Neither Absence Nor Excess of FGF23 Disturbs Murine Fetal-Placental Phosphorus Homeostasis or Prenatal Skeletal Development and Mineralization
Bibliographic record
Abstract
Fibroblast growth factor-23 (FGF23) controls serum phosphorus largely through actions on the kidneys to excrete phosphorus and reduce calcitriol. Although these actions are well established in adults and children, the role that FGF23 plays in regulating fetal phosphorus metabolism has not been previously studied. We used several mouse models to study the effect of endogenous deficiency or excess of FGF23 on fetal phosphorus metabolism. We found that intact FGF23 does not cross the placenta from mother to fetus, but wild-type fetuses normally have intact FGF23 levels that approximately equal the maternal level. Deletion of Fgf23 or 7.8-fold higher serum FGF23 levels did not disturb any parameter of fetal mineral homeostasis, including serum and amniotic fluid phosphorus, skeletal morphology, skeletal mineral content, and placental phosphorus transport. Placentas and fetal kidneys abundantly express FGF23 target genes. Cyp24a1 was significantly reduced in Fgf23 null kidneys and was significantly increased in Phex null placentas and fetal kidneys. Phex null kidneys also showed reduced expression of Klotho. However, these changes in gene expression did not disturb any physiological parameter related to phosphorus. A 50% reduction in FGF23 also failed to affect renal phosphorus excretion into amniotic fluid when either PTH or the vitamin D receptor were absent. In conclusion, FGF23 is not an important regulator of fetal phosphorous metabolism. The active delivery of phosphorus across the placenta does not require FGF23, and that process overrides any effects that absence or excess of FGF23 might otherwise have on phosphate handling by the fetal kidneys.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".