Cruciferous vegetable-derived indole-3-carbinol prevents coronavirus cell egression mechanisms in tracheal and intestinal 3D in vitro models.
Bibliographic record
Abstract
The potential antiviral effects of indole-3-carbinol (I3C), a phytochemical found in Cruciferous vegetables, were investigated. Fibroblasts and epithelial cells were co-cultured on Alvetex® scaffolds, to obtain ad hoc 3D in vitro platforms able to mimic the trachea and intestinal mucosae, which represent the primary structures involved in the coronavirus pathogenesis. The two barriers generated in vitro were treated with various concentrations of I3C for different incubation periods. A protective effect of I3C on both intestinal and trachea models was demonstrated. A significant reduction in the transcription of the two main genes belonging to the Homologous to E6AP C-terminus (HECT)-E3 ligase family members, namely NEDD4 E3 Ubiquitin Protein Ligase (NEDD4) and WW Domain Containing E3 Ubiquitin Protein Ligase 1 (WWP1), which promote virus matrix protein ubiquitination and inhibit viral egression, were detected. These findings indicate I3C potential effect in preventing coronavirus cell egression processes that inhibit viral production. Although further studies are needed to clarify the molecular mechanisms whereby HECT family members control virus life cycle, this work paves the way to the possible therapeutic use of new natural compounds that may reduce the clinical severity of future pandemics.
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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) | 0.000 | 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) | 0.001 | 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".