Optimization of the replication of hepatitis E virus genotype 3 <i>in vitro</i>
Bibliographic record
Abstract
AIMS: Hepatitis E virus (HEV) is responsible for ∼20 million human infections worldwide every year. The genotypes HEV-3 and HEV-4 are zoonotic and are responsible for most of the autochthonous HEV cases in high-income countries. There are several cell culture systems that allow for propagation of different HEV genotypes in vitro. One of these systems uses human lung carcinoma cells (A549), and was further optimized for propagation of HEV-3 47832c strain. In this study, we investigated the effect of different media supplements as well as microRNA-122 (miR-122) on improving the replication of HEV-3 47832c in A549 cells. METHODS AND RESULTS: We observed that supplementation of maintenance media with 5% fetal bovine serum was sufficient for efficient replication of HEV-3, and verified the positive effect of media supplementation with Amphotericin B, MgCl2, and dimethyl sulfoxide on replication of HEV-3. We have also demonstrated that adding miR-122 mimics to the culture media does not have any significant effect on the replication of HEV-3 47832c. CONCLUSIONS: Herein, we detected over a 6-fold increase in HEV-3 replication in A549/D3 cells by adding all three supplements: Amphotericin B, MgCl2, and dimethyl sulfoxide to the culture media, while demonstrating that miR-122 might not play a key role in replication of HEV-3 47832c.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".