Cytokine storm–based mechanisms for extrapulmonary manifestations of SARS-CoV-2 infection
Bibliographic record
Abstract
Viral illnesses like SARS-CoV-2 have pathologic effects on nonrespiratory organs in the absence of direct viral infection. We injected mice with cocktails of rodent equivalents of human cytokine storms resulting from SARS-CoV-2/COVID-19 or rhinovirus common cold infection. At low doses, COVID-19 cocktails induced glomerular injury and albuminuria in zinc fingers and homeoboxes 2 (Zhx2) hypomorph and Zhx2+/+ mice to mimic COVID-19-related proteinuria. Common Cold cocktail induced albuminuria selectively in Zhx2 hypomorph mice to model relapse of minimal change disease, which improved after depletion of TNF-α, soluble IL-4Rα, or IL-6. The Zhx2 hypomorph state increased cell membrane to nuclear migration of podocyte ZHX proteins in vivo (both cocktails) and lowered phosphorylated STAT6 activation (COVID-19 cocktail) in vitro. At higher doses, COVID-19 cocktails induced acute heart injury, myocarditis, pericarditis, acute liver injury, acute kidney injury, and high mortality in Zhx2+/+ mice, whereas Zhx2 hypomorph mice were relatively protected, due in part to early, asynchronous activation of STAT5 and STAT6 pathways in these organs. Dual depletion of cytokine combinations of TNF-α with IL-2, IL-13, or IL-4 in Zhx2+/+ mice reduced multiorgan injury and eliminated mortality. Using genome sequencing and CRISPR/Cas9, an insertion upstream of ZHX2 was identified as a cause of the human ZHX2 hypomorph state.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".