CD34 mediates dendritic cell trafficking in hypersensitivity pneumonitis (92.1)
Bibliographic record
Abstract
Abstract Hypersensitivity pneumonitis (HP) is an inflammatory lung disease characterized by a chronic T cell airway infiltration. Dendritic cells (DC) have been reported to play a crucial role in trafficking of antigen to the lymph nodes and antigen presentation in this disease. However, little is know about what triggers and mediates DC trafficking in HP. CD34 is a sialomucin best known for it’s expression on hematopoietic progenitors. This protein, which was recently reported as a facilitator of cell trafficking, is also expressed on a few subsets of mature cells such as DCs. We therefore explored whether CD34 expression in DCs was involved in DC trafficking to and from the lung in a mouse model of HP, using wild type and Cd34-/- mice. Lung inflammation and DC recruitment was evaluated in both strains. Results show that lack of CD34 expression leads to a lower lung inflammation (as characterized by lower total cell counts in the broncho-alveolar lavage). DC recruitment was reduced in the alveoli of Cd34-/- mice, but was increased in the lung tissue. Using bone marrow chimeric mice, this effect was attributed to the Cd34-/- environment (including potentially radio-resistant DCs). Lastly, intraveinous injection of wild type DCs reconstituted disease in Cd34-/- mice. We conclude that CD34 could mediate DC trafficking in HP and possibly other inflammatory lung diseases. Supported by the Canadian Institutes of Health Research (CIHR), AllerGen Network Centre of Excellence (KMM), Multiple Sclerosis Society of Canada (JLB), Michael Smith Foundation for Health Research (KMM, MRB), and FRSQ (MRB)
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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) | 0.002 | 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".