Involvement of the fractalkine pathway in the pathogenesis of childhood hemolytic uremic syndrome
Bibliographic record
Abstract
Thrombotic microangiopathy and acute renal failure are cardinal features of postdiarrheal hemolytic uremic syndrome (HUS). These conditions are related to endothelial and epithelial cell damage induced by Shiga toxin (Stx) through the interaction with its globotriaosyl ceramide receptor. However, inflammatory processes contribute to the pathogenesis of HUS by sensitizing cells to Stx fractalkine (FKN), a CX(3)C transmembrane chemokine expressed on epithelial and endothelial cells upon activation, is involved in the selective migration and adhesion of specific leukocyte subsets to tissues. Here, we demonstrated a selective depletion of circulating mononuclear leukocytes expressing the receptor for FKN (CX(3)CR1) in patients with HUS. We found a unique phenotype in children with HUS distinct from that seen in healthy, uremic, or infected controls, in which monocytes lost CX(3)CR1, down-modulated CD62L, and increased CD16. In addition, the CD56(dim) natural killer (NK) subpopulation was decreased, leading to an altered peripheral CD56(dim)/CD56(bright) ratio from 10.0 to 4.5. It is noteworthy that a negative correlation existed between the percentage of circulating CX(3)CR1(+) leukocytes and the severity of renal failure. Finally, CX(3)CR1(+) leukocytes were observed in renal biopsies from patients with HUS. We suggest that the interaction of CX(3)CR1(+) cells with FKN present on activated endothelial cells may contribute to renal injury in HUS.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".