Anti-COVID-19 potential of Azadirachta indica (Neem) leaf extract
Bibliographic record
Abstract
COVID-19 is caused by infection with the “severe acute respiratory syndrome coronavirus-2″ (i.e., SARS-CoV-2). This is an enveloped virus having a positive sense, single-stranded RNA genome; like the two earlier viruses SARS-CoV and the Middle East respiratory syndrome (MERS) virus. COVID-19 is unique in that, in the severe case, it has the propensity to affect multiple organs, leading to multiple organ distress syndrome (MODS), and causing high morbidity and mortality in the extreme case. In addition, comorbidities like age, cardiovascular disease, diabetes and its complications, obesity, are risk factors for severe COVID-19. It turns out that a most plausible, simple, single explanation for this propensity for MODS is the pivotal involvement of the vascular endothelium (VE). This is a consequence of the fact that the VE seamlessly connects all the entire vascular bed in the body, thus linking all the target organs (heart, lungs, kidney, liver, brain) and systems. Infection with SARS-CoV-2 leads to hyper-inflammation yielding uncontrolled production of a mixture of cytokines, chemokines, reactive oxygen species, nitric oxide, oxidative stress, acute phase proteins (e.g., C-reactive protein), and other pro-inflammatory substances. In the extreme case, a cytokine storm is created. Displacement of the virus bound to the VE, and/or inhibition of binding of the virus, would constitute an effective strategy for preventing COVID-19. In this regard, the acetone-water extract of the leaf of the Neem (Azadirachta indica) plant has been known to prevent the adherence of malaria parasitized red blood cells (pRBCs) to VE; prevent cytoadherence of cancer cells in metastasis; and prevent HIV from invading target T lymphocytes. We therefore hypothesize that this Neem leaf acetone-water extract will prevent the binding of SARS-CoV-2 to the VE, and therefore be an effective therapeutic formulation against COVID-19. It is therefore advocated herein that this extract be investigated through rigorous clinical trials for this purpose. It has the advantages of being (i) readily available, and renewable in favor of the populations positioned to benefit from it; (ii) simple to prepare; and (iii) devoid of any detectable toxicity.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".