Isolated hearts treated with skeletal muscle homogenates exhibit altered function
Bibliographic record
Abstract
Skeletal muscle fiber damage and necrosis can result in the release of intracellular molecules into the extracellular environment. These molecules, termed damage-associated molecular patterns (DAMPs), can act as signals capable of initiating immune and/or inflammatory responses through interactions with pattern recognition receptors. To investigate whether skeletal muscle DAMPs interact with the heart and alter cardiac function, isolated rat hearts were perfused for 75 min with buffer containing 1 μg/ml of either soleus (slow), white gastrocnemius (WG, fast), or heat-stressed white gastrocnemius (HSWG) skeletal muscle homogenates. Left ventricular developed pressure (LVDP) and rates of pressure increase/decrease (± dP/dt) were measured using the Langendorff technique. Compared to controls, no changes in LVDP or +dP/dt were observed over the 75-min perfusion when homogenates from the WG muscles were added. In contrast, at 30 min and thereafter, a decreased LVDP and +dP/dt was observed in the hearts treated with soleus muscle homogenates. The hearts treated with HSWG homogenates also showed a decrease in LVDP from 45 min until the end of perfusion. These results suggest that molecules present in slow muscle and heat-stressed muscle are capable of altering cardiac function. Thus, muscle fiber type and/or heat shock protein content of skeletal muscles may be factors that influence cardiac function following skeletal muscle damage.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".