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Record W3154734417 · doi:10.1016/j.immuni.2021.03.021

The CD94/NKG2A inhibitory receptor educates uterine NK cells to optimize pregnancy outcomes in humans and mice

2021· review· en· W3154734417 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImmunity · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersH2020 European Research CouncilMedical Research CouncilWellcome Trust
KeywordsBiologyOffspringAllelePregnancyReceptorHLA-GHuman leukocyte antigenFetusGeneImmunologyEndocrinologyAndrologyGeneticsAntigenMedicine

Abstract

fetched live from OpenAlex

The conserved CD94/NKG2A inhibitory receptor is expressed by nearly all human and ∼50% of mouse uterine natural killer (uNK) cells. Binding human HLA-E and mouse Qa-1, NKG2A drives NK cell education, a process of unknown physiological importance influenced by HLA-B alleles. Here, we show that NKG2A genetic ablation in dams mated with wild-type males caused suboptimal maternal vascular responses in pregnancy, accompanied by perturbed placental gene expression, reduced fetal weight, greater rates of smaller fetuses with asymmetric growth, and abnormal brain development. These are features of the human syndrome pre-eclampsia. In a genome-wide association study of 7,219 pre-eclampsia cases, we found a 7% greater relative risk associated with the maternal HLA-B allele that does not favor NKG2A education. These results show that the maternal HLA-B→HLA-E→NKG2A pathway contributes to healthy pregnancy and may have repercussions on offspring health, thus establishing the physiological relevance for NK cell education. VIDEO ABSTRACT.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.036
GPT teacher head0.329
Teacher spread0.293 · 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