SARS‐coronavirus modulation of myocardial ACE2 expression and inflammation in patients with SARS
Bibliographic record
Abstract
BACKGROUND: Angiotensin converting enzyme 2 (ACE2), a monocarboxylase that degrades angiotensin II to angiotensin 1-7, is also the functional receptor for severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) and is highly expressed in the lungs and heart. Patients with SARS also suffered from cardiac disease including arrhythmias, sudden cardiac death, and systolic and diastolic dysfunction. MATERIALS AND METHODS: We studied mice infected with the human strain of the SARS-CoV and encephalomyocarditis virus and examined ACE2 mRNA and protein expression. Autopsy heart samples from patients who succumbed to the SARS crisis in Toronto (Canada) were used to investigate the impact of SARS on myocardial structure, inflammation and ACE2 protein expression. RESULTS: Pulmonary infection with the human SARS-CoV in mice led to an ACE2-dependent myocardial infection with a marked decrease in ACE2 expression confirming a critical role of ACE2 in mediating SARS-CoV infection in the heart. The SARS-CoV viral RNA was detected in 35% (7/20) of autopsied human heart samples obtained from patients who succumbed to the SARS crisis during the Toronto SARS outbreak. Macrophage-specific staining showed a marked increase in macrophage infiltration with evidence of myocardial damage in patients who had SARS-CoV in their hearts. The presence of SARS-CoV in the heart was also associated with marked reductions in ACE2 protein expression. CONCLUSIONS: Our data show that SARS-CoV can mediate myocardial inflammation and damage associated with down-regulation of myocardial ACE2 system, which may be responsible for the myocardial dysfunction and adverse cardiac outcomes in patients with SARS.
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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".