Tick extracellular vesicles alter keratinocyte function in the skin epidermis
Bibliographic record
Abstract
ABSTRACT Wound healing has been extensively studied through the lens of inflammatory disorders and cancer, but limited attention has been given to hematophagy and arthropod-borne diseases. Hematophagous ectoparasites, including ticks, subvert the wound healing response to maintain prolonged attachment and facilitate blood-feeding. Here, we unveil a strategy by which extracellular vesicles (EVs) ensure blood-feeding and arthropod survival in three medically relevant tick species. Through single cell RNA sequencing and murine genetics, we demonstrate that wildtype animals infested with EV-deficient Ixodes scapularis display a unique epidermal sub-population with a mesenchymal-like transcriptional program and an overrepresentation of pathways connected to wound healing. Furthermore, tick EVs inhibit proliferation and diminish the capacity of wound closure in keratinocytes. This occurrence was linked to phosphoinositide 3-kinase activity, keratinocyte growth factor 1 (KGF-1) and transforming growth factor β (TGF-β) levels. Collectively, we uncovered a strategy employed by a blood-feeding arthropod that disrupts the circuitry in cutaneous wound healing, contributing to ectoparasite fitness.
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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".