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Record W7093308358 · doi:10.6084/m9.figshare.30434146

Targeting Th17 Cells Through Inhibition of the Nuclear Receptor (NR) Retinoic Acid Receptor-Related Orphan Receptor γt (RORγt) in Highly Sensitized Renal Transplant Patients (HSP)

2019· other· W7093308358 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2019
Typeother
Language
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsnot available
Fundersnot available
KeywordsRAR-related orphan receptor gammaRetinoic acidNuclear receptorRetinoic acid receptorOrphan receptorReceptorNephrologyTransplantation

Abstract

fetched live from OpenAlex

🧾 Abstract Targeting Th17 cells through inhibition of the nuclear receptor (NR) retinoic acid receptor related orphan receptor γt (RORγt) in highly sensitized renal transplant patients (HSP) Ahmed Fouda1,2, Sarita Negi2, Steven Paraskevas1,2, Jean Tchervenkov1,2 1Department of Experimental Surgery, 2McGill University Health Center, McGill University, Montréal, Québec, Canada Introduction: Late and mixed rejections (LMR) are the most common causes of graft loss in transplantation. Currently there is no effective therapy for this condition. T helper 17 (Th17) cells play a major role in the initiation of LMR through the promotion of tertiary lymphoid tissue. Th17 activity is regulated by several transcription factors and by the NR RORγt. Our group has developed a novel class of molecules to target RORγt. We compared in-vitro Th17 polarization in HSP (cPRA=100%) vs non-sensitized renal transplant patients (NSP, cPRA=0%) and tested one of the novel compounds for their effect on cytokine production to validate their proposed effect. Methods: PBMCs from HSP (n=3), NSP (n=3), and healthy volunteers (HV, n=3) were polarized using CD3/CD28 beads, IL6, IL23, IL1β, and TGFβ for 14 days before adding RORγt inhibitor or vehicle for another 48 hours. Intracellular IL17A and IL21 were measured by flow cytometry. Results: Th17 polarization was higher in HSP compared to NSP or HV (fig1. p<0.05). RORγt inhibitor reduced IL17A and IL21 positive cells compared to controls (fig2. p<0.05). Conclusion: Targeting RORγt may be effective therapy in Th17 mediated LMR. This offers a novel potential targeted therapy for HSP after transplantation.📁 File DescriptionThe published version from the Canadian Transplant Summit 2019 Abstract Booklet (p. 90, Abstract ID 94) and the author preprint including the original figures are both provided.📍 Conference and MetadataPresented at: Canadian Transplant Summit (CST 2019) Presentation Date: 17 October 2019 Location: Banff, Alberta, Canada Abstract Category: Translational Research Presentation Type: Poster Presentation Authors: Ahmed Fouda, Sarita Negi, Steven Paraskevas, Jean Tchervenkov Affiliation: Department of Experimental Surgery, McGill University, Montreal, QC, Canada 📚 Full CitationFouda, A.; Negi, S.; Paraskevas, S.; Tchervenkov, J. Targeting Th17 Cells Through Inhibition of the Nuclear Receptor (NR) Retinoic Acid Receptor-Related Orphan Receptor γt (RORγt) in Highly Sensitized Renal Transplant Patients (HSP). In Proc. Can. Transplant Summit 2019; p. 90 (Abstr. 94). Canadian Transplant Summit (CST 2019), Montréal, QC, Canada, 16–19 October 2019. DOI: 10.6084/m9.figshare.30434146 © 2019, Ahmed Fouda.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.219
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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