RDP58, a Novel Immunomodulatory Peptide with Anti-Inflammatory Effects. A Pharmacological Study in Trinitrobenzene Sulphonic Acid Colitis and Crohn Disease
Bibliographic record
Abstract
BACKGROUND: Tumour necrosis factor (TNF) plays a key role in the pathogenesis of Crohn disease (CD). RDP58 is a novel anti-inflammatory decapeptide which was developed using a novel rational design strategy. Recently, RDP58 has proved to be a potent inhibitor of TNF production at a post-transcriptional step. The aims of this study were to investigate the anti-inflammatory properties of RDP58 ex vivo in human CD and in vivo in an experimental model colitis. METHODS: Biopsies and lamina propria mononuclear cells from inflamed colonic mucosa of 18 CD patients were cultured for 24 h in the presence or absence of RDP58. TNF was quantified in a bioassay: interferon (IFN)-gamma and interleukin (IL)-1beta levels were measured by enzyme-linked immunosorbent assays. Colitis was induced by intra-rectal administration of 2, 4, 6 trinitrobenzene sulphonic acid (TNBS) in rats. Inflammation was assessed following 7 days of oral therapy with RDP58 or vehicle alone. RESULTS: RDP58 led to decreased TNF and IFN-gamma (but not IL-1beta) production by biopsies and lamina propria mononuclear cells from CD patients. In rats with TNBS-induced colitis, oral RDP58 therapy reduced weight loss and diarrhoea and improved macroscopic and histological inflammation scores. CONCLUSIONS: Our results suggest that RDP58 may be an effective therapy for CD with the clinical advantage of an oral administration.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".