Puerarin: A Potential Therapeutic for SARS-CoV-2 and Hantavirus Co-Infection
Bibliographic record
Abstract
Patients with Hantavirus-caused epidemic hemorrhagic fever (EHF) are at risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is currently no validated EHF/SARS-CoV-2 strategy. Several studies have recently shown Puerarin, a natural product, has potent antiviral properties. The goal of present study was to determine the mechanism of puerarin in patients with EHF/COVID-19. We use network pharmacology and bioinformatics to investigate the possible pharmacological targets, bioactivities, and molecular mechanisms of puerarin in the treatment of patients with EHF/SARS-CoV-2. The study investigated the pathogenesis of COVID-19 and EHF and the signaling pathway impacted by puerarin. 68 common genes linked to puerarin and EHF/SARS-CoV-2 were discovered during the investigation. By using protein-protein interaction (PPI) network, we identified RELA, JUN, NF-B1, NF-B2, and FOS as potential therapeutic targets. The bioactivity and signaling pathways of puerarin have also been demonstrated in the treatment of EHF and COVID-19. According to present study, puerarin could reduce excessive immune responses and inflammation through the NF-B, TNF, and HIF-1 signaling pathways. This study explored the potential therapeutic targets and mechanisms of Puerarin in the treatment of EHF/COVID-19.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".