Dysregulation of endocytic machinery and ACE2 in small airways of smokers and COPD patients can augment their susceptibility to SARS-CoV-2 (COVID-19) infections
Bibliographic record
Abstract
Lungs of smokers and chronic obstructive pulmonary disease (COPD) are severely compromised and are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) attack. The dangerous combination of enhanced SARS-CoV-2 attachment receptor protein ACE2 along with an increase in endocytic vacuoles will enable viral attachment, entry, and replication. The objective of the study was to identify the presence of SARS-CoV-2 host attachment receptor angiotensin-converting enzyme-2 (ACE2) along with endocytic vacuoles, early endosome antigen-1 (EEA1), late endosome marker RAB7, cathepsin-L, and lysosomal associated membrane protein-1 (LAMP-1) as lysosome markers in the airways of smokers and COPD patients. The study design was cross-sectional and involved lung resections from 39 patients in total, which included 19 patients with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I or GOLD stage II COPD, of which 9 were current smokers with COPD (COPD-CS) and 10 were ex-smokers with COPD (COPD-ES), 10 were normal lung function smokers, and 10 were never-smoking normal controls. Immunostaining for ACE2, EEA1, RAB7, and cathepsin-L was done. A comparative description for ACE2, EEA1, RAB7, and cathepsin-L expression pattern is provided for the patient groups. Furthermore, staining intensity for LAMP-1 lysosomes was measured as the ratio of the LAMP-1-stained areas per total area of epithelium or subepithelium, using Image ProPlus v7.0 software. LAMP-1 expression showed a positive correlation to patient smoking history while in COPD LAMP-1 negatively correlated to lung function. The active presence of ACE2 protein along with endocytic vacuoles such as early/late endosomes and lysosomes in the small airways of smokers and COPD patients provides evidence that these patient groups could be more susceptible to COVID-19.
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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) | 0.001 | 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".