Quantitative Proteomic Analyses of Influenza Virus-Infected Cultured Human Lung Cells
Bibliographic record
Abstract
Because they are obligate intracellular parasites, all viruses are exclusively and intimately dependent upon host cells for replication. Viruses, in turn, induce profound changes within cells, including apoptosis, morphological changes, and activation of signaling pathways. Many of these alterations have been analyzed by gene arrays, which measure the cellular "transcriptome." Until recently, it has not been possible to extend comparable types of studies to globally examine all the host cellular proteins, which are the actual effector molecules. We have used stable isotope labeling by amino acids in cell culture (SILAC), combined with high-throughput two-dimensional (2-D) high-performance liquid chromatography (HPLC)/mass spectrometry, to determine quantitative differences in host proteins after infection of human lung A549 cells with human influenza virus A/PR/8/34 (H1N1) for 24 h. Of the 4,689 identified and measured cytosolic protein pairs, 127 were significantly upregulated at >95% confidence, 153 were significantly downregulated at >95% confidence, and a total of 87 proteins were upregulated or downregulated more than 5-fold at >99% confidence. Gene ontology and pathway analyses indicated differentially regulated proteins and included those involved in host cell immunity and antigen presentation, cell adhesion, metabolism, protein function, signal transduction, and transcription pathways.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".