L-Carnitine Tartrate Downregulates the ACE2 Receptor and Limits SARS-CoV-2 Infection
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for one of the worst pandemics in modern history. Several prevention and treatment strategies have been designed and evaluated in recent months either through the repurposing of existing treatments or the development of new drugs and vaccines. In this study, we show that L-carnitine tartrate supplementation in humans and rodents led to significant decreases of key host dependency factors, notably angiotensin-converting enzyme 2 (ACE2), transmembrane protease serine 2 (TMPRSS2), and Furin, which are responsible for viral attachment, viral spike S-protein cleavage, and priming for viral fusion and entry. Interestingly, pre-treatment of Calu-3, human lung epithelial cells, with L-carnitine tartrate led to a significant and dose-dependent inhibition of the infection by SARS-CoV-2. Infection inhibition coincided with a significant decrease in ACE2 mRNA expression levels. These data suggest that L-carnitine tartrate should be tested with appropriate trials in humans for the possibility to limit SARS-CoV-2 infection.
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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".