Eccentric, but not concentric muscle contraction induce inflammation and impairs fibrinolysis in healthy young men
Bibliographic record
Abstract
Different types of muscle contraction can cause different damage to the musculature and differences in inflammatory responses. Acute increases in circulatory inflammation markers can influence the crosstalk between coagulation and fibrinolysis processes, increasing the risk of thrombus formation and detrimental cardiovascular events. The aim of this study was to analyze the effects of concentric and eccentric exercise on hemostasis markers, C-reactive protein (CRP), and the relationship between these variables. Eleven healthy subjects with a mean age of 25.4 ± 2.8, non-smokers, with no history of cardiovascular disease and blood type O, randomly performed an isokinetic exercise protocol consisting of 75 concentric (CP) or eccentric (EP) contractions of knee extension, divided into five sets of 15 repetitions combined with 30-s rest. Blood samples for analysis of FVIII, von Willebrand factor, tissue plasminogen activator (t-PA), plasminogen activator inhibitor type-1 (PAI-1), and CRP were collected pre, post, 24 h, and 48 h after each protocol. Increased levels of CRP at 48 h in EP versus CP ( p = 0.002), increased PAI-1 activity 48 h in EP versus CP ( p = 0.044), and a reduction in t-PA at 48 h when compared with post-protocol in both protocols ( p = 0.001). A correlation was found between CRP and PAI-1 at 48 h of PE ( r2 = 0.69; p = 0.02). This study showed that both EP and CP increase the clotting process, albeit only the exercise performed eccentrically induces inhibition of fibrinolysis. This is possibly due to the increase in PAI-1 48 h after the protocol, which correlates with the increase in inflammation as demonstrated by the CRP levels.
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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 | 0.001 |
| 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".