Therapeutic Effects of a Novel Aptamer on Coronaviral Infection-Induced Lung Injury and Systemic Inflammatory Responses
Bibliographic record
Abstract
BACKGROUND: Coronaviral infection-induced acute lung injury has become a major threat to public health, especially through the ongoing pandemic of COVID-19. Apta-1 is a newly discovered Aptamer that has anti-inflammatory effects on systemic septic responses. The therapeutic effects of Apta-1 on coronaviral infection-induced acute lung injury and systemic responses were evaluated in the present study. METHODS: Female A/J mice (at 12-14 weeks of age) were challenged with murine hepatitis virus 1 (MHV-1), a coronavirus, at 5000 PFU intranasally, followed by Apta-1 intravenously administered (100 mg/kg, twice) 1.5 h or 2 days after viral delivery. Animals were sacrificed at Day 2 or Day 4. Lung tissues were examined with H&E, immunohistochemistry staining, and western blotting. RT-qPCR was used for cytokine gene expression. Serum and plasma were collected for laboratory assessments. RESULTS: Apta-1 treatment reduced viral titers, prevented MHV-1-induced reduction of circulating blood volume and hemolysis, reduced alveolar space hemorrhage, and protease-activated receptor 1 (PAR-1) cleavage. Apta-1 treatment also significantly reduced chemokine (MKC, MCP-1, and RANTES) levels, as well as AST, ALT, total bilirubin, and reduced unconjugated bilirubin levels in the serum. CONCLUSION: Apta-1 showed therapeutic benefits in coronaviral infection-induced hemorrhage and PAR-1 cleavage in the lung. It also has anti-inflammatory effects systemically.
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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 | 0.002 |
| 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".