Systemic inflammation impairs myelopoiesis and interferon type I responses in humans
Bibliographic record
Abstract
Abstract Systemic inflammatory conditions are classically characterized by an acute hyperinflammatory phase, followed by a late immunosuppressive phase that elevates the susceptibility to secondary infections. Comprehensive mechanistic understanding of these phases is largely lacking. To address this gap, we leveraged a controlled, human in vivo model of lipopolysaccharide (LPS)-induced systemic inflammation encompassing both phases. Single-cell RNA sequencing during the acute hyperinflammatory phase identified an inflammatory CD163 + SLC39A8 + CALR + monocyte-like subset (infMono) at 4 h post-LPS administration. The late immunosuppressive phase was characterized by diminished expression of type I interferon (IFN)-responsive genes in monocytes, impaired myelopoiesis and a pronounced attenuation of the immune response on a secondary LPS challenge 1 week after the first. The infMono gene program and impaired myelopoiesis were also detected in patient cohorts with bacterial sepsis and coronavirus disease. IFNβ treatment restored type-I IFN responses and proinflammatory cytokine production and induced monocyte maturation, suggesting a potential treatment option for immunosuppression.
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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 | 0.000 |
| 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".