Skeletal Muscle Erythropoietin Expression Is Responsive to Hypoxia and Exercise
Bibliographic record
Abstract
PURPOSE: Erythropoietin is responsible for regulating the growth and development of red blood cells. Reports conflict on whether skeletal muscle is able to produce erythropoietin and release it into circulation and if exercise affects this. We set out to determine how erythropoietin is regulated in skeletal muscle and to determine whether skeletal muscle-derived erythropoietin can stimulate erythropoiesis. METHODS: Using an in vitro approach, we exposed proliferating and differentiated skeletal muscle cells to various forms of exercise-induced physiological stimuli and measured erythropoietin gene expression. To understand if skeletal muscle cells were able to stimulate erythropoiesis, independent of other cell types found in skeletal muscle, we used myoblast-conditioned media to treat bone marrow and to measure erythropoiesis through flow cytometry. We also measured erythropoietin expression and hypoxia in mice subjected to an exercise protocol designed to induce skeletal muscle oxygen stress. RESULTS: Hypoxia increased erythropoietin expression in C2C12 myoblasts, myotubes, and primary myoblasts in vitro by 50% to 130%. Bone marrow treated with media conditioned with hypoxic myoblasts for 24 h increased the number of Ter-119-positive cells by 32%. An erythropoietin-neutralizing antibody prevented this increase. Compared with unexercised controls, exhaustive exercise increased skeletal muscle HIF1α levels by 50% and HIF2α levels by 20%. Moreover, exercised skeletal muscle erythropoietin expression was 70% higher. CONCLUSION: These results demonstrate that skeletal muscle produces erythropoietin in a hypoxia and HIF-dependent manner and that hypoxia-treated muscle is capable of stimulating erythropoiesis in vitro.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".