Priming of microvascular endothelium by microbiota-derived metabolites regulates neutrophil trafficking to the liver during sepsis
Bibliographic record
Abstract
Abstract During systemic bacterial infections and sepsis, neutrophils are recruited en mass into the microcirculation of the liver and lungs as part of a coordinated intravascular response to defend the bloodstream against bacterial pathogens. The mechanisms that program this response have not been elucidated. The gut microbiota regulates immune cell development and function. In extra-intestinal organs, the microbiota conducts long-distance communication with immune cells through the release of metabolites into the bloodstream. While gut microbes augment granulopoiesis in the bone marrow, the role the microbiota and commensal-derived metabolites on neutrophil trafficking is poorly understood. Using confocal intravital microscopy, we observed that germ-free (GF) mice had impaired neutrophil recruitment to the liver, but not the lungs, during sepsis. Analysis of microbial metabolites in the gut, portal circulation (between gut and liver), and systemic circulation revealed that commensal-derived D-lactate levels are high in the gut and portal circulation, but nearly absent in the systemic circulation. Reconstitution of gut-to-liver D-lactate signalling by enteral administration restored neutrophil trafficking to the liver. In contrast, D-lactate did not impact neutrophil infiltration to the lungs, systemic levels of pro-inflammatory mediators or granulopoiesis. Instead, commensal D-lactate primed liver endothelium to express adhesion molecules required for neutrophil adhesion and crawling. Taken together, we show that compartmentalized molecular communication between gut microbes and the liver primes the microvascular endothelium for neutrophil recruitment in response to systemic bacterial infection and 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".