Intravital imaging of three different microvascular beds in SARS-CoV-2–infected mice
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) enters the respiratory tract, where it infects the alveoli epithelial lining. However, patients have sequelae that extend well beyond the alveoli into the pulmonary vasculature and, perhaps, beyond to the brain and other organs. Because of the dynamic events within blood vessels, histology does not report platelet and neutrophil behavior. Because of the rapid nontranscriptional response of these cells, neither single-cell RNA sequencing nor proteomics report robustly on their critical behaviors. We used intravital microscopy in level-3 containment to examine the pathogenesis of SARS-CoV-2 within 3 organs in mice expressing human angiotensin converting enzyme 2 (ACE-2) ubiquitously (CAG-AC-70) or on epithelium (K18-promoter). Using a neon-green SARS-CoV-2, we observed both the epithelium and endothelium infected in AC70 mice but only the epithelium in K18 mice. There were increased neutrophils in the microcirculation but not in the alveoli of the lungs of AC70 mice. Platelets formed large aggregates in the pulmonary capillaries. Despite only neurons being infected within the brain, profound neutrophil adhesion forming the nidus of large platelet aggregates were observed in the cerebral microcirculation, with many nonperfused microvessels. Neutrophils breached the brain endothelial layer associated with a significant disruption of the blood-brain-barrier. Despite ubiquitous ACE-2 expression, CAG-AC-70 mice had very small increases in blood cytokine, no increase in thrombin, no infected circulating cells, and no liver involvement suggesting limited systemic effects. In summary, our imaging of SARS-CoV-2-infected mice gave direct evidence that there is a significant perturbation locally in the lung and brain microcirculation induced by local viral infection leading to increased local inflammation and thrombosis in these organs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".