Pro-Inflammatory Mediation of Myoblast Proliferation
Bibliographic record
Abstract
Skeletal muscle satellite cell function is largely dictated by the surrounding environment following injury. Immune cell infiltration dominates the extracellular space in the injured area, resulting in increased cytokine concentrations. While increased pro-inflammatory cytokine expression has been previously established in the first 3 days following injury, less is known about the time course of cytokine expression and the specific mechanisms of cytokine induced myoblast function. Therefore, the expression of IL-1β and IL-6 at several time points following injury, and their effects on myoblast proliferation, were examined. In order to do this, skeletal muscle was injured using barium chloride in mice and tissue was collected 1, 5, 10, and 28 days following injury. Mechanisms of cytokine induced proliferation were determined in cell culture using both primary and C2C12 myoblasts. It was found that there is a ∼20-fold increase in IL-1β (p≤0.05) and IL-6 (p = 0.06) expression 5 days following injury. IL-1β increased proliferation of both primary and C2C12 cells ∼25%. IL-1β stimulation also resulted in increased NF-κB activity, likely contributing to the increased proliferation. These data demonstrate for the first time that IL-1β alone can increase the mitogenic activity of primary skeletal muscle satellite cells and offer insight into the mechanisms dictating satellite cell function following injury.
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 | 0.000 | 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 | 0.001 |
| 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 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".