Role of Diet and Nutrients in SARS-CoV-2 Infection: Incidence on Oxidative Stress, Inflammatory Status and Viral Production
Bibliographic record
Abstract
Coronavirus illness (COVID-19) is an infectious pathology generated by intense severe respiratory syndrome coronavirus 2 (SARS-CoV-2). This infectious disease has emerged in 2019. The COVID-19-associated pandemic has considerably affected the way of life and the economy in the world. It is consequently crucial to find solutions allowing remedying or alleviating the effects of this infectious disease. Natural products have been in perpetual application from immemorial time given that they are attested to be efficient towards several illnesses without major side effects. Various studies have shown that plant extracts or purified molecules have a promising inhibiting impact towards coronavirus. In addition, it is substantial to understand the characteristics, susceptibility and impact of diet on patients infected with COVID-19. In this review, we recapitulate the influence of extracts or pure molecules from medicinal plants on COVID-19. We approach the possibilities of plant treatment/co-treatment and feeding applied to COVID-19. We also show coronavirus susceptibility and complications associated with nutrient deficiencies and then discuss the major food groups efficient on COVID-19 pathogenesis. Then, we covered emerging technologies using plant-based SARS-CoV-2 vaccine. We conclude by giving nutrient and plants curative therapy recommendations which are of potential interest in the COVID-19 infection and could pave the way for pharmacological treatments or co-treatments of COVID-19.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".