Metformin Regulates the Inflammatory Response of Human Monocytes to SARS-CoV-2 Spike Glycoprotein
Bibliographic record
Abstract
Background: A hyperinflammatory state is associated with coronavirus disease 2019 (COVID-19) severity and mortality. This inflammatory process begins when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the hosts respiratory epithelium using the spike glycoprotein (S protein) to bind to the hosts cellular angiotensin-converting enzyme 2 receptor. Downstream proinflammatory response of immune cells eventually results in production of excessive pro-inflammatory cytokines in some individuals. Metformin (MTF) has been proposed as an adjunctive therapy for COVID-19 due to its antiviral and anti-inflammatory properties. Methods: In our study, we compared the inflammatory response of monocytes to various SARS-CoV-2 S proteins in cells treated with MTF. Results: We observed a differential interferon regulatory factor (IRF) and nuclear factor kappa B activation by SARS-CoV-2 S proteins in human monocytes, and a decreased IRF activation, although this was not statistically significant. MTF treatment reduced type I interferon (IFN) transcription upon human monocytes stimulation with a stabilized trimeric S protein. Conclusion: As type I IFNs can regulate the expression of other cytokines, MTF treatment may offer protection to severe COVID-19, and help reduce disease severity and mortality. Clin Infect Immun. 2021;6(3):82-85 doi: https://doi.org/10.14740/cii137
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.096 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".