Bibliographic record
Abstract
Induced by airway inflammation, the CLCA gene family products exist both as secreted and membrane‐associated proteins. The proteins modulate ion channel function, drive mucus production and generally have a pleotropic effect on airway inflammation. How CLCAs deliver such a pleotropic effect on airway inflammation is poorly understood. Here we show that hCLCA1, the primary up‐regulated human CLCA orthologue in airway inflammation, is able to modulate macrophage activation. In order for a macrophage to undertake a role of either host defense, wound healing or immune regulation, it must become “activated”. This is usually a receptor driven signal transduction event resulting in gene transcription of cytokines. Using primary porcine alveolar macrophages and the U‐937 macrophage cell model, we were able to show that conditioned media with hCLCA1 significantly increased macrophage activation over control. The pro‐inflammatory cytokines IL‐1beta, IL‐6, TNF‐alpha, IL‐8 were increased, and the anti‐inflammatory cytokine IL‐10 was decreased in the U‐937 cell line. We found this effect to be independent of hCLCA1's metalloprotease domain. Subsequent purification of hCLCA1 produced a similar response demonstrating that the effect is primarily due to hCLCA1. These are the first findings demonstrating that hCLCA1 can deliver an immune modulating effect as a signaling molecule. Funding: SHRF, EHRF and NSERC
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) | 0.000 | 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) | 0.002 | 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".