Differential transcription of Eomes and T-bet during maturation of mouse uterine natural killer cells
Bibliographic record
Abstract
During human and rodent uterine decidualization, transient but abundant numbers of uterine natural killer (uNK) cells appear, proliferate, and differentiate. uNK cells share features with peripheral NK cells but are specialized to promote interferon-gamma (IFN-gamma)-mediated, pregnancy-associated, structural changes in maternal placental arteries. In CD8+ T cells and NK cells, the transcription factors T-bet and eomesodermin (Eomes) regulate maturation and effector functions, including IFN-gamma production. No studies are reported for uNK cells. Implantation sites in T-bet null mice, which have a defect in NK cell maturation, had uNK cells normal in morphology and number and normally modified spiral arteries. As Eomes null mice are not viable, real-time polymerase chain reaction comparisons between C57Bl/6J (B6) and alymphoid (Rag2(0/0)gammac0/0) mice were used to assess uNK cell expression of T-bet, Eomes, and the target genes IFN-gamma, granzyme A, and perforin. Gestation dated (gd) uterine tissues (mixed cell composition) and 200 morphologically homogeneous, laser-capture, microdissected uNK cells of different maturation stages were used. In uterus, Eomes transcripts greatly outnumbered those of T-bet, whether donors were nonpregnant or pregnant, and increased to gd10. In uNK cells, transcripts for T-bet, Eomes, and IFN-gamma were most abundant in mature stage cells, and transcripts for granzyme A and perforin were lower at this stage than in immature or senescent cells. Thus, Eomes dominance to T-bet discriminates regulation of the uNK cell subset from that observed for peripheral NK cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".