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Record W4224289813 · doi:10.3390/cancers14092071

Innate Lymphoid Cells: Role in Immune Regulation and Cancer

2022· review· en· W4224289813 on OpenAlexafffund
Douglas C. Chung, Nicolas Jacquelot, Maryam Ghaedi, Kathrin Warner, Pamela S. Ohashi

Bibliographic record

VenueCancers · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchTerry Fox Research InstituteOntario Institute for Cancer ResearchCanadian Cancer Society
KeywordsInnate lymphoid cellImmune systemContext (archaeology)Priming (agriculture)BiologyImmunologyImmunityCancerInnate immune systemCancer researchGenetics

Abstract

fetched live from OpenAlex

Immune regulation is composed of a complex network of cellular and molecular pathways that regulate the immune system and prevent tissue damage. It is increasingly clear that innate lymphoid cells (ILCs) are also armed with immunosuppressive capacities similar to well-known immune regulatory cells (i.e., regulatory T cells). In cancer, immunoregulatory ILCs have been shown to inhibit anti-tumour immune response through various mechanisms including: (a) direct suppression of anti-tumour T cells or NK cells, (b) inhibiting T-cell priming, and (c) promoting other immunoregulatory cells. To provide a framework of understanding the role of immunosuppressive ILCs in the context of cancer, we first outline a brief history and challenges related to defining immunosuppressive ILCs. Furthermore, we focus on the mechanisms of ILCs in suppressing anti-tumour immunity and consequentially promoting tumour progression.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.026
GPT teacher head0.272
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2022
Admission routes2
Has abstractyes

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