Inducible generalized activation of hSTING-N154S expression in mice leads to lethal hypercytokinemia: a model for “cytokine storm”
Bibliographic record
Abstract
Excessive levels of circulating proinflammatory mediators, known as "hypercytokinemia," that are generated by overwhelming immune system activation can lead to death due to critical organ failure and thrombotic events. Hypercytokinemia has been frequently associated with a variety of infectious and autoimmune diseases, with severe acute respiratory syndrome coronavirus 2 infection currently being the commonest cause, of what has been termed the cytokine storm. Among its various functions within the host, STING (stimulator of interferon genes) is critical in the defense against certain viruses and other pathogens. STING activation, particularly within cells of the innate immune system, triggers potent type I interferon and proinflammatory cytokine production. We thus hypothesized that generalized expression of a constitutively active STING mutant in mice would lead to hypercytokinemia. To test this, a Cre-loxP-based system was used to cause the inducible expression of a constitutively active hSTING mutant (hSTING-N154S) in any tissue or cell type. Herein, we employed a tamoxifen-inducible ubiquitin C-CreERT2 transgenic to obtain generalized expression of the hSTING-N154S protein, thereby triggering the production of IFN-β and multiple proinflammatory cytokines. This required euthanizing the mice within 3 to 4 d after tamoxifen administration. This preclinical model will allow for the rapid identification of compounds aimed at either preventing or ameliorating the lethal effects of hypercytokinemia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".