A subscription to JoVE is required to view this content. Sign in or start your free trial.

Method Article

Chinese Medicine Enemas for Ulcerative Colitis: Mechanisms and Optimal Duration from a Systematic Review and Meta-Analysis

155 views

⸱

DOI:

10.3791/69567

⸱

May 29th, 2026

 ,  , 
1The Affiliated Hospital of Nanjing University of Chinese Medicine

In This Article

Summary

This meta-analysis of 20 animal studies (980 subjects) shows compound Chinese medicine enemas significantly improve ulcerative colitis indicators via anti-inflammation, intestinal barrier enhancement, and gut microbiota modulation. Optimal duration: 10–28 days. Despite promising results, high heterogeneity and low study quality urge caution; high-quality trials are needed for validation.

Abstract

This systematic review and meta-analysis aimed to elucidate the mechanisms underlying the efficacy of Chinese medicine enema formulations in animal models of ulcerative colitis (UC) and to provide a scientific basis for their potential clinical application. Comprehensive searches of PubMed, Web of Science, Cochrane Library, Elton B. Stephens Company (EBSCO), and ScienceDirect identified relevant animal studies published up to December 2024. Methodological quality was assessed using the SYRCLE risk of bias tool, and statistical analyses were conducted with RevMan 5.3 and Stata 15.

Twenty studies comprising 980 animals were included, with quality scores ranging from 2 to 6. Chinese medicine enemas significantly reduced histological colitis score, disease activity index, spleen index, colon damage score, and inflammatory mediators including IL-6, TNF-α, IL-1β, IL-8, COX-2 mRNA, and myeloperoxidase. They also improved body weight change, colon length, intestinal tight junction proteins (ZO-1, Occludin), IL-10 expression, and regulatory T-cell levels (CD4⁺CD25⁺FOXP3⁺), while modulating gut microbiota composition, particularly Firmicutes and Bacteroides.

These findings suggest that the therapeutic benefits of Chinese medicine enemas may derive from anti-inflammatory activity, enhancement of intestinal barrier integrity, and regulation of gut flora. However, substantial heterogeneity—likely due to differences in animal species, sex, and intervention duration—and generally low methodological quality limit the strength of the evidence. Further well-designed, high-quality preclinical and clinical studies are warranted to confirm efficacy, optimize treatment protocols, and evaluate safety for human application.

Introduction

Inflammatory bowel disease (IBD) comprises two primary types: ulcerative colitis (UC) and Crohn's disease (CD). Research indicates that genetics, environmental factors, microbial interactions, and immune dysregulation are involved in the pathogenesis of IBD1. Emerging evidence suggests an increasing incidence of IBD in developing countries2. UC is characterized by recurrent episodes of abdominal pain, diarrhea, and rectal bleeding3. Improvement of clinical symptoms and reduction of recurrence in UC patients are crucial objectives in clinical management4.

Conventional IBD therapies, including corticosteroids, immunosuppressants, and biologics, aim to control immune responses; however, long-term use is associated with significant adverse effects5. Numerous new therapeutic options have emerged in recent years. Studies suggest that topical treatments are efficient, safe, and have fewer side effects. Their advantages include faster response, reduced dosing frequency, and limited systemic absorption compared to oral treatments. Nevertheless, the number of patients receiving topical treatments remains lower than those receiving oral therapies6.

Traditional Chinese Medicine (TCM) is widely used as an effective complementary and alternative treatment for IBD, particularly in patients who have experienced adverse reactions to conventional therapies. Despite its significant therapeutic potential, the clinical application of TCM is limited by insufficient research on its mechanisms of action7.

Although numerous animal studies have reported the therapeutic effects of compound Chinese medicine enemas on UC, no meta-analysis, which has become an essential tool in evidence-based medicine for establishing the efficacy and safety of interventions8, has yet synthesized evidence of its therapeutic effectiveness from preclinical studies. Therefore, this study systematically reviewed animal experiments to evaluate the therapeutic effectiveness of compound Chinese medicine enemas. The focus was on the effects of compound Chinese medicine enemas on HCS, DAI, IL-6, TNF-α, and intestinal flora in UC animal models, aiming to inform future clinical trials and product development. This study aims to provide robust evidence-based support for the clinical application of compound Chinese medicine enemas.

