HLA-A, HSPA5, IGFBP5 and PSMA2 Are Restriction Factors for Zika Virus Growth in Astrocytic Cells
Bibliographic record
Abstract
mosquitoes Following its major outbreaks in 2013, 2014 and 2016, WHO declared it a Public Health Emergency of International Concern. Symptoms of ZIKV infection include acute fever, conjunctivitis, headache, muscle & joint pain and malaise. Cases of its transmission also have been reported via perinatal, sexual and transfusion transmission. ZIKV pathologies include meningo-encephalitis and myelitis in the central nervous system (CNS) and Guillain-Barré syndrome and acute transient polyneuritis in the peripheral nervous system (PNS). Drugs like azithromycin have been tested as inhibitors of ZIKV infection but no vaccines or treatments are currently available. Astrocytes are the most abundant cells in the CNS and among the first cells in CNS infected by ZIKV; (2) Methods: We previously used SOMAScan proteomics to study ZIKV-infected astrocytic cells. Here, we use mass spectrometric analyses to further explain dysregulations in the cellular expression profile of glioblastoma astrocytoma U251 cells. We also knocked down (KD) some of the U251 cellular proteins using siRNAs and observed the impact on ZIKV replication and infectivity; (3) Results & Conclusions: The top ZIKV dysregulated cellular networks were antimicrobial response, cell death, and energy production while top dysregulated functions were antigen presentation, viral replication and cytopathic impact. Th1 and interferon signaling pathways were among the top dysregulated canonical pathways. siRNA-mediated KD of HLA-A, IGFBP5, PSMA2 and HSPA5 increased ZIKV titers and protein synthesis, indicating they are ZIKV restriction factors. ZIKV infection also restored HLA-A expression in HLA-A KD cells by 48 h post-infection, suggesting interactions between this gene product and ZIKV.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".