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Record W4387058558 · doi:10.3389/fimmu.2023.1267697

Lineage origin and transcriptional control of autoantigen-specific T-regulatory type 1 cells

2023· review· en· W4387058558 on OpenAlexafffund
Edgar Angelats, Pere Santamaría

Bibliographic record

VenueFrontiers in Immunology · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of Calgary
FundersPraesperoGenome AlbertaAlberta Diabetes FoundationGeneralitat de CatalunyaCalifornia State University, ChicoCentres de Recerca de CatalunyaInstituto de Salud Carlos IIICanadian Institutes of Health ResearchGenome Canada
KeywordsFOXP3BiologyIL-2 receptorTranscriptional regulationT cellPopulationCell typeCell biologyRegulatory T cellLineage (genetic)PhenotypeCellImmune systemGeneticsImmunologyComputational biologyGeneTranscription factorMedicine

Abstract

fetched live from OpenAlex

T Regulatory type-1 (TR1) cells represent an immunosuppressive T cell subset, discovered over 25 years ago, that produces high levels of interleukin-10 (IL-10) but, unlike its FoxP3+ T regulatory (Treg) cell counterpart, does not express FoxP3 or CD25. Experimental evidence generated over the last few years has exposed a promising role for TR1 cells as targets of therapeutic intervention in immune-mediated diseases. The discovery of cell surface markers capable of distinguishing these cells from related T cell types and the application of next generation sequencing techniques to defining their transcriptional make-up have enabled a more accurate description of this T cell population. However, the developmental biology of TR1 cells has long remained elusive, in particular the identity of the cell type(s) giving rise to bona fide TR1 cells in vivo. Here, we review the fundamental phenotypic, transcriptional and functional properties of this T cell subset, and summarize recent lines of evidence shedding light into its ontogeny.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.255
Teacher spread0.227 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Immunology→Same topicT-cell and B-cell Immunology→French-language works237,207→