This meta-analysis focuses on rodent models (primarily Sprague-Dawley rats and C57BL/6 mice) induced by dextrose sodium sulphate or 2,4,6-Trinitrobenzenesulfonic acid solution, with intervention durations of 3–28 days, assessing key domains like histological scores (Histological Score/Disease Activity Index), inflammatory cytokines (IL-6/TNF-α), barrier proteins (ZO-1/Occludin), and gut microbiota. While providing mechanistic insights for TCM enema applications, limitations such as study heterogeneity and low methodological quality (SYRCLE scores 2–6) are addressed in the Discussion to guide cautious clinical translation. A detailed glossary of abbreviations used in this article is provided in Supplementary File 1 (Data 1).

Access restricted. Please log in or start a trial to view this content.

Protocol

All included animal studies adhered to the ARRIVE guidelines and had been approved by their respective institutional ethics committees. Blinding and randomization conducted in accordance with the SYRCLE guidelines. The review complied with PRISMA reporting standards (ID: CRD42024527636). All procedures were performed under ethical clearance to minimize bias and animal harm.

1. Software installation and preparation

  1.  Install RevMan (version 5.3, Cochrane Collaboration, https://revman.cochrane.org).
    1. Access the RevMan official website (see Table of Materials).
    2. Download the setup file compatible with the operating system (Windows .exe or Mac .pkg).
    3. Double-click the installer and follow the prompts: Next > select installation path > Next > Finish.
    4. Launch RevMan and select File > New Review > Intervention Review > Full Review.
  2.  Stata software
    1. Go to the official Stata website (see Table of Materials) and navigate to the download page.
    2. Download the installer package compatible with your operating system.
    3. Double-click the installer and follow the prompts: Next > accept license > choose installation path > Install > Finish.
    4. Launch Stata and enter the serial number, code, and authorization to activate the license.
  3.  EndNote X9 reference management software
    1. Visit the official EndNote website (see Table of Materials).
    2. Download the EndNote X9 installer for your operating system.
    3. Double-click the installer, accept license > select Typical installation > choose installation path > Install > Finish.
    4. Launch EndNote and activate with your product key or institutional credentials.
  4.  GetData graph digitizer
    1. Visit the GetData Graph Digitizer official website (see Table of Materials).
    2. Download the installer.
    3. Double-click the installer, accept license > choose installation path > Install > Finish.
    4. Launch the software to extract numerical data from figures when raw data are unavailable.
      1. Import the image of the figure into the software.
      2. Calibrate the X- and Y-axes using the scale provided in the figure.
      3. Manually mark each data point to obtain its coordinate values.
      4. Export the extracted numerical data.
      5. Cross-validate the extracted data by two independent researchers; discrepancies greater than 5% were rechecked and corrected.
        NOTE: Installation and activation of all software should be completed prior to the literature processing step to ensure seamless workflow.

2. Literature search

  1. Create the retrieval strategy.
    1. Determine search terms by first reviewing the study's objectives and key outcomes. Identify the core concepts related to ulcerative colitis, Chinese medicine enemas, and animal models.
      1. For ulcerative colitis, use terms such as "ulcerative colitis," "IBD," and "inflammatory bowel disease."
      2. For Chinese medicine enemas, include keywords like "Chinese medicine enema," "traditional Chinese medicine enema," "compound prescription enema," and related synonyms.
      3. For animal models, use terms like "rat," "mouse," "rodent," and "animal study." Combine these terms using Boolean operators (AND, OR). For example, combine “ulcerative colitis” AND “Chinese medicine enema” AND “animal model” to capture studies that meet all criteria. Adjust the search terms according to the database being used, utilizing each database’s controlled vocabulary.
      4. Refine the search by including synonyms or alternative phrases to increase the sensitivity of the search.
    2. For the detailed retrieval strategy for each database, refer to Supplementary File 1 (Data 2).
  2. Perform a literature search on five databases: PubMed, Web of Science, Cochrane Library, EBSCO, and ScienceDirect.
    1. For each database, access the official website (e.g., https://pubmed.ncbi.nlm.nih.gov for PubMed). In the search interface, enter the predefined search strategy into the Advanced Search field. For PubMed, click Advanced > Add Query Builder, then fill in the search boxes as follows:
      Field 1: “ulcerative colitis” [Title/Abstract]
      Field 2: “Chinese medicine enema” OR “traditional Chinese medicine enema” [Title/Abstract]
      Field 3: “animal experiment” OR “rat” OR “mouse” [All Fields]
    2. Combine these fields with the Boolean operator AND to ensure all conditions are met. Set the time limit from database inception to December 1, 2024, and restrict the language to English. Click Search, then use Filters > Article type > Preclinical Studies where applicable.
    3. Export all retrieved records by selecting Send to > File > Format: MEDLINE (for PubMed) or Export > RIS/BibTeX (for other databases). Save the files for import into EndNote X9 for further screening and duplicate removal.
      NOTE: Two independent reviewers performed the search using identical criteria, and discrepancies were resolved by consensus (see Table of Materials). Take PubMed as an example:
      1. Open the PubMed database website.
      2. Enter the predefined retrieval strategy according to PubMed syntax rules (see Data 2 in Supplementary File 1 for full details).

