicating that computational pharmacology methods have become an important technical pathway for elucidating the multi-component and multi-target action mechanisms of Tongxieyao Formula. The fifth category is clustering of mucosal barrier and immunity, encompassing keywords such as IL-10RA, tight junctions, epithelial barrier, intestinal permeability, and oxidative stress, demonstrating that immune regulation and mucosal barrier repair constitute critical intermediate links connecting inflammation control and microbial homeostasis.
From a temporal perspective, the keyword heat matrix in Figure 5B further reveals the activity levels and evolutionary processes of different topics across years. The results show that early high-frequency keywords were primarily concentrated on terms such as herbal formula, diarrhea, and spleen-stomach, indicating that the initial research phase focused more on classical prescription applications, symptom control, and TCM syndrome interpretation. Subsequently, keywords like network pharmacology, molecular docking, active ingredients, and target prediction gradually increased in prominence, suggesting a shift in research methodologies from traditional empirical summarization to multi-target prediction and mechanism exploration.
The keyword emergence analysis in Figure 5C reveals the phased characteristics of hotspot migration in this field from another perspective. Early emerging keywords primarily included herbal formulas, diarrhea, and spleen-stomach, highlighting the initial focus on TCM prescription applications and clinical symptom improvement. During the intermediate stage, emerging keywords shifted to network pharmacology, molecular docking, NF-κB, and inflammation, indicating a gradual transition in research emphasis toward multi-component-multi-target prediction and validation of classical inflammatory signaling pathways.
Comparative mapping of clinical evidence and mechanistic research
To further elucidate the structural differences and potential linkage pathways between 'clinical evidence flow' and 'mechanism research flow' in studies on the therapeutic effects of Tongxieyao Formula on ulcerative colitis, this study constructed a comparative knowledge mapping framework based on four dimensions: thematic comparison, evidence maturity, translational pathways, and temporal evolution.
Figure 6A compares thematic attention across six domains while distinguishing broad clinical reporting from mechanistic depth. Symptom control is mainly represented by PROs such as diarrhea, abdominal pain, stool frequency, global symptom improvement, quality of life, and TCM syndrome scores. Objective clinical targets, including endoscopic healing, histology, recurrence, inflammatory biomarkers, microbiota profiles, and epithelial-barrier markers, were less consistently integrated into the English-language corpus. In contrast, mechanistic studies showed stronger representation in inflammatory response, intestinal barrier repair, gut microbiota, and immune regulation, indicating a gap between biological hypothesis generation and standardized clinical endpoint testing.
Figure 6B's radar chart further comprehensively characterizes the two types of studies from the perspective of evidence maturity. The results demonstrate that the orange coverage generated by mechanism studies is generally larger than the blue coverage from clinical evidence studies, particularly showing stronger scalability across dimensions such as inflammatory response, gut microbiota, barrier repair, and immune regulation. This indicates that mechanism studies have achieved higher maturity in terms of thematic depth and methodological diversity.
From the perspective of transformation pathways, Figure 6C's dendrogram intuitively illustrates the connection strength between mechanistic research methods and clinical endpoints. The left side primarily includes mechanistic nodes such as network pharmacology, animal models, multi-omics/transcriptomics, and cellular validation, while the right side corresponds to clinical endpoints, including symptom improvement, inflammatory markers, recurrence control, quality of life, and mucosal healing. Most flow bands in the figure are relatively thin, with some pathways exhibiting weak connectivity, indicating limited evidence in current literature that can directly map mechanistic research findings to standardized clinical outcomes. Figure 6D demonstrates the research evolutionary characteristics of different thematic lines across early, intermediate, and recent stages from a temporal perspective. It is evident that the early stage is dominated by blue-colored clinical evidence studies, particularly in the themes of inflammatory pathways and gut microbiota, where foundational progress has been achieved. However, the overall focus remains on observational accumulation at the symptom and inflammation levels. During the mid-phase, the number of orange-colored mechanism research bubbles increased significantly, particularly showing rapid expansion in the areas of gut microbiota, barrier function, and immune regulation, indicating that this stage represents a critical period for accelerated development of mechanism research.
