Attenuation of Chronic Inflammation in Intestinal Organoids with Graphene Oxide-Mediated Tumor Necrosis Factor-α_Small Interfering RNA Delivery
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract with a complex and multifactorial etiology, making it challenging to treat. While recent advances in immunomodulatory biologics, such as antitumor necrosis factor-α (TNF-α) antibodies, have shown moderate success, systemic administration of antibody therapeutics may lead to several adverse effects, including the risk of autoimmune disorders due to systemic cytokine depletion. Transient RNA interference using exogenous short interfering RNA (siRNA) to regulate target gene expression at the transcript level offers an alternative to systemic immunomodulation. However, siRNAs are susceptible to premature degradation and have poor cellular uptake. Graphene oxide (GO) nanoparticles have been shown to be effective nanocarriers for biologics due to their reduced cytotoxicity and enhanced bioavailability. In this study, we evaluate the therapeutic efficacy of GO mediated TNF-α_siRNA using in vitro models of chronic inflammation generated by treating murine small intestines (enteroids) and large intestines (colonoids) with inflammatory agents IL-1β, TNF-α, and LPS. The organotypic mouse enteroids and colonoids developed an inflammatory phenotype similar to that of IBD, characterized by impaired epithelial homeostasis and an increased production of inflammatory cytokines such as TNF-α, IL-1β, and IL-6. We assessed siRNA delivery to these inflamed organoids using three different GO formulations. Out of the three, small-sized GO with polymer and dendrimer modifications (smGO) demonstrated the highest transfection efficiency, which led to the downregulation of inflammatory cytokines, indicating an attenuation of the inflammatory phenotype. Moreover, the transfection efficiency and inflammation-ameliorating effects could be further enhanced by increasing the TNF-α_siRNA/smGO ratio from 1:1 to 3:1. Overall, the results of this study demonstrate that ex vivo organoids with disease-specific phenotypes are invaluable models for assessing the therapeutic potential of nanocarrier-mediated drug and biologic delivery systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".