The Pivotal Role of Regulatory T Cells in the Regulation of Innate Immune Cells
Bibliographic record
Abstract
The distinction between innate and adaptive immunity is one of the basic tenets of immunology. The co-operation between these two arms of the immune system is a major determinant of the resistance or susceptibility of the host following pathogen invasion. Hence, this interactive co-operation between cells of the innate and adaptive immunity is of significant interest to immunologists. The sub-population of CD4+ T cells with regulatory phenotype (regulatory T cells; Tregs), which constitute a part of the adaptive immune system, have been widely implicated in the regulation of the immune system and maintenance of immune homeostasis. In the last two decades, there has been an explosion in research describing the role of Tregs and their relevance in several immunopathologies ranging from inflammation to cancer. The majority of these studies focus on the role of Tregs on the cells of the adaptive immune system. Recently, there is significant interest in the role of Tregs on cells of the innate immune system. In this review, we examine the literature on the role of Tregs in immunology. Specifically, we focus on the emerging knowledge of Treg interaction with dendritic cells, macrophages and neutrophils which are classical innate immune cells. We highlight this interaction as an important link between innate and adaptive immune systems which also indicate the far-reaching role of Tregs in the regulation of immune responses and maintenance of self-tolerance and immune homeostasis.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".