Human Fetal Astrocytes Infected with Zika Virus Exhibit Delayed Apoptosis and Resistance to Interferon: Implications for Persistence
Bibliographic record
Abstract
Zika virus (ZIKV) infection and persistence during pregnancy can lead to microcephaly and other fetal neurological disorders collectively known as Congenital Zika Syndrome. The immunological and virological events that contribute to the establishment of persistent ZIKV infection in humans are unclear though. Here we show that human fetal astrocytes (HFAs), the most abundant cell type in the central nervous system, become persistently infected with ZIKV resulting in continuous viral shedding for at least one month; a process that is facilitated by TIM/TAM receptors. HFAs are relatively resistant to ZIKV-induced apoptosis, a factor that may be important for chronic infection of these cells. Once infection was established, interferon treatment did not reduce virus replication. Moreover, the fact that the innate immune system was highly activated in persistently infected HFAs indicates that the virus can thrive in the presence of a sustained antiviral response. RNAseq analyses of persistently infected cells revealed that ZIKV alters host gene expression in a manner that could affect developmental processes. Conversely, data from sequencing of ZIKV genomes in persistently infected HFAs suggest that adaptive mutations were not required for establishing chronic infection. Based on these results, we postulate that HFAs are reservoirs for ZIKV in the fetal brain and that moderate apoptosis combined with inefficient antiviral response from these cells may contribute to the establishment of chronic brain infection associated with the ZIKV neurodevelopmental abnormalities.
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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".