Bibliographic record
Abstract
Communication between cells is vital for maintenance of immune homeostasis and is also required for rapid and effective immune responses.Nowhere is this balance of activity more important than at mucosal surfaces such as the respiratory tract, where resident cells must ignore potentially antigenic inhaled material while responding swiftly to clear viruses and bacteria.In this issue, Bourdonnay et al. describe a novel form of intercellular communication that helps to explain how alveolar macrophages and epithelial cells maintain pulmonary homeostasis.The function of SOCS proteins is to constrain JAK-STAT signaling and repress inflammatory reactions.We do not usually expect to find these intracellular signaling molecules in extracellular compartments, but Bourdonnay et al. showed that lung-resident alveolar macrophages (AMs) were able to secrete SOCS1 within exosomes and SOCS3 within extracellular microparticles.Uptake of these extracellular vesicles by alveolar epithelial cells (AECs) allowed SOCS1 and -3 to suppress STAT signaling following activation by cytokines.The authors demonstrated that this novel extracellular transfer system was promoted by IL-10 and PGE 2 and inhibited by LPS.The phenomenon was demonstrated in a number of model systems including both rats and mice and also, importantly, in human AMs.Moreover, secretion was not simply dependent on expression of SOCS3, because fibroblasts expressed high levels of SOCS3 but did not secrete it.Any in vitro finding needs to be robustly tested in vivo to demonstrate a physiologic effect.The authors showed that SOCS3 was abundant in bronchiolar lavage (BAL) even in naive mice; SOCS3 levels increased after administration of PGE 2 to the lungs and decreased after pulmonary delivery of LPS.Moreover, SOCS3 was retrieved from BAL from healthy human volunteers.Interestingly, exposure to cigarette smoke reduced levels of both SOCS1 and -3 in both mice and humans; so, smoking could lead to unchecked JAK-STAT activation, thereby contributing to inflammatory responses.Although it remains to be seen whether this particular form of epithelial-macrophage communication operates during respiratory infection, these data are important because they shed some light on the complex interactions that maintain homeostasis within the lung.It may be possible to exploit this system in order to down-regulate inflammation following infection and ultimately facilitate the restoration of immune homeostasis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".