Bioinformatics Analysis of the Key lncRNAs of the Viral Response Pathway in HepG2 Expressing Genotype IV Swine Hepatitis E Virus ORF3
Bibliographic record
Abstract
Hepatitis E virus (HEV) is one of the pathogens that cause viral hepatitis, and its clinical symptoms can manifest as acute, chronic viral hepatitis, or asymptomatic infection. Among them, swines are the main animal source of HEV. Open reading frame 3 (ORF3) is a multifunctional protein essential for swine hepatitis E virus (SHEV) infection and release, involved in biological processes such as intracellular signal transduction regulation. In our preliminary research, we utilized adenovirus-mediated overexpression of type IV SHEV ORF3 in HepG2 cells, extracted total RNA, and performed high-throughput long non coding RNAs (lncRNAs) and transcriptome sequencing. In this study, we screened and analyzed lncRNAs involved in the GO pathway: viral process (GO: 0016032), and combined them with differentially expressed mRNAs for target gene prediction. We identified two lncRNAs—lncRNA AL137002 (MSTRG. 7478) and lncRNA AL049840 (MSTRG. 8427)—that are associated with viral progression and have p ≤ 0.05 in HepG2 cells expressing ORF3 of porcine hepatitis E virus type IV. We predicted their five lncRNA-mRNA networks, which are lncRNA AL137002 (MSTRG. 7478)-ENST0000375440, lncRNA AL137002 (MSTRG. 7478)-ENST0000375441, lncRNA AL049840(MSTRG. 8427)-ENST0000246489, lncRNA AL049840 (MSTRG. 8427)-ENST0000554280 and lncRNA AL049840 (MSTRG. 8427)-ENST0000452929, and were used to predict their lncRNA mRNA binding sites and construct relevant molecular models. This will lay a solid foundation for further revealing the function of SHEV ORF3 and elucidating the mechanism of SHEV infection.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".