Deletion of the Fanconi Anemia C Gene in Mice Leads to Skeletal Anomalies and Defective Bone Mineralization and Microarchitecture
Bibliographic record
Abstract
ABSTRACT Fanconi anemia (FA) is a rare genetic disorder associated with a progressive decline in hematopoietic stem cells leading to bone marrow failure. FA is also characterized by a variety of developmental defects including short stature and skeletal malformations. More than half of children affected with FA have radial-ray abnormalities, and many patients have early onset osteopenia/osteoporosis. Although many Fanconi anemia genes have been identified and a molecular pathway defined, the underlying mechanism leading to bone defects remains elusive. To understand the role of FA genes in skeletal development and bone microarchitecture, we evaluated bone physiology during embryogenesis and in adult FancA- and FancC-deficient mice. We found that both FancA-/- and FancC-/- embryos have abnormal skeletal development shown by skeletal malformations, growth delay, and reduced bone mineralization. FancC-/- adult mice present altered bone morphology and microarchitecture with a significant decrease in cortical bone mineral density in a sex-specific manner. Mechanical testing revealed that male but not female FancC-/- mice show reduced bone strength compared with their wild-type littermates. Ex vivo cultures showed that FancA-/- and FancC-/- bone marrow–derived mesenchymal stem cells (BMMSC) have impaired differentiation capabilities together with altered gene expression profiles. Our results suggest that defective bone physiology in FA occurs in utero and possibly results from altered BMMSC function. These results provide valuable insights into the mechanism involved in FA skeletal defects. © 2018 American Society for Bone and Mineral Research.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".