Placental metabolic reprogramming: do changes in the mix of energy-generating substrates modulate fetal growth?
Bibliographic record
Abstract
Insufficient oxygen leads to the cessation of growth in favor of cellular survival. Our unique model of high-altitude human pregnancy indicates that hypoxia-induced reductions in fetal growth occur at higher levels of oxygen than previously described. Fetal PO(2) is surprisingly high and fetal oxygen consumption unaffected by high altitude, whereas fetal glucose delivery and consumption decrease. Placental delivery of energy-generating substrates to the fetus is thus altered by mild hypoxia, resulting in maintained fetal oxygenation but a relative fetal hypoglycemia. Our data point to this altered mix of substrates as a potential initiating factor in reduced fetal growth, since oxygen delivery is adequate. These data support the existence, in the placenta, of metabolic reprogramming mechanisms, previously documented in tumor cells, whereby HIF-1 stimulates reductions in mitochondrial oxygen consumption at the cost of increased glucose consumption. Decreased oxygen consumption is not due to substrate (oxygen) limitation but rather results from active inhibition of mitochondrial oxygen utilization. We suggest that under hypoxic conditions, metabolic reprogramming in the placenta decreases mitochondrial oxygen consumption and increases anerobic glucose consumption, altering the mix of energy-generating substrates available for transfer to the fetus. Increased oxygen is available to support the fetus, but at the cost of less glucose availability, leading to a hypoglycemia-mediated decrease in fetal growth. Our data suggest that metabolic reprogramming may be an initiating step in the progression to more severe forms of fetal growth restriction and points to the placenta as the pivotal source of fetal programming in response to an adverse intrauterine environment.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".