Ginseng Diminishes Lung Disease in Mice Immunized with Formalin-Inactivated Respiratory Syncytial Virus After Challenge by Modulating Host Immune Responses
Bibliographic record
Abstract
Formalin-inactivated respiratory syncytial virus (FI-RSV) immunization is known to cause severe pulmonary inflammatory disease after subsequent RSV infection. Ginseng has been used in humans for thousands of years due to its potential health benefits. We investigated whether ginseng would have immune modulating effects on RSV infection in mice previously immunized with FI-RSV. Oral administration of mice with ginseng increased IgG2a isotype antibody responses to FI-RSV immunization, indicating T-helper type 1 (Th1) immune responses. Ginseng-treated mice that were nonimmunized or previously immunized with FI-RSV showed improved protection against RSV challenge compared with control mice without ginseng treatment. Ginseng-mediated improved clinical outcomes after live RSV infection were evidenced by diminished weight losses, decreased interleukin-4 cytokine production but increased interferon-γ production, modulation of CD3 T-cell populations toward a Th1 response, and reduced inflammatory response. Ginseng-mediated protective host immune modulation against RSV pulmonary inflammation was observed in different strains of wild-type and mutant mice. These results indicate that ginseng can modulate host immune responses to FI-RSV immunization and RSV infection, resulting in protective effects against pulmonary inflammatory disease.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".