ArticleInflammation2023
Investigation of TLR4 Antagonists for Prevention of Intestinal Inflammation.
Article in Inflammation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- Taking its TOLL: the role of toll-like receptor 4 in human health and disease, and its potential as a therapeutic target.Frontiers in immunology · 2026Review
- L-Citrulline Improves Recovery of Enterocytes While Not Affecting Gut Microbiota in an In Vitro Model of Chemotherapy-Induced Gastrointestinal Mucositis.Biomedicines · 2025Article
- Chicory supplementation improves growth performance in juvenile ostriches potentially by attenuating enteritis.Frontiers in veterinary science · 2024Article
- New Insights into the Mechanism ofMarine drugs · 2023Article
- Microbial Metabolites as Ligands to Xenobiotic Receptors: Chemical Mimicry as Potential Drugs of the Future.Drug metabolism and disposition: the biological fate of chemicals · 2023Review
- Melatonin-Microbiome Two-Sided Interaction in Dysbiosis-Associated Conditions.Antioxidants (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Activation of toll-like receptor 4 (TLR4) has been shown to be a major influence on the inflammatory signalling pathways in intestinal mucositis (IM), as demonstrated by TLR4 knock-out mice. Pharmacological TLR4 inhibition has thus been postulated as a potential new therapeutic approach for the treatment of IM but specific TLR4 inhibitors have yet to be investigated. As such, we aimed to determine whether direct TLR4 antagonism prevents inflammation in pre-clinical experimental models of IM. The non-competitive and competitive TLR4 inhibitors, TAK-242 (10 µM) and IAXO-102 (10 µM), respectively, or vehicle were added to human T84, HT-29, and U937 cell lines and mouse colonic explants 1 h before the addition of lipopolysaccharide (LPS) (in vitro: 100 µg/mL; ex vivo: 10 µg/mL), SN-38 (in vitro: 1 µM or 1 nM; ex vivo: 2 µM), and/or tumour necrosis factor-alpha (TNF-α) (5 µg/mL). Supernatant was collected for human IL-8 and mouse IL-6 enzyme-linked immunosorbent assays (ELISAs), as a measure of inflammatory signalling. Cell viability was measured using XTT assays. Explant tissue was used in histopathological and RT-PCR analysis for genes of interest: TLR4, MD2, CD14, MyD88, IL-6, IL-6R, CXCL2, CXCR1, CXCR2. SN-38 increased cytostasis compared to vehicle (P < 0.0001). However, this was not prevented by either antagonist (P > 0.05) in any of the 3 cell lines. Quantitative histological assessment scores showed no differences between vehicle and treatment groups (P > 0.05). There were no differences in in vitro IL-8 (P > 0.05, in all 3 cells lines) and ex vivo IL-6 (P > 0.05) concentrations between vehicle and treatment groups. Transcript expression of all genes was similar across vehicle and treatment groups (P > 0.05). TLR4 antagonism using specific inhibitors TAK-242 and IAXO-102 was not effective at blocking IM in these pre-clinical models of mucositis. This work indicates that specific epithelial inhibition of TLR4 with these compounds is insufficient to manage mucositis-related inflammation. Rather, TLR4 signalling through immune cells may be a more important target to prevent IM.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.