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Tolerogenic dendritic cells and their potential applications

2011· review· en· W1620336138 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueImmunology · 2011
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsHospital for Sick ChildrenMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsImmune systemImmunityBiologyAntigenImmunologyImmune tolerancePopulationDendritic cellAcquired immune systemCell biologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Dendritic cells (DCs) play a pivotal role in regulating the balance between immunity and tolerance of the immune system. Recent advancements in DC biology and techniques for manipulating the function of these cells have shown their immense therapeutic potential for treating a variety of immune disorders. Theoretically, antigen-specific tolerogenic DCs can be generated in vitro and delivered to patients to correct the dysfunctional immune responses that attack their own tissues or over-react to innocuous foreign antigens. However, DCs are a heterogeneous population of cells with differences in cell surface makers, differentiation pathways and functions. Studies are needed to examine which subset of DCs can be used for what type of applications. Furthermore, most of the information on tolerogenic DCs has been obtained from animal models and translational studies are needed to examine how a DC therapeutic strategy can be implemented clinically to modulate immunity.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.021
GPT teacher head0.262
Teacher spread0.240 · 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