Role of <scp>T</scp>‐regulatory cells in the response to hepatitis <scp>B</scp> vaccine in hemodialysis patients
Bibliographic record
Abstract
Human disease elicits a complex array of biological processes that results in long-term protective immunological memory to infectious agents. Chronic kidney disease is known to impair induction of sustained immunological memory to hepatitis B vaccine (HBVax) antigens. We asked the question: Does end-stage renal disease promote changes in subtypes of regulatory T (Treg) cells that correlate with diminished amnestic response to HBVax antigen compared to healthy controls? The study design and setting was a prospective observational cohort at a veterans affairs medical center. End-stage renal disease patients on hemodialysis (HD) were compared with individuals with self-reported normal kidney function. All subjects received HBVax. Peripheral blood was sampled for assessment for Treg cells pre and post vaccination. CD4+ FOXP3 Treg numbers were similar between HD and healthy subjects during a 14-day time period post vaccination. HD subjcts had lower anti-HBSag antibody than CON (control) subjects (330 ± 108.7 vs. 663.1 ± 129.7 IU/mL; P = 0.063). Hemodialysis subjects with resting Tregs higher than the median value in our cohort demonstrated a significantly lower change in HBsAB at 30 days post booster vaccination (P = 0.030). No such relationship was found for the activated Treg subset among HD subjects, or either subset among CON subsets. In our limited comparison study of 11 HD and 8 CON subjects, Treg subsets did not differ between the two groups; but differences in the suppressive Treg numbers in the HD group could explain the altered antibody response to HBVax and is worthy of further study.
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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 | 0.001 |
| 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".