Intracellular and Extracellular Lipopolysaccharide Signaling in Sepsis: Avenues for Novel Therapeutic Strategies
Bibliographic record
Abstract
Sepsis is defined as organ dysfunction due to a dysregulated systemic host response to infection. During gram-negative bacterial infection and other acute illness such as absorption from the gut infection, lipopolysaccharide (LPS) is a major mediator in sepsis. LPS is able to trigger inflammation through both intracellular and extracellular pathways. Classical interactions between LPS and host cells first involve LPS binding to LPS binding protein (LBP), a carrier. The LPS-LBP complex then binds to a receptor complex including the CD14, MD2, and toll-like receptor 4 (TLR4) proteins, initiating a signal cascade which triggers the secretion of pro-inflammatory cytokines. However, it has been established that LPS is also internalized by macrophages and endothelial cells through TLR4-independent pathways. Once internalized, LPS is able to bind to the cytosolic receptors caspases-4/5 in humans and the homologous caspase-11 in mice. Bound caspases-4/5 oligomerize and trigger the assembly of the nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3 inflammasome followed by the activation of inflammatory caspase-1 resulting in subsequent release of interleukin-1β. Caspases-4/5 also activate the perforin gasdermin D and purinergic receptor P2X7, inducing cell lysis and pyroptosis. Pyroptosis is a notable source of inflammation and damage to the lung endothelial barrier during sepsis. Thus, inhibition of caspases-4/5/1 or downstream effectors to block intracellular LPS signaling may be a promising therapeutic approach in adjunction with neutralizing extracellular LPS for 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".