Tumor necrosis factor receptor 2 in allergen tolerance: a perspective view
Bibliographic record
Abstract
Central and peripheral tolerance are key to maintain immune homeostasis. Imbalance of these processes often leads to diseases such as allergy, cancer or autoimmune disorders. During the immune response to allergens, several regulatory immune cells play a role in the development of peripheral tolerance and maintenance of homeostasis by inhibiting the development of CD4+ type 2 helper T cells, impairing the production of pro-allergenic cytokines, reducing the activation of effector cells driving allergic inflammation and generating allergen-neutralizing antibodies. However, the precise mechanisms of how peripheral immune tolerance is effectively maintained in healthy people, but not in allergic patients are still not well understood. Immune checkpoints have recently been proposed as critical molecular pathways across diseases for understanding how the immune system maintains homeostasis in many pathologies such as cancer, type 1 diabetes, multiple sclerosis, Crohn’s disease and allergy, among others. Particularly in the context of allergy, in-depth studies on immune checkpoint pathways might lead to emerging therapeutic targets. Tumor necrosis factor receptor 2 (TNFR2) is a crucial protein involved in promotion, expansion and maintenance of immune tolerance, being suggested as a key target for the treatment of several immune-based diseases including allergy. Here, we review the involvement of TNFR2 in allergic inflammation and allergen tolerance, its structural properties, signaling pathways, and importance for immune tolerance as a common mechanism, with the focus on possible implications for novel immunomodulatory treatments of allergic diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".