Therapeutic Benefits of Regulating Inflammation in Autoimmunity
Bibliographic record
Abstract
Autoimmunity results from the dysregulation of the immune system leading to tissue damage. Th1 and Th17 cells are known to be cellular mediators of inflammation in autoimmune diseases. The specific cytokine milieu within the site of inflammation or within secondary lymphatic tissues is important during the priming and effector phases of T cell response. In this review, we will address the nature of the inflammatory response in the context of autoimmune disease, specifically we will discuss the role of dendritic cells following stimulation of their innate pathogen recognition receptors in directing the development of T cell responses. We will focus on how dendritic cell subsets change the balance between major players in autoimmunity, namely Th1, Th17 and regulatory T cells. Th17 cells, once thought to only act as pathogenic effectors through production of IL-17, have been shown to have regulatory properties as well with co-production of the anti-inflammatory cytokine IL-10 by a subset now referred to as regulatory Th17 cells. IL-17 is important in the induction of autoimmune diseases such as experimental autoimmune encephalomyelitis (EAE) and inflammatory bowel disease (IBD). Study of the inflammatory process following encounter with agents that stimulate the innate immune responses such as adjuvants opens a new horizon for the discovery of therapeutic agents including those derived from microorganisms. Microbial products such as adjuvants that function as TLR ligands may stimulate the immune system by interacting with Toll-like receptors (TLR) on antigen-presenting cells. Microbial agents such as Bacille Calmette-Guérin (BCG) or Freund's adjuvant (CFA) that induce a Th17 response are protective in models of autoimmune diseases particularly EAE and type 1 diabetes (T1D). The induction of innate immunity by these microbial products alters the balance in the cytokine microenvironment and may be responsible for modulation of the inflammation and protection from autoimmunity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".