The effects of aging and exercise on lung mechanics, surfactant and alveolar macrophages
Bibliographic record
Abstract
Introduction It has been well established that advancing age leads to changes to the respiratory system and an associated susceptibility to lung diseases. Furthermore, exercise may counteract this pulmonary disease susceptibility. To start to investigate the underlying processes of these effects we explored the baseline characteristics due to aging and exercise on lung mechanics and on two important components of a healthy pulmonary environment, alveolar macrophage function and the pulmonary surfactant system. It was hypothesized that aging would impact lung mechanics, macrophage polarization and the status of the surfactant system, and that these changes would be mitigated by exercise. Experimental approach: Male C57BL/6 mice were housed from 2–3 to 22 months, for the aged group, or until 4 months of age for young control mice. Mice in both the young and aged groups were randomized to either voluntarily running exercise or non‐exercise for a 2 month period. Mice were euthanized and lung mechanics were analyzed using a Flexivent ventilator. Subsequently, the lungs were lavaged to obtain pulmonary surfactant and alveolar macrophages. Pulmonary surfactant was analyzed for surfactant pool sizes and activity whereas alveolar macrophages were examined for a response to pro‐and anti‐inflammatory stimuli. Results Changes in lung mechanics, such as increased compliance and decreased airway resistance, were observed in the aged cohorts. These changes were not affected by exercise. The quantity as well as the biophysical activity of the pulmonary surfactant system was unaffected by either aging or exercise. More alveolar macrophages were recovered from exercising aged mice as compared to both the young and non‐exercising groups. Support or Funding Information Western Strategic Support, Lawson Internal Research Funds This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0.000 |
| 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".