Murine Fetal Serum Phosphorus is Set Independent of FGF23 and PTH, Except in the Presence of Maternal Phosphate Loading
Bibliographic record
Abstract
Fibroblast growth factor 23 (FGF23) appears to play no role until after birth, given unaltered phosphate and bone metabolism in Fgf23- and Klotho-null fetuses. However, in those studies maternal serum phosphorus was normal. We studied whether maternal phosphate loading alters fetal serum phosphorus and invokes a fetal FGF23 or parathyroid hormone (PTH) response. C57BL/6 wild-type (WT) female mice received low (0.3%), normal (0.7%), or high (1.65%) phosphate diets beginning 1 week prior to mating to WT males. Fgf23+/- female mice received the normal or high-phosphate diets 1 week before mating to Fgf23+/- males. One day before expected birth, we harvested maternal and fetal blood, intact fetuses, placentas, and fetal kidneys. Increasing phosphate intake in WT resulted in progressively higher maternal serum phosphorus and FGF23 during pregnancy, while PTH remained undetectable. Fetal serum phosphorus was independent of the maternal phosphorus and PTH remained low, but FGF23 showed a small nonsignificant increase with high maternal serum phosphorus. There were no differences in fetal ash weight and mineral content, or placental gene expression. High phosphate intake in Fgf23+/- mice also increased maternal serum phosphorus and FGF23, but there was no change in PTH. WT fetuses remained unaffected by maternal high-phosphate intake, while Fgf23-null fetuses became hyperphosphatemic but had no change in PTH, skeletal ash weight or mineral content. In conclusion, fetal phosphate metabolism is generally regulated independently of maternal serum phosphorus and fetal FGF23 or PTH. However, maternal phosphate loading reveals that fetal FGF23 can defend against the development of fetal hyperphosphatemia.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".