A Functional Assessment of Fetal Liver and Monocyte-Derived Macrophages in the Lung Alveolar Environment
Bibliographic record
Abstract
It is becoming clear that every organ is seeded by a population of fetal liver-derived macrophages that are replaced at different rates by monocyte-derived macrophages. Using the Ms4a3tdTomato reporter mouse that reports on monocyte-derived alveolar macrophages (Mo-AMs) and our ability to examine AM function using our multichannel intravital microscopy, we examined the fetal-liver derived alveolar macrophage (FL-AM) and Mo-AM populations within the same mouse under various environmental conditions. The experiments unveiled that AMs migrated from alveolus to alveolus and phagocytosed bacteria identically regardless of ontogenic origin. Using 50 PFU of influenza A virus (IAV) determined using the Madin-Darby canine kidney (MDCK) cell line, we noted that both populations were susceptible to IAV-induced immunoparalysis, which also led to impaired phagocytosis of secondary bacterial infections. Both FL-AMs and Mo-AMs were trained by β-glucan to resist IAV-induced paralysis. Over time (40 wk), Mo-AMs began to outperform FL-AMs, although both populations were still sensitive to IAV. Our data also show that clodronate depletion of AMs leads to replenishment, but by FL-AMs, and these macrophages do show some functional impairment for a limited time. Overall, the system is designed such that new macrophages rapidly assume the function of tissue-resident macrophages when both populations are examined in an identical environment. These data do differ from artificial depletion methods that compare Mo-AMs and FL-AMs.
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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".