Enhanced TLR7-dependent production of type I interferon by pDCs underlies pandemic chilblains
Bibliographic record
Abstract
Outbreaks of chilblains were reported during the COVID-19 pandemic. Given the essential role of type I interferon (I-IFN) in protective immunity against SARS-CoV-2 and the association of chilblains with inherited type I interferonopathies, we hypothesized that excessive I-IFN responses to SARS-CoV-2 might underlie the occurrence of chilblains in this context. We identified a transient I-IFN signature in chilblain lesions, accompanied by an acral infiltration of activated plasmacytoid dendritic cells (pDCs). Patients with chilblains were otherwise asymptomatic or had mild disease without seroconversion. Their leukocytes produced abnormally high levels of I-IFN upon TLR7 stimulation with agonists or ssRNA viruses-particularly SARS-CoV-2-but not with DNA agonists of TLR9 or the dsDNA virus HSV-1. Moreover, the patients' pDCs displayed cell-intrinsic hyperresponsiveness to TLR7 stimulation regardless of TLR7 levels. Inherited TLR7 or I-IFN deficiency confers a predisposition to life-threatening COVID-19. Conversely, our findings suggest that enhanced TLR7 activity in predisposed individuals could confer innate, pDC-mediated, sterilizing immunity to SARS-CoV-2 infection, with I-IFN-driven chilblains as a trade-off.
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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".