Immune Cell Targets of Infection at the Tick-Skin Interface during Powassan Virus Transmission
Bibliographic record
Abstract
Powassan virus (POWV) is a tick-borne flavivirus that can result in a severe neuroinvasive disease with 50% of survivors displaying long-term neurological sequelae. Human POWV cases have been documented in Canada, the United States, and Russia. Although the number of reported POWV human cases has increased in the past fifteen years, POWV remains one of the less studied human pathogenic flaviviruses. Ixodes ticks are the vectors for POWV, and the virus is transmitted to a host's skin very early during the tick feeding process. Central to the successful transmission of a tick-borne pathogen are complex interactions between the host immune response and early tick-mediated immunomodulation, all of which initially occur at the skin interface. In our prior work, we examined the cutaneous immune gene expression during the early stages of POWV-infected Ixodes scapularis feeding. The present study serves to further investigate the skin interface by identifying early cell targets of infection at the POWV-infected tick feeding site. An in vivo infection model consisting of POWV-infected ticks feeding on mice for short durations was used in this study. Skin biopsies from the tick feeding sites were harvested at various early time points, enabling us to examine the skin histopathology and detect POWV viral antigen in immune cells present at the tick feeding site. The histopathology from the present study demonstrates that neutrophil and mononuclear cell infiltrates are recruited earlier to the feeding site of a POWV-infected tick versus an uninfected tick. This is the first report demonstrating that macrophages and fibroblasts contain POWV antigens, which suggests that they are early cellular targets of infection at the tick feeding site. These data provide key insights towards defining the complex interactions between the host immune response and early tick-mediated immunomodulation.
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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".