Endurance exercise training promotes medullary hematopoiesis
Bibliographic record
Abstract
Endurance exercise is a poorly defined yet powerful mediator of hematopoiesis. The purpose of this study was to directly investigate the effects of endurance exercise training on hematopoiesis and to identify potential mechanisms responsible for any observed changes. Four-week-old male C57Bl/6 mice were trained on a treadmill at progressive speeds over a 10-wk period. Tissues were harvested 2 d following the final training session. Flow cytometry, the cobblestone area-forming cell assay, and the methycellulose colony-forming unit assay were used to assess medullary and mobilized hematopoietic stem and progenitor cells. Quantitative real-time PCR and Western blots were used to measure hematopoietic cytokine production. Histochemistry was also used to assess adaptations to exercise in the bone marrow niche. Depending on the cell type, endurance training increased medullary and mobilized hematopoietic stem and progenitor cell content from 50 to 800%. Training also reduced marrow cavity fat by 78%. Skeletal muscle hematopoietic cytokine expression was also increased at least 60% by training. Sedentary mice served as controls for the above experiments. In conclusion, endurance exercise training greatly promotes hematopoiesis and does so through improvements in medullary niche architecture as well as increased skeletal muscle hematopoietic cytokine production.
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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 | 0.000 | 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".