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Record W2154536286 · doi:10.1080/08830180600785868

Immune Mechanisms and Therapeutic Potential of CpG Oligodeoxynucleotides

2006· review· en· W2154536286 on OpenAlexaff
Heather L. Wilson, Arshud Dar, Scott Napper, A. Marianela Lopez, Lorne A. Babiuk, George Mutwiri

Bibliographic record

VenueInternational Reviews of Immunology · 2006
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsToll-Like Receptor 9CpG OligodeoxynucleotideImmune systemCpG siteImmunologyBiologyToll-like receptorTLR9ImmunotherapyReceptorInnate immune systemCancer researchDNA methylationGeneGeneticsGene expression

Abstract

fetched live from OpenAlex

Unmethylated CpG motifs in bacterial DNA and synthetic oligodeoxynucleotides activate immune cells that express Toll-like Receptor 9. Activation through this receptor triggers cellular signaling that leads to production of a proinflammatory and a Th1-type, antigen-specific immune response. The immunostimulatory effects of CpG oligodeoxynucleotides confer protection against infectious disease, allergy and cancer in animal models, and clinical trials have been initiated. However, CpG oligodeoxynucleotides may exacerbate disease in some situations. We will review current concepts in the mechanisms of activating Toll-like Receptor 9 with CpG oligodeoxynucleotides and highlight opportunities for using large animal models to better determine the mechanisms of action.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.297
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations73
Published2006
Admission routes1
Has abstractyes

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