FGF-23 Is a Negative Regulator of Prenatal and Postnatal Erythropoiesis
Bibliographic record
Abstract
Abnormal blood cell production is associated with chronic kidney disease (CKD) and cardiovascular disease (CVD). Bone-derived FGF-23 (fibroblast growth factor-23) regulates phosphate homeostasis and bone mineralization. Genetic deletion of Fgf-23 in mice (Fgf-23(-/-)) results in hypervitaminosis D, abnormal mineral metabolism, and reduced lymphatic organ size. Elevated FGF-23 levels are linked to CKD and greater risk of CVD, left ventricular hypertrophy, and mortality in dialysis patients. However, whether FGF-23 is involved in the regulation of erythropoiesis is unknown. Here we report that loss of FGF-23 results in increased hematopoietic stem cell frequency associated with increased erythropoiesis in peripheral blood and bone marrow in young adult mice. In particular, these hematopoietic changes are also detected in fetal livers, suggesting that they are not the result of altered bone marrow niche alone. Most importantly, administration of FGF-23 in wild-type mice results in a rapid decrease in erythropoiesis. Finally, we show that the effect of FGF-23 on erythropoiesis is independent of the high vitamin D levels in these mice. Our studies suggest a novel role for FGF-23 in erythrocyte production and differentiation and suggest that elevated FGF-23 levels contribute to the pathogenesis of anemia in patients with CKD and CVD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".