HVEM/LIGHT/BTLA/CD160 cosignaling pathways as targets for immune regulation
Bibliographic record
Abstract
Abstract This review highlights how the blockade of the co-stimulatory HVEM/LIGHT interaction or agonist signaling through the inhibitory BTLA and CD160 receptors could contribute to the control of deleterious immune responses. Immunosuppression is currently the treatment of choice to attenuate the chronic deterioration of tissue function as a result of the effector mechanisms of the immunological response in transplant rejection and autoimmune diseases. However, global immunosuppression greatly increases the risk of acquiring life-threatening infections and is associated with organ toxicity when used long-term. Thus, alternative approaches that inhibit only the unwanted immune responses and preserve general immunity are highly desirable. The receptor/ligand pairs involved in the cross-talk between DC and T cells have been the focus of intense and exciting research during the last decade. The HVEM/LIGHT/BTLA/CD160 costimulatory/coinhibitory pathway has emerged as a potential target for the development of immune therapeutic interventions. Herein, we will summarize and discuss how blockade of the costimulatory HVEM/LIGHT interaction or agonist signaling through the inhibitory BTLA and CD160 receptors could contribute to the control of deleterious immune responses.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".