Alveolar macrophage depletion is associated with increased surfactant pool sizes in adult rats
Bibliographic record
Abstract
Pulmonary surfactant is a lipid-protein material that is essential for normal lung function. Maintaining normal and consistent alveolar amounts of surfactant is in part dependent on clearance of surfactant by alveolar macrophages (AM). The present study utilized a rat model of AM depletion to determine the impact on surfactant pool sizes and function over time. Male Sprague-Dawley rats were anesthetized and intratracheally instilled with PBS-liposomes (PBS-L) or dichloromethylene diphosphonic acid (DMDP) containing liposomes (DMDP-L) and were killed at various time points up to 21 days for compliance measurements, AM cell counts, and surfactant analysis. AM numbers were significantly decreased 1, 2, and 3 days after instillation in DMDP-L vs. PBS-L, with 72% depletion at 3 days. AM numbers returned to normal levels by 5 days. In DMDP-L rats, there was a rapid increase in surfactant-phospholipid pools, showing a ninefold increase in the amount of surfactant in the lavage 3 days after liposome instillation. Surfactant accumulation progressed up to 7 days, with pools normalizing by 21 days. The increase in surfactant was due to increases in both subfractions of surfactant, the large aggregates (LA) and small aggregates. Surfactant protein A levels, relative to LA phospholipids, were not increased. There was a decreased extent of surfactant conversion in vitro for LA from DMDP-L rats compared with controls. It is concluded that the procedure of AM depletion significantly affects surfactant metabolism. The increased endogenous surfactant must be considered when utilizing the AM depletion model to study the role of these cells during lung insults.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".