Is Growth Differentiation Factor 11 a Realistic Therapeutic for Aging-Dependent Muscle Defects?
Bibliographic record
Abstract
This "Controversies in Cardiovascular Research" article evaluates the evidence for and against the hypothesis that the circulating blood level of growth differentiation factor 11 (GDF11) decreases in old age and that restoring normal GDF11 levels in old animals rejuvenates their skeletal muscle and reverses pathological cardiac hypertrophy and cardiac dysfunction. Studies supporting the original GDF11 hypothesis in skeletal and cardiac muscle have not been validated by several independent groups. These new studies have either found no effects of restoring normal GDF11 levels on cardiac structure and function or have shown that increasing GDF11 or its closely related family member growth differentiation factor 8 actually impairs skeletal muscle repair in old animals. One possible explanation for what seems to be mutually exclusive findings is that the original reagent used to measure GDF11 levels also detected many other molecules so that age-dependent changes in GDF11 are still not well known. The more important issue is whether increasing blood [GDF11] repairs old skeletal muscle and reverses age-related cardiac pathologies. There are substantial new and existing data showing that GDF8/11 can exacerbate rather than rejuvenate skeletal muscle injury in old animals. There is also new evidence disputing the idea that there is pathological hypertrophy in old C57bl6 mice and that GDF11 therapy can reverse cardiac pathologies. Finally, high [GDF11] causes reductions in body and heart weight in both young and old animals, suggestive of a cachexia effect. Our conclusion is that elevating blood levels of GDF11 in the aged might cause more harm than good.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".