        NOTE: The operator AND requires all connected keywords to be present in the record. The operator OR means at least one of the listed keywords must be present. Parentheses () define the order of logical operations. Set the search time limit from database inception to December 1, 2024.
      3. Download all retrieved literature: Save > PubMed > Create file.

3. Literature screening

NOTE: Take PubMed retrieved data as an example, managed using EndNote X9.

  1.  Import the retrieved literature into EndNote: File > Import > Options > Import Options > select PubMed (NLM) > Import (Data 2 in Supplementary File 1).
  2.  Create inclusion and exclusion groups in EndNote: My Groups > Create group set or Create group (Data 4 in Supplementary File 1).
    Exclusion groups may include:
    Inappropriate intervention (not Chinese medicine enema)
    Inappropriate subjects (non-UC models, or clinical/in vitro studies)
    Duplicate publications
    Language other than English
  3. Remove duplicates: Go to All References > References > Find Duplicates > Cancel. Select all duplicate entries in the results list, drag them to the left Trash folder for deletion. After automatic duplicate removal, manually check again to ensure no duplicates remain (Data 5 in Supplementary File 1).
  4.  Screening process: In the first round, read titles and abstracts to exclude studies that do not meet the inclusion criteria. In the second round, review the full texts of the remaining studies to confirm their final eligibility.
  5.  Manual search and author contact: Perform manual retrieval of references cited in the included studies. Contact corresponding authors by email when relevant data are missing or unclear, to increase inclusion rate and reduce uncertainty.
  6.  Researcher involvement: Perform literature search and screening with two independent researchers. Resolve disagreements through discussion. If unresolved, consult a third researcher for the final decision.
  7. Documenting the process: Use Microsoft Word or relevant software to create a PRISMA 2020 flow diagram documenting the number of studies retrieved and excluded at each stage, along with reasons for exclusion (see Supplementary File 2).

4. Data extraction

  1. Prepare a spreadsheet that includes the following variables:
    Study information: Author, year of publication.
    Animal details: Species, strain, sex, weight range, and sample size.
    Model induction method: Specify whether DSS, TNBS, or other approaches were used.
    Intervention details: Dose or concentration, administration frequency, and duration.
    Outcomes measured: Include histological colitis score (HCS), disease activity index (DAI), colon length (CL), body weight change (BWC), spleen index, inflammatory cytokines, intestinal barrier proteins, and microbiota composition, among others. The standardized data extraction format is detailed in Data 6 in Supplementary File 1.
  2. For multiple intervention doses, extract highest-dose group data by identifying, within each included study, the experimental subgroup that received the maximum dose of the compound Chinese medicine enema.
    1. When multiple dosage levels were reported, record data corresponding to the highest concentration or dose, as stated in the methods or results section of the original article.
    2. If the unit or concentration was unclear, verify the dose hierarchy based on the authors’ descriptions or tables. Two independent reviewers cross-checked the extracted data, and any discrepancies were resolved through discussion.
  3. For outcomes measured at multiple time points, record final measurement by identifying, in each included study, the last time point at which the outcome was assessed after the intervention.
    1. When multiple time points were reported, extract data from the final post-treatment observation to reflect the overall therapeutic effect.
    2. If multiple endpoints were presented in tables or figures, use the value corresponding to the last reported measurement period. Two independent reviewers verified the extracted time points to ensure accuracy and consistency.
  4. Enter the formula =SEM_value × SQRT (sample_size) in a new cell to convert the standard error of the mean (SEM) to the standard deviation (SD). Copy the resulting SD values into the RevMan data table. Verify accuracy by recalculating the conversion for one representative study9.
  5. Convert medians and quartiles to means and SDs as required10,11.
  6. Have two reviewers extract data independently; resolve any discrepancies through discussion.
    NOTE: Data from figures are digitized with GetData Graph Digitizer when raw values are not provided.

