Nipah Virus Entry and Egress from Polarized Epithelial Cells
Bibliographic record
Abstract
Highly pathogenic Nipah virus (NiV) infections are transmitted via airway secretions and urine, commonly via the respiratory route. Epithelial surfaces represent important replication sites in both primary and systemic infection phases. NiV entry and spread from polarized epithelial cells therefore determine virus entry and dissemination within a new host and influence virus shedding via mucosal surfaces in the respiratory and urinary tract. To date, there is no knowledge regarding the entry and exit sites of NiV in polarized epithelial cells. In this report, we show for the first time that NiV can infect polarized kidney epithelial cells (MDCK) from both cell surfaces, while virus release is primarily restricted to the apical plasma membrane. Substantial amounts of basolateral infectivity were detected only after infection with high virus doses, at time points when the integrity of the cell monolayer was largely disrupted as a result of cell-to-cell fusion. Confocal immunofluorescence analyses of envelope protein distribution at early and late infection stages suggested that apical virus budding is determined by the polarized sorting of the NiV matrix protein, M. Studies with stably M-expressing and with monensin-treated cells furthermore demonstrated that M protein transport is independent from the glycoproteins, implying that the M protein possesses an intrinsic apical targeting signal.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".