Peeling Back Immunity: Citrus Peel Extract as A Potential Natural Immunomodulator for Systemic Lupus Erythematosus
Bibliographic record
Abstract
Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease characterized by chronic inflammation and dysregulation of the immune system. Current treatments for SLE often involve general immunosuppressants and antimalarial medications, which can have significant side effects and may not be effective for all patients. This has led researchers to explore alternative therapeutic options, including natural compounds with anti-inflammatory and immunomodulatory properties. Citrus peel extract has emerged as a promising candidate for SLE treatment due to its rich content of bioactive compounds, mainly polyphenols. In various studies, various studies have shown that these compounds possess potent anti-inflammatory and immunomodulatory effects. This study investigated Citrus peel extract’s anti-inflammatory and immunomodulatory effects on peripheral blood mononuclear cells (PBMCs) from SLE patients. PBMCs from ANA-positive SLE patients were treated with Citrus peel extract at 25, 50, and 100 μg/mL. Flow cytometry was used to analyze Th1 (CD4+IFNγ+), Th17 (CD4+IL17A+), and Treg (CD4+CD25+Foxp3+) cell populations. Citrus peel extract significantly decreased Th1 and Th17 cells while increasing Treg cells dose-dependently by inducing interleukin-10 anti-inflammatory cytokine. At 100 μg/mL, the extract reduced Th1 cells from 12.70 to 7.83 % and Th17 cells from 18.47 to 11.67 % while increasing Treg cells from 0.14 to 3.67 %. Phytochemical screening revealed the presence of flavonoids, which likely mediate these immunomodulatory effects through suppression of inflammatory cytokines and transcription factors. These results suggest Citrus peel extract can help restore immune balance in SLE by suppressing pathogenic Th1/Th17 responses and promoting regulatory T cells and IL-10. The extract shows promise as a potential natural immunomodulatory adjuvant therapy for autoimmune conditions like SLE. Further research is needed to elucidate the molecular mechanisms and evaluate clinical efficacy. HIGHLIGHTS Citrus peel extract significantly modulates immune cell populations in SLE patients by decreasing pro-inflammatory, Th1 and Th17 cells. Citrus peel extract regulates immune responses in SLE by upregulating regulatory T cells. Immunomodulatory effects are likely mediated by flavonoids present in the extract. GRAPHICAL ABSTRACT
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".