5. Risk of bias assessment

  1. Use the SYRCLE risk of bias tool12 to assess study quality across ten domains, including randomization, allocation concealment, blinding, and outcome reporting.
  2. Rate each item as low, high, or unclear risk, and summarize results in RevMan. For each domain, review methods section—assign low if randomization stated, high if not, unclear if vague. Tally scores (0–10) in RevMan table.

6. Statistical analysis

  1. Start the meta-analysis in RevMan 5.3.
    1. In the main menu, go to Data and analyses > Add Comparison.
    2. Enter the name of the experimental group (e.g., “enema”) and the control group (e.g., “ulcerative colitis”) > click Finish (Data 7 in Supplementary File 1).
    3. To add the outcome indicators, select Add Outcome, choose the variable type (Continuous for continuous variables or Dichotomous for dichotomous variables), click Next, enter the name of the outcome indicator (e.g., “Histopathological score (HCS)”, “Disease activity index (DAI)”, “Colon length (CL)”, “Body weight change (BWC)”), and then click Finish (Data 8 in Supplementary File 1).
    4.  Add study data: Add Study Data > select the reference from the included literature list > Finish (Data 9 and Data 10 in Supplementary File 1).
    5. For each outcome, manually enter the extracted data (mean, standard deviation (SD), and sample size for each group) into the data table.
  2. Perform statistical model selection.
    1. For continuous outcomes, use Mean Difference (MD) when the unit of measurement is the same across all included studies. Use Standardized Mean Difference (SMD) when measurement units differ between studies.
    2. Set 95% confidence intervals (CI) for all effect size estimates. Select the statistical model as follows: Use a fixed-effect (FE) model if heterogeneity is low (I2 ≤ 50%). Use a random-effects (RE) model if heterogeneity is high (I2 > 50%).
      NOTE: In this analysis, apply the random-effects model due to variations in species, modeling, and regimens.
  3. Generate forest plots.
    1. In RevMan, after entering all relevant data, click Statistical Model (FE or RE as determined above) > Forest Plot.
    2. Review the plot for effect size estimates, heterogeneity statistics (I2, χ2 test), and overall P values (see Data 11 in Supplementary File 1).
  4. Perform advanced analyses and publication bias assessment in Stata 15.0.
    1. Import the aggregated effect size and standard error (or variance) into Stata.
    2. For publication bias, run Egger’s regression test via the command: metabias effect_size se_effect, egger
    3. Generate funnel plots using: metafunnel effect_size se_effect
    4. For potential missing studies, apply the trim-and-fill method in Stata 15.0 by entering the command: metatrim effect_size se_effect, egger This function estimates the number of potentially missing studies caused by publication bias, fills the funnel plot symmetrically, and recalculates the pooled effect size to provide an adjusted estimate.
    5. For meta-regression or subgroup analyses (if required): metareg effect_size var1 var2
  5. Perform subgroup and sensitivity analyses.
    1. Create subgroups in RevMan 5.3 by selecting Data and Analyses > Add Subgroup Analysis, then define subgroup categories according to Animal species (mouse, rat), Sex (male, female, unknown) Treatment duration (≤7 days, >7 days).
    2. Enter the corresponding study data into each subgroup to compare pooled effect sizes and evaluate heterogeneity reduction. For sensitivity analysis, re-run the meta-analysis, excluding one study at a time.
  6. Perform publication bias assessment.
    1. Conduct Egger’s regression test for datasets with ≥ 10 studies.
    2. Apply Trim-and-fill method to estimate potential missing studies and adjust pooled estimates.
  7. Perform duration-effect analysis.
    1. Classify included studies based on intervention length (days).
    2. For each key outcome (HCS, DAI, CL, BWC, MPO, TNF-α, IL-6, etc.), plot duration-response radar charts.
    3. Identify optimal treatment window for Chinese medicine enema in UC animal models.
      NOTE: With all analyses complete, compile results into RevMan forest plots and Stata outputs. The extracted data were entered into RevMan 5.3 to generate forest plots. The software automatically calculated pooled effect sizes (MD/SMD) and confidence intervals (95% CI) under fixed- or random-effects models, producing visual forest plots for each outcome. For Stata, the effect size and standard error were imported. Publication bias and advanced analyses were performed. Proceed to manuscript reporting per PRISMA, ensuring ethical compliance and bias checks. This concludes the meta-analysis protocol for TCM enema UC evaluation.

