Vero Cell Proteomic Changes Induced by Zika Virus Infection
Bibliographic record
Abstract
The re-emergence and the recent spread of the Zika virus (ZIKV) has raised significant global concerns due to lack of information in patient diagnosis and management. Thus, in addition to gaining more basic information about ZIKV biology, appropriate interventions and management strategies are being sought to control ZIKV-associated diseases and its spread. This study's objective is to identify host cell proteins that are significantly dysregulated during ZIKV infection. SOMAScan, a novel aptamer-based assay, is used to simultaneously screen >1300 host proteins to detect ZIKV-induced host protein dysregulation at multiple time points during infection. A total of 125 Vero cell host proteins, including cytokines such as CXCL11 and CCL5, interferon stimulated gene 15, and translation initiation factors EIF5A and EIF4G2, are significantly dysregulated after ZIKV infection. Bioinformatic analyses of 77 host proteins, that are significantly dysregulated ≥1.25-fold, identify several activated biological processes, including the JAK/STAT, Tec kinase, and complement cascade pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".