Overview of SARS-CoV-2 Outbreak and Potential Therapeutic Strategies
Bibliographic record
Abstract
The increasing severity of the ongoing COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains an urgent global issue to be addressed. Despite several heroic and concerted efforts, morbidity and mortality continue to increase. Providing a therapeutic respite in the form of an effective antiviral agent and, potentially, a vaccine remains an uphill task. The SARS-CoV-2 is an enveloped positive-sense single-stranded RNA virus, with an unusual potential for rapid reproduction and mutation, transmitted majorly through aerosols. The virus replicates in the mucosa of the upper respiratory tract, which accounts for its early symptoms. Multiple organs can be affected and can also be asymptomatic. SARS-CoV-2 has genomic similitude to the SARS-CoV and MERS-CoV viruses, being members of the same family, Betacoronaviridae. These similarities have been explored as potential therapeutic targets. Developing a drug at a pandemic speed usually involves initial drug repurposing strategies, and the ongoing pandemic has not been an exception. With notable recruitments ranging from the old antimalarial agent, Chloroquine/Hydroxychloroquine, to the macrolide Azithromycin, to ACE inhibitors, to antiviral agents like Lopinavir/Ritonavir and more recently, the RNA polymerase inhibitor, Remdesivir, the search is still ongoing. Sourcing from highly reputable reports and studies conducted so far, this review elaborates on the biology of the SARS-CoV-2 virus, highlighting its structure, shared genetic similarities and variants, with respect to being potential therapeutic targets, as well as a commentary on the therapeutic approaches that have been explored in the quest to develop an effective antiviral agent.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".