Equine alveolar macrophages and monocyte-derived macrophages respond differently to an inflammatory stimulus
Bibliographic record
Abstract
Alveolar macrophages (AMs) are the predominant innate immune cell in the distal respiratory tract. During inflammatory responses, AMs may be supplemented by blood monocytes, which differentiate into monocyte-derived macrophages (MDMs). Macrophages play important roles in a variety of common equine lower airway diseases, including severe equine asthma (SEA). In an experimental model, an inhaled mixture of Aspergillus fumigatus spores, lipopolysaccharide, and silica microspheres (FLS), induced SEA exacerbation in susceptible horses. However, whether equine AMs and MDMs have differing immunophenotypes and cytokine responses to FLS stimulation is unknown. To address these questions, alveolar macrophages/monocytes (AMMs) were isolated from bronchoalveolar lavage fluid and MDMs derived from blood of six healthy horses. Separately, AMMs and MDMs were cultured with and without FLS for six hours after which cell surface marker expression and cytokine production were analyzed by flow cytometry and a bead-based multiplex assay, respectively. Results showed that regardless of exposure conditions, AMMs had significantly higher surface expression of CD163 and CD206 than MDMs. Incubation with FLS induced secretion of IL-1β, IL-8, TNF-α and IFN-γ in AMMs, and IL-8, IL-10 and TNF-α in MDMs. These results suggest that AMMs have a greater proinflammatory response to in vitro FLS stimulation than MDMs, inferring differing roles in equine lung inflammation. Variability in recruitment and function of monocyte-macrophage populations warrant more detailed in vivo investigation in both homeostatic and diseased states.
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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 | 0.001 |
| 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".