Further analysis of Table 5 reveals that it systematically summarizes the core differences between clinical evidence studies and mechanistic studies from a thematic domain-comparison perspective, along with their translational significance. The results indicate that clinical evidence studies provide more direct application-oriented guidance in aspects such as symptom control, disease activity/remission, and recurrence prevention, whereas mechanistic studies demonstrate more systematic explanatory capabilities in areas including inflammatory signaling, gut microbiota modulation, intestinal barrier repair, and immune cell regulation. The presentation in Table 5 does not merely offer parallel descriptions of the two study types but also highlights the logical chain between them that remains inadequately integrated: while basic research has progressively identified multiple potential target points and regulatory axes, these biological discoveries have yet to be widely incorporated into standardized clinical evaluation systems.
Concluding summary of results
In summary, the results show a rapidly growing but uneven TXYF-UC research landscape. China-centered institutions dominate output and collaboration, mechanistic studies have expanded strongly since 2020, and the knowledge base increasingly emphasizes inflammatory signaling, microbiota, barrier repair, and computational pharmacology. However, the clinical stream remains less standardized, especially in its limited separation of PROs from objective endoscopic, histologic, biomarker, and microbiota endpoints. The main evidence gap is therefore not simply a lack of mechanistic hypotheses, but the limited translation of these hypotheses into prospective, mechanism-informed clinical designs.
DATA AVAILABILITY:
The final raw and processed bibliometric datasets supporting the results of this study are publicly available in the Zenodo repository: https://zenodo.org/records/20810496.
Figure 1: Overall study workflow for bibliometric and clinical-mechanistic knowledge mapping. The diagram summarizes database retrieval, duplicate removal, title/abstract screening, full-text eligibility assessment, structured data extraction, thematic classification, bibliometric visualization, and synthesis of clinical-versus-mechanistic evidence. Please click here to view a larger version of this figure.
Figure 2: Annual publication trends and overall characteristics of studies on Tongxie Yaofang for ulcerative colitis. (A) Annual publication trends and cumulative growth of clinical evidence, mechanistic, and translational studies. (B) Proportional distribution of study categories and internal composition of mechanistic research. (C) Temporal bubble matrix of major research approaches across early, middle, and recent stages. Please click here to view a larger version of this figure.
Figure 3: Global distribution and collaboration network of countries/regions, institutions, and authors in research on Tongxie Yaofang for ulcerative colitis. (A) Normalized country/region map of publication distribution, citation intensity, and collaboration links; Taiwan, Hong Kong, and Macao affiliation records are treated as China regional records for country-level interpretation. (B) Country/region collaboration network. (C) Regional institutional collaboration clusters. (D) Core institutional co-authorship network. (E) Author collaboration network. Please click here to view a larger version of this figure.
Figure 4: Journal landscape and co-citation knowledge base of studies on Tongxie Yaofang for ulcerative colitis. (A) Major source journals; bar length indicates publication count, numeric labels indicate total citations, and colored squares indicate journal quartile. (B) Journal association and citation-coupling structure across TCM, phytomedicine, ethnopharmacology, complementary medicine, pharmacology, and gastroenterology-related outlets. (C) Co-citation knowledge-base modules, including UC inflammatory mechanisms, TCM compound intervention evidence, gut microbiota and mucosal barrier research, and network-pharmacology methodology. Please click here to view a larger version of this figure.
Figure 5: Keyword co-occurrence, thematic clustering, and temporal evolution of research hotspots. (A) Keyword co-occurrence network showing five major thematic clusters in the field. (B) Temporal heatmap of keyword frequency across publication years. (C) Burst-keyword analysis showing the staged evolution of emerging research frontiers. Please click here to view a larger version of this figure.
