Switching Host Metabolism as an Approach to Dampen SARS-CoV-2 Infection
Bibliographic record
Abstract
BACKGROUND: COVID-19 pandemic, a global threat, adversely affects all daily lives, altered governmental plans around the world, and urges the development of therapeutics and prophylactics to avoid the expansion of the viral infection. With the recent gradual opening after long lockdown, several recommendations have been placed, with dietary modification as one of the most important approaches that have been appraised. SUMMARY: Here, we are reviewing how changing the host metabolism, particularly changing the host metabolic state from the carbohydrate-dependent glycolytic state to a fat-dependent ketogenic state, may affect viral replication. Furthermore, the impact of intermittent fasting (IF) in triggering metabolic switch along with the impact of supplementation with medium-chain triglycerides (MCTs) such as lauric acid in repressing the envelope formation and viral replication is also addressed. The amalgamation of IF and a ketogenic diet rich in MCTs is thought to work as a prophylactic measure for normal people and adjunct therapy for infected persons. Key Message: A diet regimen of ketogenic breakfast along with supplementation with two doses of lauric acid-rich MCTs at breakfast and lunch times, followed by 8-12-h IF and a dinner rich with fruits and vegetables, could be a potential prophylactic strategy and adjuvant therapy to combat SARS-CoV-2 infections.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".