Association of Selected Phenotypic Markers of Lymphocyte Activation and Differentiation with Perinatal Human Immunodeficiency Virus Transmission and Infant Infection
Bibliographic record
Abstract
This study of a subset of women and infants participating in National Institutes of Health Pediatric AIDS Clinical Trials Group protocol 185 evaluated lymphocyte phenotypic markers of immune activation and differentiation to determine their association with the likelihood of human immunodeficiency virus (HIV) transmission from the women to their infants and the potential for early identification and/or prognosis of infection in the infants. Lymphocytes from 215 human immunodeficiency virus type 1 (HIV)-infected women and 192 of their infants were analyzed by flow cytometry with an extended three-color panel of monoclonal antibodies. Women who did not transmit to their infants tended to have higher CD4+ T cells. Most notably, levels of total CD8+ T cells and CD8+ CD38+ cells made significant independent contributions to predicting the risk of mother-to-child transmission. Adjusting for HIV-1 RNA level at entry, a one percentage-point increase in these marker combinations was associated with a nine percent increase in the likelihood of maternal transmission. Total as well as naive CD4+ T cells were significantly higher in uninfected than infected infants. Total CD8+ cells, as well as CD8+ cells positive for HLA-DR+, CD45 RA+ HLA-DR+, and CD28+ HLA-DR+ were elevated in infected infants. Detailed immunophenotyping may be helpful in predicting which pregnant HIV-infected women are at increased risk of transmitting HIV to their infants. Increasing differences in lymphocyte subsets between infected and uninfected infants became apparent as early as six weeks of age. Detailed immunophenotyping may be useful in supporting the diagnosis of HIV infection in infants with perinatal HIV exposure.
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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 | 0.001 | 0.003 |
| 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".