Figure 6: Comparative knowledge mapping of clinical evidence and mechanistic research in Tongxie Yaofang for ulcerative colitis. (A) Dumbbell plot comparing relative thematic attention between clinical evidence studies and mechanistic research across six core domains. (B) Radar chart showing comparative maturity profiles of clinical evidence and mechanistic research. (C) Sankey diagram illustrating translational linkage between mechanistic methods and clinical outcome endpoints. (D) Temporal bubble matrix showing the stage-wise evolution of thematic emphasis and the persistent clinical translation gap. Please click here to view a larger version of this figure.
| Item | Specification |
| Database | Web of Science Core Collection (WoSCC) |
| Search field | Topic search (TS) |
| Time span | From database inception to December 31, 2025 |
| Core search string | TS = ((“Tongxie Yaofang” OR “Tong Xie Yao Fang” OR “Tongxie-Yaofang” OR “Tongxie formula” OR “TXYF”) AND (“ulcerative colitis” OR “UC”)) |
| Language restriction | English |
| Document types | Article; Review |
| Indexing scope | SCI-Expanded and related WoSCC collections as available |
| Inclusion criteria | Studies explicitly focusing on Tongxie Yaofang and ulcerative colitis; bibliographic records with sufficient metadata for bibliometric analysis; English-language articles or reviews |
| Exclusion criteria | Duplicates; conference abstracts; editorials; letters; corrections; records unrelated to TXYF or UC; articles without usable bibliographic information |
| Data extraction fields | Title, authors, year, journal, country/region, institution, keywords, abstract, citations, and study category |
| Thematic classification | Clinical evidence studies; mechanistic studies; translational/bridge studies |
| Analysis tools | Microsoft Excel, VOSviewer, CiteSpace |
| Main outputs | Publication trends, collaboration networks, journal landscape, co-citation structure, keyword hotspots, and comparative mapping of clinical vs mechanistic themes |
Table 1: Search strategy, data source, and eligibility criteria for the bibliometric analysis. This table reports the WoSCC source, exact topic-search query, search time span, language, and document-type restrictions, inclusion/exclusion criteria, extracted fields, classification framework, analysis tools, and main outputs.
| Category | Item | Count |
| By document type | Mechanistic original studies | 5 |
| Review articles | 1 | |
| Protocol / study-registration record | 1 | |
| Translational multi-omics / microbiota-oriented studies | 1 | |
| By journal / source | Phytomedicine | 2 |
| Evidence-Based Complementary and Alternative Medicine | 2 | |
| Aging (Albany NY) | 1 | |
| Medicine | 1 | |
| Journal of Ethnopharmacology | 1 | |
| INPLASY | 1 | |
| By dominant methodological orientation | Network pharmacology / docking / dynamics | 4 |
| Animal or disease-model validation | 3 | |
| Multi-omics / microbiota / FMT validation | 1 | |
| Clinical-effect synthesis protocol | 1 |
Table 3: Quantitative summary of document types, journal sources, and methodological orientation. Counts summarize the distribution of directly relevant core records by document type, journal/source, and dominant method, including network pharmacology, animal/disease-model validation, multi-omics/microbiota/FMT validation, and clinical-effect synthesis protocol work.
