ACE2 (Angiotensin-Converting Enzyme 2) in Cardiopulmonary Diseases
Bibliographic record
Abstract
Discovery of ACE2 (angiotensin-converting enzyme 2) revealed that the renin-angiotensin system has 2 counterbalancing arms. ACE2 is a major player in the protective arm, highly expressed in lungs and gut with the ability to mitigate cardiopulmonary diseases such as inflammatory lung disease. ACE2 also exhibits activities involving gut microbiome, nutrition, and as a chaperone stabilizing the neutral amino acid transporter, B 0 AT1, in gut. But the current interest in ACE2 arises because it is the cell surface receptor for the novel coronavirus, severe acute respiratory syndrome coronavirus-2, to infect host cells, similar to severe acute respiratory syndrome coronavirus-2. This suggests that ACE2 be considered harmful, however, because of its important other roles, it is paradoxically a potential therapeutic target for cardiopulmonary diseases, including coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2. This review describes the discovery of ACE2, its physiological functions, and its place in the renin-angiotensin system. It illustrates new analyses of the structure of ACE2 that provides better understanding of its actions particularly in lung and gut, shedding of ACE2 by ADAM17 (a disintegrin and metallopeptidase domain 17 protein), and role of TMPRSS2 (transmembrane serine proteases 2) in severe acute respiratory syndrome coronavirus-2 entry into host cells. Cardiopulmonary diseases are associated with decreased ACE2 activity and the mitigation by increasing ACE2 activity along with its therapeutic relevance are addressed. Finally, the potential use of ACE2 as a treatment target in COVID-19, despite its role to allow viral entry into host cells, is suggested.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".