Placental Remote Control of Fetal Metabolism: Trophoblast mTOR Signaling Regulates Liver IGFBP-1 Phosphorylation and IGF-1 Bioavailability
Bibliographic record
Abstract
The mechanisms mediating the restricted growth in intrauterine growth restriction (IUGR) remain to be fully established. Mechanistic target of rapamycin (mTOR) signaling functions as a placental nutrient sensor, indirectly influencing fetal growth by regulating placental function. Increased secretion and the phosphorylation of fetal liver IGFBP-1 are known to markedly decrease the bioavailability of IGF-1, a major fetal growth factor. We hypothesized that an inhibition of trophoblast mTOR increases liver IGFBP-1 secretion and phosphorylation. We collected conditioned media (CM) from cultured primary human trophoblast (PHT) cells with a silenced RAPTOR (specific inhibition of mTOR Complex 1), RICTOR (inhibition of mTOR Complex 2), or DEPTOR (activates both mTOR Complexes). Subsequently, HepG2 cells, a well-established model for human fetal hepatocytes, were cultured in CM from PHT cells, and IGFBP-1 secretion and phosphorylation were determined. CM from PHT cells with either mTORC1 or mTORC2 inhibition caused the marked hyperphosphorylation of IGFBP-1 in HepG2 cells as determined by 2D-immunoblotting while Parallel Reaction Monitoring-Mass Spectrometry (PRM-MS) identified increased dually phosphorylated Ser169 + Ser174. Furthermore, using the same samples, PRM-MS identified multiple CK2 peptides coimmunoprecipitated with IGFBP-1 and greater CK2 autophosphorylation, indicating the activation of CK2, a key enzyme mediating IGFBP-1 phosphorylation. Increased IGFBP-1 phosphorylation inhibited IGF-1 function, as determined by the reduced IGF-1R autophosphorylation. Conversely, CM from PHT cells with mTOR activation decreased IGFBP-1 phosphorylation. CM from non-trophoblast cells with mTORC1 or mTORC2 inhibition had no effect on HepG2 IGFBP-1 phosphorylation. Placental mTOR signaling may regulate fetal growth by the remote control of fetal liver IGFBP-1 phosphorylation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".