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Record W3005215567 · doi:10.1038/s41467-020-14442-6

Immunological history governs human stem cell memory CD4 heterogeneity via the Wnt signaling pathway

2020· article· en· W3005215567 on OpenAlexaff
Hassen Kared, Shu Wen Tan, Mai Chan Lau, Marion Chevrier, Crystal Tan, Wilson How, Glenn Wong, Marie Strickland, Benoît Malleret, Amanda Amoah, Karolina Pilipow, Veronica Zanon, Naomi Mc Govern, Josephine Lum, Jin Miao Chen, Bernett Lee, Maria Carolina Florian, Hartmut Geiger, Florent Ginhoux, Ezequiel Ruíz-Mateos, Tamàs Fülöp, Reena Rajasuriar, Adeeba Kamarulzaman, Tze Pin Ng, Enrico Lugli, Anis Larbi

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversité de Sherbrooke
FundersNational Institute of Environmental Health Sciences
KeywordsWnt signaling pathwayStem cellBiologySignal transductionCell biologyComputational biology

Abstract

fetched live from OpenAlex

Abstract The diversity of the naïve T cell repertoire drives the replenishment potential and capacity of memory T cells to respond to immune challenges. Attrition of the immune system is associated with an increased prevalence of pathologies in aged individuals, but whether stem cell memory T lymphocytes (T SCM ) contribute to such attrition is still unclear. Using single cells RNA sequencing and high-dimensional flow cytometry, we demonstrate that T SCM heterogeneity results from differential engagement of Wnt signaling. In humans, aging is associated with the coupled loss of Wnt/β-catenin signature in CD4 T SCM and systemic increase in the levels of Dickkopf-related protein 1, a natural inhibitor of the Wnt/β-catenin pathway. Functional assays support recent thymic emigrants as the precursors of CD4 T SCM . Our data thus hint that reversing T SCM defects by metabolic targeting of the Wnt/β-catenin pathway may be a viable approach to restore and preserve immune homeostasis in the context of immunological history.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.040
GPT teacher head0.256
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations42
Published2020
Admission routes1
Has abstractyes

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