Access restricted. Please log in or start a trial to view this content.

Results

A total of 1,146 potentially relevant articles were identified from five databases, comprising 65 from PubMed, 92 from Web of Science, 56 from EBSCO, none from the Cochrane Library, and 933 from Science Direct. After the removal of 91 duplicate records, 1,055 articles remained.

Subsequently, the full texts of these articles were reviewed, resulting in the exclusion of 1,035 articles based on the predefined exclusion criteria. Ultimately, twenty studies met the eligibility criteria and were inc...

Access restricted. Please log in or start a trial to view this content.

Discussion

This study aimed to investigate the protective effects and underlying mechanisms of compound Chinese medicine enema in animal models of ulcerative colitis. A total of 20 papers involving 980 animals were included. The compound Chinese medicine enema was found to improve several clinical symptoms of ulcerative colitis, including colon length, disease activity index, histological colitis score, body weight change, spleen index, and colon damage score. Moreover, the enema demonstrated modulation of various inflammatory mark...

Access restricted. Please log in or start a trial to view this content.

Disclosures

All authors declare that they have no conflicts of interest related to this work.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 82341229, Grant No. 82174379, Grant No. 82174372 and Grant No. 82405401), Chinese Medicine Treatment of Dominant Diseases (Clinical Evidence-based Competence Enhancement) Foundation (No: k2023BZ02), the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), Jiangsu Province Capability Improvement Project through Science, Technology and Education, the Scientific Research Project of Jiangsu Association of Chinese Medicine (No: PDJH2026013), and the High-level Academic Talents Cultivation Project of Jiangsu Province Hospital of Chinese Medicine (No: k2026yrc71).

Access restricted. Please log in or start a trial to view this content.

Materials

List of materials used in this article
NameCompanyCatalog NumberComments
Cochrane LibraryCochrane Libraryhttps://www.cochranelibrary.com/
EBSCOEBSCO Industrieshttps://www.ebsco.com/
Endnote X9Cochrane https://support.clarivate.com/Endnote/s/
GetDataGetData Graph Digitizerhttps://getdata-graph-digitizer.com/
PROSPERONational Institute for Health and Care Researchhttps://www.crd.york.ac.uk/PROSPERO/
PubMedNational Library of Medicinehttps://pubmed.ncbi.nlm.nih.gov/
RevManCochrane https://revman.cochrane.org/
ScienceDirectElsevierhttps://www.sciencedirect.com/
STATAStataCorphttps://www.stata.com/
Web of ScienceClarivate Analyticshttps://www.webofscience.com/

