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Record W2922658020 · doi:10.1016/j.celrep.2019.02.108

Single-Cell Resolution and Quantitation of Targeted Glucocorticoid Delivery in the Thymus

2019· article· en· W2922658020 on OpenAlexfundno aff
Matthew D. Taves, Paul R. Mittelstadt, Diego M. Presman, Gordon L. Hager, Jonathan D. Ashwell

Bibliographic record

VenueCell Reports · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsGlucocorticoid receptorGlucocorticoidParacrine signallingTranscription factorBiologyCell biologyNuclear receptorReceptorCellIn vivoEndocrinologyBiochemistryGeneGenetics

Abstract

fetched live from OpenAlex

Glucocorticoids are lipid-soluble hormones that signal via the glucocorticoid receptor (GR), a ligand-dependent transcription factor. Circulating glucocorticoids derive from the adrenals, but it is now apparent that paracrine glucocorticoid signaling occurs in multiple tissues. Effective local glucocorticoid concentrations and whether glucocorticoid delivery can be targeted to specific cell subsets are unknown. We use fluorescence detection of chromatin-associated GRs as biosensors of ligand binding and observe signals corresponding to steroid concentrations over physiological ranges in vitro and in vivo. In the thymus, where thymic epithelial cell (TEC)-synthesized glucocorticoids antagonize negative selection, we find that CD4+CD8+TCRhi cells, a small subset responding to self-antigens and undergoing selection, are specific targets of TEC-derived glucocorticoids and are exposed to 3-fold higher levels than other cells. These results demonstrate and quantitate targeted delivery of paracrine glucocorticoids. This approach may be used to assess in situ nuclear receptor signaling in a variety of physiological and pathological contexts.

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 score0.017
Threshold uncertainty score0.434

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 head0.012
GPT teacher head0.205
Teacher spread0.193 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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