The IgV domain of the poliovirus receptor alone is immunosuppressive and binds to its receptors with comparable affinity
Bibliographic record
Abstract
Abstract PVR (poliovirus receptor) functions as a ligand that signals through TIGIT and CD96 to induce suppression of T-cell and NK-cell responses. Alternatively, PVR binds to CD226, resulting in a co-stimulatory signal. To date, TIGIT antibody antagonists have been developed to restore immune functions and allow PVR to signal though CD226 in the context of cancer immunotherapy. Due to PVR receptor heterogeneity, agonizing either of these pathways with a recombinant form of the PVR extracellular domain represents a therapeutic strategy for either immunosuppression or activation. Here, we developed a minimal murine PVR-Fc fusion construct, consisting of only the IgV domain of PVR (vdPVR-Fc), and assessed its ability to dampen inflammatory responses in a murine model of psoriasis. vdPVR-Fc and PVR-Fc containing the full-length extracellular domain bound to TIGIT, CD96 and CD226 with similar low nanomolar affinities as defined by surface plasmon resonance. vdPVR-Fc was also able to suppress the in-vitro proliferation of murine CD4+ and CD8+ T-cells in mixed splenocyte cultures. Importantly, vdPVR-Fc delayed the onset, and reduced inflammatory responses (scaling and thickness) in a murine model of psoriasis. Collectively, our results suggest that the minimal IgV domain of PVR is sufficient to dampen immune responses in-vitro and attenuate symptoms of psoriasis in-vivo.
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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".