Role of Human Antigen R (HuR) in the Regulation of Pulmonary ACE2 Expression
Bibliographic record
Abstract
Patients with COPD may be at an increased risk for severe illness from COVID-19 because of ACE2 upregulation, the entry receptor for SARS-CoV-2. Chronic exposure to cigarette smoke, the main risk factor for COPD, increases pulmonary ACE2. How ACE2 expression is controlled is not known but may involve HuR, an RNA binding protein that increases protein expression by stabilizing mRNA. We hypothesized that HuR would increase ACE2 protein expression. We analyzed scRNA-seq data to profile ELAVL1 expression in distinct respiratory cell populations in COVID-19 and COPD patients. HuR expression and cellular localization was evaluated in COPD lung tissue by multiplex immunohistochemistry and in human lung cells by imaging flow cytometry. The regulation of ACE2 expression was evaluated using siRNA-mediated knockdown of HuR. There is a significant positive correlation between ELAVL1 and ACE2 in COPD cells. HuR cytoplasmic localization is higher in smoker and COPD lung tissue; there were also higher levels of cleaved HuR (CP-1). HuR binds to ACE2 mRNA but knockdown of HuR does not change ACE2 protein levels in primary human lung fibroblasts (HLFs). Our work is the first to investigate the association between ACE2 and HuR. Further investigation is needed to understand the mechanistic underpinning behind the regulation of ACE2 expression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".