COVID-19 Lung Pathogenesis in SARS-CoV-2 Autopsy Cases
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major public health issue. COVID-19 is considered an airway/multi-systemic disease, and demise has been associated with an uncontrolled immune response and a cytokine storm in response to the virus. However, the lung pathology, immune response, and tissue damage associated with COVID-19 demise are poorly described and understood due to safety concerns. Using post-mortem lung tissues from uninfected and COVID-19 deadly cases as well as an unbiased combined analysis of histology, multi-viral and host markers staining, correlative microscopy, confocal, and image analysis, we identified three distinct phenotypes of COVID-19-induced lung damage. First, a COVID-19-induced hemorrhage characterized by minimal immune infiltration and large thrombus; Second, a COVID-19-induced immune infiltration with excessive immune cell infiltration but no hemorrhagic events. The third phenotype correspond to the combination of the two previous ones. We observed the loss of alveolar wall integrity, detachment of lung tissue pieces, fibroblast proliferation, and extensive fibrosis in all three phenotypes. Although lung tissues studied were from lethal COVID-19, a strong immune response was observed in all cases analyzed with significant B cell and poor T cell infiltrations, suggesting an exhausted or compromised immune cellular response in these patients. Overall, our data show that SARS-CoV-2-induced lung damage is highly heterogeneous. These individual differences need to be considered to understand the acute and long-term COVID-19 consequences.
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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 | 0.001 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".