Differential Expression of PCSK9 Modulates Infection, Inflammation, and Coagulation in a Murine Model of Sepsis
Bibliographic record
Abstract
INTRODUCTION: Proprotein convertase subtilisin/kexin type 9 (PCSK9) targets lipoprotein receptors for degradation, thereby reducing hepatic lipid clearance. PCSK9 inhibition reduces mortality in septic mice, presumably through increased hepatic clearance of pathogen lipids due to increased lipoprotein receptor concentrations. However, PCSK9 overexpression in vivo has not been studied in sepsis. Therefore, this study aimed to evaluate the effects of differential PCSK9 expression on systemic infection, inflammation, and coagulation in sepsis. METHODS: Wild-type, PCSK9 knockout (KO), and transgenic (Tg) mice that overexpress PCSK9 were subjected to sham surgery or cecal ligation and puncture (CLP). Bacterial loads were measured in lungs, peritoneal cavity fluid, and blood. Organ pathology was assessed in lungs, liver, and kidneys. Lung myeloperoxidase activity, and plasma concentrations of alanine aminotransferase (ALT), creatinine, cell-free DNA (cfDNA), protein C, thrombin-antithrombin (TAT) complexes, interleukin (IL)-6, and IL-10 were also measured 6 h postoperatively. Morbidity was assessed for 16 h following CLP. RESULTS: Overexpression of PCSK9 in mice increased liver and kidney pathology, plasma IL-6, ALT, and TAT concentrations during sepsis, whereas PCSK9 KO mice exhibited reduced bacterial loads, lung and liver pathology, myeloperoxidase activity, plasma IL-10, and cfDNA during CLP-induced sepsis. All septic mice had reduced plasma levels of protein C, but the protein C ratio relative to normal was significantly decreased in PCSK9 Tg mice. Dyspnea, cyanosis, and overall grimace scores were greatest in septic mice overexpressing PCSK9, whereas PCSK9 KO mice retained core body temperature during sepsis. CONCLUSION: These findings demonstrate that PCSK9 deficiency confers protection against systemic bacterial dissemination, organ pathology, and tissue inflammation, particularly in the lungs and liver, while PCSK9 overexpression exacerbates multi-organ pathology as well as the hypercoagulable and pro-inflammatory states in early 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".