Mapping Quantitative Trait Loci That Influence Femoral Cross-sectional Area in Mice
Bibliographic record
Abstract
Size and shape are critical determinants of the mechanical properties of skeletal elements and can be anticipated to be highly heritable. Moreover, the genes responsible may be independent of those that regulate bone mineral density (BMD). To begin to identify the heritable determinants of skeletal geometry, we have examined femoral cross-sectional area (FCSA) in male and female mice from two inbred strains of mice with divergent FCSA (C57BL/6 [B6] and DBA/2 [D2]), a large genetically heterogeneous population (n = 964) of B6D2F2 mice and 18 BXD recombinant inbred (RI) strains derived from their F2 cross. Femora were harvested from 16-week-old mice and FCSA (bone and marrow space enclosed within the periosteum) was measured at the midshaft by digital image analysis. In all mouse populations examined, FCSA was positively correlated with body weight and weight-corrected FCSA (WC-FCSA) values were normally distributed in the BXD-RI and F2 populations, suggesting polygenic control of this trait. Genome-wide quantitative trait locus (QTL) analysis of the B6D2F2 population revealed regions on four different chromosomes that were very strongly linked to WC-FCSA (chromosomes 6, 8, 10, and X) in both genders. Evidence of gender-specific genetic influences on femoral geometry was also identified at three other chromosomal sites (chromosomes 2, 7, and 12). Supporting evidence for the WC-FCSA QTLs on chromosomes 2, 7, 8, 10, and 12 also was present in the RI strains. Interestingly, none of these WC-FCSA QTLs were identified in our previous QTL analysis of whole body BMD in the same B6D2F2 population. Thus, the genetic determinants of bone size appear to be largely, if not entirely, distinct from those that regulate BMD attainment. The identification of the genes responsible for geometric differences in bone development should reveal fundamentally important processes in the control of skeletal integrity.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".