Regulation of Lean Mass, Bone Mass, and Exercise Tolerance by the Central Melanocortin System
Bibliographic record
Abstract
Signaling via the type 4-melanocortin receptor (MC4R) is an important determinant of body weight in mice and humans, where loss of function mutations lead to significant obesity. Humans with mutations in the MC4R experience an increase in lean mass. However, the simultaneous accrual of fat mass in such individuals may contribute to this effect via mechanical loading. We therefore examined the relationship of fat mass and lean mass in mice lacking the type-4 melanocortin receptor (MC4RKO). We demonstrate that MC4RKO mice display increased lean body mass. Further, this is not dependent on changes in adipose mass, as MC4RKO mice possess more lean body mass than diet-induced obese (DIO) wild type mice with equivalent fat mass. To examine potential sources of the increased lean mass in MC4RKO mice, bone mass and strength were examined in MC4RKO mice. Both parameters increase with age in MC4RKO mice, which likely contributes to increases in lean body mass. We functionally characterized the increased lean mass in MC4RKO mice by examining their capacity for treadmill running. MC4R deficiency results in a decrease in exercise performance. No changes in the ratio of oxidative to glycolytic fibers were seen, however MC4RKO mice demonstrate a significantly reduced heart rate, which may underlie their impaired exercise performance. The reduced exercise capacity we report in the MC4RKO mouse has potential clinical ramifications, as efforts to control body weight in humans with melanocortin deficiency may be ineffective due to poor tolerance for physical activity.
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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 | 0.001 | 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".