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Record W1993779367 · doi:10.1182/blood-2011-04-350553

Wnt4 regulates thymic cellularity through the expansion of thymic epithelial cells and early thymic progenitors

2011· article· en· W1993779367 on OpenAlexafffund
Krista M. Heinonen, Juan Ruiz Vanegas, Sylvie Brochu, Jingdong Shan, Seppo Vainio, Claude Perreault

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health ResearchNovo Nordisk Fonden
KeywordsBiologyProgenitor cellProgenitorCancer researchCell biologyImmunologyPathologyMedicineStem cell

Abstract

fetched live from OpenAlex

Thymus atrophy is the most common immunopathology in humans, and its occurrence is hastened by several factors that coalesce in patients receiving chemotherapy and most of all in recipients of hematopoietic cell transplantation. We have shown previously that posthematopoietic cell transplantation thymic function was improved by retroviral overexpression of Wnt4 in donor hematopoietic cells. Here, by using both conventional and conditional null mutant mice, we show that Wnt4 regulates steady-state thymic cellularity by a thymic epithelial cell (TEC)-dependent mechanism. The absence of Wnt4 suppressed fetal and postnatal thymic expansion and resulted in decreased TEC numbers, an alteration of the medullary-to-cortical TEC ratio, and a disproportionate loss of the most immature cKit(hi) thymocyte precursors. Wnt4 also is implicated in the maintenance of adult thymopoiesis, although the impact of its deletion once thymic involution has been initiated is more subtle. Together, our results show that Wnt4 controls thymic size by modulating TEC expansion and the earliest, TEC-dependent steps of thymocyte development both in the fetal and postnatal thymus. Wnt4 and its downstream signaling pathways could thus represent interesting candidates to improve thymic output in subjects with thymic atrophy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.438

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.198
Teacher spread0.188 · 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 teacher head, not a consensus.

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

Citations57
Published2011
Admission routes2
Has abstractyes

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