| Domain | Clinical evidence stream | Mechanistic research stream | Translational implication |
| Symptom control | Usually discussed in terms of diarrhea relief, abdominal pain reduction, and overall clinical improvement | Supported indirectly by anti-inflammatory, barrier-protective, and microbiota-modulating effects | Symptom-level outcomes should be linked to validated biologic markers in future trials |
| Inflammatory response | Commonly reported as reduced disease activity or improved inflammatory indices in review/protocol-level synthesis | NF-κB/NLRP3, MAPK/AKT, and IL-10RA/NF-κB are recurrent signaling axes | Mechanistic biomarkers can be embedded into prospective clinical trial endpoints |
| Intestinal barrier repair | Clinically relevant but insufficiently standardized in openly retrievable English studies | Tight-junction protection, epithelial integrity restoration, and immune–epithelial crosstalk are repeatedly emphasized | Barrier-function indicators should be paired with endoscopic or histologic outcomes |
| Gut microbiota | Mentioned as a plausible therapeutic direction in integrated evidence synthesis | Strongly highlighted in recent mechanistic work, especially microbiota remodeling, SCFA-related taxa, and FMT validation | Microbiota profiles may become key translational readouts in TXYF-based UC studies |
| Immune regulation | Clinical reporting remains broad and mostly nonspecific | Macrophage polarization, cytokine regulation, and IL-10RA-dependent signaling are prominent | Immunophenotyping could improve mechanistic interpretability of clinical benefit |
| Disease progression | Clinical recurrence prevention is discussed more often than hard progression endpoints | Newer studies extend from colitis control to colitis-associated colorectal cancer prevention and mitophagy regulation | Future work should examine whether TXYF modifies long-term mucosal healing and carcinogenesis risk |
| Evidence structure | Dedicated English-language UC clinical trials appear sparse in the openly retrievable corpus | Mechanistic and preclinical studies dominate the visible English literature | The field needs better balance between high-quality clinical evidence and deep mechanistic validation |
Table 5: Comparative framework of clinical evidence and mechanistic themes. This table contrasts clinical and mechanistic research streams across symptom control, inflammatory response, intestinal barrier repair, gut microbiota, immune regulation, disease progression, and evidence structure, and highlights translational implications for future mechanism-informed trials.
Discussion
This study provides a structured map of the English-language WoSCC literature on TXYF for UC and shows that the field has expanded rapidly since 2020. The mapped corpus is China-led, institutionally concentrated, and increasingly mechanism-oriented. Clinical evidence remains visible but comparatively less standardized, whereas mechanistic work has become denser around NF-kB/NLRP3, MAPK/AKT, IL-10RA/NF-kB signaling, microbiota remodeling, epithelial-barrier protection, macrophage polarization, mitophagy, and computational pharmacology2,14,15,16,17,18,19,20,21,22,23,24,25. The central finding is therefore a translational disconnect: biological hypotheses are abundant, but they are not yet routinely tested through prospective clinical designs with predefined objective endpoints.
For clinical practice, the findings should be interpreted cautiously. The English-language WoSCC corpus does not capture the full Chinese-language clinical literature indexed in CNKI, Wanfang, SinoMed, or other regional databases, and therefore cannot be used alone to conclude that clinical exploration of TXYF is absent. Instead, it indicates that internationally indexed English reports provide limited standardized clinical endpoint evidence. Future clinical TXYF studies should separate PROs, such as diarrhea, abdominal pain, stool frequency, quality of life, and TCM syndrome scores, from objective targets such as Mayo score components, endoscopic healing, histologic activity, fecal calprotectin, C-reactive protein, cytokines, microbiota profiles, and epithelial-barrier markers.
Future research should move from parallel clinical and preclinical streams toward a mechanism-to-clinic roadmap. A mechanistically driven clinical trial could enroll patients using standardized UC activity criteria, stratify participants by disease extent and prior therapy, record TXYF formulation and dose transparently, and define co-primary or hierarchical endpoints that pair PRO improvement with endoscopic, histologic, and biomarker outcomes. Mechanistic substudy modules could prospectively test NF-kB/NLRP3, MAPK/AKT, IL-10RA/NF-kB, macrophage polarization, tight-junction proteins, short-chain fatty-acid-related taxa, and microbiota-derived metabolites. This design would allow mechanistic signals to be evaluated as predictors, mediators, or pharmacodynamic readouts rather than post hoc explanations.
A second priority is to critically appraise the current dependence on network pharmacology, molecular docking, and target prediction. These approaches can generate useful hypotheses for multi-component formulas, but purely in silico predictions may produce false-positive target-pathway associations when not supported by dose-relevant exposure data, perturbation experiments, validated disease models, or causal microbiota transfer. The field should therefore reduce the need for repetitive virtual screening studies and prioritize experimentally validated multi-omics, organoid, or cell culture validation, animal model causality tests, and fecal microbiota transplantation designs linked to clinical endpoints.
