Dietary and Serum Phosphorus Regulate Fibroblast Growth Factor 23 Expression and 1,25-Dihydroxyvitamin D Metabolism in Mice
Bibliographic record
Abstract
Fibroblast growth factor-23 (FGF-23) is a novel circulating peptide that regulates phosphorus (Pi) and vitamin D metabolism, but the mechanisms by which circulating FGF-23 itself is regulated are unknown. To determine whether the serum FGF-23 concentration is regulated by dietary intake of Pi, we fed wild-type (WT), Npt2a gene-ablated (Npt2a(-/-)), and Hyp mice diets containing varying Pi contents (0.02-1.65%). In WT mice, increases in dietary Pi intake from 0.02-1.65% induced a 7-fold increase in serum FGF-23 and a 3-fold increase in serum Pi concentrations. Across the range of dietary Pi, serum FGF-23 concentrations varied directly with serum Pi concentrations (r(2) = 0.72; P < 0.001). In Npt2a(-/-) mice, serum FGF-23 concentrations were significantly lower than in WT mice, and these differences could be accounted for by the lower serum Pi levels in Npt2a(-/-) mice. The serum concentrations of FGF-23 in Hyp mice were 5- to 25-fold higher than values in WT mice, and the values varied with dietary Pi intake. Fgf-23 mRNA abundance in calvaria was significantly higher in Hyp mice than in WT mice on the 1% Pi diet; in both groups of mice, fgf-23 mRNA abundance in calvarial bone was suppressed by 85% on the low (0.02%) Pi diet. In WT mice fed the low (0.02%) Pi diet, renal mitochondrial 1alpha-hydroxylase activity and renal 1alpha-hydroxylase (P450c1alpha) mRNA abundance were significantly higher than in mice fed the higher Pi diets and varied inversely with serum FGF-23 concentrations (r(2) = 0.86 and r(2) = 0.64; P < 0.001, respectively). The present data demonstrate that dietary Pi regulates the serum FGF-23 concentration in mice, and such regulation is independent of phex function. The data suggest that genotype-dependent and dietary Pi-induced changes in the serum FGF-23 concentration reflect changes in fgf-23 gene expression in bone.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".