Tetrahydro-benzothiophene ROR gamma t Inverse Agonists to Target Th17 in a Sensitized Skin Allograft Mouse Model
Bibliographic record
Abstract
🧾 AbstractBackground: Th17 cells play a critical role in acute cellular as well as in chronic antibody mediated allograft rejection. We have recently designed tetrahydro-benzothiophene derivatives as novel inverse agonists of retinoic acid receptor-related orphan receptor gamma t (RORγt) and demonstrated in vitro activity in Th17 polarization assay from PBMCs. The objective of the current study is to determine the effect of tetrahydro-benzothiophene derivatives on the rejection of complete mismatch skin graft in a sensitized murine model. Methods: C57BL/6 mice were sensitized by administration of 10^7 Balb/c splenocytes (IP) at day 0, 7 and 14 and transplanted with Balb/c skin grafts at day fifteen. Mice were injected daily with a tetrahydro-benzothiophene RORγt inverse agonist (TF-S14, 1mg/kg, IP), or tacrolimus (0.5mg/kg, IP) or combination. Graft survival was evaluated daily for rejection end point (100% necrosis). Skin grafts were sampled at day five for histology. Results: Tetrahydro-benzothiophene RORγt inverse agonist prolonged median graft survival from 6 to 13.5 and from 7 to 23 days when combined with tacrolimus, Figure 1. Neutrophilic infiltration of skin-grafts decreased in RORγt inverse agonist, or combination therapy compared to vehicle or tacrolimus treated mice, Figure 2. Conclusions: The novel tetrahydro-benzothiophene RORγt inhibitor offers a new therapeutic mechanism to treat rejection in highly sensitized patients regardless of degree of donor mismatch.🗓️ Presentation NoteThis abstract represents a reformatted and regionally presented version of the same experimental work initially showcased at the American Transplant Congress (ATC 2023) on 7 June 2023, emphasizing the tetrahydro-benzothiophene scaffold and its translational relevance in Th17-mediated rejection.📁 File DescriptionFouda_Abstract_ESOT2023_Original.pdf — Original version of the abstract. This is the identical file submitted and published on the ESOT 2023 Virtual Congress platform (Abstract ID: 397466; Session: BOS2_12; Presented: 19 September 2023).Abstract_ESOT2023_Booklet_Page109.pdf — Scanned page (p. 109) from the printed Proc. Eur. Soc. Organ Transplant. Congr. 2023 booklet containing the same abstract.📍 Conference and MetadataPresented at: 21st International Transplant Congress of the European Society for Organ Transplantation (ESOT 2023) Presentation Date: 19 September 2023 Location: Athens, Greece Abstract Category: Transplantation Immunology Presentation Type: Oral PresentationAuthors: Ahmed Fouda, Mohamed-Taoubane Maallah, Sarita Negi, Steven Paraskevas, Jean Tchervenkov Affiliation: Department of Experimental Surgery, McGill University, Montreal, QC, Canada 📚 Full CitationFouda, A.; Maallah, M. T.; Negi, S.; Paraskevas, S.; Tchervenkov, J. Tetrahydro-benzothiophene RORγt Inverse Agonists to Target Th17 in Sensitized Skin Allograft Mouse Model. In Proc. Eur. Soc. Organ Transplant. Congr. 2023; 21, p. 109 (Abstr. 23). 21st Congress of the European Society for Organ Transplantation (ESOT 2023), Athens, Greece, 17–20 September 2023. Also published in ESOT Virtual Congress 2023 (Abstract ID: 397466; Session: BOS2_12; Presented: 19 September 2023). DOI: 10.6084/m9.figshare.30422329 © 2023, Ahmed Fouda.
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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) | 0.001 | 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 | 0.001 |
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".