IGF signalling and endocytosis in the human villous placenta in early pregnancy as revealed by comparing quantum dot conjugates with a soluble ligand
Bibliographic record
Abstract
A complex combination of trafficking and signalling occurs at the surface of the placenta. The system delivers maternal nutrients to the fetus and facilitates gaseous exchange, whilst mediating signal transduction to support and stimulate the growth of the placenta itself. IGF-I is acknowledged as a maternally-derived ligand important in the regulation of placental growth. Here we show that quantum dots bearing IGF can stimulate IGF receptor (IGF1R) phosphorylation in the syncytio- (maternal-facing) and cyto- (fetal-facing) trophoblast bilayer that forms the outer boundary of the placenta, in a distribution similar to the one resulting from exposure to a soluble ligand. The conjugates are internalised by a clathrin-dependent pathway and delivered to a syncytioplasmic compartment that differs from conventional late endosomes and lysosomes. Two discrete downstream responses are evident in different cellular compartments: phosphorylation of P70S6K in the non-proliferative syncytiotrophoblast and of AKT in the cytotrophoblast. Co-conjugation of IGF-quantum dots with an RGD-containing ligand permits penetration beyond the syncytium, into the cytoplasm of the underlying cytotrophoblast. These data reveal the existence of a trans-syncytial pathway that allows maternal mitotic signals to penetrate to the inner progenitor cells, which must proliferate to support placental and consequently fetal growth.
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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".