References

  1. Gecse, K. B., Vermeire, S. Differential diagnosis of inflammatory bowel disease: imitations and complications. Lancet Gastroenterol Hepatol. 3 (9), 644-653 (2018).
  2. Zhou, J. L., et al. Trends and projections of inflammatory bowel disease at the global, regional and national levels, 1990–2050: a bayesian age-period-cohort modeling study. BMC Public Health. 23 (1), 2507(2023).
  3. Siegel, C. A. Explaining risks of inflammatory bowel disease therapy to patients. Aliment Pharmacol Ther. 33 (1), 23-32 (2010).
  4. Christophi, G., Rengarajan, A., Ciorba, M. Rectal budesonide and mesalamine formulations in active ulcerative proctosigmoiditis: efficacy, tolerance, and treatment approach. Clin Exp Gastroenterol. 9, 283-289 (2016).
  5. Weizman, A. V., et al. Characterisation of complementary and alternative medicine use and its impact on medication adherence in inflammatory bowel disease. Aliment Pharmacol Ther. 35 (3), 342-349 (2011).
  6. Berlin, J. A., Golub, R. M. Meta-analysis as evidence: building a better pyramid. JAMA. 311 (6), 603-605 (2014).
  7. Page, M. J., et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev. 10 (1), 89(2021).
  8. Zhang, X. M., Zhang, Y. B., Chi, M. H. Soy protein supplementation reduces clinical indices in type 2 diabetes and metabolic syndrome. Yonsei Med J. 57 (3), 681-689 (2016).
  9. Luo, D., et al. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res. 27 (6), 1785-1805 (2018).
  10. Wan, X., et al. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 14 (1), 135(2014).
  11. Hooijmans, C. R., et al. Meta-analyses of animal studies: an introduction of a valuable instrument to further improve healthcare. ILAR J. 55 (3), 418-426 (2014).
  12. Cao, Y. B., et al. Effects of Changtai granules, a traditional compound Chinese medicine, on chronic trinitrobenzene sulfonic acid-induced colitis in rats. World J Gastroenterol. 11 (23), 3539-3543 (2005).
  13. Che, Y. H., et al. Effects of the traditional Chinese medicine formula Ento-PB in experimental models of ulcerative colitis. Nat Prod Commun. 17 (3), 1-10 (2022).
  14. Cheng, X., et al. Huangkui Lianchang decoction attenuates experimental colitis by inhibiting the NF-κB pathway and autophagy. Front Pharmacol. 13, 951558(2022).
  15. Cui, Y., et al. Integrated network pharmacology, molecular docking and animal experiment to explore the efficacy and potential mechanism of Baiyu decoction against ulcerative colitis by enema. Drug Des Devel Ther. 17, 3453-3472 (2023).
  16. Dong, L., et al. Anemone chinensis Bunge aqueous enema alleviates dextran sulfate sodium-induced colitis via inhibition of inflammation and regulation of the colonic mucosal microbiota. J Ethnopharmacol. 288, 115010(2022).
  17. Guo, S. M., et al. Effect of traditional Chinese medicinal enemas on ulcerative colitis of rats. World J Gastroenterol. 10 (13), 1914-1917 (2004).
  18. Han, Z., et al. Systems pharmacology and transcriptomics reveal the mechanisms of Sanhuang decoction enema in ulcerative colitis with additional Candida albicans infection. Chin Med. 16 (1), 1-16 (2021).
  19. Han, Z., et al. Integrative transcriptomic and metabonomic profiling analyses reveal the molecular mechanism of Huankuile suspension on TNBS-induced ulcerative colitis. Aging (Albany NY). 13 (4), 5087-5103 (2021).
  20. Jing, C., et al. Efficacy of Qifu Lizhong enema prescription on intestinal mucosal tight-junction modulation in a rat model of ulcerative colitis. J Tradit Chin Med. 43 (2), 303-311 (2023).
  21. Lin, J. C., et al. QingBai decoction regulates intestinal permeability in DSS-induced colitis through modulation of Notch and NF-κB signalling. Cell Prolif. 52 (2), e12547(2019).
  22. Liu, B., et al. Exploration of mechanisms underlying Yu’s enema formula in treating ulcerative colitis by blocking the RhoA/ROCK pathway. Curr Pharm Des. 30 (2), 115-124 (2024).
  23. Liu, D. Y., et al. Pharmacological effects of Ba-Wei-Xi-Lei powder on ulcerative colitis in rats with enema application. Am J Chin Med. 34 (3), 461-469 (2006).
  24. Shi, L., et al. Effect of Yang-activating and stasis-eliminating decoction on intestinal mucosal permeability in DSS-induced ulcerative colitis rats. J Tradit Chin Med. 37 (4), 452-460 (2017).
