Habitual aerobic exercise increases plasma pentraxin 3 levels in middle-aged and elderly women
Bibliographic record
Abstract
Chronic inflammation that occurs with aging is one of the risk factors for cardiovascular disease. Regular exercise may prevent cardiovascular morbidity by decreasing chronic systematic inflammation. Additionally, excess inflammation can be reduced by the anti-inflammatory protein pentraxin 3 (PTX3). Thus, both habitual exercise and PTX3 have an anti-inflammatory effect. However, it is unclear whether regular exercise leads to increased plasma PTX3 concentration. In the present study, we investigated the effects of regular aerobic exercise on plasma PTX3 concentration in middle-aged and elderly women. Twenty-two postmenopausal women (60 ± 6 years) were randomly divided evenly into 2 groups (i.e., exercise intervention and control). Subjects in the exercise group completed 2 months of regular aerobic exercise training (walking and cycling, 30-45 min, 3-5 days·week⁻¹). Before and after the intervention, we evaluated plasma PTX3 concentration, peak oxygen uptake, blood chemistry, and arterial distensibility (carotid arterial compliance and β-stiffness) in all participants. There were no significant differences in baseline parameters between the 2 groups. Plasma PTX3 concentration was significantly increased in the exercise group after the intervention (p < 0.05). High-density lipoprotein cholesterol, peak oxygen uptake, and arterial compliance were also significantly increased (p < 0.05), while β-stiffness was markedly decreased (p < 0.01) after the intervention. On the other hand, there was no change in the parameters tested in the control group. This study demonstrates that regular aerobic exercise increases plasma PTX3 concentration with improvement of high-density lipoprotein cholesterol, peak oxygen uptake, and arterial distensibility in postmenopausal women.
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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".