Impaired immune defense in hemodialysis patients: Role of α‐defensins?
Bibliographic record
Abstract
The mechanisms underlying the impaired immune response in hemodialysis (HD) patients are not completely understood. The α-defensins human neutrophil peptides-1, 2, and 3 are low molecular weight peptides with antimicrobial activity and important effector molecules of innate immune responses. We now examined the expression of these peptides in HD patients. Seventy-six patients on chronic HD treatment (mean time on HD 5.8 years; mean age 70 years) were studied and compared with 38 healthy volunteers and 20 patients with infections and normal renal function. Expression of α-defensins was analyzed semiquantitatively in leukocytes on the messenger RNA (mRNA) level by reverse transcriptase polymerase chain reaction; the α-defensin protein levels in serum were detected by enzyme-linked immunosorbent assay. α-Defensin concentrations (140 ± 10.5 ng/mL; mean ± standard error of the mean) as well as mRNA levels in leukocytes (82.9 ± 7.9 arbitrary units [a.u.]) in HD patients were not significantly different from those in healthy volunteers (156 ± 15.2 ng/mL; 81.4 ± 11.3 a.u.). Defensin levels were independent of the time of the patient on HD and their age. During infection periods (mean increase of the C-reactive protein to 161 ± 17.3 mg/L), defensin serum levels increased to 321 ± 65 ng/mL (P < 0.005) and mRNA expression in leukocytes to 159 ± 19.2 a.u. (P < 0.05). These increases were not significantly different from those in patients with normal renal function (298 ± 46.8 ng/mL and 128 ± 9.1 a.u., respectively) suffering from infections (C-reactive protein 222 ± 26.6 mg/L). Our results suggest that the impaired immune defense in dialysis patients is not due to a deficiency in α-defensins in these patients as neither basal levels nor expression during infections were reduced compared with subjects with normal renal function.
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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) | 0.001 | 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".