Posttranscriptional Regulation of Human Leukocyte Antigen G During Human Extravillous Cytotrophoblast Differentiation1
Bibliographic record
Abstract
Human maternal tolerance to a semiallogenic fetus may be maintained, in part, by the unusual expression pattern of antigen-presenting molecules in placental trophoblast cells. Extravillous cytotrophoblast (EVC) cells, which invade the maternal decidua, express high levels of human leukocyte antigen G (HLA-G), a nonclassical, major histocompatibility complex (MHC) class I molecule. HLA-G transcripts have been detected in tumors and other tissues, yet protein accumulation is rare. We show that, within EVC cells themselves, the mRNA is more broadly expressed than the protein. Specifically, accumulation of HLA-G protein was markedly delayed during EVC cell differentiation. To elucidate this mechanism, we performed a comprehensive analysis comparing the expression of HLA-G and proteins essential for MHC class I expression at the cell surface. The transporter for antigen processing proteins TAP1 and TAP2, as well as tapasin and beta(2)-microglobulin, appeared to be coordinately expressed throughout EVC cell columns. Strikingly, they all accumulated well in advance of the HLA-G protein but concurrently with its mRNA. A similar delay in the accumulation of the HLA-G protein was observed in vitro, using cultures of chorionic villi. We conclude that posttranscriptional regulation of HLA-G is fundamental to EVC cell development and is achieved independently of the peptide loading system. This represents a novel mechanism of MHC class I regulation.
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 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".