Gene Expression Profiling of Apoptosis Regulators in Patients with Sepsis
Bibliographic record
Abstract
INTRODUCTION: Sepsis is associated with a dysregulation of apoptosis in immune cells, which has been implicated in both immunosuppression and multiple organ failure. We describe the expression profiles of genes encoding key regulators of apoptosis in highly purified monocytes, granulocytes and CD4+ T lymphocytes. METHODS: Sixteen patients with sepsis were recruited from the intensive care unit and were compared with 24 healthy controls. RNA was isolated from highly purified monocyte, granulocyte and CD4+ T-lymphocyte populations. Gene expression profiles were determined using multiplex ligation-dependent probe amplification for the simultaneous detection of 30 pro- and anti-apoptotic target genes. RESULTS: Relative to healthy controls, patients with sepsis showed increased transcription of both pro- and anti-apoptotic genes in peripheral blood leukocytes. Specific monocyte, granulocyte and CD4+ T-lymphocyte mRNA profiles were identified. Anti-apoptotic profiles were found in monocytes and granulocytes, while CD4+ T lymphocytes displayed a foremost pro-apoptotic mRNA profile. CONCLUSIONS: These data indicate that in patients with sepsis, the alterations in apoptosis of circulating leukocytes occur in a cell-specific manner.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".