Impaired natural killer cell counts and cytolytic activity in patients with severe COVID-19
Why this work is in the frame
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Bibliographic record
Abstract
The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-driven coronavirus disease 2019 (COVID-19) has caused unprecedented human death and has seriously threatened the global economy. Early data suggest a surge in proinflammatory cytokines in patients with severe COVID-19, which has been associated with poor outcomes. We recently postulated that the inflammatory response in patients with severe COVID-19 disease is not inhibited by natural killer (NK) cells, resulting in a "cytokine storm." Here, we assessed the NK-cell functional activity and the associated cytokines and soluble mediators in hospitalized COVID-19 patients. Significantly impaired NK-cell counts and cytolytic activity were observed in COVID-19 patients when compared with healthy controls. Also, cytokines like interleukin 12 (IL12), IL15, and IL21 that are important for NK-cell activity were not detected systematically. Serum concentrations of soluble CD25 (sCD25)/soluble IL2 receptor α (sIL2-Rα) were significantly elevated and were inversely correlated with the percentage of NK cells. Impaired NK-cell cytolytic activity together with other laboratory trends including elevated sCD25 were consistent with a hyperinflammatory state in keeping with macrophage-activation syndrome. Our findings suggest that impaired counts and cytolytic activity of NK cells are important characteristics of severe COVID-19 and can potentially facilitate strategies for immunomodulatory therapies.
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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 it