Combination of Angiotensin (1-7) Agonists and Convalescent Plasma as a New Strategy to Overcome Angiotensin Converting Enzyme 2 (ACE2) Inhibition for the Treatment of COVID-19
Bibliographic record
Abstract
Coronavirus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the most concerning health problem worldwide. SARS-CoV-2 infects cells by binding to angiotensin-converting enzyme 2 (ACE2). It is believed that the differential response to SARS-CoV-2 is correlated with the differential expression of ACE2. Several reports proposed the use of ACE2 pharmacological inhibitors and ACE2 antibodies to block viral entry. However, ACE2 inhibition is associated with lung and cardiovascular pathology and would probably increase the pathogenesis of COVID-19. Therefore, utilizing ACE2 soluble analogs to block viral entry while rescuing ACE2 activity has been proposed. Despite their protective effects, such analogs can form a circulating reservoir of the virus, thus accelerating its spread in the body. Levels of ACE2 are reduced following viral infection, possibly due to increased viral entry and lysis of ACE2 positive cells. Downregulation of ACE2/Ang (1-7) axis is associated with Ang II upregulation. Of note, while Ang (1-7) exerts protective effects on the lung and cardiovasculature, Ang II elicits pro-inflammatory and pro-fibrotic detrimental effects by binding to the angiotensin type 1 receptor (AT1R). Indeed, AT1R blockers (ARBs) can alleviate the harmful effects associated with Ang II upregulation while increasing ACE2 expression and thus the risk of viral infection. Therefore, Ang (1-7) agonists seem to be a better treatment option. Another approach is the transfusion of convalescent plasma from recovered patients with deteriorated symptoms. Indeed, this appears to be promising due to the neutralizing capacity of anti-COVID-19 antibodies. In light of these considerations, we encourage the adoption of Ang (1-7) agonists and convalescent plasma conjugated therapy for the treatment of COVID-19 patients. This therapeutic regimen is expected to be a safer choice since it possesses the proven ability to neutralize the virus while ensuring lung and cardiovascular protection through modulation of the inflammatory response.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".