Prior reviews and mechanism-focused studies have summarized TXYF as a classical prescription with potential anti-UC effects and have proposed multi-target actions involving inflammatory signaling, microbiota, barrier repair, macrophage polarization, and mitophagy14,15,16,17,18,19,20,26,27,28. This bibliometric analysis extends those narrative and experimental contributions by showing how these topics are organized across journals, collaborations, keyword clusters, co-citation modules, and temporal trends. Compared with general bibliometric work on TCM for inflammatory bowel disease26, the present analysis narrows the focus to TXYF and explicitly contrasts clinical evidence with mechanistic research.
The strengths of this study include a reproducible WoSCC search strategy, explicit inclusion/exclusion criteria, operational classification of clinical, mechanistic, and translational records, and a revised endpoint-coding framework that separates PROs from objective clinical and biological endpoints. Several limitations remain. The analysis was restricted to English-language WoSCC records; Chinese-language databases such as CNKI, Wanfang, and SinoMed were not included, which may underrepresent RCTs, observational studies, and real-world evidence conducted in China. Bibliometric maps reflect metadata quality and indexing practices, and they do not replace formal risk-of-bias assessment, meta-analysis, or experimental validation.
Disclosures
The authors have nothing to disclose.
Acknowledgements
The authors sincerely thank the Department of Pharmacy at Dongtai People's Hospital for providing institutional support and an academic environment for this bibliometric work. The authors also thank colleagues who assisted with literature retrieval, data checking, and manuscript discussion. No specific external funding or grant support was reported for this study.
Materials
| Name | Company | Catalog Number | Comments |
|---|---|---|---|
| CiteSpace | Chaomei Chen, Drexel University | https://citespace.podia.com/ | Co-citation analysis, cluster analysis, timeline visualization, and burst keyword detection. |
| Microsoft Excel | Microsoft Corporation | https://www.microsoft.com/en-in/microsoft-365/Excel | Data cleaning, duplicate checking, descriptive statistics, annual publication counts, research-type classification, and table preparation. |
| VOSviewer | Centre for Science and Technology Studies, Leiden University | https://www.vosviewer.com/ | Construction and visualization of author, institution, country, journal, and keyword co-occurrence networks. |
| Web of Science Core Collection | Clarivate Analytics | https://clarivate.com/academia-government/scientific-and-academic-research/research-discovery-and-referencing/web-of-science/web-of-science-core-collection/ | Primary bibliographic database used to retrieve English-language articles and reviews on Tongxie Yaofang and ulcerative colitis. |
References
- Zhang A, et al. Emerging insights into inflammatory bowel disease from the intestinal microbiota perspective: A bibliometric analysis. Front Immunol. 2023;14:1264705.
- Liu X, et al. Investigation of Tongxie-Yaofang formula in treating ulcerative colitis based on network pharmacology via regulating MAPK/AKT signaling pathway. Aging (Albany NY). 2024;16(2):1911-1924.
- Yang Y, Liu Z, Lyu H. Traditional Chinese medicine-induced treatment in colitis-associated colorectal cancer. Chin Med J. 2023;136(10):1249-1250.
- Allegretti JR, Bordeianou LG, Damas OM. Challenges in IBD research 2024: Pragmatic clinical research. Inflamm Bowel Dis. 2024;30(Suppl 2):S55-S66.
- Hao WR, Cheng CY, Cheng TH. Enhancing ulcerative colitis treatment with traditional Chinese medicine. World J Clin Cases. 2024;12(30):6358-6360.
- Hu Y, Chen LL, Ye Z. Indigo naturalis as a potential drug in the treatment of ulcerative colitis: A comprehensive review of current evidence. Pharm Biol. 2024;62(1):818-832.
- Li J, Dan W, Zhang C. Exploration of berberine against ulcerative colitis via TLR4/NF-kB/HIF-1alpha pathway by bioinformatics and experimental validation. Drug Des Devel Ther. 2024;18:2847-2868.
