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Record W3044908311 · doi:10.1038/s41385-020-0326-2

The dialogue between unconventional T cells and the microbiota

2020· review· en· W3044908311 on OpenAlex
Qiaochu Lin, Meggie Kuypers, Dana J. Philpott, Thierry Mallevaey

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

VenueMucosal Immunology · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsCrosstalkBiologyImmune systemAutoimmunityInnate immune systemImmunologyNatural killer T cellInnate lymphoid cellCell biologyCD8

Abstract

fetched live from OpenAlex

The mammalian immune system is equipped with unconventional T cells that respond to microbial molecules such as glycolipids and small-molecule metabolites, which are invisible to conventional CD4 and CD8 T cells. Unconventional T cells include invariant natural killer T (iNKT) cells and mucosa-associated invariant T (MAIT) cells, which are involved in a wide range of infectious and non-infectious diseases, such as cancer and autoimmunity. In addition, their high conservation across mammals, their restriction by non-polymorphic antigen-presenting molecules, and their immediate and robust responses make these 'innate' T cells appealing targets for the development of one-size-fits-all immunotherapies. In this review, we discuss how iNKT and MAIT cells directly and indirectly detect the presence of and respond to pathogenic and commensal microbes. We also explore the current understanding of the bidirectional relationship between the microbiota and innate T cells, and how this crosstalk shapes the immune response in disease.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.005

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.

Opus teacher head0.023
GPT teacher head0.263
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