Gene Expression Profiles during <i>In Vivo</i> Human Rhinovirus Infection: Insights into the Host Response
Bibliographic record
Abstract
RATIONALE: Human rhinovirus infections cause colds and trigger exacerbations of lower airway diseases. OBJECTIVES: To define changes in gene expression profiles during in vivo rhinovirus infections. METHODS: Nasal epithelial scrapings were obtained before and during experimental rhinovirus infection, and gene expression was evaluated by microarray. Naturally acquired rhinovirus infections, cultured human epithelial cells, and short interfering RNA knockdown were used to further evaluate the role of viperin in rhinovirus infections. MEASUREMENTS AND MAIN RESULTS: Symptom scores and viral titers were measured in subjects inoculated with rhinovirus or sham control, and changes in gene expression were assessed 8 and 48 hours after inoculation. Real-time reverse transcription-polymerase chain reaction for viperin and rhinoviruses was used in naturally acquired infections, and viperin mRNA levels and viral titers were measured in cultured cells. Rhinovirus-induced changes in gene expression were not observed 8 hours after viral infection, but 11,887 gene transcripts were significantly altered in scrapings obtained 2 days postinoculation. Major groups of up-regulated genes included chemokines, signaling molecules, interferon-responsive genes, and antivirals. Viperin expression was further examined and also was increased in naturally acquired rhinovirus infections, as well as in cultured human epithelial cells infected with intact, but not replication-deficient, rhinovirus. Knockdown of viperin with short interfering RNA increased rhinovirus replication in infected epithelial cells. CONCLUSIONS: Rhinovirus infection significantly alters the expression of many genes associated with the immune response, including chemokines and antivirals. The data obtained provide insights into the host response to rhinovirus infection and identify potential novel targets for further evaluation.
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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".