Specific Immunity to Cytomegalovirus in Pediatric Cardiac Transplantation
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) infection is implicated in endothelial dysfunction and graft damage after pediatric heart transplantation. CMV-specific immune responses are thought to be necessary for CMV viral control but there is little data in pediatric heart transplantation. METHODS: We studied 28 consecutive pediatric heart transplant recipients for 1 year posttransplant. CMV T-cell expressing IFN-γ, TNF-α, and IL-2 in response to ex vivo stimulation with CMV lysates or peptides were measured. Circulating cytokines were measured in plasma. Generalized Additive Models were applied to the data to model changes of cell population dynamics over time. RESULTS: CMV-specific T cell-mediated responses were impaired in the first 8 weeks posttransplant. During this period, 25% of patients had CMV viremia, of which those with VLs of 10 000 or more CMV deoxyribonucleic acid copies/mL were given ganciclovir. In this group, the frequency of CD4+ and CD8+ T cells producing IFN-γ and the CD8+CD57+ granzyme B+ T-cell population increased at 12 to 24 weeks and remained elevated for the duration of the study. CONCLUSIONS: We have shown that CMV viremia is associated with CMV-specific immune responses and increased CD8+CD57+ granzyme B+ cells at 1 year posttransplant; however, early responses were not predictive of impending CMV viremia. It remains to be seen if the early CMV immune response detected is associated with endothelial and allograft damage, in light of previous studies demonstrating increased vasculopathy in pediatric patients with CMV viremia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".