Multi-omic analysis of PBMCs in sepsis reveals widespread cytotoxic dysfunction and an increased population of CD69 expressing naïve CD4+ T cells
Bibliographic record
Abstract
Introduction: Sepsis is responsible for 1 in 5 deaths globally and the majority of those who survive have lasting health issues. A hallmark of sepsis is a deregulated inflammatory response to infection, with leukocytes playing a critical role. Methods: This study utilised a targeted single-cell multi-omics approach to characterise peripheral blood mononuclear cell (PBMC) populations and their transcriptomic profiles in an Irish cohort of people with (i) sepsis and (ii) bacteraemia without sepsis (defined as clinically significant positive blood culture without sepsis as assessed by the Clinical Microbiology service). Results: Variable leukocyte distributions were identified, with decreased cytotoxic lymphocytes, including CD8+ T cells, natural killer cells, CD56+ T cells, γδ T cells, mucosal-associated invariant T cells, and increased T helper (Th) cell subsets within sepsis samples. Additionally, PBMCs from sepsis samples displayed an impaired expression profile in effector T cells, resulting in widespread suppression of PBMC cytotoxic activity. Discussion: These results identify potential mechanisms underlying the functional impairment witnessed in sepsis. Such mechanisms may inform future diagnostic and treatment strategies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".