Neutrophil and monocyte activation in chronic kidney disease patients under hemodialysis and its relationship with resistance to recombinant human erythropoietin and to the hemodialysis procedure
Bibliographic record
Abstract
The aim of the present work was to further clarify leukocyte activation due to hemodialysis (HD) procedures and to investigate its relationship with recombinant human erythropoietin resistance. Therefore, we studied the expression of CXCR1 and CD11b on neutrophils, as well as the monocyte expression of CD11b, HLA-DR, and CD14. We studied 34 chronic kidney disease (CKD) patients under HD and recombinant human erythropoietin treatment (26 responders and 8 nonresponders to recombinant human erythropoietin therapy). All CKD patients' blood samples were collected before and immediately after the HD procedure. Eighteen healthy individuals (blood donors) were also studied as a control group. Hematological data, neutrophil (CD11b and CXCR1), and monocyte (CD11b, HLA-DR, and CD14) cell surface markers were measured in all patients (before and after the HD procedure) and controls. When compared with the controls, CKD patients presented a significant decrease in CXCR1 neutrophil expression, and in CD14 monocyte expression, accompanied by a significant increase in HLA-DR monocyte expression. When comparing the 2 groups of patients, we found that nonresponders showed an additional decrease in CXCR1 neutrophil expression. After the HD procedure, a statistically significant increase in CD14 and CD11b monocyte surface markers and a decrease in CXCR1 neutrophil expression and in HLA-DR monocyte expression was found. These data further strengthen our previous studies, showing that neutrophils and monocytes are activated in CKD patients, particularly in nonresponder patients. Moreover, this activation is due, at least in part, to the HD procedure, although we should not exclude that it can also be due to the enhanced inflammatory process observed in nonresponder patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".