Contributions from Self-Renewal and Trafficking to the Uterine NK Cell Population of Early Pregnancy
Bibliographic record
Abstract
Uterine NK (uNK) cells are abundant in human and murine uteri during decidualization. It is unclear whether precursors of uNK (pre-uNK) cells self-renew or are recruited from other sites. To assess self-renewal of pre-uNK cells, uterine segments from NK cell-competent mice were grafted orthotopically into NK/uNK cell-deficient or wild-type mice. Only in wild-type recipients did decidualized grafts contain uNK cells, indicating that pre-uNK cells do not self-renew in uterus. To identify pre-uNK cell sources, thymus, bone marrow, lymph node, or spleen cells were grafted from virgin or pregnant NK cell-competent donors into mated NK/uNK cell-deficient recipients. Cells from secondary lymphoid tissues of pregnant donors gave high level uNK cell reconstitution, which was independent of chemokine receptors CCR2 or CCR5. Pregnancy-induced changes to lymphocyte-endothelial cell interactions were documented using adhesion of human lymphocytes to frozen mouse tissue sections under shear. A dynamic increase was observed in L-selectin- and alpha(4) integrin-dependent adhesion of CD56(bright) NK cells to decidualizing uterus and in human PBL adhesion to lymph node endothelium. These data support a model that attributes the dramatic increases in human and murine uNK cells during decidualization to precursor cell recruitment.
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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".