Expression of a constitutively active human<i>STING</i>mutant in hematopoietic cells produces an<i>Ifnar1</i>-dependent vasculopathy in mice
Bibliographic record
Abstract
STING-associated vasculopathy with onset in infancy (SAVI) is an autoinflammatory disorder characterized by blood vessel occlusions, acral necrosis, myositis, rashes, and pulmonary inflammation that are the result of activating mutations in the STimulator of Interferon Genes (STING). We generated a transgenic line that recapitulates many of the phenotypic aspects of SAVI by targeting the expression of the human STING-N154S–mutant protein to the murine hematopoietic compartment.hSTING-N154Smice demonstrated failure to gain weight, lymphopenia, progressive paw swelling accompanied by inflammatory infiltrates, severe myositis, and ear and tail necrosis. However, no significant lung inflammation was observed. X-ray microscopy imaging revealed vasculopathy characterized by arteriole occlusions and venous thromboses. Type I interferons and proinflammatory mediators were elevated inhSTING-N154Ssera. Importantly, the phenotype was prevented inhSTING-N154Smice lacking the type I interferon receptor gene (Ifnar1). This model, based on a mutant human STING protein, may shed light on the pathophysiological mechanisms operative in SAVI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".