Design and Development of a Pseudotyped-lentivirus for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)
Bibliographic record
Abstract
Background and purpose: Pseudoviruses, due to their immunity and adaptability, are valuable tools for developing vaccines and therapeutic drugs, particularly for emerging viruses. SARS-CoV-2, due to its high mortality rate and ease of transmission, should be handled under Biosafety Level 3 conditions, making the development of vaccines and therapeutic drugs challenging in many research centers. The present study aimed to produce a lentivirus pseudotype that can be used in neutralization assays based on pseudovirus under Biosafety Level 2 conditions. Materials and methods: The SARS-CoV-2 Spike protein gene was inserted into the HIV-1 genome. Confirmation of entry was obtained through flow cytometry, electron microscopy, and immunofluorescence. Finally, the neutralization capacity of convalescent COVID-19 patients' sera was measured using the pseudovirus-based neutralization assay. Results: The results of flow cytometry, electron microscopy, and immunofluorescence confirmed the entry of the Spike gene. Furthermore, the sera of convalescent patients showed significantly higher neutralizing capacity compared to the control group that had not been exposed to SARS-CoV-2. Conclusion: The results of this study demonstrated that the use of the produced lentivirus pseudotype can measure the neutralizing capacity of patients' sera, and the pseudovirus-based neutralization assay serves as a suitable alternative for assessing the neutralization of live SARS-CoV-2. Moreover, this test can effectively evaluate vaccines or therapeutic drugs for combating this deadly virus.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".