Uterine natural killer cells: insights into their cellular and molecular biology from mouse modelling
Bibliographic record
Abstract
In primates, including women, and in rodents, natural killer lymphocytes (NK cells) have a unique relationship with the decidualizing uterus. Implantation sites from genetically modified and transplanted mice have proven useful models for understanding potential mechanisms involved in the recruitment, activation and functions of human CD56(bright) uterine (u)NK cells. Key findings are reviewed in this article. In mice, uNK precursor cells are recruited from secondary lymphoid tissues and are activated coincident with their uterine arrival. uNK cells proliferate, produce cytokines (interferon gamma (IFN-gamma) and interleukin 18 (IL-18) and IL-27), and terminally differentiate into granulated lymphocytes. Many uNK cells proliferate within the myometrium at each implantation site forming a structure, the mesometrial lymphoid aggregate of pregnancy (MLAp) that surrounds blood vessels servicing each placenta. Post-mitotic uNK cells are abundant within decidua basalis; frequently (<25%) associating with spiral arteries, intramurally and intraluminally. From mid-gestation, numbers of uNK cells decline. Studies of implantation sites in mice lacking uNK cells, IFN-gamma, components of IFN-gamma-induction and -signalling pathways or IFN-gamma-regulated genes indicate that uNK cell-derived IFN-gamma is essential in triggering pregnancy-induced spiral artery modification. Decidual maintenance and uNK cell death are additional effects of uNK cell-derived IFN-gamma. Thus, during the first half of gestation, uNK cells contribute to and sustain important changes in the maternal placental bed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".