Erythroid precursors and progenitors suppress adaptive immunity and get invaded by SARS-CoV-2
Bibliographic record
Abstract
SARS-CoV-2 infection is associated with lower blood oxygen levels, even in patients without hypoxia requiring hospitalization. This discordance illustrates the need for a more unifying explanation as to whether SARS-CoV-2 directly or indirectly affects erythropoiesis. Here, we show significantly enriched CD71 + erythroid precursors/progenitors in the blood circulation of COVID-19 patients. We found that these cells have distinctive immunosuppressive properties. In agreement, we observed a strong negative correlation between the frequency of these cells with T and B cell proportions in COVID-19 patients. The expansion of these CD71 + erythroid precursors/progenitors was negatively correlated with the hemoglobin levels. A subpopulation of abundant erythroid cells, CD45 + CD71 + cells, co-express ACE2, TMPRSS2, CD147, and CD26, and these can be infected with SARS-CoV-2. In turn, pre-treatment of erythroid cells with dexamethasone significantly diminished ACE2/TMPRSS2 expression and subsequently reduced their infectivity with SARS-CoV-2. This provides a novel insight into the impact of SARS-CoV-2 on erythropoiesis and hypoxia seen in COVID-19 patients.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".