Congenital Zika virus infection impairs corpus callosum development
Bibliographic record
Abstract
Abstract Congenital Zika Syndrome (CZS) is a set of birth defects caused by Zika virus (ZIKV) infection during pregnancy. Microcephaly is its main feature, but other brain abnormalities are found in CZS patients, such as ventriculomegaly, brain calcifications, and dysgenesis of the corpus callosum. Many studies have focused on microcephaly, but it remains unknown how ZIKV infection leads to callosal malformation. To tackle this issue, we infected mouse embryos in utero with a Brazilian ZIKV isolate and found that they are born with a reduction in callosal area and density of callosal neurons. ZIKV infection also causes a density reduction of PH3+ cells, intermediate progenitor cells and SATB2+ neurons. Moreover, axonal tracing revealed that callosal axons are reduced and misrouted. Also, ZIKV infected cultures show a reduction of callosal axon length. GFAP labelling showed that in utero infection compromises glial cells responsible for midline axon guidance. The RNA-Seq data from infected brains identified downregulation of axon guidance and axonogenesis related genes. In sum, we showed that ZIKV infection impairs critical steps of corpus callosum formation by disrupting not only neurogenesis but also axon guidance and growth across the midline. Summary Statement Zika virus infection during development impairs the formation of corpus callosum by disturbing axon guidance and growth of callosal neurons.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".