The CXCR4/CXCR7/SDF-1 pathway contributes to the pathogenesis of Shiga toxin–associated hemolytic uremic syndrome in humans and mice
Bibliographic record
Abstract
Hemolytic uremic syndrome (HUS) is a potentially life-threatening condition. It often occurs after gastrointestinal infection with E. coli O157:H7, which produces Shiga toxins (Stx) that cause hemolytic anemia, thrombocytopenia, and renal injury. Stx-mediated changes in endothelial phenotype have been linked to the pathogenesis of HUS. Here we report our studies investigating Stx-induced changes in gene expression and their contribution to the pathogenesis of HUS. Stx function by inactivating host ribosomes but can also alter gene expression at concentrations that minimally affect global protein synthesis. Gene expression profiling of human microvascular endothelium treated with Stx implicated a role for activation of CXCR4 and CXCR7 by their shared cognate chemokine ligand (stromal cell-derived factor-1 [SDF-1]) in Stx-mediated pathophysiology. The changes in gene expression required a catalytically active Stx A subunit and were mediated by enhanced transcription and mRNA stability. Stx also enhanced the association of CXCR4, CXCR7, and SDF1 mRNAs with ribosomes. In a mouse model of Stx-mediated pathology, we noted changes in plasma and tissue content of CXCR4, CXCR7, and SDF-1 after Stx exposure. Furthermore, inhibition of the CXCR4/SDF-1 interaction decreased endothelial activation and organ injury and improved animal survival. Finally, in children infected with E. coli O157:H7, plasma SDF-1 levels were elevated in individuals who progressed to HUS. Collectively, these data implicate the CXCR4/CXCR7/SDF-1 pathway in Stx-mediated pathogenesis and suggest novel therapeutic strategies for prevention and/or treatment of complications associated with E. coli O157:H7 infection.
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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) | 0.002 | 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".