Cross-Talk Between Alveolar Macrophages and Lung Epithelial Cells is Essential to Maintain Lung Homeostasis
Bibliographic record
Abstract
The main function of the lung is to perform gas exchange while maintaining lung homeostasis despite environmental pathogenic and non-pathogenic elements contained in inhaled air. Resident cells must keep lung homeostasis and eliminate pathogens by inducing protective immune response and silently remove innocuous particles. Which lung cell type is crucial for this function is still subject to debate, with reports favoring either alveolar macrophages (AMs) or lung epithelial cells (ECs) including airway and alveolar ECs. AMs are the main immune cells in the lung in steady-state and their function is mainly to dampen inflammatory responses. In addition, they phagocytose inhaled particles and apoptotic cells and can initiate and resolve inflammatory responses to pathogens. Although AMs release a plethora of mediators that modulate immune responses, ECs also play an essential role as they are more than just a physical barrier. They produce anti-microbial peptides and can secrete a variety of mediators that can modulate immune responses and AM functions. Furthermore, ECs can maintain AMs in a quiescent state by expressing anti-inflammatory membrane proteins such as CD200. Thus, AMs and ECs are both very important to maintain lung homeostasis and have to coordinate their action to protect the organism against infection. Thus, AMs and lung ECs communicate with each other using different mechanisms including mediators, membrane glycoproteins and their receptors, gap junction channels, and extracellular vesicles. This review will revisit characteristics and functions of AMs and lung ECs as well as different communication mechanisms these cells utilize to maintain lung immune balance and response to pathogens. A better understanding of the cross-talk between AMs and lung ECs may help develop new therapeutic strategies for lung pathogenesis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".