Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for an unprecedented global pandemic that has prompted attempts to mitigate its rapid transmission. A major barrier has been a limited understanding of the mechanisms that underlie its pathogenesis. Angiotensin converting enzyme (ACE) 2 may be an important receptor that the virus targets to establish infection, and this is upregulated with ACE inhibitor and angiotensin-receptor blocker (ARB) therapy. It has been suggested that avoidance of ACE inhibitor/ARB therapy may be advisable due to the theoretical risk of SARS-CoV-2 infection in these patients. A review of the literature to further investigate this possibility corroborated the significance of ACE2 for viral entry of SARS-CoV-2. However, the development of potentially fatal respiratory complications (i.e. acute respiratory distress syndrome; ARDS) appears to be influenced by a downregulation of ACE2 activity, rather than an increase. The literature suggests ACE2 has a protective role against lung injury by cleaving angiotensin II (Ang II). The effects of this are twofold: accumulated Ang II is associated with more pronounced lung deterioration, and the loss of its degradation products that have anti-inflammatory properties enables unopposed lung damage to take place. There is emerging evidence that this is also true for SARS-CoV-2 infection; increased viral load is associated with higher Ang II and extent of lung damage. Overall, the evidence indicates that viral attachment decreases, rather than increases, ACE2 activity which may contribute to the respiratory complications seen in severe cases. As such, discontinuation of ACE inhibitor/ARB therapy is currently not warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".