Tumor Necrosis Factor-α (TNF-α) Stimulates Chemotactic Response in Mouse Myogenic Cells
Bibliographic record
Abstract
Migration of transplanted myogenic cells occurs during both embryogenesis and regeneration of skeletal muscles and is important for successful myoblast transplantation, but little is known about factors that promote chemotaxis of these cells. Tumor necrosis factor-alpha (TNF-alpha) is known to induce chemotactic effect on several cell types. In this study, we investigated its influence on the in vitro and in vivo motility of C2C12 and primary myoblasts. In the in vitro test performed in the blind-well Boyden chambers, we showed that TNF-alpha (50-400 U/ml) significantly enhanced the ability of myogenic cells to migrate. The dose-response curve for this factor was bell shaped, with maximum activity in the 200 U/ml range. In the in vivo test, intramuscular administration of TNF-alpha was performed by an Alzet pump connected to a perforated polyethylene microtube inserted in the tibialis anterior (TA) of CD1 mice. In these experiments, myoblasts were injected under the muscle epimysium. The recipient mice were immunosuppressed with FK506. Our results showed that, 5 days after myoblast transplantation, cells migrated further in the muscles infused with TNF-alpha than in the muscles not exposed to TNF-alpha. TNF-alpha not only has a chemotactic activity but may also modify cell migration via its action on matrix metalloproteinase (MMP) expression. The proteolytic activities of the MMPs secreted in the muscles were thus also assessed by gelatin zymography. The results showed an increased of MMP-2 and MMP-9 transcripts in the TNF-alpha-infused muscles injected with myogenic cells. Myoblast migration during transplantation may be enhanced by overlapping gradients of several effector molecules such as TNF-alpha, interferon-gamma (INF-gamma), and interleukins, released at the site of muscle injury. We propose that TNF-alpha may promote myoblast migration directly through chemotactic activity and indirectly by enhancing MMP activity at the site of muscle injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".