- Wang Y, et al. Ferroptosis: A new mechanism of traditional Chinese medicine for treating ulcerative colitis. Front Pharmacol. 2024;15:1379058.
- Liang Y, et al. Ulcerative colitis: Molecular insights and intervention therapy. Mol Biomed. 2024;5(1):42.
- Zhao ZH, Dong YH, Jiang XQ. Five commonly used traditional Chinese medicine formulas in the treatment of ulcerative colitis: A network meta-analysis. World J Clin Cases. 2024;12(22):5067-5082.
- Wang T, Liu X, Zhang W. Traditional Chinese medicine treats ulcerative colitis by regulating gut microbiota, signaling pathway and cytokine: Future novel method option for pharmacotherapy. Heliyon. 2024;10(6):e27530.
- Ekstedt N, Jamiol-Milc D, Pieczynska J. Importance of gut microbiota in patients with inflammatory bowel disease. Nutrients. 2024;16(13):2092.
- Qu F, Xu B, Kang H. The role of macrophage polarization in ulcerative colitis and its treatment. Microb Pathog. 2025;199:107227.
- Chen Z, et al. Tong Xie Yao Fang: A classic Chinese medicine prescription with potential for the treatment of ulcerative colitis. Evid Based Complement Alternat Med. 2021;2021:5512220.
- Zou H, et al. Exploring the molecular mechanism of Tong Xie Yao Fang in treating ulcerative colitis using network pharmacology and molecular docking. Evid Based Complement Alternat Med. 2022;2022:9038222.
- Zhang Y, et al. Tongxie-Yaofang formula regulated macrophage polarization to ameliorate DSS-induced colitis via NF-kB/NLRP3 signaling pathway. Phytomedicine. 2022;106:154432.
- Tang L, Liu Y, Tao H, Feng W, Ren C. Network pharmacology integrated with molecular docking and molecular dynamics simulations to explore the mechanism of Tongxie Yaofang in the treatment of ulcerative colitis. Medicine (Baltimore). 2024;103(36):e39569.
- Xu Z, et al. Tong-Xie-Yao-Fang induces mitophagy in colonic epithelial cells to inhibit colitis-associated colorectal cancer. J Ethnopharmacol. 2024;334:118541.
- Shang Z, Zhou L, Liu Y, Yi B. Tongxie Yaofang attenuates ulcerative colitis by modulating gut microbiota and IL-10RA/NF-kB-mediated macrophage polarization. Phytomedicine. 2025;148:157459.
- INPLASY. Protocol record for meta-analysis and network pharmacology related to Tongxie Yaofang and ulcerative colitis. INPLASY. 2024;20240001.
- Chen B, Dong X, Zhang JL. Natural compounds target programmed cell death signaling mechanism to treat ulcerative colitis: A review. Front Pharmacol. 2024;15:1333657.
- Guo J, Li L, Cai Y. Correction: The development of probiotics and prebiotics therapy to ulcerative colitis: A therapy that has gained considerable momentum. Cell Commun Signal. 2024;22:294.
- Wang X, Peng J, Cai P. The emerging role of the gut microbiota and its application in inflammatory bowel disease. Biomed Pharmacother. 2024;179:117302.
- Zhang W, Zou M, Fu J, Xu Y, Zhu Y. Autophagy: A potential target for natural products in the treatment of ulcerative colitis. Biomed Pharmacother. 2024;176:116891.
- Chen S, et al. Macrophages: Emerging targets for ulcerative colitis. Front Immunol. 2025;16:1623491.
- Wang J, Chen X, Yuan M. Bibliometric analysis of traditional Chinese medicine in the treatment of inflammatory bowel disease. Allergol Immunopathol. 2024;52(3):31-41.
- Meade S, et al. Gut microbiome-associated predictors as biomarkers of response to advanced therapies in inflammatory bowel disease: A systematic review. Gut Microbes. 2023;15(2):2287073.
- Wang C, et al. Gut microbiota and metabolites as predictors of biologics response in inflammatory bowel disease: A comprehensive systematic review. Microbiol Res. 2024;282:127660.