Premature aging‐like phenotype in <i>fibroblast growth factor 23</i> null mice is a vitamin D‐mediated process
Bibliographic record
Abstract
Fibroblast growth factor 23 null mice (Fgf-23-/-) have a short lifespan and show numerous biochemical and morphological features consistent with premature aging-like phenotypes, including kyphosis, severe muscle wasting, hypogonadism, osteopenia, emphysema, uncoordinated movement, T cell dysregulation, and atrophy of the intestinal villi, skin, thymus, and spleen. Furthermore, increased vitamin D activities in homozygous mutants are associated with severe atherosclerosis and widespread soft tissue calcifications; ablation of vitamin D activity from Fgf-23-/- mice, by genetically deleting the 1alpha(OH)ase gene, eliminates atherosclerosis and ectopic calcifications and significantly rescues premature aging-like features of Fgf-23-/- mice, resulting in prolonged survival of Fgf-23-/-/1alpha(OH)ase-/- double mutants. Our results indicate a novel role of Fgf-23 in developing premature aging-like features through regulating vitamin D homeostasis. Finally, our data support a new model of interactions among Fgf-23, vitamin D, and klotho, a gene described as being associated with premature aging process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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".