Time course effects of exercise training on pulmonary injury induced by exposure to cigarette smoke in mice
Bibliographic record
Abstract
Rationale: Experimental study recently developed by our group showed that the regular physical training attenuated the pulmonary injury in an experimental model of chronic exposure to cigarette smoke (CS). Objective : The goal of this study was to evaluate the time course effects of the mechanisms related to the exercise protection. Methods : Male C57BL/6 mice were divided into four groups: control, exercise, smoke and smoke+exercise. Exposure to CS and treadmill training were carried out: 5 days/week for 4, 8 and 12 weeks. We evaluated lung mechanics by using a FlexiVent ventilator (Scireq, Montreal, Canada); the number of total and differentials cells in bronchoalveolar lavage fluid (BALF); mean linear intercept (LM); TNFα, IL-1β, IL6, IL10, TBARS, antioxidant enzymes (SOD, Gpx and TRAP) in the lung tissue. Results: Exercise protected mice exposed to CS from the: reduction on tissue damping and tissue elastance (p<0.01) after 12 weeks; increase in total inflammatory cells in BALF preferably due to recruitment of neutrophils and lymphocytes after 8 weeks and lymphocytes and macrophages after 12 weeks (p<0.001) and increase in LM after 12 weeks. The protection conferred by exercise in mice exposed to CS was induced by an increase in IL6, IL10 and antioxidants enzymes (SOD, GSH/GSSG, TRAP) and a decrease in TNFα and TBARS levels. Conclusion: Exercise protection in mice exposed to CS is more pronounced after 12 weeks and the mechanisms involved include anti-inflammatory mediators and antioxidants enzymes that have an important role in COPD development. .
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".