Toll-like Receptor 9, CpG DNA and Innate Immunity
Bibliographic record
Abstract
Innate immunity provides the first line of defense against invading pathogens and is essential for survival in the absence of adaptive immune responses. Innate immune recognition relies on a limited number of germ-line encoded receptors, such as Toll-like receptors (TLRs), that evolved to recognize conserved molecular patterns of microbial origin. To date, ten transmembrane proteins in the TLR family have been described. It is becoming increasingly clear that bacterial CpG DNA and synthetic oligodeoxynucleotides (ODN) containing unmethylated CpG are potent inducers of the innate immune system including dendritic cells (DCs), macrophages, and natural killer (NK) and NKT cells. Recent studies indicate that mucosal or systemic delivery of CpG DNA can act as a potent adjuvant in a vaccine combination or act alone as an anti-microbial agent. Recently, it was shown that TLR9 is essential for the recognition of unmethylated CpG DNA since cells from TLR9-deficient mice are unresponsive to CpG stimulation. Although the effects of CpG DNA on bone marrow-derived cells are beginning to unfold, there has been little or no information regarding the mechanisms of CpG DNA function on non-immune cells or tissues. This review focuses on the recent advances in CpG-DNA/TLR9 signaling effects on the activation of innate immunity.
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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) | 0.005 | 0.005 |
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".