Naloxone for COVID-19
c19early.org
COVID-19 Treatment Clinical Evidence
COVID-19 involves the interplay of 400+ viral and host proteins and factors, providing many therapeutic targets.
c19early analyzes 6,000+ studies for 210+ treatments—over 17 million hours of research.
Only three high-profit early treatments are approved in the US.
In reality, many treatments reduce risk,
with 25 low-cost treatments approved across 163 countries.
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Naso/
oropharyngeal treatment Effective Treatment directly to the primary source of initial infection. -
Healthy lifestyles Protective Exercise, sunlight, a healthy diet, and good sleep all reduce risk.
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Immune support Effective Vitamins A, C, D, and zinc show reduced risk, as with other viruses.
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Thermotherapy Effective Methods for increasing internal body temperature, enhancing immune system function.
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Systemic agents Effective Many systemic agents reduce risk, and may be required when infection progresses.
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High-profit systemic agents Conditional Effective, but with greater access and cost barriers.
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Monoclonal antibodies Limited Utility Effective but rarely used—high cost, variant dependence, IV/SC admin.
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Acetaminophen Harmful Increased risk of severe outcomes and mortality.
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Remdesivir Harmful Increased mortality with longer followup. Increased kidney and liver injury, cardiac disorders.
Naloxone may be beneficial for
COVID-19 according to the studies below.
COVID-19 involves the interplay of 400+ viral and host proteins and factors providing many therapeutic targets.
Scientists have proposed 11,000+ potential treatments.
c19early.org analyzes
210+ treatments.
We have not reviewed naloxone in detail.
, The innate immune response in SARS-CoV2 infection: focus on toll-like receptor 4 in severe disease outcomes, Frontiers in Immunology, doi:10.3389/fimmu.2025.1658396
Innate immunity is the first line of defense against infections, including the detection and response to SARS-CoV-2. Cells of the innate system are usually activated within hours after pathogen exposure and do not generate conventional immunological memory. In this review, the current knowledge of the innate immune cells and of pattern-recognition receptors in sensing and responding to SARS-CoV-2 to mount a protective response has been shortly reviewed. Subsequently, the evasion strategies of the virus, as the inhibition of IFN-I/III production and autophagic response, counteracting the innate cell activity (including NK cells), have been briefly outlined. In the course of the infection, these strategies are also capable of rendering dysfunctional most innate cells, thus deeply interfering with the onset and maintenance of adaptive immunity. Possible mechanism(s) for the maintenance of dysfunctional innate immune response are also discussed. In this context, the importance of a rapid and robust activation of innate immunity through toll-like receptor (TLR) 4 as a key paradigm central to host defense against COVID-19 pathogenesis is also illustrated. We also discuss how the viral excess plus inflammatory signals upregulating TLR4 on innate cells may initiate a vicious loop which maintains and improves hyperinflammation, leading to the most critical outcomes. Targeting the TLR4 or its signaling pathway may be a promising therapeutic strategy, offering the dual benefits of viral suppression and decreasing inflammation.
, Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding, Scientific Reports, doi:10.1038/s41598-023-30095-z
AbstractThe search for an effective drug is still urgent for COVID-19 as no drug with proven clinical efficacy is available. Finding the new purpose of an approved or investigational drug, known as drug repurposing, has become increasingly popular in recent years. We propose here a new drug repurposing approach for COVID-19, based on knowledge graph (KG) embeddings. Our approach learns “ensemble embeddings” of entities and relations in a COVID-19 centric KG, in order to get a better latent representation of the graph elements. Ensemble KG-embeddings are subsequently used in a deep neural network trained for discovering potential drugs for COVID-19. Compared to related works, we retrieve more in-trial drugs among our top-ranked predictions, thus giving greater confidence in our prediction for out-of-trial drugs. For the first time to our knowledge, molecular docking is then used to evaluate the predictions obtained from drug repurposing using KG embedding. We show that Fosinopril is a potential ligand for the SARS-CoV-2 nsp13 target. We also provide explanations of our predictions thanks to rules extracted from the KG and instanciated by KG-derived explanatory paths. Molecular evaluation and explanatory paths bring reliability to our results and constitute new complementary and reusable methods for assessing KG-based drug repurposing.