Novel roles of mechanistic target of rapamycin signaling in regulating fetal growth†
Bibliographic record
Abstract
Mechanistic target of rapamycin (mTOR) signaling functions as a central regulator of cellular metabolism, growth, and survival in response to hormones, growth factors, nutrients, energy, and stress signals. Mechanistic TOR is therefore critical for the growth of most fetal organs, and global mTOR deletion is embryonic lethal. This review discusses emerging evidence suggesting that mTOR signaling also has a role as a critical hub in the overall homeostatic control of fetal growth, adjusting the fetal growth trajectory according to the ability of the maternal supply line to support fetal growth. In the fetus, liver mTOR governs the secretion and phosphorylation of insulin-like growth factor binding protein 1 (IGFBP-1) thereby controlling the bioavailability of insulin-like growth factors (IGF-I and IGF-II), which function as important growth hormones during fetal life. In the placenta, mTOR responds to a large number of growth-related signals, including amino acids, glucose, oxygen, folate, and growth factors, to regulate trophoblast mitochondrial respiration, nutrient transport, and protein synthesis, thereby influencing fetal growth. In the maternal compartment, mTOR is an integral part of a decidual nutrient sensor which links oxygen and nutrient availability to the phosphorylation of IGFBP-1 with preferential effects on the bioavailability of IGF-I in the maternal-fetal interface and in the maternal circulation. These new roles of mTOR signaling in the regulation fetal growth will help us better understand the molecular underpinnings of abnormal fetal growth, such as intrauterine growth restriction and fetal overgrowth, and may represent novel avenues for diagnostics and intervention in important pregnancy complications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".