Comparison of upper and lower airway expression of SARS-COV-2 receptors in mild allergic asthmatics
Bibliographic record
Abstract
Background: SARS-CoV-2 virus infects host cells through ACE2 and TMPRSS2 receptors. Protein levels of ACE2 and TMPRSS2 have not been assessed in allergic airways. Methods: We collected biopsies of endobronchial tissue from steroid-naïve mild allergic asthmatics (AA n=23) and non-asthmatic controls (NA n=11), and inferior nasal turbinate tissue from AA with allergic rhinitis (AR n=8) and non-AA/AR controls (NR n=5). Tissue was immune-stained for SARS-CoV-2 receptor ACE2 and surface protein TMPRSS2. The number of immuno-positive cells in epithelium and laminae propria was expressed per mm2 of tissue. Results: The number of cells expressing ACE2 was higher in AA endobronchial tissue compared to NA control and AR nasal tissue. TMPRSS2 was higher in AR nasal tissue compared to NR control, and higher in control NA endobronchial tissue versus control NR nasal tissue. Co-expression of ACE2+TMPRSS2 was higher in AA endobronchial tissue versus NA control and trending higher in AR nasal tissue versus NR control (p=0.08). Conclusion: Overall, ACE2 is more highly expressed in endobronchial tissue versus nasal tissue, suggesting SARS-CoV-2 may more readily infect lower versus upper airways. It is unknown whether the higher expression of ACE2 and ACE2+TMPRSS2 observed in the airways of mild allergic asthmatic donors versus control donors translates to higher susceptibility to infection.
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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 | 0.001 | 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".