Improved survival in experimental sepsis with an orally administered inhibitor of apoptosis
Bibliographic record
Abstract
The pathophysiology of sepsis involves excessive lymphocyte apoptosis, which correlates with adverse outcomes, and disordered cytokine production, which may promote host injury. As the protease inhibitor (PI) class of antiretroviral agents is known to prevent apoptosis in vitro, we evaluated their effect on survival, lymphocyte apoptosis, and consequent cytokine production in mice with sepsis induced by cecal ligation and perforation. Mice pretreated with PIs have improved survival (67%; P<0.0005) compared with controls (17%) and a significant (P<0.05) reduction in lymphocyte apoptosis. Even mice receiving therapy beginning 4 h after perforation demonstrated improved survival (50%; P<0.05) compared with controls. PI therapy is also associated with an increase in the Th1 cytokine TNF-alpha (P<0.05) early in sepsis and a reduction in the Th2 cytokines IL-6 and IL-10 (P<0.05) late in sepsis; despite no intrinsic antibacterial effects, PI also reduced quantitative bacterial blood cultures. The beneficial effects of PI appear to be specific to lymphocyte apoptosis, as lymphocyte-deficient Rag1-/- mice did not experience benefit from treatment with PI. Thus, inhibition of lymphocyte apoptosis by PI is a candidate approach for the treatment of sepsis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".