  25. Tan, Y. Y., et al. Ding’s herbal enema treats DSS-induced colitis in mice by regulating the gut microbiota and maintaining Treg/Th17 balance. Exp Ther Med. 22 (6), 1368(2021).
  26. Wang, S., et al. Effects of modified Sanhuang decoction enema on TNF-α and colonic IL-1β, IL-6 in ulcerative colitis rats. Chin J Integr Med. 20 (11), 865-869 (2014).
  27. Wen, J., et al. Mechanism of Bawei Xileisan in DSS-induced ulcerative colitis in mice. J Ethnopharmacol. 188, 31-38 (2016).
  28. Yongbiao, H., et al. Xilei San ameliorates experimental colitis in rats by degrading pro-inflammatory mediators and promoting mucosal repair. Evid Based Complement Alternat Med. 2014, 1-10 (2014).
  29. Yu, W., et al. Systems pharmacology approach to determine active compounds and mechanisms of Xipayi KuiJie’an enema in ulcerative colitis. Sci Rep. 7 (1), 1189(2017).
  30. Yu, W., et al. Three types of gut bacteria collaborate to improve Kui Jie’an enema treatment in DSS-induced colitis mice. Biomed Pharmacother. 113, 108751(2019).
  31. Yun, H. F., et al. Pingkui enema alleviates TNBS-induced ulcerative colitis by regulating inflammatory factors, Bifidobacterium, and intestinal barrier. Evid Based Complement Alternat Med. 2020, 3896948(2020).
  32. Han, Y., et al. Qing Hua Chang Yin alleviates chronic colitis in mice by protecting intestinal barrier and improving colonic microflora. Front Pharmacol. 14, 1170345(2023).
  33. Zhu, M. Z., et al. Edible exosome-like nanoparticles from Portulaca oleracea L mitigate DSS-induced colitis via expansion of double-positive CD4⁺CD8⁺ T cells. J Nanobiotechnol. 21 (1), 120(2023).
  34. Ramos, G. P., Papadakis, K. A. Mechanisms of disease: inflammatory bowel diseases. Mayo Clin Proc. 94 (1), 155-165 (2019).
  35. Le Loupp, A. G., et al. Activation of the prostaglandin D₂ metabolic pathway in Crohn’s disease: involvement of the enteric nervous system. BMC Gastroenterol. 15 (1), 123(2015).
  36. Sartor, R. B. Pathogenesis of Crohn’s disease and ulcerative colitis. Nat Clin Pract Gastroenterol Hepatol. 3 (7), 390-407 (2006).
  37. Keshavarzian, A., et al. Increased interleukin-8 in rectal dialysate from ulcerative colitis patients: evidence for a biological role in colonic inflammation. Am J Gastroenterol. 94 (3), 704-712 (1999).
  38. Piechota-Polanczyk, A., Fichna, J. Role of oxidative stress in pathogenesis and treatment of inflammatory bowel diseases. Naunyn Schmiedebergs Arch Pharmacol. 387 (7), 605-620 (2014).
  39. Li, M., et al. Beneficial effects of celastrol on immune balance by modulating gut microbiota in experimental ulcerative colitis mice. Genomics Proteomics Bioinformatics. 20 (2), 288-303 (2022).
  40. Peng, K., et al. Kuijie decoction ameliorates ulcerative colitis by affecting intestinal barrier, gut microbiota, metabolic pathways and Treg/Th17 balance. J Ethnopharmacol. 319, 116936(2024).
  41. Atreya, I., Atreya, R., Neurath, M. F. NF-κB in inflammatory bowel disease. J Intern Med. 263 (6), 591-596 (2008).
  42. Ahmed, S., Xu, R. Nuclear factor-κB in inflammatory bowel disease and colorectal cancer. Am J Dig Dis. 1 (2), 84-96 (2014).
  43. Ungaro, R., et al. Ulcerative colitis. Lancet. 389 (10080), 1756-1770 (2017).
  44. Shen, Y., et al. Protective effects of Lizhong decoction on ulcerative colitis in mice by suppressing inflammation and ameliorating gut barrier. J Ethnopharmacol. 259, 112879(2020).
  45. Bozkurt, H. S., Bilgin, K. A new treatment for ulcerative colitis: intracolonic Bifidobacterium and xyloglucan application. Eur J Inflamm. 18, 1-8 (2020).
  46. Zhou, Y., et al. Gut microbiota offers universal biomarkers across ethnicity in inflammatory bowel disease diagnosis and infliximab response prediction. mSystems. 3 (1), e00188-17(2018).
  47. Ru, X., et al. Effect of Chinese herbal enema prescription on renal function, enterogenous uremic toxins and intestinal barrier in CKD stage 3–5 predialysis participants: a randomized controlled trial. Medicine (Baltimore). 104 (32), e43791(2025).

Access restricted. Please log in or start a trial to view this content.

Reprints and Permissions

Tags

Animal ModelsIntestinal BarrierInflammatory MediatorsGut MicrobiotaDisease Activity IndexRegulatory T Cells
Contact Us
Recommend to Library

Privacy

Terms of Use

Policies

Copyright © 2026 MyJoVE Corporation. All rights reserved.